Dissertation by Jin Su Jeong

TESIS DOCTORAL

APROXIMACIÓN A LA PLANIFICACIÓN COLABORATIVA MEDIANTE ANÁLISIS DE DECISIÓN ESPACIAL MULTI‐CRITERIO PARA LA INTEGRACIÓN DE CONSTRUCCIONES RURALES EN SU ENTORNO A TRAVÉS DE HERRAMIENTAS SIG‐WEB

JIN SU JEONG Departamento de Expresión Gráfica

2013

TESIS DOCTORAL

“APROXIMACIÓN A LA PLANIFICACIÓN COLABORATIVA MEDIANTE ANÁLISIS DE DECISIÓN ESPACIAL MULTI‐CRITERIO PARA LA INTEGRACIÓN DE CONSTRUCCIONES RURALES EN SU ENTORNO A TRAVÉS DE HERRAMIENTAS SIG‐WEB”

JIN SU JEONG Departamento de Expresión Gráfica

Conformidad de los directores:

Fdo: Lorenzo García Moruno Fdo: Julio Hernández Blanco

2013

Doctorado en Ingeniería Gráfica, Geomática y Proyectos del Departamento de Expresión Gráfica de la Universidad de Extremadura

presentado por Jin Su Jeong para optar al grado del doctor en España en Diciembre 2013

Jin Su Jeong APROXIMACIÓN A LA PLANIFICACIÓN COLABORATIVA MEDIANTE ANÁLISIS DE DECISIÓN ESPACIAL MULTI‐CRITERIO PARA LA INTEGRACIÓN DE CONSTRUCCIONES RURALES EN SU ENTORNO A TRAVÉS DE HERRAMIENTAS SIG‐WEB • A COLLABORATIVE PLANNING APPROACH USING MULTI‐CRITERIA SPATIAL DECISION ANALYSIS TO INTEGRATE RURAL BUILDINGS INTO A LANDSCAPE IN GIS‐ENABLED WEB ENVIRONMENT December 2013

de acuerdo con la Mención de Doctorado Europeo

accorded with the European Doctoral Mention

Diciembre 2013

Tesis Doctoral por Jin Su Jeong

December 2013

A COLLABORATIVE PLANNING APPROACH USING MULTI‐CRITERIA SPATIAL DECISION ANALYSIS TO INTEGRATE RURAL BUILDINGS INTO A LANDSCAPE IN GIS‐ENABLED WEB ENVIRONMENT

A Dissertation by Jin Su Jeong

ABSTRACT

There is often a difficult relationship between rural buildings and the landscape. Selection of rural buildings’ site is a complex process to solve a discordant relation with other components of rural landscapes and needs many diverse criteria to deal with its situation. This may be overcome by methodologies that support a decision‐making processes for establishing harmonious relationships and sustainable environment integrity within a unique framework. The definition of such a framework assumes critical importance because the internet appears to provide the primary mechanism for allowing users the opportunity to acquire diverse geographic information system (GIS) data sources and to support collaborative planning process amongst planners, stakeholders and the public in the asynchronous and distributed environment. This research provides an approach how a spatial methodology for integrating rural tourism buildings into landscapes and coupling multi‐ criteria evaluations (MCE) into a web environment that uses a GIS technique can support to solve the current problem; an application of the proposed interface for Hervás (northern Extremadura region), Spain, is further presented. The analytical hierarchy process (AHP) is used to generate the alternative decisions using the multi‐criteria evaluation techniques standardized by fuzzy membership functions. The parameters are categorized into three criteria groups, namely physical, environmental and economic, and constraints verified by a group discussion with the experts and field survey, making them more objective. With the aid of the simple additive weighting (SAW) method, the calculation of final grading values in multiple criteria problem is evaluated for the study region. Then, this research describes the possibility to design and implement a web‐based GIS application, named ‘e‐shift’, with the methodology consisting of a general overview, a multi‐criteria spatial decision support system, an interoperable knowledge map and a post‐task questionnaire to identify spatial models. Through the implemented web interface, stakeholders reflected their individual experience to achieve desirable planning outcomes by the asynchronous and distributed collaboration with the increased public participation. Based on the qualitative and quantitative data set, this study examined the identification of spatial models for the various perceptions and knowledge sharing of building integrations into a rural landscape, the certification of the possible impact on tourism and the definition of interface usability. To strengthen data interpretation, these hypotheses are analyzed by four different clusters with the aid of analysis of variance (ANOVA) and principal component analysis (PCA) test: weak ties, socially linked, roots and resources, and dedicated to the place according to social and emotional relations. In general, most participants revealed positive responses to the questionnaires and an interesting fact amongst the

findings is the difference between roots and resources (positive to building integrations) and dedicated to the place (negative to building integrations). In general, however, the differences between the clusters were relatively small. Thus, the relevant of an emotional attachment to the place and willingness to participate future integration did not differ significantly although it is often assumed to their close interrelation. In conclusions, first, the methodology presents the combination of a spatial clustering process revealed the most suitable areas for rural buildings siting with their landscapes. The proposed methodology is intended to solve the rural building integration problem with its landscape and to facilitate the flexible methodology implementation from decision alternatives involved in the decision making process. Also, it can be easily extend as taking other parameters of criteria and sub‐criteria which could yield different decision alternatives. Second, the web design and implementation describes users can learn interactively and iteratively about the nature of the problem, and their own preferences for desirable characteristics of solution, the knowledge map supports and stimulates the sharing of opinions and, hence the clarification and discussion of interests behind user’s preferences. Third, the analyzed results obtained by the web demonstrates that the web application can achieve consensus on recommendations for the spatial planning with the implementation of decision alternatives through improved understanding of the complex nature of the current problems and understanding of the other interest groups’ preferences. The objective was that with an exhaustive analysis that involved all the interest groups, public acceptance and commitment to the decisions to be made was achieved for integrating rural tourism buildings to their landscapes.

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RESUMEN

Con frecuencia se observa una difícil relación entre las construcciones rurales y su entorno. La selección de la ubicación de edificaciones rurales es un proceso complejo que conlleva dar respuestas a relaciones discordantes con otros componentes del entorno rural, requiriéndose criterios muy diversos. Para afrontar el proceso de integración, pueden plantearse metodologías que agrupen las etapas de toma de decisión, permitiendo establecer una relación harmoniosa y una integridad medioambiental sostenible con un marco único de trabajo. La definición de este marco de trabajo tiene una importancia crítica, y en este sentido, internet constituye un mecanismo primario para dar a los usuarios la oportunidad de adquirir información variada a través de sistemas de información geográfica (SIG) y apoyar procesos colaborativos de planificación entre los agentes involucrados en el proceso y el público en general, en un entorno asincrónico y distribuido. La investigación que se presenta en esta Tesis Doctoral proporciona una aproximación de cómo una metodología espacial, para la integración de edificaciones turísticas rurales en su entorno, y el acoplamiento de sistemas de evaluación multi‐criterio (EMC) en un entorno web que emplea tecnología SIG, es una solución adecuada para dar respuesta al problema actual de integración; presentándose una aplicación de esta interfaz para Hervás (comarca del norte de Extremadura), España. Se emplea un proceso analítico jerárquico (PAJ) para generar decisiones alternativas a través del empleo de técnicas de evaluación multi‐criterio estandarizadas mediante funciones de pertenencia difusa. Los parámetros se categorizan según las limitaciones que se establezcan y en tres grupos de criterios: físicos, medioambientales y económicos, todo ello verificado mediante grupos de discusión de expertos y entrevistas personales, haciéndolas así más objetivas. Para la región de estudio, los valores de puntuación final, en el sistema de análisis multi‐criterio, se lleva a cabo con la ayuda del método de ponderación aditiva simple (PAS). Así, este trabajo de investigación describe el diseño y la implementación de una aplicación SIG‐WEB, denominada ‘e‐shift’. La metodología de esta aplicación consiste en un área de información general, un zona de sistema de apoyo a la toma de decisión espacial multi‐criterio, un área de mapas de intercambio de conocimiento y finalmente un cuestionario post‐ tarea para identificar los modelos espaciales. A través de la implementación de esta web, los agentes involucrados en el proceso de integración pueden mostrar sus experiencias individuales, y así alcanzar los resultados deseados para la planificación a través de una colaboración asincrónica y distribuida. Basándose en un conjunto de datos cualitativos y cuantitativos, este estudio examina la identificación de modelos espaciales a través de diversas percepciones y información compartida de integraciones de edificaciones en

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entornos rurales, la certificación del posible impacto en el turismo y establecer la funcionalidad del interfaz. Para fortalecer la interpretación de los resultados, las hipótesis planteadas se han analizado a través del análisis de varianza (ANOVA) y análisis de componentes principales (ACP) mediante la formación de cuatro clústeres en función de la relación social y emocional con el área de estudio: lazos débiles, vinculaciones sociales, raíces y recursos. En general, la mayoría de los participantes mostraron respuestas positivas a las cuestiones formuladas, y un aspecto a destacar ha sido las diferencias encontradas entre los grupos raíces y recursos (positivos a la integración de edificaciones), en relación a aquellos con vínculos afectivos o sociales en la zona (negativos a la integración de edificaciones). Aunque, conviene resaltar, que las diferencias entre los diferentes clústeres fue relativamente pequeña. Así, la relevancia de los lazos afectivos hacia el área de estudio y la voluntad de participar en futuras integraciones no difirió significativamente, aunque es habitualmente asumida una estrecha interrelación. En conclusión, la metodología propuesta presenta, en primer lugar, la combinación de procesos de agrupación espacial, que permitió identificar las áreas más adecuadas para la integración de edificaciones rurales en sus entornos, resolviendo así los problemas de integración y facilitando una metodología flexible para considerar decisiones alternativas en los procesos de toma de decisiones. Permitiendo, además, considerar de forma sencilla otros parámetros de criterios y sub‐criterios, que pueden conducir a diferentes alternativas de decisión. En segundo lugar, el diseño de la aplicación web y su implementación, indica que los usuarios pueden aprender o recabar información interactivamente y de forma iterativa sobre la naturaleza del problema, y sus propias preferencias para las características deseables de la solución, los mapas de conocimiento fomentan y estimulan la compartición de opiniones y más aún la clarificación y discusión de los intereses que hay más allá de las preferencias de los usuarios. En tercer lugar, el análisis de los resultados obtenidos demuestra que la aplicación web puede proporcionar consenso en las recomendaciones para la planificación espacial mediante de la implementación de decisiones alternativas a través de un mejor entendimiento de la compleja naturaleza del problema y de la comprensión de las preferencias de otros grupos interesados en el proceso. El objetivo es que, con un análisis exhaustivo que involucre a todos los grupos con intereses, la aceptación del público y el compromiso con las decisiones a tomar, se logre una correcta integración de las edificaciones turísticas rurales en sus entornos.

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PUBLICATIONS

This dissertation is based on ideas, fragments and figures that have appeared previously in the following publications:

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2011. Web‐based interoperability system: a collaborative method to integrate rural buildings with their surroundings. Proceedings on 16th International Conference on Urban Planning and Regional Development in the Information Society GeoMultimedia, Essen, Germany.

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., Carver, S., 2011. An interoperable web‐based GIS application to integrate rural buildings with their surroundings. Proceedings on VI Iberian Congress of Agricultural Engineering, Evora, Portugal.

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2012. Integrating buildings into a rural landscape using a multi‐criteria spatial decision analysis in GIS‐enabled web environment. Biosystems Engineering, 112(2), 82‐92.

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2012. A spatial assessment for re‐mixing buildings on the rural fringe of Spain. Proceedings on 17th International Conference on Urban Planning and Regional Development in the Information Society GeoMultimedia, Schwechat, Austria.

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2013. A site planning approach for rural buildings into a landscape using a spatial multi‐criteria decision analysis methodology. Land Use Policy, 32, 108‐ 118.

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2013. Un modelo web para el apoyo de tomas de decisiones en la integración de edificaciones rurales mediante planificación espacial multi‐criterio (A decision‐supporting web model for integrating rural buildings with multi‐criteria spatial planning). Informes de la Construcción, accepted. [Appendix B, p. 155].

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2013. Tool support for web‐aided requirement practicalities in rural planning. Proceedings on VII Iberian Congress of Agricultural Engineering and Horticultural Sciences, Madrid, Spain.

Jeong, J.S., Hernández‐Blanco, J., García‐Moruno, L., 2013. Approaches to validating a mutual participatory web‐planning interface in rural Extremadura (Spain). Land Use Policy, under review.

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DEDICATION

With love and gratitude, this dissertation is dedicated to my wonderful parents and beloved partner who supported me throughout this entire venture.

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ACKNOWLEDGEMENTS

I am grateful for the support of my friends and colleagues without whom writing this dissertation would have been much harder. I would like to give my sincere appreciation to my director, Prof. Dr. Lorenzo García Moruno. He has given me guidance and support since I was inspired to start this research. He encouraged me to acquire new knowledge and gave me a lot of advice to solve all problems during my study. I would also like to express my gratitude to the co‐director, Prof. Dr. Julio Hernández Blanco for putting so much effort into this dissertation. The constructive discussions with you have significantly shaped this work. Thank you also for the constant feedback that helped me to keep the big picture in mind. Thanks also go to David and Andrés who gave a hand to realize the application installation on the web. Last but not least, thanks to my family members and friends for their love and support.

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TABLE OF CONTENTS

ABSTRACT ...... xi RESUMEN ...... xiii PUBLICATIONS ...... xv DEDICATION ...... xvii ACKNOWLEDGEMENTS ...... xix TABLE OF CONTENTS ...... xxi LIST OF FIGURES ...... xxiii LIST OF TABLES ...... xxvii 1. INTRODUCTION ...... 1 1.1. Overview ...... 1 1.1.1. Rural buildings and their integration in landscapes ...... 3 1.1.2. Multi‐criteria spatial planning method ...... 7 1.1.3. Collaboration mechanism and technology ...... 12 1.1.4. Web‐based GIS application ...... 14 1.1.5. Managing knowledge and its mapping...... 19 1.1.6. Summary ...... 21 1.2. Problem statement ...... 22 1.3. Research outline ...... 23 2. JUSTIFICATIONS AND OBJECTIVES ...... 25 2.1. Research justifications ...... 25 2.1.1. Originality ...... 25 2.1.2. Significance of study ...... 25 2.1.3. Generalizability ...... 26 2.1.4. Substantiality ...... 26 2.2. Research objectives ...... 26 3. MATERIALS AND METHODS ...... 29 3.1. Philosophical assumptions ...... 29 3.2. Selected case study ...... 30 3.3. Multi‐criteria spatial methodology ...... 32 3.4. Web prototyping process ...... 35

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3.5. Measurement variables ...... 41 4. RESULTS ...... 45 4.1. Summary overview ...... 45 4.1.1. A site planning approach for rural buildings into a landscape using a spatial multi‐criteria decision analysis methodology ...... 47 4.1.2. Integrating buildings into a rural landscape using a multi‐ criteria spatial decision analysis in GIS‐enabled web environment ...... 67 4.1.3. Un modelo WEB para la asistencia en la toma de decisiones en la integración de las construcciones rurales mediante planificación espacial multi‐criterio ...... 83 4.1.4. Approaches to validating a mutual participatory web‐ planning interface in rural Extremadura (Spain) ...... 98

5. CONCLUSIONS AND FUTURE WORK ...... 121 5.1. Summary and discussion ...... 121 5.2. Limitations ...... 124 5.3. Future research ...... 125 REFERENCES ...... 127 APPENDIX A ...... 147 APPENDIX B ...... 153 VITA ...... 159

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LIST OF FIGURES

Figure 1.1: The integration process of rural buildings with their surroundings. p. 7

Figure 1.2: Classification matrix of knowledge processes. Adopted from Davenport (2005). p. 20

Figure 3.1: The outline of web prototyping process. p. 35

Figure 3.2: The prototype application workflow process in the view of client‐side and in the view of server‐side, cshtml (C#) was used to make the coding paradigms. p. 37

Figure 3.3: A typical collaboration of the MVC components. p. 38

Chapter 4.1.1:

Fig. 1: An example of a single dispersed tourism‐related commercial building based on the proposed construction size. p. 51

Fig. 2: Flowchart of rural building siting model. p. 52

Fig. 3: Location of the study area in Hervás (northern Extremadura), Spain. p. 54

Fig. 4: (A) Hierarchical structure shows the general aspect with the attention of physical suitability map process to make the decision of rural buildings siting problem. (B) Physical suitability map derived by 0.12, 0.23, 0.34, 0.09 and 0.08 factor weight for (a) elevation, (b) slope, (c) aspect, (d) vegetation type and (e) visibility sub‐criterion. p. 58

Fig. 5: (A) Hierarchical structure shows the general aspect with the attention of environmental suitability map process to make the decision of rural buildings siting problem. (B) Environmental suitability map derived by 0.28, 0.09, 0.12, 0.45 and 0.06 factor weight for (a) sensitive ecosystem, (b) water source, (c) surface water, (d) land use and (e) urban area sub‐criterion. p. 60

Fig. 6: (A) Hierarchical structure shows the general aspect with the attention of economic suitability map process to make the decision of rural buildings siting problem. (B) Economic suitability derived by 0.28, 0.05, 0.09, 0.43 and 0.15 factor weight for (a) site access, (b) population density, (c) residential area, (d) tourist area and (e) agricultural area sub‐criterion. p. 62

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Fig. 7: (A) Hierarchical organisation presents the final step to make the suitability map. (B) Possible suitability maps and their most appropriate areas over index value 9, derived by the physical, environmental and economic criteria applying different weights (a) equal weights, 0.33; (b) 0.50, 0.25 and 0.25; (c) 0.25, 0.50 and 0.25; (d) 0.25, 0.25 and 0.50, respectively. p. 65

Chapter 4.1.2:

Fig. 1: Location of the study area used in developing the prototype. p. 71

Fig. 2: Hierarchical structure of decision evaluation problem. p. 72

Fig. 3: The conceptual framework of the interoperable web‐based GIS application. p. 75

Fig. 4: The system architecture overview of interoperable web‐based GIS application. p. 75

Fig. 5: Web page that presents the feasible locations for rural buildings and the five criteria that the users must weight to classify one of them, the most important decision criteria, after logged in. p. 77

Fig. 6: Web page that shows the classified feasible sites with the users’ submitted weights of the decision criteria and displays the sub‐criteria of the submitted criterion that the users submit the relative importance weights using slider bars and text fields. p. 78

Fig. 7: Web page that displays the users’ submitted classifications according to a time rate, a knowledge map, and enables the users to check other users’ classifications, supporting communication. p. 79

Fig. 8: The prototype workflow process. p. 80

Chapter 4.1.3:

Figura 1: Mapa de situación del área de estudio Hervás. p. 88

Figura 2: Organización jerárquica del proceso de decisión mediante los criterios de evaluación planteados. p. 92

Figura 3: Despliegue del proceso del flujo de trabajo de e‐shift. p. 93

Figura 4: Selección de páginas web que muestran el proceso de toma de decisión espacial multi‐criterio. p. 95

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Chapter 4.1.4:

Fig. 1: The workflow deployment process of the web interface, named ‘e‐shift’. p. 105

Fig. 2: Web page that shows the criteria selection process that users must select one of three criteria and equal weight option, after logged in the system. p. 106

Fig. 3: (a) web page that presents sub‐criteria selection for three criteria that users can submit the relative importance weights using drop down menus; and (b) web page that demonstrates the final suitability map with constraints and categorized map selection options as clicking the radio buttons. p. 107

Fig. 4: The flow diagram of the web‐based post‐task survey questionnaire. p. 108

Fig. 5: The MCDA weighting ranking results of criteria and sub‐criteria. p. 111

Fig. 6: Score plot after PCA of the individuals in the four cluster groups defined by the two first PCs, PC1 and PC2. p. 117

Fig. 7: Loading plot after PCA of the variables in the questions defined by the two first PCs, PC1 and PC2. p. 118

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LIST OF TABLES

Table 1.1: Visual and aesthetic elements. Adopted from Español (1995). p. 6

Table 1.2: Common public participation methods in planning. Adopted from Wiedemann and Femer (1993) and Tang (2006). p. 10

Table 1.3: Time‐space matrix for classifying collaboration technology. Adopted from Munkvold (2003). p. 13

Table 3.1: Axiomatic contrasts of research paradigms. Adopted from Pickard and Dixon (2004). p. 30

Chapter 4.1.1:

Table 1: The relative importance of pair‐wise comparison and its numerical rates. p. 53

Table 2: The physical criteria calculation of pair‐wise comparison matrix in relation to the five sub‐criteria. p. 57

Table 3: The environmental criteria calculation of pair‐wise comparison matrix in relation to the five sub‐criteria. p. 59

Table 4: The economic criteria calculation of pair‐wise comparison matrix in relation to the five sub‐criteria. p. 61

Chapter 4.1.3:

Tabla 1: Los cuatros criterios principales y su desglose en sub‐criterios. p. 91

Tabla 2: Matriz de comparación por pares para el cálculo numérico de los pesos de los criterios. p. 92

Chapter 4.1.4:

Table 1: Socio‐demographic background variables of the participants in survey (n=212). p. 110

Table 2: Perceptions of building integration amongst the cluster groups, showing significant (p≤0.1) differences. p. 112

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Table 3: Perceptions of possible impact on tourism amongst the cluster groups, showing significant (p≤0.1) differences. p. 113

Table 4: Perceptions of knowledge sharing amongst the cluster groups, showing significant (p≤0.1) differences. p. 114

Table 5: Perceptions of usability testing amongst the cluster groups, showing significant (p≤0.1) differences. p. 116

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INTRODUCTION

1. This first chapter describes an introduction to present a scenario elaborating on establish theories of related fields to provide a baseline: the significant associated fields are rural buildings and their integration in a landscape, multi‐criteria spatial planning method, collaboration mechanism and technology, web‐based geographic information system (GIS) applications, and knowledge management and its mapping. Then, it describes the motivation stating current problems which are needed to define its scope and the deductive chain that contain the hypotheses. The outline of subsequent chapters is provided in the end of this chapter.

1.1. Overview

Some landscapes are still preserved to have a close relationship and harmonious balance with natural resources, farming, and human settlement carefully sited and oriented (Di Fazio, 1988). However, over the last few decades, particularly in Southern Europe, there have been significant and often discordant changes in the relationship between rural buildings and their landscapes (Mennella, 1997). Tourism has long been identified as a powerful tool for development, spurring economic growth, increasing foreign exchange, smallholder investment, and local employment (De Kadt, 1979). European landscape planning policy has particular building codes to protect local cultural identity and promote landscape quality (Council of the European Union, 2001). In some cases, tourism has resulted in increased environmental protection and funds for environment conservation (Pigram, 1980). The appropriate integration of man‐made constructions into their surroundings, however, is not yet a common consideration in general planning practice (De Vriesa et al., 2012; Tassinari et al., 2007). Therefore, professionals1 must consider appropriate integration and environmental location in mind to harmoniously balance rural buildings within their landscape setting (Bell, 1995; Tandy, 1979). Several researchers have referred to general design criteria for improving the visual impact of the appearance of rural buildings in the landscape. The characteristics considered include the correct siting of the buildings in relation to the natural contours of the landscape; their shape and form, materials of construction, colors, textures, subdivision of volumes; their relationship to existing buildings and groupings; the organization of the space surrounding the buildings which links them to the landscape (Di Fazio, 1988; Schmitt, 2003; Smardon, 1979). The

1 The term of professionals was defined in the four results which are posed in Chapter 4.1.1 to 4.1.4.

integration of the building with landscape usually depends more on the right choice of location than on any other weighted factors (Hernández et al., 2004b; Montero et al., 2005). GIS offers useful tools to study the location in depth when considering spatial planning limitations and opportunities, visual characteristics, and the overall landscape scene (Domingo‐Santos et al., 2011; Hernández et al., 2004b; Tassinari and Torreggiani, 2006). The spatial modeling used by GIS allows for analyzing large volumes of spatial data which give geographical expression to the economical, social, cultural ecological policies of societies (Böhme and Schön, 2006; Hermann and Osinski, 1999). From this modeling, decision‐makers (or planners and local authorities) can find the current state of affairs and some idea of future conditions, ideally the possible consequences of the plans and policies they may have under consideration (Blaschke, 2006). The problems of spatial planning usually incorporate a large number of stakeholders (experts and non‐experts) with different backgrounds, interests, authorities and interpretations of some of their issues (Fountas et al., 2006). A collaborative process is the right way to reconcile the individual approaches and to make decisions satisfying all or most participants (users: stakeholders and the public) (Jankowski et al., 1997). Multi‐criteria evaluation (MCE) is one particular type of spatial planning that has been developed to help decision‐makers explore and solve multiple complicated problems (Hwang and Yoon, 1981; Malczewski, 1999; Roy, 1996). Because of the number of factors involved, collaborative processes can be seen as an integration process aimed at solving complicated decision‐making (Renger et al., 2008). A range of participants with different levels of individual experience are able to share their knowledge to investigate compromise solutions and resolve conflicting views to provide desirable planning outcomes (Simão et al., 2009). Over the last decade, efforts have been made to develop integrative tools capable of dealing with both the analytical and communication side of spatial planning and design process within a unique framework (Jankowski et al., 1997; Ruiz and Ferández, 2009; Voss et al., 2004). The definition of such a framework assumes critical importance because the internet appears to provide the primary mechanism for allowing interested stakeholders the opportunity to participate in the planning and design process using asynchronous and distributed collaboration (Voinov and Bousquet, 2010). The internet as some researchers have mentioned already offers a new way to allow and facilitate participatory decision‐making processes and to generate a new public sphere supporting interaction and debate amongst participants (Batty, 1998; Kingston et al., 2000). Decision‐makers develop manners to use these technologies to work effectively and efficiently with the participants and to grant opportunities to some interested stakeholders using asynchronous and distributed collaboration (Al‐Kodmany, 2001; Voinov and Bousquet, 2010). Thus, multi‐criteria decision analysis (MCDA) incorporating

with the technology provides ways to help decision‐makers explore and solve multiple and complicated decision problems (Hwang and Yoon, 1981; Keefer et al., 2004; Malczewski, 1999; Roy, 1996). One of widely accepted decision‐making methods is the analytic hierarchy process (AHP) that is an effective approach to take out the relative importance weights of the criteria in a specific decision‐making situation (Gemitzi et al., 2006; Saaty, 1977). Typically, the criteria have different significance which shows participants’ preference as the alternatives for them on each criterion (Saaty, 1996, 2005). One of the most crucial steps in any multiple criteria problem is the accurate estimation of the pertinent data. Although qualitative information about the criterion importance can be found, it is difficult to quantify it correctly (Faraji Sabokbar, 2005). This research describes an investigation into how a mutual participatory web‐based GIS planning interface coupled with a spatial methodology can be a unique and cohesive framework to identify and formulate suitable criteria and spatial models for the right spatial planning integration, with the primary aim of highlighting the interrelations between rural tourism buildings and their landscapes. The methodology explains the determination of rural tourism buildings’ site suitability with the AHP and constraints for MCDA and the simple additive weighting (SAW) based on the understanding of the existing regional planning and policies (Eastman, 2003). The general goal of this work is to examine how the research can contribute to support stakeholders’ decision‐making, together with its application to an empirical case study in Hervás, Spain. The implemented web application allowed us to calibrate the method, measuring users’ perception and knowledge sharing about building integration, defining the interface adequacy, and certifying the possible impact on tourism suitable carried out the analyses through the qualitative and quantitative database set. Thus, this system could be used as a channel to collaborate and communicate the integration of rural buildings and their surroundings to users who have specific and practical purposes.

1.1.1. Rural buildings and their integrations in landscapes

The suitable integration of the numerous man‐made elements is related with various interconnected factors which affect to the building itself and the relationship between the building and the current countryside environment and raises the questions of how negative impacts on these factors can be minimized (De Vriesa et al., 2012; Jeong et al., 2012; Tassinari and Torreggiani, 2006). European landscape planning policy with the particular building codes issued for protecting their cultural identity and for promoting landscape quality. The appropriate integration of man‐made constructions into their surroundings, however, is not still much common yet (Tassinari et al., 2007). To be fully adopted and implemented in general practice, the designer must bear integration and functionality in mind and plan buildings which can satisfy traditional construction styles and

materials and do match modern agricultural needs to be sited respecting their environmental emplacement (Bell, 1995; Tandy, 1979). To solve the problems mentioned above, the previous approaches are needed to be investigated first.

Previous studies on building elements and its landscape

In recent and contemporary rural architecture, several causes of the poor landscape impact are described as the following: first, the increasingly uniform conception of little design consideration for the unique characteristics of the location and surroundings during planning and construction; second, heavy reliance on standardized design solutions and prefabricated building components to fulfill functional requirements whist limiting both design and construction costs, and third, little consideration for the relations between buildings and open spaces to make the failure to involve local construction companies and professionals with expertise in design (Schmitt, 2003). Several researchers have described and referred the main factors and general design criteria for improving the visual impact of the appearance of rural buildings on the landscape. Considered characteristics are correct siting in relation to the natural contours of the landscape, shape and form, materials, colors, textures, subdivision of volumes, relationship to existing buildings and groupings, organization of the space surrounding the building which links the building to the landscape, construction details and finishing elements (Di Fazio, 1988; Schmitt, 2003). Additionally, a fundamental observation is that good appearance is not something which can be added at the final stage of the design process, since it is strictly inherent in the conception of the building and is the result of structural, functional and economic choices (Di Facio, 1989). And reconciling aesthetic quality with economic constraints is both necessary and possible, since improved appearance does not necessarily involve additional costs (Damm, 1982). The definition of guidelines and reference standards is followed by the investigation of current traditional buildings’ types and their exterior materials and the study of up‐to‐date solutions which have been proposed as to review the evolution of rural building design and construction, especially agricultural one, during the last century in Spain in order to assess how the changes in rural landscape have been influenced by this type of building and to process solutions for improving the control of future building design (Ayuga, 1989, 2001; Di Facio, 1989; Fichera and Di Fazio, 1989). The followings are the factors considered to understand the problem arising from the relationship between a building element and the landscape (Ayuga, 2001; García et al., 2006, 2010):

 The landscape value: Many researchers have mentioned that landscape assessment is extensively discussed (Bishop and Leahy, 1989; Shafer, 1969; Smardon, 1979; Tveit et al., 2006). A simple quantitative method can be used from the point of view of building integration to evaluate the effect of the intervention related with the landscape value (Cañas et al., 1996; García et al., 2006, 2010).  The building location: The building integration with landscape usually depends more on the right location selection than on any other weighted factors. GIS offers useful tools to study the location in depth as considering planning limitations, opportunities, visual characteristics and the scene (Hernández et al., 2004a, 2004b). More studies of GIS will be examined in the following paragraph.  The visual elements: After selected a correct location, the scene in which the building will be set needs to be investigated and analyzed as to consider the importance of the places in terms of number of travelers or the interest of the people in that places (García et al., 2006). The visual elements of the scene that characterize the landscape describes in the Table 1.1 (Español, 1995; USDA Forest Service, 1974).  The traditional buildings’ elements and harmonies: The professionals must bear integration in mind and plan buildings in rural areas satisfying traditional buildings’ elements which are their texture, volumes, strength lines, etc. to match modern agricultural needs and to respect their environmental emplacement (Bell, 1995; García et al., 2010; Tandy, 1979).  The construction elements: To adapt constructions better to the landscape and traditional constructions, each element need to be studied as using the proper element, the position and repetition within building, the possibility of modification or development, and the cost change (García et al., 2010; Reyes, 2009).

GIS has emerged over the last 20 years as an effective tool not only for analyzing spatial data but also for evaluating resource management alternatives (Appleton et al., 2002; Hermann and Osinski, 1999; Kangas et al., 2000; Seppelt and Voinov, 2002). In reality, in many cases, data are simply stored and processed in a GIS centered on the patterns of land cover and land use, and of social, economic, and demographic characteristics. Decision‐makers need to know not only the current state of affairs but also require some idea of future conditions. Ideally they would like to be able to see the possible consequences of the plans and policies they may have under consideration (Blaschke, 2006). This is often realized in a finite set of scenarios or through one of the many different predictive computational modeling techniques available (Seppelt and Voinov, 2002). The latter mainly use regular tessellations like regular grids or lattices and support the search for ‘optimal’ spatial

decisions (Makowski et al., 2000; Martinnez‐Falero et al., 1998; Seppelt and Voinov, 2002).

Table 1.1: Visual and aesthetic elements (Español, 1995).

Element Characteristics Spectrum/ Color Saturation/ Lightness Surface Regularity/ Density/ Texture Grain Size/ Internal Contrast Sharpness/ Line Complexity/ Direction Formation Geometry/ Form Complexity/ Orientation Scenic Composition/ Space Scenic Background/ Composition Sitting of Units Scenic Occupation/ Scale Contrast of Scales

Among the factors mentioned earlier, two factors to stance rural buildings and their integration in landscapes which are more intrigued to start this research are reviewed: first, the location selection using GIS technologies (Hernández et al., 2004a, 2004b); and second, the visual element evaluation of man‐made constructions and other landscape components on photographic management (García et al., 2003, 2006, 2010), which are depicted in Figure 1.1:

 Territorial system analysis: The aim of this study is to make an initial selection of the possible sites using GIS technologies. In the analytical and diagnostic sequences required to process the planning directives of a territory, the study area can be characterized in terms of its physical/natural, socio‐economic and legal/institutional subsystems together with human establishment (Gómez Orea, 1994).  Spatial location analysis: The purpose of this process is to evaluate buildings’ spatial location based on GIS, which is to check the visual impact of man‐made constructions with the landscape and to select the location where this impact will be least. This process is using the criteria of visual integration, scenic composition and scenic background and is related with the second method, visual element evaluation (Hernández et al., 2004a, 2004b).

 Visual element analysis: The purpose of this evaluation is to analyze visual elements of buildings related with their surroundings using computer technologies. This process checks the relationship between two types of the same characteristic shown in Table 1.1 as the following categories (García et al., 2003, 2006, 2010): first, visual continuity describing the relationship between two similar types in a diagram or scale that buildings copy and reproduce their surroundings’ value which has no diversity and new contrasts; second, diversity describing the relationship between two types separated by a certain distance which has more diversity and contrast to enrich a scene.

Figure 1.1: The integration process of rural buildings with their surroundings.

1.1.2. Multi‐criteria spatial planning method

Spatial planning refers to the methods used by the public sector to influence the distribution of people and activities in spaces of various scales as well as the location of the various infrastructures, recreation and nature areas, which includes all levels of land‐use planning including urban planning, regional planning, environmental planning, national spatial plans, and in the European Union (EU) levels (CEMAT, 2006). One of the earliest definitions comes from the European Regional/Spatial Planning Charter (Böhme and Schön, 2006):

"Regional/spatial planning gives geographical expression to the economic, social, cultural and ecological policies of society. It is at the same time a scientific discipline, an administrative technique and a policy developed as an interdisciplinary and comprehensive approach directed towards a balanced regional development and the physical organization of space according to an overall strategy."

The problems of spatial planning usually incorporate a large number of decision‐makers with different backgrounds, interests, authorities and interpretations of some of their issues (Fountas et al., 2006). A collaborative process is the right way to reconcile the individual approaches and to lead solutions satisfying all or most participants. For fair, rational and efficient decision‐making

procedures, the well‐tried interaction of decision‐makers with GIS has to be integrated with a framework (Gordon et al., 1997).

Collaborative and iterative spatial planning

Spatial planning involved many dimensions is a complex enterprise in which decision‐makers often are not fully aware of the range of factors or implications related. Sometimes, a definitive problem statement is not available in advance and the consequences of a particular decision are not obvious at the outset (Rittel and Weber, 1973). Insights into what the problem is and how it can be solved are commonly gained incrementally during successive problem exploration cycles (Hendriks and Vriens, 2000; Holz et al., 2006). The increasing segmentation of expertise areas and the current trend to democratize planning and decision‐making due to the number of factors involved, spatial planning cannot be the enterprise of a sole person. Because of this, different areas of expertise are required to address them for the multiple dimensions of a spatial problem (Fountas et al., 2006; Renger et al., 2008). In addition, the consequences of a planning decision require public involvement in the planning process; public participants will be those who will have to live with an implemented solution. Consequently, spatial planning must be resulted from a collaborative process in which a range of stakeholders can express their concerns and works on a trade‐off solution with seeking to solve their geographical problem (Simão et al., 2009). The numerous references of spatial planning support system contain tools which have been particularly designed to aid either the analytical side and/or communicative side of spatial planning. Over the last decade, efforts have been made to develop integrative tools capable of dealing with both the analytical and communication side of spatial planning and design process within a unique framework (Jankowski et al., 1997; Ruiz and Ferández, 2009; Voss et al., 2004). The definition of such a framework assumes critical importance because the internet appears to provide the primary mechanism for allowing interested stakeholders the opportunity to participate in the planning and design process using asynchronous and distributed collaboration (Voinov and Bousquet, 2010). Notwithstanding the constraints to participation in spatial planning that result from social groups’ differential access to computers (Carver et al., 2001; Davison and Cotten, 2003; Kingston, 2002), the continuous increase in the internet adoption makes it a suitable medium for collaboration. Thus, information plays an essential role in the planning and design process. Normally, stakeholders who involve in investigating a decision problem have background knowledge gained through personal experience or reading‐based sources on the problem. Both types of knowledge are crucial in decision‐making (McCall, 2003).

Spatial decision supporting systems

Spatial decision support systems (SDSSs) are explicitly designed to help decision‐makers solve complex and semi‐structured spatial problems (Densham, 1991). SDSSs are rooted in the decision support systems (DSSs) literature and are emerged from there in the mid 1980s (Armstrong et al., 1986), when technological advances enabled computers to process spatial information. From the numerous different definitions which describe the characteristics of DSS, one can extract that the term DSS generally describes systems that assist the user in analyzing data and support him/her in making a decision (Densham, 1991). DSSs are applied to semi‐structured problems, which cannot be solved based on pure hard facts, but which require the user to set his/her preferences as a second input to the system (Simão et al., 2009). In spite of their roots, SDSS can be easily differentiated with DSS because the term SDSS refers to DSS which was developed for spatial decision‐making problems (Simão and Densham, 2004). The aim of SDSS is laid on spatial problems and is reflected in the functionality related with such systems: the acquisition and management of spatial data; the representation of geographical objects and their spatial relations; the performance of spatial analysis; and the creation of map‐ based outputs (Densham, 1991). These functions provide to support users in defining decisions’ preferences. The terms, public participant geographic information system (PPGIS) and SDSS, are closed related in the literature and not always clearly defined (Simão et al., 2009). Hence, communication is an essential stage in the decision‐making process; only through communication is it possible to find a solution that reconciles the conflicting objectives that result from different people’s opinions. Only through such a process can the final outcome be accepted by the majority (Simão et al., 2009; Tang, 2006).

Participation methods in spatial planning and decision‐making

Public participation is the process to allow those affected by a decision to have an input into that decision (Smith, 1993). This term also refers to the involvement of the public in the planning process. In general, the public means all stakeholders in the community except the planning authorities such as developers, interest groups and individuals. The ultimate purpose of public participation is to integrate well developed public opinion into collective actions and decisions (Innes and Booher, 2000). To meet the diverse participation needs, different participation methods have been developed at the various stages of the decision‐making process. The common public participation methods in planning shown in the Table 1.2 as the following, which presents a respective method that can reach on Wiedemann and Femers’ participation ladder described on the Table 1.2.

Table 1.2: Common public participation methods in planning (Wiedemann and Femer, 1993; Tang, 2006).

Wiedemann & Femers’ Method Character Ref. Participation Ladder • Solicit information/opinion from representative sample of citizens. Opinion • Same questions are asked of every Step 1 Survey individual surveyed. • Survey types: postal, interview, telephone, online. • Mandatory requirement to notify adjacent Neighbor landowners of proposed planning Step 1 and 2 Notifications applications, whose comments may or may not be required. Exhibitions • A presentation/exhibit of planning proposal made by planning authority. Step 1 and 2 • For education & information purposes. Consulting • A compilation of key information on the Documents subject matters to be consulted. Step 1 and 2 • May request feedback from readers.

Written • Formally invite public to provide written Methods Comments feedback on planning proposals during Step 1, 2 and 3 mandatory consultation period. • Formal presentation by consulting team in open forum. Public • Public is given the chance to voice Meeting opinions and ask questions, but has no Conventional Step 1, 2 and 3 Forums direct impact on recommendations. • Extensively used to solicit information and input on particular issues. • No formal votes/decisions are made. • Similar to the setting of public meetings Public but public views are recorded for the Hearings purpose of informing the decision‐makers. Step 1, 2 and 3 • Decision‐making body makes a decision to approve or reject the proposal. Citizen Small group selected to represent views to Advisory various groups/communities and to Step 1, 2, 3, 4 and 5 Committees examine significant issues and make recommendations to decision‐makers.

Basic Web • Provides static or interactive information Sites on the subject matters to be consulted. Step 1, 2 and 3

• Accepts feedback via email. Online Discussion • Facilitates communication and discussion among participants about important issues. Step 1, 2, 3, 4 and 5 Methods Forums • Usually supports online voting/polling. based

• Utilize GIS technology to support and/or ‐ facilitate participation.

PPGIS • Depending on individual systems, Web Step 1, 2, 3, 4 and 5 available services vary from delivery of map information to spatial decision support system.

As presented in Table 1.2, the common public participation methods for planning are two methods: the conventional and web‐based method. These methods describe the different degree of the public

involvement at decision‐making. The following indicates the detail information of these two methods:

 Conventional methods: This method can reach one‐to‐many interaction which is the most widely used methods such as surveys and public meetings. Especially, the public meetings have been criticized by numerous researchers (Carver, 2001; Jackson, 2000; Kingston, 1998; Wilcox, 1994) as the following disadvantages and limits of participation degree: ∙ The separated speakers and audience, authoritative decision‐ makers have all the information, knowledge and expertise which are compared to a partially informed public (Tang, 2006), ∙ The fixed time and place, people from other commitments are excluded and the meeting is used to convince the public to adopt the proposal rather than opening up for exchange of views or consensus building.

 Web‐based methods: This method has been developed by information and communication technologies (ICTs) advance to make online participation. ICTs have a number of advantages over the conventional participation methods as the below (Tang, 2006): ∙ Asynchronous participation, removing time and location barriers to access anytime and from anywhere with the internet connections, ∙ Relatively anonymous and less confrontational, encouraging the silent majority to participate the process of the decision‐ making, ∙ Two‐to‐multi‐way information flow, allowing exchange and share of information and knowledge in the effective manner.

Based on the participation objectives at respective levels of Wiedemann and Femers’ participation ladder, the objective of participation describes each step as the following: step 1 is public right to know; step 2 is informing the public; step 3 is public right to object; step 4 is public participation in defining interests, actors and determining agenda; step 5 is public participation in assessing risks and recommending solutions; and, step 6 is public participation in final decision. For the step 1, 2 and 3, they can be defined as broadcast model with having one‐to‐many‐interaction. From the step 4 to the end, they can be defined as participative model with having many‐to‐ many interaction. Participation activities need to satisfy the principles of participatory planning approach over the restricted participation to enable effective communication among the participants (Carver et al., 1998). Communication plays an important role in spatial planning and decision‐making (Healey, 1997). Through these activities, the participants can be better reflected in the final outcome and the

collection of information and knowledge is used as the evaluation of planning options.

1.1.3. Collaboration mechanism and technology

Collaboration is becoming obligatory at the industrial globalization and is requiring a high order of involvement and different approach to share and create information at the practical reality. Based on these situations, collaborative circumstances must be created (Schrage, 1990). The concept of collaboration is an interpersonal recursive process that embodies co‐operative ventures of working together to realize shared goals and even to reach an identical objective (Marinez‐Moyano, 2006). Based on the thought of a team working together effectively, collaboration can be expressed as a process of value creation towards problem solving, given a set of constraints, such as limited expertise, time, financial constraints (Lorenz et al., 1999). To satisfy collaboration, the common communication space is necessary between participants’ interactions and their works. The space is rather a medium not a physical space to communicate team members. The communication of each participant through the medium of shared space can only successful if all agree on a common understanding.

Collaboration elements and modes

A number of factors are essential to achieve the effective collaboration, which depends on the environment where the collaboration takes place. There are six required elements for effective collaboration such as common purpose, mutual respect, shared paradigm, clear communication, co‐location, and compatible incentive (Lorenz et al., 1999):

 Common Purpose has to be recognized by participants. The participants may have the different goals from conflict sources but must replace their short‐time goals to the overall goal.  Mutual Respect has to be required in the category of collaboration for each other. In any relationship, it takes time to develop a good working relationship with successful experience and awareness of limitations.  Shared Paradigm makes an easier transition to foster collaborative relationships. Even though the individual ideas cannot be mutually exclusive, it can prevent power struggles among participants.  Clear Communication supports the effective communication and collaboration as recognizing varies styles and forms of communication and as updating tasks, progress, facts, and concerns each other.

 Co‐location is one of collaborative conditions because proximity makes easier exchange of information (Kraut et al., 2002). However, recently collaborators cannot be in the same location easily so it will be an interesting issue.  Compatible Incentive is about straight financial concern, which mostly relates with the individual. Incentive scheme is the core motivation for individuals to work productively (Barnard, 1968). Also, collaborators often feel uncomfortable sharing competitive knowledge if they do not receive proper credit for their contribution towards the common goal (Haldin‐Herrgard, 2000; Williamson, 1995).

Collaboration technologies are categorized into with two elements: time and space dimension. Time dimension is divided into synchronous and asynchronous collaboration and space dimension is separated into same location and different location (DeSanctis and Gallupe, 1987). For better understanding of the scope of collaboration and their differences, the time‐space matrix is described in the Table 1.3. Sometimes the technologies, however, are not strictly one location due to the increased project complexity.

Table 1.3: Time‐space matrix for classifying collaboration technology (Munkvold, 2003).

Synchronous Asynchronous Email/ Calendar and scheduling systems/ Electronic meeting systems/ Co‐location Document management systems/ Face‐to‐face Electronic bulletin boards/ Workflow management systems Audio conferencing/ Email/ Data conferencing/ Calendar and scheduling systems/ Desktop conferencing/ Document management systems/ Distributed Instant messaging/ Electronic bulletin board/ Telephone call/ Web‐based team/project rooms/ Video conferencing Workflow management systems

Collaboration mechanism and technology impacts

For the more effective collaboration, clear goals need to be set in advance and then participants can work successfully towards achieving goals (Huang et al., 2003). Computer‐supported collaborative works are involved with the technology and the social side as a medium for communication as described many literatures. However, the electronic systems’ use has advantages and disadvantages. Electronic meeting systems allow more equal amounts of contributions across participants than in face‐to‐face meetings (Hollan and Stornetta, 1992). Gestures, non‐verbal communication, and tacit knowledge are hard to express and cannot be transferred well over distance media even computer‐ supported collaborative works have the merit of the distance (Olson and Olson, 2000; Olson et al., 2002). Many researchers still argue that

perfect mimics of the face‐to‐face approach would make participants to reach the goal. ICTs could be used to create wholly new forms and to accomplish what previously was not possible (Hollan and Stornetta, 1992). Media richness is related with ICTs’ success as mentioned by many researchers. ICTs’ success depends on media richness which depends on information richness of channels, featuring cue variety, feedback, and message personalization, as candidate needs (Daft and Lengel, 1986; Daft et al., 1997). A more recent approach to explain the relation between technology and user is adaptive structural theory to support the companies’ efforts to achieve their goals (DeSanctis and Marshall, 1994). Media richness theory2 provides good explanations for many communication related studies, but more recently this theory is questioned as having not a significant impact (Rice, 1992), nor being able to predict the selection of the media (Fulk et al., 1990). It is apparent that the technology cannot be the replacement of technology‐less collaboration and communication. Hence, the use of ICTs has to be carefully evaluated in any industry regarding the ability of technology or software to achieve the organizational requirements and the potential benefits for the organization itself.

1.1.4. Web‐based GIS application

As indicated the previous sections, the number of web‐based applications that use techniques derived from GIS have seen an enormous increase (Haklay et al., 2008). Through a web application, tools equipped with GIS can support a wide range of planning activities and can facilitate the coordination between the planning authorities and pubic in the planning process. Thus, using tools in the planning process can be a simple map of the world to front‐ending complex spatial analyses of spatial distributions and processes ranging from day‐to‐day to future planning which make the process more effective. To give users’ expected results of real time GIS analysis, the proper tool requirements are important with the choice of mapping, development technologies and standards, and database. This further provides an evaluation and assessment between different technologies and their usefulness in different situations in order to perform in a range of circumstances

General considerations of web‐based GIS application

Like many other fast growing information technologies, there is uncertainty for the coherent terminology use when addressing the geospatial datasets “online” distribution as follows: GIS online which is shared geographic information (Plewe, 1997); internet GIS (Peng, 1999); web‐based GIS or simply web GIS (Grunwald et al., 2003). Both internet GIS and web‐based GIS use the client/server computing model

2 http://en.wikipedia.org/wiki/Media_richness_theory.

made up of three basic elements: presentation, business logic and data (Hall, 1994). The presentation element provides the user interface to the system, whereas the business logic deals with the actual computation. The data element holds all information inside the system usually stored in a database (Keßler, 2004). The partition into server and client goes somewhere between three elements, described as thin to thick client depending on his/her participant level (Peng and Tsou, 2003). Web‐based GIS is a GIS distributed across a computer network to integrate, disseminate, and communicate geographic information on the world wide web (WWW) (Peng and Tsou, 2003). Also it provides end‐users3 a cost‐saving solution to access up‐to‐date spatial datasets and information comparing to other GIS systems (Horanont et al., 2002; Painho et al., 2001). Hence, an important part of every web‐based GIS application is its mapping or visualization technology, which makes it possible to show data in the form of maps. Visualization of data as maps has become increasingly popular, with hundreds of websites presenting geographic data. The popularity of web‐based mapping applications arises in large part through the wide dissemination of software that makes it easy for users and developers to publish map data. Improvements in usability through improved user interfaces also account for the increased popularity of visualization techniques (Aoidh et al., 2008). In similar vein, the growing interest in visualization and analysis of social networks has led to the development of several methods of structural analysis in order to analyze individual and group behavior. This visualization is not limited to the display of raw data in maps but is increasingly widely applied in the representation of large spatial databases (Bishop and Lange, 2005).

Information mapping

The information mapping approach is started from the research on how readers deal with large amounts of complex information resulted in a standard approach for organizing and communicating information (Horn, 1965). From this point of view, information mapping is a useful mean to assist information as summarizing and visualizing the non‐ visual content, structure and interrelationships of the bunch of documents. The focus is on two‐dimensional interactive information maps that can be used to summarize large volumes of textual information and can provide interfaces to browse the whole corpus and retrieve particular documents of interest. Information maps are being developed to tackle the modern‐day challenges of information overload – too much, too fast and too unmitigated (Shenk, 1998). What is information mapping? The information map is a visual tool to abstract, summarize and present large data volumes, facilitating interactive investigation by users (Lin, 1997). Typically, it maps non‐ geographical and abstract space information and can be considered as

3 http://en.wikipedia.org/wiki/End‐user.

a part of the larger research area such as information presentation (Stuart et al., 1999). The integrated set of principles and techniques enables to break complex information into its most basic elements and then presents those elements optimally for readers. It makes readers can quickly and easily scan and retrieve the information they need (Horn, 1965). A set of 7 principles of information mapping is to organize information effectively so that it is easy to access, understand, and remember: first, chunking4 is a group content into small manageable units, makes information digestible and comprehensive; second, relevance is to put together what belongs together or omit irrelevant information; third, labeling is to give a meaningful label/title to each chunk; fourth, consistency is to use the same labels, titles, formats and/or structures for the same subjects; fifth, integrated graphics is to use illustrations, figures and tables as integrated part of the next; sixth, accessible detail is to use details/illustrations/clarifications where needed and complete abstract presentations with concrete examples; and last, hierarchy of chunking and labeling is to organize an accessible structure for content chunks by grouping them into larger chucks and labeling them (Namahn, 2000). Based on 7 principles of information mapping, well‐designed information maps have the three key advantages as the following: first, a sense of the whole describes the ability to summarize and meaningfully convey a large amount of information into a limited space, usually a single personal computer (PC) screen; second, revealing hidden connections shows the underlying semantic 5 structures of a collection of documents through shared concepts and the similarity between them; and third, exploration shows users to easily and intuitively browse and forage through the information space (Dodge and Kitchin, 2001).

Web GIS application development standards

The internet or an intranet is an application that indicates web application, accessed over a network (Shklar and Rosen, 2009). Because of web browsers’ ubiquity and convenience for clients, web application is popular and accepted (Peng and Tsou, 2003). Thus, a key reason for its popularity is the capacity to maintain and update it without distributing and installing software on potentially thousands of clients and is the inherent support for cross‐platform6 compatibility (Fowler and Stanwick, 2004). Web applications development standards give the standards related with the actual development of the web GIS application and require different techniques and technologies that can develop the performance of a web GIS application. Web applications development

4 http://en.wikipedia.org/wiki/Chunking_%28computing%29. 5 http://en.wikipedia.org/wiki/Semantics. 6 http://en.wikipedia.org/wiki/Cross‐platform.

standards can be broken down into design standard and development standard as the following (Adnan et al., 2010):

 Design standards: Design standards are related with the pre‐ development for web GIS applications. These are needed to be decided before starting the development of the web GIS application. Website wireframe7 is a concept for web design and development, which is a basic visual guide used in interface design to suggest the structure of a website and relationships between its pages. Web wireframes describe as simple line drawing to show the placement of elements in the web page (Miller, 2008). Because developers can see the web GIS application design in prototype form and give feedbacks, web wireframes enhance the usability of a web GIS application as saving a lot of time and making final design decision before web GIS application development (Adnan et al., 2010).

The recent software engineering innovation described design patterns explains common problems and solutions in object‐oriented programming paradigm (OPP) (Chambers et al., 2000). OPP represents an attempt to make programs more closely model the way people think about and deal with the world. At heart, we can find entities that have behaviors, that hold information, and that can interact with one another (Pillay, 2007). In the case of design patterns, they provide general solutions to commonly occurring problems by using template to clarity the relationship between different entities of a software or web application. They can be used in web‐based GIS applications to standardize the application according to the problem domain and hence tuning the web application to work better (Chambers et al., 2000).

 Development standards: Development standards are to choose an appropriate web GIS application development technology. These describe a way to use different development technologies in the efficient way, explain the use of memory and physical storage, and provide a common standardized protocol for communication with other web GIS applications (Adnan et al., 2010). To achieve web‐based GIS applications, a sort of development technologies is available for different operating platforms. Development technologies are including in active server pages (ASP)8, java server pages (JSP)9, active server pages dot net (ASP.NET)10, and hypertext preprocessor (PHP)11. The

7 http://en.wikipedia.org/wiki/Website_wireframe. 8 http://en.wikipedia.org/wiki/Active_server_pages. 9 http://en.wikipedia.org/wiki/Java_server_pages. 10 http://en.wikipedia.org/wiki/ASP.NET. 11 http://en.wikipedia.org/wiki/Hypertext_Preprocessor.

choice of technologies depends on the developer’s operating environment.

The OPP uses objects and their integrations to design and develop software or web applications with well structured, scalable and better operating performance (Pillay, 2007). In the case of a web‐based GIS application, OPP shows a better choice for developing a web‐based GIS application and copes with the new challenges involving performance and scalability of applications in a real world environment (Chambers et al., 2000). In addition, as one of important web GIS application parts, database management systems (DBMS) is complex and mission‐critical 12 software systems that embodies decades of academic and industrial research and intense corporate software development among the earliest widely deployed online server systems as to pioneer design solutions spanning not only data management but also applications, operating systems, and networked services (Hellerstein et al., 2007). DBMS is more important in the case of web‐based GIS application due to geographical referenced data storage requirements. The web‐based GIS application can use and can display the geographically referenced data in a database in the form of maps. The performance improvement of web‐based GIS application represents how efficiently database indicates the response time of the DBMS for retrieving/storing records and handles multiple read/write requests to different database tables. There are three tuning procedures devised for the enhancement of database performance, appropriate use of normalization, stored procedures, and indexes:

 Normalization is a technique used to reduce data redundancy while maintaining integrity of the data in the database and by dividing a single table into multiple tables as to retain unique field values across different tables. In the case of web‐based GIS applications, the use of normalization depends on the volume of data which given application has to handle. At the same time the normalization increases the number of joins between the tables that need to be resolved structured query language (SQL)13 queries when accessing the data and therefore the web application may work better without the normalization if there are millions of records (Fotache, 2006).  Stored Procedure is similar to procedure that can access input parameters and can return a value back to the calling program. Because stored procedures are stored physically in the database dictionary, DBMS creates the parse plan for their execution when a procedure is called for the first time. This improves the speed access to the database and enhances the performance of the web application using stored procedures (Microsoft, 2009).

12 http://en.wikipedia.org/wiki/Mission_critical. 13 http://en.wikipedia.org/wiki/Sql.

 Database Index enhances the data retrieval speed from a database as an important concept. Database index are created in one or more columns of a table and enables a database system to perform rapid random lookups on the database table simultaneously reducing database server load. The architecture of a database index classifies as clustered or un‐clustered: the clustered index is based on the ordering of the actual data records and the un‐clustered index, by contrast, is not based on the ordering of actual records (Smith, 2006).

1.1.5. Managing knowledge and its mapping

One of the most important resources in any organization is knowledge (Ofek and Sarvary, 2001; Smith, 2001). The success or even the survival of any organization depends on how effectively it manages the knowledge present internally and externally (Drucker, 1994; Egbu, 1999; Switzer, 2008). Organizational knowledge is recognized as a key resource and a variety of perspectives suggest that the ability to marshal and deploy knowledge dispersed across the organization is an important source of organizational advantage (Teece, 1998; Tsai and Ghoshal, 1998). Significant efforts have been made by industries to develop and implement systems to manage capturing, storing and retrieval of explicit project related information. Traditional organizations are beginning to comprehend that knowledge and its inter‐organizational management, as well as individual and organizational capability building, is becoming crucial factors for gaining and sustaining competitive advantages (Preiss et al., 1996). However, not enough attention has been paid towards managing tacit knowledge (Lin et al., 2006; Newell et al., 2006).

Knowledge map classifications

Several definitions on what forms data, information, and knowledge have been named in many literatures. Data is raw numbers and facts, information is processed data, and knowledge is authenticated information as the common view (Dretske, 1981; Vance, 1997). There are two types of knowledge exist within organizations; explicit and tacit which can greatly reduce the time spent on problem solving and can increase the quality of work. However, it can be argued that the presumption of hierarchy from data to information to knowledge with each varying along some dimension such as context, usefulness or interpretability can be misleading (Venters, 2001). What is knowledge map? It can be defined as a knowledge “yellow pages” or a cleverly constructed database that points to knowledge but does not contain it (Davenport and Prusak, 1998). In general, knowledge map indicates to people, documents and databases which enable a person to find a proper knowledge source. For an organization, one needs to study what kind of knowledge work will be as using different solutions for different types before implement any kind of

knowledge management solutions (Ruikar et al., 2007). A matrix provided in Figure 1.2 is a broad classification of knowledge work to understand this better (Davenport, 2005). From the context to managing knowledge, collaboration work is the most difficult to address and this type of work is very iterational and improvisational. Thus, workers who are experts do this in their roles with a certain degree of education and/or experience behind them (Anumba et al., 2003; Davenport, 2005). Hence, organizations need to put workers in more knowledge available to them to improve this type of knowledge work. The static nature of most knowledge maps, however, is an obstacle of disseminate knowledge just‐in‐time 14 (Mertins et al., 2001). With web‐based technologies method, it can enhance a static knowledge map with easy additions and modification (Davenport and Prusak, 1998).

Figure 1.2: Classification matrix of knowledge processes (Davenport, 2005).

Collaborative knowledge management solutions

Knowledge management (KM) has existed long since as a broad and expanding topic (Scarbrough et al., 1999). Many such approaches to KM are identified and have been categorized in various ways (Alavi and Leidner, 2001; Earl, 2001; Schultze, 1998). In today’s information centric world, people deal with a great amount of information every day. Many different kinds of information systems are interpreting data

14 http://en.wikipedia.org/wiki/Just_in_time_%28business%29.

and transforming it into some kind of information (Dave and Koskela, 2009). Many tools and techniques of knowledge management within organizations have been discussed over the years and among these ICTs have prompted workers and organizations to utilize platforms for collaborative knowledge sharing (Hearn et al., 2002; Newell et al., 2006). In the organizational context, KM has existed in different forms and from a knowledge‐based perspective, is necessary to concern how to integrate the disparate knowledge of individual organizational members into products, services, processes and routines that benefit the organization as a whole (Poyhonen, 2005). The knowledge creation basis of organizations is the continuous interaction and conversion from tacit into explicit knowledge among individuals, teams, and organizational to inter‐organizational level (Nonaka et al., 1996). However, there is no formal agreement about what knowledge management actually involves and how it is actually related to knowledge transfer, which is different depending on things and/or people (Fricke and Faust, 2006). Many researchers have discussed that KM cannot be implemented using technology alone even though technology has an important role to play (Anumba et al., 2003; Davenport and Prusak, 1998; Ruikar et al., 2007). They have pointed out that information and communication technologies have been implemented to support KM and also KM oriented non‐information technology is quite effective within organizations. Some KM technologies is using expensive information technology (IT) infrastructure which is difficult to implement and has an increased emphasis on explicit knowledge (Al‐Ghassani, 2002). These tools show the negative impact causing information overload due to unorganized and ad‐hoc information exchange on organizations’ KM capabilities. Information technologies used by knowledge workers for communication are in two categories; channel and platforms (McAfee, 2006). Channels are the low degree of commonality such as emails, direct messaging, and documents management system and in contrast, platforms are the high degree of commonality and are widely available content generated by a selected group of individuals such as intranet, extranet, and information portals. Although ICT’s limitations have been argued by researchers, we need to take what ICT has to offer within the context of knowledge management and recognize what the technology has to offer rather than how it is implemented or managed (Davenport, 2005).

1.1.6. Summary

Reviewing relevant literatures on rural building and their integrations on landscapes, spatial MCDA planning mechanism, collaboration mechanism and technology, web‐based GIS applications, and knowledge management and mapping elaborate the theoretical and technical perspective of this study. Review of these multidisciplinary

research areas provides a theoretical and methodological foundation for this work. Studies on current transformations in the integration of rural buildings and their landscapes have demonstrated the importance to investigate the proper location selection and design criteria/evaluation and the integration and adaptation of information technology in this field. Literature outlined the key issues collaboration which indicates the potentials to bridge the geographical distance among users using technology. By using tools such as web‐based GIS applications, decision‐makers could achieve shared goals. The collaboration mechanism and technology pointed out an approach on how to measure and structure the work tasks of decision‐makers. Also, this method has the advantage that relates with communication and has already produced good results in the industries. They have established the significance to research web‐based GIS application including spatial planning to allow decision‐making for stakeholders. With information technology as a promising tool, collaborative tools are to support the users to be successful based on the environment in which collaboration is applied. The best collaborative technology is if all team members are deeply committed in the complex and intense situation. Thus, knowledge exchanging between participants based information technology tools indicates the strength for future application to support collaborative efforts as a critical actual use. Other background information might need to be added.

1.2. Problem statement

The many man‐made constructions’ cluttering is being introduced in the rural area and their recreational potential is growing and makes human movements to rural areas which is coinciding with the urban sprawl in the last 20th century (Dwyer and Childs, 2004; Van der Wulp, 2009). Although there are some movements to improve the current situation, rural planning has still not evolved to deal with this new rural area changes (Montero et al., 2005) but careful choosing locations of rural buildings which follows and meets certain criteria could mitigate the negative impacts on rural environments (Bell, 1995; García et al., 2006; Tandy, 1979). Thus, to the best of our knowledge, for the brevity’s sake, few studies have been conducted on rural buildings’ spatial clustering process that explicitly integrates MCDA and GIS technique. The use of web‐based information system has significant potential and provides different channels as a part of IT development to help users make better decisions and support knowledge sharing across geographical distributed teams (Thysen, 2000). Whilst the majority of information management processes are heavily based traditional means of information collaboration and communication such as face‐ to‐face meetings with the exchange of paper documents printed out from own computer. The need to increase the efficiency of these processes via exchanging massive volumes of information at high speed

and at relatively low cost has been long recognized by the industry (Deng et al., 2001). The application of ICTs had some success but also had some difficulties. One challenge is dealing with the various software tools each trade is using and their area. Anumba et al. (2002) stated that “in particular, there are very few tools available to support distributed asynchronous collaboration.” Current studies as Orr mentioned (2004) indicate that there are over 260 web‐based collaboration systems (WBCS) available on the market. The appearance of these technologies gives new chances for users to implement this to their own purposes. However, in the current industries, many practitioners are still hesitant using the web‐based applications and even grant little recognition to their potentials. Practitioners’ concerns are that WBCS do not enable them to achieve successful projects or may even waste more time (Laiserin, 2002). With a close investigation of the current methods for determining the location of different types of rural buildings with a landscape, these studies often deal with minimization of the overall environmental impact of these developments and mainly have essentially economic approaches, the analysis of criteria concerning the location strategy (Hsu and Tan, 1999; Inyang et al., 2003). In particular, this research is the first of its kind in applying techniques of MCE/MCDA combined with fuzzy standardization and the SAW for evaluating rural tourism building siting into a landscape on the rural fringe of the northern Extremadura region, Hervás (Spain). Also, there are no the exact systems, the web collaboration systems enabled GIS coupled with the proposed methodology, which can be a unique and cohesive framework to identify and formulate suitable criteria and spatial models for the right spatial planning integration, with the primary aim of highlighting the interrelations between rural tourism buildings and their landscapes to contribute stakeholders’ decision‐making. Only a few research efforts have been conducted on various aspects of web‐based GIS collaboration systems to integrate rural buildings and their surroundings. These studies have rarely focused on the impact of decision supporting, users’ perception, tourism resource, and knowledge mapping together. There is no research that provides empirical advice on how to implement these technologies to integrate rural buildings with their surroundings based on the methodology. Also, the usability of this system has rarely demonstrated empirically. Therefore, there is a need for empirical research to fully investigate the potential of these technologies and enrich understanding of how users can use these technologies for the specific use. This study will guide the development of an appropriate use to integrate rural tourism buildings and their surroundings to solve the current research problem.

1.3. Research outline

This outline explains what each chapter of dissertation articulates for the person who will read. The first chapter presents an introduction to

provide theories of related fields, the motivation referring problem statement, and the outline of subsequent chapters. Chapter 2 demonstrates the research justifications and objectives starting from a previous baseline. Research justifications start with a general summary and then have four different elements which are pursuing any potential research needs: originality; significance of the study; capability of generalization; substantiality. Then, research objectives elaborate to establish a long term goal, a theoretical foundation for clarifying the contribution of the web interface of multi‐ criteria decision support system, predicting users’ perception to integrate rural buildings and their surroundings, together with tourism resource impact, making the knowledge mapping and its usability. Chapter 3 describes the research materials and methodologies, the post positivistic study combining qualitative and quantitative methodologies, which are the importance of multiple measures and observations and the need to use of triangulation to build a better theory (Gorman et al., 1997; Guba et al., 1988). The primary research sources are publications of the academia and industry as well as in‐ depth survey with users. The methodologies in the framework are four phases: a case study elaborating the current status of rural planning; a spatial methodology in order to determine suitable locations of rural buildings; a prototyping outline to implement a web‐based GIS application; finally, a system testing and evaluation using MCE ranking weighting and survey questionnaire analyzed by content and statistics analysis. Chapter 4 summarizes and mentioned the four research results which are already published and in progress in various international journals, having great relevance in the area of application of this work. It was divided into three distinct parts based on the research objectives: a paper with a location selection methodology based on spatial methodologies; two papers with a conceptual web implementation conducted in hypothesis testing based on the proposed methodologies; a paper with a practical testing corroborating and substantiating analytical evidences and discussions from web surveys’ data to identify users’ data related sequences. This thus checks the long term goal, a theoretical foundation for clarifying the contribution of the web application. Chapter 5 summarizes and discusses findings, contributions, originality and generality, to verify the research hypotheses and objectives. The dissertation articulates the scope and limitations of this research and stances the suggestion of possible future researches in the end of this chapter.

JUSTIFICATIONS AND OBJECTIVES

2. Based on the overviews and problem statements earlier in the introduction chapter, this research demonstrates some of justifications and objectives inspired by them as the following.

2.1. Research justifications

The question, why carry out a particular research, is that every researcher has at the beginning of each research. The aim of this research is to strengthen the body of knowledge and to examine facts and theories. This research contributes to the body of knowledge and facts and theories by implementing answers to the problem statements and questions mentioned earlier and current chapter. Four elements are needed to pursue any potential research necessities: an original idea; the significance of the study; the capability of generalization of potential results; and the substantiality that the work will construct fact proofs.

2.1.1. Originality

The proposed web application itself is not new; some similar researches have been performed in the industries and academic fields but there are no the exact applications to achieve the research objectives. Previous researches had investigated several limited and different aspects of tools (Jankowski et al., 1997; Ruiz and Ferández, 2009; Voss et al., 2004), not capable of dealing with both the analytical and communication side of spatial planning and knowledge sharing process within a unique framework.

2.1.2. Significance of study

The integration of the rural building with landscape usually depends more on the right choice of location than on any other weighted factors (Jeong et al., 2012, 2013). Selection of rural buildings’ site is a complex process to solve a discordant relation with other components of rural landscapes, needs many diverse criteria to deal with its situation, and concerns multiple stakeholders (experts and non‐experts) with conflicting views. In this sense, they must bear how rural buildings should be sited or integrated as respecting their environmental emplacement to satisfy multiple criteria such as traditional contexts and residential needs (Bell, 1995; Tandy, 1979). Along with online collaboration systems’ growing, collaboration process is to understand the information content and users’ utilization and to solve problems to make decision (Renger et al., 2008). To ground improvement of existing systems, this research investigates the

specific use of these web collaborative applications with the geographic information system (GIS) techniques that are as simple as presenting a simple map to front‐ending complex spatial analyses. In general, the studies are dealing with data from participants’ involvement and employed case studies. It is a new approach to produce as a byproduct of the use of supporting decision‐making, measuring users’ perception, and making the knowledge mapping together using the technologies. The system developed in this study could be a new alternative to support decision‐making and to measure users’ perception on rural building integration into a landscape and possible tourism impact based on web GIS application and to archive users to share and reuse personal knowledge and therefore, conveniently provide knowledge map for proximate users. This system is a channel to collaborate and communicate to integrate rural buildings and their surroundings for users having the specific and practical purposes. An important benefit of this tool includes a monitoring work process. Another benefit is to determine and demonstrate the feasibility of web GIS application by studying the needs of the practical and academic fields.

2.1.3. Generalizability

This research has used the data from empirical case and survey acquiring previous researches and users’ participation through the web application. For this reason, this study has relatively the capability of generalization.

2.1.4. Substantiality

The research produces the evidence of decision‐making interface with handling information and knowledge, users’ perception with using multiple criteria and knowledge mapping with using participants’ information flow based on web‐based GIS technologies with a spatial methodology, which have not been investigated in that depth prior. The strength of the evidence is outstanding as it is based on practical data and not from experimental or controlled environments. A detailed clarification of the study results can be shown in the following Chapter 4.

2.2. Research objectives

The long term goal of this research is to establish a theoretical foundation for clarifying the contribution of the interface of multi‐ criteria decision support system, predicting users’ perception to integrate rural buildings and their surroundings, particularly on tourism resource impact, and making the knowledge mapping together using the technologies. The web application has been developed to operationalize the proposed theoretical framework. The prototype implemented an online, interactive tool with a database to store practical information and knowledge. The specific objectives of this research are corresponding to:

1) Describe a spatial methodology for determining the location/site suitability of rural tourism building based on the understanding the limitations of the existing regional planning in the northern Extremadura region, Hervás (Spain), using the analytical hierarchy process (AHP) for multi‐criteria evaluations (MCE) combined with fuzzy standardization and the simple additive weighting (SAW) (Eastman, 2003) in a GIS environment.

2) Demonstrate design and implementation of web GIS application with the proposed spatial methodology which can help decision‐makers learn interactively and iteratively about the nature of the problem and their own preferences for desirable characteristic of solution and solve complex spatial problems reflected in the functionality with the associated system and which can identify and formulate suitable criteria and spatial models for the right rural tourism buildings’ integration into their landscapes.

3) Test and observe the effect of the process of how the research can contribute to support consensus on stakeholders’ decision‐ making, allowed them to calibrate the method, measuring users’ perception and knowledge sharing about building integration, defining the interface adequacy, and certifying the possible impact on tourism resource suitable carried out the analyses through the qualitative and quantitative database set.

MATERIALS AND METHODS

3. The research was started with philosophical assumptions labeled as post positivistic study combining with qualitative and quantitative methodologies. Then, it was carried out in four phases where the current status of rural planning with a case study in Hervás (Extremadura, Spain), especially rural building integration considering its landscape, was investigated first; second, a spatial methodology was described in order to determine suitable locations in the proposed case study area; third, prototyping process and actual implementation of web application was elaborated to make an interactive prototype with a spatial method, a take‐off to develop sophisticated web tools; fourth, variables were measured through the web interface where users had participated two variables which are the multi‐criteria evaluation (MCE) ranking weighting and post‐task survey questionnaire, and were analyzed through content and statistics analysis.

3.1. Philosophical assumptions

The stance of this research is labeled as post‐positivism which often combines both qualitative and quantitative methodologies (Gorman and Clayton, 1997; Guba and Lincoln, 1988). Post‐positivistic study is seen as a compromise between the traditional positivist from of inquiry and the more recent alternative forms of inquiry, such as constructivism. Own basic axioms of each research paradigm can guide not only its research process but also the way research which is perceived and applied (Guba, 1992; Pickard and Dixon, 2004). Table 3.1 outlines the basic axioms of the traditional positivist, post‐positivist and constructivist research paradigms (Guba and Lincoln, 2005; Pickard and Dixon, 2004). Moreover, the implications of this research are connected to those beliefs. Post positivists assert that the goal of research is to try continuously to achieve the goal obtaining absolute truth and objectivity, even though we never fully achieve that goal. Therefore, post positivists emphasize the importance of multiple measures and observations and the need to use triangulation to build a better theory (Denzin and Lincoln, 1994; Guba and Lincoln, 1988). Based on this perspective, the research will be both quantitative and qualitative.

Table 3.1: Axiomatic contrasts of research paradigms (Pickard and Dixon, 2004).

Issue Positivism Post‐positivism Constructivism

Critical realism – Ontology: “real” reality but Relativism – local Naive realism – Dealing with only imperfectly and specific co‐ “real” reality but the nature of and constructed apprehensible being probabilistically realities apprehensible

Epistemology: Dealing with Modified the nature of Objectivist/dualist objectivist/dualist Subjectivist/transac knowledge, its (knower can be (objectivity tional (researcher presuppositions, independent of the approximated by and subject are foundations, known) external interdependent) extent and verification) validity Modified Hermeneutical/dial Experimental/mani experimental/mani ectical; empathetic pulative; pulative; critical interaction verification of multiplism; Methodology between researcher hypotheses; chiefly falsification of and subject; quantitative hypotheses; may interpretation and methods include qualitative interaction methods Context and time Context and time dependent independent Context and time generalizations Outcomes of generalizations dependent working leading to models the research leading to ‘natural’ hypotheses leading for predictions; immutable laws or to understanding probabilistically predictions true laws

3.2. Current status of rural planning with the selected case study

The study area is Hervás15, an approximately 60 km2 area located in the Ambroz Valley region of the northern Cáceres province (Extremadura) on the border of the Salamanca province (Castilla y León) and in the foothills of the Béjar and Gredos Sierra. Hervás is one of 8 municipalities in the Ambroz Valley region: Abadía, Aldeanueva del Camino, Baños de Montemayor, Casas del Monte, La Garganta, Gargantilla, Hervás, and Segura de Toro. Due to its large population, this area is the administrative and commercial center of the Ambroz Valley region. In this region, land use is dominated by a multifunctional agrosylvopastroal system, the Dehesa16, corresponding to specific cultural landscape which deciduous forests predominated with the chestnut tree that gives an important nucleus of chestnut product companies. Also this system corresponds to high biological,

15 See Chapter 4.1.1 to 4.1.4 which describe the case study area and its fringe region. 16 http://en.wikipedia.org/wiki/Dehesa_%28pastoral_management%29.

scenic and recreational value with abundant rivers and wetlands that are tourist destinations for the summer period. As some researchers have already mentioned, development in rural regions depends on complex economic, social and political processes (Terluin, 2003). Looking at the study region, the most significant income source of this area during 18th and 19th century was the traditional wood working and crafts from a socioeconomic view. From the fifties to eighties, the abandonment, an enormous emigration to the cities, happened in this study area which was evolving on a new regional mosaic (Nieto Masot and Gurría, 2001). Furthermore, the socio‐economic and political transformations in Extremadura, which led to increased agricultural wages, coupled with migration from the countryside, made it difficult to maintain low‐cost manual shrub clearing and traditional management (Jaraíz et al., 2013). In the nineties, the introduction of several European initiatives in Extremadura occurred to change this region for the sustainable rural development (LEADER and PRODER projects). The LEADER (91/C180/12) and the PRODER (Royal Decree 206/1996 dated 9 February 1996) projects are both public programs which adopt on a local initiative approach, targeting rural areas as their field of intervention. Although two programs have a scope difference, both programs are aimed at promoting rural development, locally based with local partners, and pursue a development model, not based exclusively on agricultural activities. During the last decades, rural buildings’ developments due to the holiday residences’ growths and its natural environments have increased for tourist activities which show the results of significantly increased constructions of new hotels and rural houses (Jaraíz et al., 2013; Montero et al., 2005). These do, however, cause their consequent impacts. As we can see similar issues in other countries, the continuing development in urban and rural environments has caused substantial changes to land use which are reflected in the loss of traditional landscapes (Pinto‐Correia, 2000; Pinto‐Correia and Mascarenhas, 1999; Tassinari et al., 2008). In a very short period, it has resulted in the destabilization of the nature due to the accelerated land use changes associated with tourism and urbanization. The recent response for the current situation (LESOTEX, Law 15/2001 of land and landscape planning of Extremadura) is linked to territorial and regional planning: plans, programs and different actions including territorial repercussion but cannot give the proper answer for this situation yet because of not giving a coherent answer to the real problems for their planning. Rural development changes are progressing faster than the rise of their understanding and awareness (Wascher et al., 1999). The current unsuccessful planning policies and instruments need modification and/or new alternatives which need to be developed and implemented. Also, the planning process is put forward for public debate to obtain alternative suggestions, objections and views and for collaboration with other associations and individuals.

3.3. Multi‐criteria spatial methodology

In the study area, Hervás (the northern Extremadura region), aforementioned, although some planning policies have been practiced by people that had an approximate knowledge of the region, they cannot support to deal with their real planning problems which will give the proper and coherent answer. According to the way of evaluation criteria’ influence to rural tourism building integration, extensive criteria and evaluation steps are considered to identity the best available building location and to eliminate subsequent impacts (i.e. debasement of visual attraction and recreational value and degradation of ecosystem) and adverse long‐term effects (i.e. substantial changes to land use, loss of traditional landscape and quality deterioration of local environment). Although criteria weights are objectively based upon real data, the weights assignment in the process of MCE are considered partly subjective because it is dependent upon decisions made by the authors, based on the relevant literatures, regional polices and European Union (EU) directives. To reduce possible authors’ subjectivity, to verify the weights generated, and to reach a consensus for weights, an analytical procedure is considered, a group discussion for final criteria consensus with a panel of experts (Eastman et al., 1993; Kapetsky and Nath, 1997). The MCE gives transparent ways to systematically organize and analyze complicated decision‐making problems and to support the elicitation of preferences in participatory decision‐making within a structured framework (constraints, physical, environmental and socio‐ economic) (Hwang and Yoon, 1981; Keefer et al., 2004; Malczewski, 1999). Extensive criteria and evaluation processes are considered and classified into six constraints and three main criteria with each four sub‐criteria involved in the computation process as the follow17:

 Constraints: The following six constraints limit the analysis to the particular geographic areas (1) environmentally protected areas, sensitive ecosystem following European commission regulation for nature & biodiversity policy (NATURA, 2000); (2) important aquifers such as springs and/or ground water wells with high groundwater pollution risk; (3) surface water bodies to prevent water surface pollution; (4) specific vegetation and land use types with the dense vegetation formation; (5) highways and railways followed by legal limits for minimum distance; (6) areas prohibited to construct commercial buildings by the regional building ordinance.  Factors relevant to physical evaluations: The following four factors related with the physical evaluation of the selected study area were analyzed; (1) morphology: having an important

17 The evaluation criteria, sub‐criteria and constraints were followed by the fourth result in Chapter 4: Approaches to validating a mutual participatory web‐planning interface in rural Extremadura (Spain).

role for environmental attributes’ derivation along with slope, aspect and specific catchment area and plan (Gallant and Wilson, 2000); (2) orientation: showing the better aspect for aesthetical reason not for any legal restrictions and having environmental attributes’ derivation; (3) land use: resolving public conflicts over the acceptance of unwanted buildings integration to consider the current land development from the Landsat bands of the digital elevation model (DEM)18; (4) visibility: aiming to preserve the aesthetic protection of inhabited areas from the designated points but not based on any legal restrictions.  Factors relevant to environmental concerns: The following four factors related with the environmental concern of the selected study area were analyzed; (1) sensitive ecosystem: dealing with the potential pollution or degradation of natural environments of unique ecological and/or aesthetic interest based on legal restrictions (NATURA, 2000); (2) water source: including springs and/or groundwater wells calculated using Euclidean distance functions using ESRI ArcGIS 9.3; (3) surface water: relating with lakes and rivers with continuous water flows which have a potential final receiver of treated or even untreated pollution; (4) vegetation type: including the ecological uniqueness of the forested and deforested vegetation and spatial spread of these natural formations based on the normalized difference vegetation index (NDVI)19.  Factors relevant to socio‐economic parameters: The following four factors related with the socio‐economic evaluation of the selected study area were analyzed; (1) site access infrastructure: including the existing transport networks, the main routes for tourists, such as highways, local roads and train railways; (2) population density: considering an influence zone around city, town and human settlement associated with economic activities; (3) residential area: relating with towns and villages representing a high concentration of human activities associated the surrounding resources’ demands besides the presence of urban centers; (4) tourism resource area: including tourist, cultural and urban area examined by the various distance calculations from each zone and by the legal restrictions based on land use and cover type.

First screening using exclusionary criteria can represent as dividing the study area in two land categories: suitable (suitability index 1) and unsuitable (suitability index 0). All criteria in the 3 categories (physical, environmental and socio‐economic) were quantified using a common scale, i.e., a 0‐255 byte grading value. The grading value 0 was assigned to the least suitable areas and 255 to the most suitable ones,

18 http://en.wikipedia.org/wiki/Digital_elevation_model. 19 http://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index.

transforming the different measurement units of the factor images into comparable suitability values. In the process, a sigmoidal fuzzy membership function, monotonically increasing and monotonically decreasing, was the most commonly used function (Eastman, 2003)20. There were four parameters specifying the sigmoidal membership function: (a) membership rises above 0; (b) membership becomes 1; (c) membership falls below 1; (d) membership becomes 0. Fuzzy functions can standardize map layers in geographic information system (GIS) and evaluate the possibility of each pixel belonging to a fuzzy set by evaluating any of a series of fuzzy set membership functions (Voloshyn et al., 2003). The approach consisted of the following steps:

(a) Development of a digital GIS database development incorporating all spatial information. To create a digital geo database using the spatial analysis tools provided by GIS, ESRI ArcGIS 9.3 as a commercial GIS software was used to perform the spatial analysis processes (Maguire, 1991); (b) Determination of constraints and evaluation criteria and formation of the hierarchical multi‐criteria structure; (c) Implementation of the analytical hierarchy process (AHP) method implementation combined with fuzzy function standardization to extract the criteria relative importance weights based on pair‐wise comparisons (Eastman, 2003). By comparing pairs of criteria, decision makers can quantify their opinions about the magnitude of the criteria; (d) Implementation of the simple additive weighting (SAW) method to calculate suitability indexes.

The AHP method is an effective approach to extract the relative importance weights of the criteria in a specified decision‐making problem. One of the most crucial steps in any multiple criteria problem is the accurate estimation of the pertinent data. Although qualitative information about the criterion importance can be found, it is difficult to quantify it correctly. The AHP has steps including specifying the hierarchical structure, determining the relative importance weights of the criteria and sub‐criteria, assigning preferred weights of each alternative and determining the final score (Faraji Sabokbar, 2005). The next stage was to specify the relative importance weights of the criteria and sub‐criteria through pair‐wise comparison. The AHP is based on pair‐wise comparisons, which are used to determine the relative importance of each criterion. By comparing pairs of criteria at a time and using a scale expression, decision makers can quantify their opinions about the criteria’s magnitude (Saaty, 1996). The pair‐wise comparison matrix (PCM) formed by the decision makers must keep in mind the following attributes, aii = 1 and aij = 1/aji.

20 See http://www.corp.at/archive/CORP2012_45.pdf (Fig. 3: The Sigmoidal fuzzy membership functions (A‐monotonically increasing, B‐monotonically decreasing, C and D‐symmetric curves) in the proceedings entitled as “A spatial assessment for re‐ mixing buildings on the rural fringe of Spain” of the publication list [p. xv]).

The criteria’s relative importance weights implied by the previous comparisons were calculated. The estimation of the right principal eigenvector21 of the PCM is approximated using the geometric mean of the PCM’s each row (Saaty, 1996). Then, the application of the SAW method estimates the suitability index which is a widely utilized method for the calculation of final grading values in multiple criteria problems (Hwang and Yoon, 1981). Evaluation criteria were combined in a grid that contains all grades calculated from each of the separate grids. The grading values for each evaluation criterion are included in the complex grid at the appropriate attribute field (Chen and Hwang, 1992). The relative importance weights of the evaluation criteria were calculated by using the PCM matrix as shown in Eq. (1) (Yoon and Hwang, 1995):

∑ (1)

where Vi is the suitability index for area i, wj is the relative importance weight of criterion j, vij is the grading value of area i under criterion j, n is the total number of criteria.

3.4. Web prototyping process

Generally, prototyping consists of building an experimental system rapidly and inexpensively to evaluate (Laudon et al., 1994). This section indicates that the concept and feasibility of the web prototype application demonstrated in the following procedure as shown in Figure 3.1. The four process model of development and testing is described to be a beginning model for demonstration and evaluation purposes. These steps are described in detail in the following paragraphs.

Figure 3.1: The outline of web prototyping process.

Process 1: Verification of basic requirements

This step is to identify the basic requirements of users for the web prototype application. To satisfy research justifications and objectives,

21 http://en.wikipedia.org/wiki/Eigenvector.

types and volumes of data such as decision‐making, measurement of users’ perception and knowledge mapping, will be analyzed in the following Chapter 4. What types of data will be used? Who will be involved with the data? How will the data be organized or shared? The questions as the above will be collected to approach this basic process.

Process 2: System design specification

This step is to achieve the needs of users as to consider system forms and capabilities. The following components are consisted to show the system design concepts22:

 The conceptual model: This model prescribes the major constituents of the overall system structure and function. Moreover, it is a model that describes how the system works.  The user model: It is a model that explains how users will use the system and matches users’ practical needs. Also, this model describes system components and their relationships each other.  The user interface design: This process prescribes the function of system interface. It will help users employ this system with accessibility and efficiency, which are the major aspects of this stage which describe specifically in the following step.  The system database design: This is a process of defining database model and the concept of data entities and database management.

Process 3: System implementation

This step is to develop a web prototype application according to the basic requirements and the design concepts mentioned above. The general structure of this prototype is a client/server system, defining the collaboration and communication between clients and servers (Umar, 1997). The conceptual framework of the web‐based GIS application used fundamentally consists of a general overview area, a multi‐criteria spatial decision supporting system borrowed from GIS, a knowledge map area and a post‐task questionnaire area in the consistent approach of a single user interface via the internet as illustrated its workflow in Figure 3.2. The web application is compatible with any web browser but is required to use higher than version than Internet Explorer (IE) 8.0. All four sections have a single web form for authenticated users. Users that choose not to log in are non‐authenticated and are only able to browse only first part of the

22 See http://www.corp.at/archive/CORP2011_23.pdf (Section 5. Conceptual design in the proceedings entitled as “Web‐based interoperability system: a collaborative method to integrate rural buildings with their surroundings” of the publication list [p. xv]).

system and cannot actively participate in the rest part of application process23.

Figure 3.2: The prototype application workflow process24 in the view of client‐ side and in the view of server‐side, cshtml (C#) was used to make the coding paradigms.

The client/server model defines the communication between clients and servers (Umar, 1997). In this research, it is important to indicate that we applied the system architecture pattern, model‐view‐controller (MVC) which the programming language Smalltalk25 first defined the MVC concept it in the 1970’s as shown in Figure 3.3. Especially in object‐oriented systems, its design idiom has become commonplace since that time. It is common to think of an application as having three main layers: presentation (UI: user interface), application logic, and resource management but MVC architecture separates the data from its presentation and business logic. Specifically, we applied the ASP.NET MVC4 Framework26 in this study which is an open source web application framework that implements the MVC pattern. An example is as shown in the following extract which specifies the controller part of MCE weighting ranking selection:

{ public class MCSDController : controllers.SessionsController {

23 See Chapter 4.1.4 which demonstrates some screenshot images of the implemented web application. 24 See Appendix B presenting the detailed workflow process chart done by Microsoft Office Visio 2007 [p. 157]. 25 http://en.wikipedia.org/wiki/Smalltalk. 26 http://en.wikipedia.org/wiki/ASP.NET_MVC_Framework.

public string GetMenuForSteps( ) { return Classes.CMenuConstructor.GetSubMenu(cSession.l angueSelected, CLBusiness.CConstants.MENU_MCSD, (in t)CLBusiness.CEnums.ActionsForMscd.Evaluation); public string StepsResume( ) { . . . return CLBusiness.C .CDataAccess.SaveStepsComment(Cl asses.CPaths.GetXmlDataPath(Request), step,cSession.use r_active.userId, comments); } } }

Figure 3.3: A typical collaboration of the MVC components.

technology of the internet and stands for the fifth revision of the hypertext markup language (HTML) standard. Thus, for dynamic programs, JavaScript is a commonly used client side scripting language, which is responsible for the communication between the server and the client. Thus, the term Ajax27 is introduced in this study and has envisaged a new era of web application in which "richness", "responsiveness" and "simplicity" were the key words involved (Garrett, 2005). The acronym “Ajax” stands for asynchronous JavaScript and extensible markup language (XML). In fact, the techniques enabling Ajax are more than what is motioned in the full name. An example is as shown in the following extract which specifies a sub‐criteria selection of MCE ranking weighting process:

. . . } function showImage(messageShow) { if (filteringSelection() == false) { if (messageShow == 'ShowMessage') alert('Please select one of parameters'); } else { $.ajax({ url: '@Url.Action("LoadMapStep2", "MCSD")', data: { selMorphology:$("#selMorphology :selected").val(), selOrientation: $("#selOrientation :selected").val(), selLandUse: $("#selLandUse :selected").val(),selVis ibility: $("#selVisibility :selected").val() }, success: function (data) { $("#divImage").html(data); . . . }

To operate the web prototype application, some functional and technical requirements need to be classified (Haklay et al., 2008). Functional requirements for a web GIS application include the ability such as real‐time data acquisition and analysis, user‐side operation with a web browser only, performance of under a few seconds per request and low maintenance cost for the user across heterogeneous

27 http://en.wikipedia.org/wiki/Ajax_%28programming%29.

computing environments. Technical support requirements include hardware, software, and internet connection, and some development tools. The internet connection used should have a wide bandwidth. The general overview area was structurally divided into four sections and each section comprised of a single web page: the home page gave introductory information about the research, the user instruction, the contact information, the registration form and the login page by which a user could fully access the system and facilitate access to other resources. The multi‐criteria spatial decision supporting system supported the building location/site selection associated with the suggested spatial process. Each step had its own function to document users’ knowledge through comment transcript in the bottom of the main work area. It was expected that a single person would not have the full view and in‐depth knowledge required. The knowledge map area absorbs all parts of the application including comment transcripts and personal tacit knowledge (Polanyi, 1996), and represents the final resource for sharing and reuse among users as a communication space. Therefore, users enhance their own experiences and tacit knowledge through the knowledge mapping process. Finally, the post‐task questionnaire verifies the users’ perception of building integration within the rural landscape28. To perform the proper execution of the interface, we followed some requirements, functional and technical support such as real‐time data acquisition, user‐side operation and low maintenance cost that give heterogeneous computing environments for functional ones and hardware, software, internet connection and development tools for technical ones, need to be classified (Haklay et al., 2008). Thus, to understand different types of website users and their cognitive factors, we adopted the user analysis which guided to design the web model according to five usability measures: easy to learn; efficient for the user; easy to remember; be equipped with built‐in error protection; and, subjectively pleasing (Nielsen, 1994; Sawasdichai and Poggenphol, 2003). The general aim of web prototype is a multi‐criteria application with the selected case study area, especially suitable for rural tourism buildings integrations and their elements for decision‐makings in a sense of both supporting the analysis of participants’ different aspects, and presents an interface for remote participation via the web.

Process 4: Prototype testing

This step is to demonstrate first approach of web prototype application testing: developer testing to assess usability and capability of the system which is also to find out whether the prototype application works correctly and accomplishes the design concepts. The prototype is classified by the following: this phase incorporates the data creation of rural tourism buildings and their surroundings by the developer.

28 See Chapter 4.1.4 which presents 16 post‐task survey questionnaires based on 4 different categories.

The actual users do not involve in the developer testing. This is only to be carried out by the developer to fix bugs which are encountered during the process of decision‐making, perception assessment, knowledge mapping, and survey participation.

3.5. Measurement variables

This step is to explicit empirical testing to evaluate its interface, usability to check decision‐making, users’ perception, and documenting personal knowledge as a map in the practical fields. This phase of the prototype testing is associating with a multi‐criteria decision analysis (MCDA) ranking weighting and a survey in the form of a post‐task questionnaire. Participants, actual users, will receive the questionnaire page after using the web application. Through the measurement variables, this step is also to evaluate the logical and physical concepts of the application. The functionality of the application will be evaluated in order to conclude whether the application can be effectively used within the practical fields. In this study, the data were collected via the implemented web‐ based interface, e‐shift (www.e‐shift.eu). Through the interface, users have participated two variables which are the MCDA ranking weighting and post‐task survey questionnaire. Both variables were first tested in a pilot study and then developed further. Altogether, these comprised 258 participants who were categorized into items related with socio‐demographic background. The MCDA ranking process yielded a total 243 responses from the sample, amounting to 94% of the total number of the actual participants to the web interface. On the other hand, the web‐based post‐task questionnaire survey gave a total 212 responses from the sample, amounting to 82% of the total number of the actual participants to the web tool. Two sample data were analyzed using content and statistics analysis approaches.

MCDA ranking weights and survey questionnaire

The design, implementation and execution of the preference elicitation for the MCDA tasks, the rural tourism building integrations, are a significant part of the overall task effort. In the process of the AHP weights determination, users directly decide their own set of weights while they are using the proposed interface. The three criteria with four sub‐criteria are the extent of detection with participants’ history data in the whole 4 steps. All data assigned by users is directly saved to the database management system (DBMS). After ranking weights through the interface, participants can involve with the post‐task survey questionnaire. The process to select locations for rural building integrations using the MCDA, here users can explore the study area and then express their preferences on three main decision criteria, namely physical, environmental and socio‐economic criteria and equal weight depending on users’ preference. Users must log in and select one

criterion out of three available which is given the maximum score and the remaining criteria are weighted with respect to this or can select the equal weight for three criteria. Easton (1973) and Malczewski (1999) have described this simplification technique based on the ratio estimation procedure. Then, in the following pages, users need to weight sub‐criteria showing the relative importance of the decision criteria at the same time. The relative importance, using a drop down menu that displays the exact value, assigns 1 to the least suitable and 10 to the most suitable. After evaluating all decision criteria and sub‐ criteria, a final page displays the classification of the selected feasible site results and in this page users can decide to apply constraints into the final map and categorized suitability area as simply checking a radio button. At this point, users are more aware of the task that they are involved in and, arguably, are better able to judge the parameters of location integration (Jeong et al., 2012). The expected scope, design, validation, analysis and use of the preference survey need to be described29. First, a web‐based survey questionnaire have been designed as clear manner using up‐to‐date standards which will perform individual preference elicitations due to the large number of participants to be surveyed (Reips, 2002). To get as many respondents as possible, it is based on an interactive web‐based survey which will not only provide a qualitatively better elicitation of preferences but will directly store the results in a data server. The technical implementation was achieved to generate dynamic web‐ pages, the online questionnaire and to save the transferred data to database server. Thus, it did not contain additional plug‐ins or special software on the clients’ side computer. Another important factor for ensuring the acceptance of web‐based survey was the validation of intended participants’ requirements. As a confirmatory step, personal interview have been conducted to validate the survey as designed by conducting a limited number to check any difference in preferences revealed by the survey. In the other way, we can do a follow‐up after the full survey.

Measures

There are two types of measures to collect variables in this study. First is the weighting ranking of the MCDA process which quantified using a common scale, i.e., a 1 to 10 grading value. The grading value 1 was assigned to the least favorable criteria and 10 to the most favorable one, transforming the different measurement units of the factor images into comparable suitability values. Then, the items used to collect information based on the survey about each of the indicators of attitude toward rural tourism buildings integration, perceived quality, and interface satisfaction employ five‐point scales ranging from (1) completely disagree to (5) completely agree, respectively since the AHP

29 See Chapter 4.1.4, Fig. 4. The flow diagram of the web‐based post‐task survey questionnaire [p. 108].

scales are from 1 to 10 which are too fine. The remaining survey grades are interpolated from the minimum to maximum values.

Data analysis

Data was analyzed using qualitative and quantitative methods including content analysis, statistics analysis and frequent classification result count for knowledge sharing. Content analysis focuses on collecting qualitative and quantitative data on various types of the MCDA, MCDA comment history, and knowledge classification and comment history that are employing a coding scheme. To understand the participants’ opinions on the interface, the web‐based post‐task questionnaires were distributed to the participating users to collect quantitative data. Also, to comprehend the characteristics and relationships of samples, statistics analysis techniques based on the analysis of variance (ANOVA) test at the 0.1 significance level and the principal component analysis (PCA) test were applied to analyze the questionnaire data30. The results from the survey are expressed as means ± standard deviation and were analyzed using a one‐way ANOVA. When ANOVA detected significant differences between mean values, means were compared using Tukey’s test31 at the p ≤ 0.1 significance level. For statistical studies, SPSS 15.0 software was used (SSPS Inc., Chicago, IL, USA). Principal components and classification analysis were assessed by using the Unscrambler 9.8 software (CAMO Process AS, Oslo, Norway). The web‐based survey provide an interactive analysis of alternatives, thus not only assuring a qualitatively better elicitation of preferences, but also providing a valuable incentive to complete the survey which will assure a consistency between the specified preferences and the resulting, Pareto‐efficient solution32. Thus, frequent counts of the MCDA classifications indicates to gather quantitative data which is showing the knowledge sharing process, saved to the different database server.

30 See Chapter 4.1.4, Fig. 6. Score plot after PCA of the individuals in the four cluster groups defined by the two first PCs PC1 and PC2 and Fig. 7. Loading plot after PCA of the variables in the questions defined by the two first PCs PC1 and PC2 [p. 117]. 31 See http://academic.udayton.edu/gregelvers/psy216/spss/1wayanova.htm. 32 See http://en.wikipedia.org/wiki/Pareto_efficiency.

RESULTS

4. The results obtained in this dissertation are collected in four papers published or processing in various international journals covered by the Science Citation Index,33 Journal Citation Reports34 and all of great relevance in the area of application of this work. Generally, it is divided into three distinct parts according to research objectives mentioned earlier in Chapter 2.

4.1. Summary overview

The research results which are already published and progressing in various international journals are divided into three parts with four papers based on the research objectives:

First, this paper presents a multi‐criteria spatial decision analysis approach using geographic information system (GIS) technique for evaluating the suitability of rural buildings site selection with a case study in Hervás (northern Extremadura region), Spain. The aim of the methodology is to evaluate the suitability of the study region in order to optimally site a new single dispersed tourism‐related commercial building with landscapes. Combination of a spatial clustering process reveals the most suitable areas for rural buildings siting with their landscapes. The proposed methodology is intended to solve the rural building integration problem with its landscape and to facilitate the flexible methodology implementation from decision alternatives involved in the decision making process.

Second, these two papers describes web design and implementation with methodologies that support a decision‐making processes for establishing harmonious relationships and sustainable environment integrity within a unique framework. It developed a spatial methodology for integrating new rural buildings associated with tourist functions into landscapes and coupling multi‐criteria evaluations (MCE) into a web environment that uses a GIS technique. Through the proposed web design and implementation, users can learn interactively and iteratively about the nature of the problem, and their own preferences for desirable characteristics of solution, the knowledge map supports and stimulates the sharing of opinions and, hence the clarification and discussion of interests behind user’s preferences.

33 See http://thomsonreuters.com/products_services/science/science_products/a‐ z/science_citation_index/. 34 See http://thomsonreuters.com/products_services/science/science_products/a‐ z/journal_citation_reports/.

Third and final, in this article, a mutual participatory web‐planning interface is developed to support rural tourism building integrations into a landscape that combine multi‐criteria decision analysis (MCDA) with the aid of the simple additive weighting (SAW). Starting with the implemented web interface with the methods, stakeholders can reflect their individual experience to achieve desirable planning outcomes by the asynchronous and distributed collaboration with the increased public participation. Based on the qualitative and quantitative content and survey data set, this study examines the identification of spatial models for the different perceptions and knowledge sharing of building integrations into a rural landscape, the certification of the possible impact on tourism and the definition of interface usability.

4.1.1. A site planning approach for rural buildings into a landscape using a spatial multi‐criteria decision analysis methodology

A site planning approach for rural buildings into a landscape using a spatial multi‐criteria decision analysis methodology

Land Use Policy 32, 108‐118 (2013)

Jin Su Jeong, Lorenzo García‐Moruno, Julio Hernández‐Blanco

Selection of rural buildings’ site is a complex process to solve a discordant relation with other components of rural landscapes and needs many diverse criteria to deal with its situation. This paper presents a multi‐criteria spatial decision analysis approach using geographic information system (GIS) technique for evaluating the suitability of rural buildings site selection with a case study in Hervás (northern Extremadura region), Spain. The aim of the methodology is to evaluate the suitability of the study region in order to optimally site a new single dispersed tourism‐related commercial building with landscapes. The analytical hierarchy process (AHP) is used to generate the alternative decisions using the multi‐criteria evaluation techniques standardised by fuzzy membership functions. The parameters are categorised into three criteria groups, namely physical, environmental and economic criteria and then the weights are verified by a group discussion with the experts for final weight consensus making them more objective. With the aid of the simple additive weighting (SAW) method, the calculation of final grading values in multiple criteria problem is evaluated for the study region. The resulting land suitability is reported on a grading scale of 0–10, which is, respectively, from least to most suitable areas. Combination of a spatial clustering process reveals the most suitable areas for rural buildings siting with their landscapes. The proposed methodology is intended to solve the rural building integration problem with its landscape and to facilitate the flexible methodology implementation from decision alternatives involved in the decision making process.

Keywords: rural building location planning; multi‐criteria decision analysis; analytical hierarchy process; suitability assessment.

1. Introduction

The suitable siting planning of the numerous man‐made elements is related with various interconnected factors which affect to the building itself and the relationship between the building and the current countryside environment and raises the questions of how negative impacts on these factors can be minimised (De Vriesa et al., 2012; Jeong et al., 2012; Tassinari and Torreggiani, 2006). The many man‐made constructions’ cluttering is being introduced in the rural area and its’ recreational potential is growing and makes human movements to rural areas which is coinciding with the urban sprawl in the last 20th century (Dwyer and Childs, 2004; Van der Wulp, 2009). As a powerful tool, tourism also has long been identified for development, spurring economic growth, increasing foreign exchange, smallholder investment, and local employment (De Kadt, 1979). However, regional planning has not evolved to deal with this new rural area changes (Montero et al., 2005) but careful choosing locations of rural buildings which follows and meets certain criteria could mitigate the negative impacts on rural environments (Bell, 1995; García et al., 2006; Tandy, 1979).

The spatial modelling used by geographic information system (GIS) allows for analyzing large volumes of spatial data which give geographical expression to the economical, social, cultural ecological policies of societies (Böhme and Schön, 2006; Hermann and Osinski, 1999). GIS offers useful tools to study the location in depth when considering spatial planning limitations, opportunities, visual characteristics and the overall landscape scene (Domingo‐Santos et al., 2011; Hernández et al., 2004b; Tassinari and Torreggiani, 2006). From this modelling, decision‐makers (or planners and local authorities) can find the current state of affairs and some idea of future conditions, ideally the possible consequences of the plans and policies they may have under consideration (Blaschke, 2006). The problems of spatial planning usually incorporate a large number of stakeholders (experts and non‐experts) with different backgrounds, interests, authorities and interpretations of some of their issues (Fountas et al., 2006). A collaborative process is the right way to reconcile the individual approaches and to make decisions satisfying all or most participants (users: stakeholders and the public) (Jankowski et al., 1997).

Multi‐criteria evaluation (MCE) is one particular type of spatial planning to help decision makers explore and solve multiple and complicating problems (Hwang and Yoon, 1981; Malczewski, 1999; Roy, 1996). This process forms three phases: first, identifying the problem; second, designing the alternative solutions to the problem; third, choosing the best alternative of the decision making process (Forman and Selly, 2001). Decision‐making includes choosing from various criteria and alternatives. The criteria usually have different importance and the alternatives in turn differ on users’ preference for them on each criterion. We need a way to measure to make such tradeoffs and

choices. Measuring needs a good understanding of the measurement methods as well as the different scales of measurement (Saaty, 1996, 2005). The analytic hierarchy process (AHP) is a widely accepted decision‐making method that is an effective approach to extract the relative importance weights of the criteria in a specified decision‐ making problem (Gemitzi et al., 2006; Saaty, 1996, 2005). One of the most crucial steps in any multiple criteria problem is the accurate estimation of the pertinent data. Although qualitative information about the criterion importance can be found, it is difficult to quantify it correctly (Faraji Sabokbar, 2005).

A close investigation of the current methods was carried out for determining the location of different types of rural buildings with a landscape. These studies often deal with minimization of the overall environmental impact of these developments and mainly have essentially economic approaches, the analysis of criteria concerning the location strategy (Hsu and Tan, 1999; Inyang et al., 2003; Lahdelma et al., 2002). To the best of our knowledge, for the brevity’s sake, few studies have been conducted on rural buildings’ spatial clustering process that explicitly integrates multi‐criteria decision analysis and GIS. In particular, this paper is the first of its kind in applying techniques of MCE combined with fuzzy standardisation and the simple additive weighting (SAW) for evaluating rural building siting into a landscape on the rural fringe of the northern Extremadura region, Hervás (Spain). By identifying local level criteria and indicators for spatial planning and evaluating alternative management schemes in a participatory decision environment, this study fills a crucial knowledge gap in design and planning processes and implementing sustainable rural development management in the Extremadura region. Also, this study is relevant to other rural areas with comparable socio‐ economic and environmental set‐up.

The present paper describes a method for determining the site suitability of new single dispersed tourism‐related commercial building based on the understanding the limitations of the existing regional planning in the northern Extremadura region, Hervás (Spain), using the AHP for MCE combined with fuzzy standardisation and the SAW (Eastman, 2003) in a GIS environment. The methodology presented herein evaluates the entire study area using a common grading scale, i.e. 0–10 byte grading value, where 0 values a site fully unsuitable for new rural building integration while 10 values a site optimum for its integration. Evaluation criteria are determined based on European planning policy (Council of the European Union, 2001) and regional planning law on Extremadura (LESOTEX, Law 15/2001 of land and landscape planning of Extremadura) and the relevant literature review which make the innovation of the evaluation criteria used and then we have a group discussion with a group of experts to validate the criteria’s weights more objective although they were objectively based upon real data. Evaluation criteria identify a spatial data treatment

with a grading system based on physical, environmental and economic aspects. In addition, the utilisation of sophisticated spatial statistics methods is an innovation in the rural building siting process, giving some efforts in the analysis of the results, showing the tools provided by GIS and spatial statistics are very important. Also, another goal of this research is to show this technique’s flexibility as exploring different decision alternatives and patterns. The proposed approach is illustrated using a case study which is discussed and the methodology applied in this study in “Materials and methods” section. “Results” and “Conclusions” sections discuss the results and the conclusions from this approach.

2. Materials and methods

A sound rural building siting process into a landscape requires the considerations of extensive criteria and evaluation steps in order to identify the appropriate location or locations and to eliminate the overall negative impact and its subsequent effect on rural environment which affect to choose the criteria and in the weight attributed in the case study region. In the proposed study area, tourism‐related jobs can be found in many different sectors, including food service, lodging, entertainment, retail sales, travel planning, and sectors providing transport services. In addition, local planning laws give building design guidelines directly and restrictions as well, regarding to maximum building area, maximum building height, and maximum number of floors. Based on this information, we define that the general characteristics of the building, a single dispersed tourism‐related commercial building, have the construction size: 80% building to land ratio and 200% floor area ratio of 100 m2 land (based on 10 m × 10 m grading cell) with minimum 3 m floor height as depicted in Fig. 1 (Hernández et al., 2007).

Fig. 1: An example of a single dispersed tourism‐related commercial building based on the proposed construction size.

A substantial multi‐disciplinary evaluation process with multiple set of criteria is applied through the use of the spatial analysis tools provided by GIS with MCE enhanced fuzzy factor standardisation, based on

certain evaluation criteria (physical, environmental and economic). In this paper, the SAW method is selected for the evaluation of the final suitability index to solve the multiple criteria problem. The research procedures are as shown in Fig. 2 that presents the flowchart of the siting model:

 Standardising a GIS database development which includes all spatial information related with the study region.  Determining the evaluation criteria which form the multi‐ criteria hierarchical formation.  Using pair‐wise comparison matrix (PCM) to determine the relative importance weights by implementing the AHP method. As shown in Table 1, decision‐makers can apply their opinions for quantifying the extent of the criteria and sub‐criteria.  Aggregating the criteria weights and attribute values to yield suitability scores of the areas using SAW method.  Implementing a spatial clustering process to represent the suitable siting areas.

Fig. 2: Flowchart of rural building siting model.

The methodology presented here did not initially exclude unsuitable areas as a primary screening and the whole region was evaluated for new tourism‐related commercial building siting. The methodology, therefore, resulted as the land evaluation based on the suitability indexes. In a certain attribute map, the suitability grade assignment for every class is carried out in the ArcGIS software. In the study case area of Hervás (Spain), the suitability index is assessed as to use the SAW.

Table 1: The relative importance of pair‐wise comparison and its numerical rates.

More Less important Definition important intensity intensity Equal importance or 1 1 preference More or less equal to moderate 2 1/2 importance or preference More or less moderate 3 1/3 importance or preference More or less moderate to 4 strong importance or 1/4 preference More or less strong importance 5 1/5 or preference More or less strong to very 6 strong importance or 1/6 preference More or less very strong 7 1/7 importance or preference More or less very to extremely 8 strong importance or 1/8 preference More or less extreme 9 1/9 importance or preference

2.1. Description of the study area

Hervás is the study region analysed in the present paper located in the Ambroz Valley region of the northern Cáceres province (Extremadura) of Spain between 40◦51ʹ26ʹʹ N and 5◦16ʹ57ʹʹ W as depicted in Fig. 3. The region has a total area of approximately about 60 km2. In this region, land use is dominated by a multifunctional agrosylvopastroal system, the Dehesa, corresponding to specific cultural landscape which deciduous forests predominated with the chestnut tree that gives an important nucleus of chestnut product companies. Also this system corresponds to high biological, scenic and recreational value with abundant rivers and wetlands that are tourist destinations for the summer period.

Fig. 3: Location of the study area in Hervás (northern Extremadura), Spain.

As some researchers have already mentioned, development in rural regions depends on complex economic, social and political processes (Terluin, 2003). Looking at the study region, the most significant income source of this area during 18th and 19th century was the traditional wood working and crafts from a socioeconomic view. From the fifties to eighties, the abandonment, an enormous emigration to the cities, happened in this study area which was evolving on a new regional mosaic (Nieto Masot and Gurría, 2001). Furthermore, the socio‐economic and political transformations in Extremadura, which led to increased agricultural wages, coupled with migration from the countryside, made it difficult to maintain low‐cost manual shrub clearing and traditional management (Jaraíz et al., 2013). In the nineties, the introduction of several European initiatives in Extremadura occurred to change this region for the sustainable rural development (LEADER and PRODER projects). The LEADER (91/C180/12) and the PRODER (Royal Decree 206/1996 dated 9 February 1996) projects are both public programmes which adopt on a local initiative approach, targeting rural areas as their field of intervention. Although two programmes have a scope difference, both programmes are aimed at promoting rural development, locally based with local partners, and pursue a development model, not based exclusively on agricultural activities. During the last decades, rural buildings’ developments due to the holiday residences’ growths and its natural environments has increased for tourist activities which show the results of significantly increased constructions of new hotels and rural houses (Jaraíz et al., 2013; Montero et al., 2005).

These do, however, cause their consequent impacts. As we can see similar issues in other countries, the continuing development in urban and rural environments has caused substantial changes to land use which are reflected in the loss of traditional landscapes (Pinto‐Correia, 2000; Pinto‐Correia and Mascarenhas, 1999; Tassinari et al., 2008). In a

very short period, it has resulted in the destabilisation of the nature due to the accelerated land use changes associated with tourism and urbanisation. The recent response for the current situation (LESOTEX, Law 15/2001 of land and landscape planning of Extremadura) is linked to territorial and regional planning: plans, programmes and different actions including territorial repercussion but cannot give the proper answer for this situation yet because of not giving a coherent answer to the real problems for their planning. Rural development changes are progressing faster than the rise of their understanding and awareness (Wascher et al., 1999). The current unsuccessful planning policies and instruments need modification and/or new alternatives which need to be developed and implemented. Also, the planning process is put forward for public debate to obtain alternative suggestions, objections and views and for collaboration with other associations and individuals.

2.2. Evaluation of the decision‐making criteria

Although criteria weights are objectively based upon real data, the weights assignment in the process of MCE are considered partly subjective because it is dependent upon decisions made by the authors, based on the relevant literatures, regional polices and European Union (EU) directives. To reduce possible authors’ subjectivity, to verify the weights generated, and to reach a consensus for weights, an analytical procedure is considered, a group discussion for final weight consensus with a panel of experts (Eastman et al., 1993; Kapetsky and Nath, 1997). In this study, an expert panel including professors, regional policy makers, planners and local authorities who will be one of decision‐ makers for regional projects for regional projects was involved in the weighting process for this application. Then, the selected criteria and sub‐criteria are classified into three main criteria with sub‐criteria, namely, physical, environmental and economic criteria. Fifteen sub‐ criteria are involved in the computation process, more specifically (1) elevation; (2) slope; (3) aspect; (4) vegetation type; (5) visibility; (6) presence of sensitive ecosystem following European commission regulation for nature and biodiversity policy (NATURA, 2000); (7) presence of water source; (8) presence of surface water; (9) land use

types and planning policies; (10) proximity to urban area; (11) site access; (12) population density; (13) proximity to residential area; (14) proximity to tourist area; (15) proximity to agricultural area. The first physical criteria group includes criterion 1–5; the second environmental one comprises criterion 6–10; the third economic one involves criterion 11–15. The hierarchical structure of decision process consists of four levels: first level shows the main goal, rural building suitability; second level represents criteria which support the main goal; third level is sub‐criteria of each criterion; fourth level demonstrates the spatial attributes of each sub‐criterion.

2.2.1. Physical criteria

First criteria group comprises the five sub‐criteria, specifically, elevation, slope, aspect, vegetation type and visibility which are related to the physical and morphological evaluation of the selected study area as shown in Fig. 4 using the weighted factors from Table 2:

Elevation: Elevation is a basic parameter and an important role in earth surface and atmospheric process and for environmental attributes’ derivation along with slope, aspect and specific catchment area and plan (Gallant and Wilson, 2000). In this study, locations with higher elevations with the maximum height 1725 m are usually not technically suitable for the selection of new rural buildings construction. The spatial representation of land elevation with the sub‐criterion weight (0.15) is shown in Fig. 4a. Slope: As a basic parameter, slope is for environmental attributes’ derivation and affects many important landscape processes such as erosion potential, runoff rates and velocity of overland and subsurface flow. The slope is an important sub‐criterion in the proposed methodology which was expressed in degrees. Sites with steep slopes are usually not technically suitable for new rural buildings construction. The grading was based on the premise that the flatter area, the greater its suitability for rural buildings’ construction. The spatial representation of land slope with the sub‐criterion weight (0.07) is depicted in Fig. 4b. Aspect: Aspect as one of sub‐criterion in physical criteria is for the better orientation for aesthetical reason not for any legal restrictions and also is a basic parameter such as elevation and slope for environmental attributes’ derivation mentioned earlier. Aspects with south and west orientation in the study area are usually less suitable based on the geographical analysis to site new rural buildings integration. The spatial representation of land aspect with the sub‐ criterion weight (0.05) is shown in Fig. 4c. Vegetation type: Vegetation type includes the evaluation based on the ecological uniqueness of the deforested vegetation and the spatial spread of these natural formations covering four types of the study region: dense vegetation formation; scattered vegetation formation; the cultivated land and the rocky terrain; non‐cultivated and the

pastures (LESOTEX). In this study, dense vegetation formation is less suitable for new rural building siting. The spatial representation of vegetation type with the sub‐criterion weight (0.28) is shown in Fig. 4d. Visibility: Visibility aims to the aesthetic protection of inhabited areas as to site the new rural buildings which are not based on any legal restrictions (Hernández et al., 2004b). The radial and visible distances from the site accessing point such as main roads (highways and local roads) of the study area are usually less suitable for new rural buildings integration. In this case, direct distance was not sole parameter because the study area is relatively close to urban centres and roads which cannot be seen due to surface morphology. The spatial representation of visibility analysis with the sub‐criterion weight (0.43) is shown in Fig. 4e.

Table 2: The physical criteria calculation of pair‐wise comparison matrix in relation to the five sub‐criteria.

Pair‐wise comparison 9 point continuous rating scale: the physical criteria Vegetation Sub‐criteria Elevation Slope Aspect Visibility Weights type Elevation 1 0.15 Slope 1/3 1 0.07 Aspect 1/4 1/2 1 0.05 Vegetation 3 4 5 1 0.28 type Visibility 4 5 6 2 1 0.43

λmax = 5.19, CI = 0.048, RI5 = 1.12 and CR = 0.04 < 0.1.

2.2.2. Environmental criteria

Environmental criteria have five sub‐criteria, presence of sensitive ecosystem following European commission regulation for nature & biodiversity policy (NATURA, 2000); presence of water source; presence of surface water; land use type; proximity to urban area which are related with the evaluation of the selected study area as shown in Fig. 5 based on the weighted factors from Table 3:

Sensitive ecosystem: Sensitive ecosystem is significant due to the potential pollution or degradation of sensitive ecosystems. This sub‐ criterion is included in the European commission regulation for nature & biodiversity policy, NATURA (2000). According to the legislation, new buildings should not degrade natural environments or areas of unique ecological and/or aesthetic interest. In this study, close to the sensitive ecosystem is less suitable for new rural building integration. The spatial representation of sensitive ecosystem with the sub‐ criterion weight (0.28) is shown in Fig. 5a.

Water source: The spatial determination of the water source needs to be simplified from the water buffer zones calculated using Euclidean distance functions that measure a straight distance. Water sources in the presented study include in springs or groundwater wells (Gemitzi et al., 2006). The radial distances from these sources are usually less suitable for new rural buildings siting. The spatial representation of water sources with the sub‐criterion weight (0.09) is shown in Fig. 5b. Surface water: Each surface water source is a potential final receiver of the risk analyses, relating to those carried out by to meet their EU Water Framework Directive (WFD, Directive 2000/60/EC) obligations associated with the protection of surface water ecology. The information derived was especially needed to notify future risk analyses and inform strategies to reduce the associated uncertainties (Page et al., 2012). Surface water is also using the spatial determination as calculated using Euclidean distance functions. In this study, lakes and rivers with continuous water flows were considered as surface water sources. The radial distances from these surface waters are usually less suitable for new rural buildings siting. The spatial representation of surface waters with the sub‐criterion weight (0.12) is shown in Fig. 5c.

Land use: Land use is significant to resolve public conflicts over the acceptance of unwanted buildings integration. The land use criterion differs from the vegetation type criterion in that it aims to consider economic development covering eight types of the study region: dense vegetation formation; scattered vegetation formation; surface water; the cultivated land and the rocky terrain; non‐cultivated and the pastures; agricultural area; urban area; industrial parameters that are affected by the siting of adjacent new rural buildings (LESOTEX). In this study, dense vegetation formation same as the vegetation type criterion is less suitable for new rural building siting. The spatial representation of land use with the sub‐criterion weight (0.45) is shown in Fig. 5d. Urban area: The direct distance of sites under examination from urban areas was taken into account to determine the grades of this sub‐ criterion. The land cover uses an unsupervised classification incorporating an iterative process of a random selection from the pixels’ spectral reflectance from the Landsat bands of the digital elevation model (DEM) (Tassinari and Torreggiani, 2006). The closer distances from urban area in the presented study area are usually less suitable for new rural buildings integration. The spatial representation of urban area proximity with the sub‐criterion weight (0.06) is shown in Fig. 5e.

Table 3: The environmental criteria calculation of pair‐wise comparison matrix in relation to the five sub‐criteria.

Pair‐wise comparison 9 point continuous rating scale: the environmental criteria Water Surface Land Urban Sub‐criteria Ecosystem Weights source water use area Ecosystem 1 0.28 Water 1/4 1 0.09 source Surface 1/3 2 1 0.12 water Land use 2 5 4 1 0.45 Urban area 1/4 1/2 1/2 1/6 1 0.06

λmax = 5.09, CI = 0.023, RI5 = 1.12 and CR = 0.02 < 0.1.

2.2.3. Economic criteria

Economic criteria category has five sub‐criteria, site access; population density; proximity to residential area; proximity to tourist area; proximity to agricultural area. As mainly having essentially economic approaches, a large number of existing studies deal with the criteria analysis, concerning the location strategies to be implemented for processing sites (Hsu and Tan, 1999; Jovanovic, 2003). These economic criteria are related with the evaluation of the selected study region as shown in Fig. 6 using the weighted factors from Table 4:

Site access: The existing road networks are the main routes of transport tourists which allow them to access to the study areas. Highways, local roads and train railways are the sources of site access infrastructures. Euclidean distances from the existing roads and railways were calculated using minimum distances from infrastructure features to every grid cell. The closer distances from each site access in the presented study area are usually less suitable for new rural buildings integration. The spatial representation of site access infrastructures’ proximity with the sub‐criterion weight (0.28) is shown in Fig. 6a. Population density: Dense population considers an influence zone around city, town and human settlement associated with economic distances, according to the 2011 census data provided by the national statistical institute (INE: instituto nacional de estadística) of Spain. The further distances from a higher population are considered as less suitable for siting new rural building in the presented study area. The spatial representation of the dense population with the sub‐criterion weight (0.05) is shown in Fig. 6b. Residential area: Residential area including towns and villages represents a high concentration of human activities associated the surrounding resources’ demands besides the presence of urban centres. The closer distances from the residential area are considered as less

suitable for integrating new rural building in the presented study region. The spatial representation of the residential area proximity with the sub‐criterion weight (0.09) is shown in Fig. 6c. Tourist area: Tourist area including cultural and archaeology zone is important during the rural building siting process due to the rich economical and cultural background of the study area. According to the legislation, siting a building in areas of cultural interest is not allowed to protect the national cultural inheritances including archaeological and historical sites. The closer distances from the tourist area are considered as less suitable for integrating new rural building in the presented study region. The spatial representation of the tourist and cultural area proximity with the sub‐criterion weight (0.43) is shown in Fig. 6d. Agricultural area: Areas around the existing agricultural fields are more likely to undergo land use changes (LESOTEX). Areas with minimum distance with legal restrictions are required to protect them. Euclidean distances from the existing agricultural areas were calculated using minimum distances from agricultural fields’ features to every grid cell. The closer distances from the agricultural area are considered as less suitable for integrating new rural building in the presented study region. The spatial representation of the agriculture area proximity with the sub‐criterion weight (0.15) is shown in Fig. 6e.

Table 4: The economic criteria calculation of pair‐wise comparison matrix in relation to the five sub‐criteria.

Pair‐wise comparison 9 point continuous rating scale: the economic criteria Site Residential Tourist Agricultural Sub‐criteria Population Weights access area area area Site access 1 0.28 Population 1/5 1 0.05 Residential 1/4 2 1 0.09 area Tourist area 3 5 4 1 0.43 Agricultural 1/3 3 2 1/3 1 0.15 area

λmax = 5.18, CI = 0.045, RI5 = 1.12 and CR = 0.04 < 0.1.

Fig. 6: (A) Hierarchical structure shows the general aspect with the attention of economic suitability map process to make the decision of rural buildings siting problem. (B)Economic suitability derived by 0.28, 0.05, 0.09, 0.43 and 0.15 factor weight for (a) site access, (b) population density, (c) residential area, (d) tourist area and (e) agricultural area sub‐criterion.

2.3. Evaluation of site suitability

Land use suitability mapping and analysis is one of the most useful applications of GIS for planning and management (Brail and Klosterman, 2001; Collins et al., 2001; Hopkins, 1977; McHarg, 1969). Generally defined, land use suitability mapping and analysis tries for identifying the most appropriate spatial pattern for future land uses, regarding with its requirements, preferences, and/or predictors of some activity (Collins et al., 2001; Hopkins, 1977). In this step, the methodologies were used to combine the evaluation criteria determining the site suitability for new tourism‐related commercial building into a landscape. Starting with the AHP combined with fuzzy standardisation, we got the relative importance weight using the PCM and the grading values as examining and judging the current condition of the indicators under each criterion. Then, the SAW method mentioned earlier was utilised for the suitability index calculations.

2.3.1. Standardising map layers using the fuzzy logic

Map layers are standardised in GIS by fuzzy functions. Fuzzy functions evaluate the possibility of each pixel belonging to a fuzzy set by evaluating any of a series of fuzzy set membership functions. To apply

fuzzy functions in the GIS environment in this case study, all the map layers are digitised or imported and converted to a raster format with 10 m × 10 m grid cells. All criteria in 3 categories (physical, environmental and economic) were quantified using a common scale, i.e. a 0–10 grading value, with 0 as the least and 10 as the maximum suitability rate at each criterion. In the process, a sigmoidal fuzzy membership function, monotonically increasing and monotonically decreasing, was the most commonly used function (Eastman, 2003). There were four parameters specifying the sigmoidal membership function: (a), membership rises above 0; (b), membership becomes 1; (c), membership falls below 1; (d), membership becomes 0. Fuzzy functions can standardise map layers in GIS and evaluate the possibility of each pixel belonging to a fuzzy set by evaluating any of a series of fuzzy set membership functions (Voloshyn et al., 2003).

2.3.2. The AHP method and application

The AHP as an MCE technique was utilised to extract the relative importance weights of criteria and was applied for formulate the assessment system in a specified decision‐making problem (Saaty, 1996; Zeleny, 1982). This method based on the PCM is to specify the hierarchical structure, to determine the relative importance weights of the criteria and sub‐criteria, and to assign preferred weights of each alternative and determine the final score. The PCM structured by the decision‐makers is depending on the perceived importance of each criterion using certain predetermined points of scale as shown in Table 1 (Balana et al., 2010). In this study, a nine‐point scale was used and must obey the following attributes, aii = 1 and aij = 1/aji. The calculations of criteria’ relative importance weights are the next step which is implied by the previous comparisons. The estimation of the right principal eigenvector of the PCM can be approximated using the geometric mean of each row of the PCM (Saaty, 1996). If the PCM is perfectly consistent, then aij = aik × akj for all possible combinations of comparisons in the PCM. It is rare to have a perfectly consistent PCM. The AHP method includes an index called consistency ratio (CR) that indicates the overall consistency of the PCM (Golden et al., 1989; Vargas and Zahedi, 1993). According to Saaty (1996), the CR should have a value of less than 10%, indicating consistency of the matrix. The PCM formed by authors based on the real data and the consensus group discussion with the experts in the present paper as shown Tables 2–4 the calculated priority weight of all criteria is shown in the last column of each table. The AHP parameters indicate the judgements of the final relative importance weights that seem reasonable.

2.3.3. Suitability index calculation

The method, the application of the SAW, as the last step was used a 9 point scale to extract information that a score is given to each indicator by comparing the indicator’s current status relative to some desired condition. Then, it is to calculate the final grading values in multiple‐

criteria problems (Hwang and Yoon, 1981) based on the grading scale used in the present work for the suitability index is 0–10, which is, respectively, from the least to the most suitable area as shown in Eq. (1) (Yoon and Hwang, 1995). Each indicator shows a score to compare the indicator’s current status relative to some desired condition: score 9 is the indicator presenting the excellent performance condition; score 7 is the indicator showing the good performance condition; score 5 is the indicator explaining the acceptable performance condition; score 3 is the indicator displaying the fair performance condition; score 1 is the indicator demonstrating unfavourable performance condition to each desired condition. Intermediate indicators, 2, 4, 6 and 8, are using to each desired scoring condition (Balana et al., 2010; Chen and Hwang, 1992).

∑ (1) where Vi is the area i’s suitability index, wj is the criterion j’s relative importance weight, vij is the grading value of area i under criterion j, n is the total number of criteria. Evaluation criteria were combined in a grid that includes all grades calculated from each separate grid. Each evaluation criterion’s grading values are contained in the complex grid at the appropriate attribute field.

4. Results and discussion

Regarding the final land suitable map layer, the appropriate areas were identified for new rural building siting of Hervás (the northern Extremadura region), Spain (see Fig. 7). The methods of SAW were selected as the proper way to dissolve the multiple criteria problem of new single dispersed tourism‐related commercial building with landscapes. As shown in Fig. 7, the possible clustering scenarios were illustrated as using three major criteria which were combined with fifteen sub‐criteria as the previous step.

The maps in Fig. 7 use four different scenarios generated by different weights applied to the criteria. For instance, alternative (a) applies equal weights to three criteria (0.33); alternative (b) applies a weight of 0.50 to the physical criteria and a weight of 0.25 to the rest criteria; alternative (c) applies a weight of 0.50 to the environmental criteria and a weight of 0.25 to the rest criteria; alternative (d) applies a weight of 0.50 to the economic criteria and a weight of 0.25 to the rest criteria. Also, Fig. 7 presents that land suitability increases as the suitability index increases. Areas with suitability indexes from 0 to 4 can be generally considered as unsuitable for new rural building siting. Sites with grades ranging from 9 to 10 are expected to be the best sites for new rural building siting in the proposed study area. For example, it shows the categorised percentage area: the best area in alternative (a) is 6.19% with high membership values of 9–10 from total area; alternative (b) assigns the most suitable area of 7.28% with high membership values of 9–10 from total area; alternative (c) assigns the

most suitable area of 3.05% with high membership values of 9–10 from total area; alternative (d) assigns the most suitable area of 7.12% with high membership values of 9–10 from total area.

The results of the clustering process are also interesting to point out that different spatial patterns have been generated by the weights assigned to the physical, environmental and economic objectives and to indicate that the presented methodology is able to reveal the most suitable areas for new single dispersed tourism‐related commercial building to its environment, as well as to give an initial ranking of the suitable areas. Therefore, integrated multi‐criteria spatial decision model based on the methodology presented in the proposed paper with the developments mentioned earlier can be very useful in the final decision.

5. Conclusions

This paper presents an efficient application of GIS‐based multicriteria evaluation for characterising and assessing suitable sites of new single dispersed tourism‐related commercial buildings into a rural landscape in the Hervás area (the Extremadura region), Spain. In particular, the

case study has presented an approach of the AHP/SAW clustering procedures for generating a wide range of decision alternatives for these rural building suitability problems, considered to eliminate subsequent impacts and adverse long‐term effects which affect to choose it. The MCE was utilised to form the siting problem into a decision structure of four hierarchical levels: the goal, evaluation criteria, sub‐criteria and spatial attributes. Then, the AHP method was utilised to extract the relative importance weights of the evaluation criteria and the SAW method is utilised to calculate the suitability indexes, in order to solve the rural building integration problem with its landscape.

The selection of criteria presented in this work was limited to only currently available data from public sources in accordance to Extremadura (LESOTEX, Law 15/2001 of land and landscape planning of Extremadura) and EU legislation and relevant literatures. Thus, as an analytical procedure, a group discussion session with the experts was considered to reduce authors’ subjectivity, to identify the weights generated, and to reach a consensus for weights. The methodology presented, however, is flexible as far as criteria’ determination is concerned. Also, the methodology can easily extend as taking other parameters of criteria and sub‐criteria which could yield different decision alternatives. The main goal of these preliminary results, therefore, is the flexible methodology implementation rather than all possible criteria and sub‐criteria evaluation. The study results demonstrate that the goal of the approach is not to find a single suitable solution, but to explain the weighting flexibility strengths of the application. Likewise, the methodology discussed in this paper can be very useful not only in the final decision but also in the decision‐ making process.

Acknowledgements

The authors express their thanks to the financial support from Ministerio de Ciencia e Innovación (BIA 2007‐61166) and Captación y Formación de Recursos Humanos de Excelencia en Investigación, Desarrollo e Innovación (Universidad de Extremadura) which have spurred and are spurring this research.

4.1.2. Integrating buildings into a rural landscape using a multi‐criteria spatial decision analysis in GIS‐enabled web environment

Integrating buildings into a rural landscape using a multi‐ criteria spatial decision analysis in GIS‐enabled web environment

Biosystems Engineering 112(2), 82‐92 (2012)

Jin Su Jeong, Lorenzo García‐Moruno, Julio Hernández‐Blanco

There is often a difficult relationship between rural buildings and the landscape. This may be overcome by methodologies that support a decision‐ making processes for establishing harmonious relationships and sustainable environment integrity within a unique framework. Preliminary results are presented from a continuing broad research project developing a spatial methodology for integrating new rural buildings associated with tourist functions into landscapes and coupling multi‐criteria evaluations (MCE) into a web environment that uses a geographic information system (GIS) technique. Use of the internet allows users easy access to diverse GIS data sources and also allows support collaboration amongst planners, stakeholders and the public. The aim of this methodology, which applies an overlay and index method involving several parameters, is to evaluate its suitability in the study region, Hervás, Spain, in order to optimally plan for rural building integration within its landscape. The methodology used intermediate suitability maps classified by five evaluation criteria, namely physical, visual, economic, social, and environmental criteria. A combination of the five intermediate maps resulted in a final composite suitability map for buildings in a rural landscape. The possibility of designing and implementing a GIS‐ enabled web application with the methodology, consisting of a general overview, a multi‐criteria spatial decision support system, an interoperable knowledge map and a post‐task questionnaire to identify spatial models for the different perceptions of building integration within the rural landscape and to certify the possible economic impact on tourism, is presented.

Keywords: rural building integration; web‐GIS; multi‐criteria evaluation; collaborative planning.

1. Introduction

Over the last few decades, particularly in Southern Europe, there has been significant and often discordant changes in the relationship between rural buildings and their landscapes (Mennella, 1997). Tourism has long been identified as a powerful tool for development, spurring economic growth, increasing foreign exchange, smallholder investment, and local employment (De Kadt, 1979). European landscape planning policy has particular building codes to protect local cultural identity and promote landscape quality (Council of the European Union, 2001). In some cases, tourism has resulted in increased environmental protection and funds for environment conservation (Pigram, 1980). However, the appropriate integration of man‐made constructions into their surroundings is not yet a common consideration in general planning practice (De Vriesa, de Grootb, & Boersb, 2012; Tassinari, Torreggiani, Paolinelli, & Benni, 2007). Professionals must consider appropriate integration and environmental location in mind to harmoniously balance rural buildings associated with tourism within their landscape setting (Bell, 1995; Tandy, 1979).

Decision making is particularly complex when multiple stakeholders (experts and non‐experts) are involved in spatial planning (Fountas, Wulfsohn, Blackmore, Jacobsen, & Pederson, 2006). Multi‐criteria evaluation (MCE) is one particular type of spatial planning that has been developed to help decision makers (or planners) explore and solve multiple complicated problems (Hwang & Yoon, 1981; Malczewski, 1999; Roy, 1996). Because of the number of factors involved, collaborative processes can be seen as an integration process aimed at solving complicated decision making (Renger, Kolshoten, & Devreede, 2008). A range of participants with different levels of individual experience are able to share their knowledge to investigate compromise solutions and resolve conflicting views to provide desirable planning outcomes (Simão, Densham, & Haklay, 2009). Over the last decade, efforts have been made to develop integrative tools capable of dealing with both the analytical and communication side of spatial planning and design process within a unique framework (Jankowski, Nyerges, Smith, Moore, & Horvath, 1997; Ruiz & Ferández, 2009; Voss et al., 2004). The definition of such a framework assumes critical importance because the internet appears to provide the primary mechanism for allowing interested stakeholders the opportunity to participate in the planning and design process using asynchronous and distributed collaboration (Voinov & Bousquet, 2010).

Several researchers have referred to general design criteria for improving the visual impact of the appearance of rural buildings in the landscape. The characteristics considered include the correct siting of the buildings in relation to the natural contours of the landscape; their shape and form, materials of construction, colours, textures,

subdivision of volumes; their relationship to existing buildings and groupings; the organisation of the space surrounding the buildings which links them to the landscape (Di Fazio, 1988; Schmitt, 2003; Smardon, 1979). The integration of the building with landscape usually depends more on the right choice of location than on any other weighted factors (Montero, López‐Casares, García‐Moruno, & Hernández‐Blanco, 2005). Geographic information systems (GIS) offers useful tools to study the location in depth when considering spatial planning limitations and opportunities, visual characteristics, and the overall landscape scene (Domingo‐Santos, Fernández de Villarán, Rapp‐Arrarás, & Corral‐Pazos de Provens, 2011; Hernández, García, & Ayuga, 2004b; Tassinari & Torreggiani, 2006). GIS is also a helpful tool in solving current situations and market research has shown an enormous increase in web‐based applications that use GIS techniques (Haklay, Singleton, & Parker, 2008). After a proposed location has been selected, the scene in which the building is to be set needs investigation and analysis to consider the visual elements of the scene that characterise the landscape in terms stakeholders’ interests (Ayuga, 2001; Español, 1995; García, Hernández, & Ayuga, 2006; Smardon, 1979).

The objective of this work was to present a spatial methodology for the integration of new rural buildings associated with tourist functions and their landscapes coupling both MCE and GIS techniques, together with application of the approach to a case study in Hervás, Spain. The emphasis was to design and implement a GIS‐enabled web‐based application developed with the proposed methodology which can identify and formulate suitable criteria and spatial models for the right spatial planning integration, with the primary aim of highlighting the interrelationships between rural buildings and their landscapes. The application developed in this study could be a new approach to support decision making, to measure user perception, to archive personal knowledge maps which can be conveniently shared and reused, and to certify the possible economic resource associated with tourism. Thus, this system could be used as a channel to collaborate and communicate the integration of rural buildings and their surroundings to users who have specific and practical purposes.

2. Materials and method

2.1. Selected case study

The study area was Hervás, an approximately 60 km2 area region located in the Ambroz Valley region of the northern Cáceres province (Extremadura) on the border of the Salamanca province (Castilla y León) and in the foothills of the Béjar and Gredos Sierra as shown in Fig. 1. Hervás is one of 8 municipalities in the Ambroz Valley region: Abadía, Aldeanueva del Camino, Baños de Montemayor, Casas del Monte, La Garganta, Gargantilla, Hervás, and Segura de Toro. Due to its large population, this area is the administrative and commercial centre of the Ambroz Valley region. In terms of geographical and

landscapes features, water resources in this region are essential for both the agrarian and leisure activities. This region is dominated by deciduous forests with the chestnut tree as the outstanding species.

Fig. 1: Location of the study area used in developing the prototype.

From a socio‐economic view, the most significant income source of this area during 18th and 19th century was traditional wood working and crafts. A large emigration to the cities resulted in depopulation area from the 1950s to the 1980s (Nieto & Gurría, 2001). In the early 1990s, this trend coincided with the introduction of several European initiatives in Extremadura, Spain (LEADER and PRODER projects) that encouraged sustainable rural development, especially in those rural municipalities which had higher economic deficits. Due to the development of holiday residences and the area’s natural environment, the development of rural buildings for tourist activities has increased during the last few decades.

The development of buildings for tourism does, however, have consequential impacts. As some researchers have described, the continuing development in urban and rural environments has caused substantial changes to land use which are reflected in the loss of traditional landscapes (Tassinari, Carfagna, Benni, & Torreggiani, 2008). Over a short period, it has resulted in the destabilisation of nature due to the accelerated land use changes and urbanisation. In response to these changes, a recent regional law in Spain (LESOTEX, Law 15/2001 for Land and Landscape Planning of Extremadura) has tried to provide a coherent answer to land use and landscape planning problems for the Extremadura community. Notwithstanding this, many municipalities are still awaiting their general planning approval by the administration in agreement with this regional legislation (LESOTEX). Municipal planning has failed to keep up with the requirements imposed by the new rural urbanism (Montero et al., 2005). Rural developments, therefore, need to be considered both in terms of sustainable environment integrity and collaborative human goals expressed within the planning and design process.

2.2. Criteria group description and application

In order to determine suitable locations for integrating new rural buildings concerned with tourism to their surroundings in Hervás, Spain, different methods such as overlay and index method involving several parameters were applied through the use of the spatial analysis

tools provided by geographic information system (GIS) with multi‐ criteria evaluation (MCE) enhanced with fuzzy factor standardisation. The evaluation criteria used in this research were classified into five main categories, namely physical, visual, environmental, social and economic criteria involved the computation process and selected on the relevant literature, regional polices and EU directives mentioned earlier.

Fourteen sub‐criteria were involved in the computation process, allocated to five main categories according to the way they influence rural building integration to their landscapes. More specifically, the following 14 sub‐criteria were introduced into the computation process: (1) morphology; (2) orientation; (3) vegetation type; (4) external visibility; (5) internal visibility; (6) presence of sensitive ecosystem following European Commission Regulation for Nature & Biodiversity Policy (NATURA, 2000); (7) presence of water source; (8) land use types and planning policies; (9) population density; (10) proximity to urban area; (11) proximity to cultural area; (12) site access; (13) proximity to residential area; (14) proximity to tourist and agricultural areas as shown in Fig. 2, the four level hierarchical structure of the decision evaluation problem. The first level, rural building location suitability, represented the decision‐making goal, the second level represented five different criteria to achieve the first level, the third level represented each sub‐criteria and the fourth level represented the spatial attributes of each sub‐criteria.

Fig. 2: Hierarchical structure of decision evaluation problem.

The study area was rasterised into 10m × 10m grid cells. All criteria in the 5 categories were quantified using a common scale, i.e., a 0‐255 byte grading value. Each of these grid cells revealed a single site‐sized land parcel for the purposes of further analysis. The grading value 0 was assigned to the least suitable areas and 255 to the most suitable ones, transforming the different measurement units of the factor images into comparable suitability values. In the process, a sigmoidal fuzzy membership function, monotonically increasing and monotonically decreasing, was the most commonly used function (Eastman, 2003). There were four parameters specifying the sigmoidal membership function: (a), membership rises above 0; (b), membership becomes 1; (c), membership falls below 1; (d), membership becomes 0. Fuzzy functions can standardise map layers in GIS and evaluate the possibility of each pixel belonging to a fuzzy set by evaluating any of a series of fuzzy set membership functions (Voloshyn, Gnatienko, & Drobot, 2003). The approach consisted of the following steps:

(a) Development of a digital GIS database development incorporating all spatial information. To create a digital geo database using the spatial analysis tools provided by GIS, ESRI ArcGIS 9.3 as a commercial GIS software was used to perform the spatial analysis processes (Maguire, 1991); (b) Determination of the evaluation criteria and formation of the hierarchical multi‐criteria structure; (c) Implementation of the analytical hierarchy process (AHP) method implementation combined with fuzzy function standardization to extract the criteria relative importance weights based on pair‐wise comparisons (Eastman, 2003). By comparing pairs of criteria, decision makers can quantify their opinions about the magnitude of the criteria; (d) Implementation of the simple additive weighting (SAW) method to calculate suitability indexes.

makers must keep in mind the following attributes, aii = 1 and aij = 1/aji. The criteria’s relative importance weights implied by the previous comparisons were calculated. The estimation of the right principal eigenvector of the PCM is approximated using the geometric mean of the PCM’s each row (Saaty, 1996). Then, the application of the SAW method estimates the suitability index which is a widely utilized method for the calculation of final grading values in multiple criteria problems (Hwang & Yoon, 1981). Evaluation criteria were combined in a grid that contains all grades calculated from each of the separate grids. The grading values for each evaluation criterion are included in the complex grid at the appropriate attribute field (Chen & Hwang, 1992). The relative importance weights of the evaluation criteria were calculated by using the PCM matrix as shown in Eq. (1) (Yoon & Hwang, 1995):

∑ (1) where Vi is the suitability index for area i, wj is the relative importance weight of criterion j, vij is the grading value of area i under criterion j, n is the total number of criteria.

2.3. The conceptual framework

The conceptual framework of the web‐based GIS application used fundamentally consists of a general overview area, a multi‐criteria spatial decision supporting system borrowed from GIS, a knowledge map area and a post‐task questionnaire area in the consistent approach of a single user interface via the internet as illustrated in Fig. 3. To start the framework process, users access info.asp, a single web artefact, and the framework deploys through the web browsers in the users’ machine. All four sections have a single web form for authenticated and non‐authenticated users. Users that choose not to log in are non‐ authenticated and are only able to browse through the system and cannot actively participate in the planning process.

The general overview area was structurally divided into four sections and each section comprised of a single web page: the home page gave introductory information about the research, the user manual, the contact information, and the registration form by which the user could fully access the system and facilitate access to other resources. The multicriteria spatial decision supporting system supported the building location/site selection associated with the suggested spatial process as already referred in Section 2.2. Each step had its own function to document users’ knowledge through comment transcript in the bottom of the main work area. It was expected that a single person would not have the full view and in‐depth knowledge required. The knowledge map area absorbs all parts of the application including comment transcripts and personal tacit knowledge (Polanyi, 1996), and represents the final resource for sharing and reuse among users. Therefore, users enhance their own experiences and tacit knowledge

through the knowledge mapping process. Finally, the post‐task questionnaire verifies the users’ perception of building integration within the rural landscape.

Fig. 3: The conceptual framework of the interoperable web‐based GIS application.

2.4. The general system architecture

The general structure of the prototype application is a client/server system. The client/server model defines the communication between clients and servers (Umar, 1997). The system architecture, which is shown in Fig. 4, has five major system components: the user’s web browser, the web server, the application server, the map server, and the database server. The arrows and numbers in Fig. 4 explain the starting and ending points of an information processing procedure.

Fig. 4: The system architecture overview of interoperable web‐based GIS application.

The system starts with users’ inputs in the web browser. A web browser is a common product (client) running on a common system platform, but service providers (servers) have more diversified types. The web server provides for the efficient processing responding to users’ hypertext transfer protocol (HTTP) requests. For dynamic programs, JavaScript is necessary to bridge client and server‐side communications. The application server is programmed by active server pages (ASP), a server‐side script, which obtains these parameters and parses them as a structured query language (SQL) query to the database server, MySQL. The database management system (DBMS) returns its results to the ASP program, which processes the result and provides output. The ASP is a server‐side script to create dynamic web pages that are able to retrieve and display database data and modify data records. The ASP was developed as an embedded text script rather than a compiled program. This method of processing request is frequently used in today’s web application. In the case of map files, MapServer (http://mapserver.org/), an open source platform which was originally developed in the mid 1990s at the University of Minnesota, USA, was used. In the 5.6.6 version it can render these files including the information about spatial objects, classification method, symbol use, and labelling. The client JavaScript program gets the parameters of the data which a user has requested. Users can repeat the same procedure according to their preferences (Jeong, García, & Hernández, 2011).

To operate the prototype application, some functional and technical requirements need to be classified (Haklay et al., 2008). Functional requirements for a GIS‐enabled web application include the ability such as real‐time data acquisition and analysis, user‐side operation with a web browser only, performance of under a few seconds per request and low maintenance cost for the user across heterogeneous computing environments. Technical support requirements include hardware, software, and internet connection, and some development tools. The internet connection used should have a wide bandwidth.

3. Results and discussion

3.1. An implementation of the conceptual framework

For the selected case study area, the conceptual framework as currently implemented uses the information within the internet information server (IIS) to enable participants to make decisions on the issue of integrating rural buildings and their components within landscapes. The implementation of the prototype supports asynchronous collaboration as shown in Figs. 5‐7. Each system module is implemented as an independent component in the prototype. Although the prototype has four steps, it is intended to be a holistic and seamless environment with a top navigation bar and other components as visually consistent web pages. Thus, an analysis of each step’s functionality and capability will produce more specific design requirements of the prototype.

The sample for the prototype will be operated by the general public, including those with little experience of the internet, as well as professionals with greater levels of experience. User analysis helps to understand different types of website users and their cognitive factors which will guide the website developer to anticipate user courses of action (Sawasdichai & Poggenpohl, 2003). For that reason, the user interface was designed to meet five usability criteria: 1) easy to learn, 2) efficient for the user, 3) easy to remember, 4) be equipped with built‐in error protection, and 5) subjectively pleasing (Nielsen, 1994). The user interface will play a crucial role in the correct and productive use of the information system. Accessible designs use colour, image, and graphics to guide users, as well as using understandable and easily navigable content.

The first step in the process is essentially a general overview area that is divided into four sections. All sections consist of a single web page for authenticated and non‐authenticated users: the information page has an introduction which briefly explains what the objective of this prototype is; the second page gives general instructions how to use the system; the third page is a registration form required to use the system with full access; the fourth page includes contact information which has a link to access social network services (SNS) using the web

administrator. User profiles obtained by the third section are used to characterise the types of users interested in the prototype, to compile users’ different backgrounds, and to establish the users’ proficiency with computers. Information in the four sections is structured and presented in a way that improves usability and accessibility. The implementation requirements for this step mostly relate to the user model, the user interface and navigation.

The second corresponds to the selection of location using MCE. Here users can explore the study area of rural buildings and other landscape components integration and then express their preferences on five main decision criteria, namely physical, visual, environmental, social and economic criteria, that the users must weight to classify the suitability maps of the entire study region (Fig. 5). To process this web page, the user must log in and select one criterion, out of the five available, that they consider the most important in deciding whether or not a feasible site is suitable for a rural building integration. The selected criterion is given the maximum score and the remaining criteria are weighted with respect to this. This simplification technique using the ratio estimation procedure is described by Malczewski (1999) and Easton (1973). The following page is similar that the users’ input

and is to set the relative importance of the decision criteria that determines the assignment of feasible sites to the categories. The relative importance, using a slider bar associated with a text field that displays the exact value, assigns 0 to the least suitable and 255 to the most suitable (Fig. 6). Thus, the text field is easy to edit so the users can directly enter their own criterion weights. The approach for selecting the location is to provide users with information about locations that are technically feasible for a rural buildings to be constructed and ask their opinions on which of three categories best describes the locations best: advisable, adequate, or inadequate. After evaluating all decision criteria, a final page displays the classification of the selected feasible site results. At this point, users are more aware of the task that they are involved in and, arguably, are better able to judge the parameters of location integration.

The third step has two parts: the first provides a knowledge map which is a data archive of all users’ results. The second supports communication on each user’s classification (Fig. 7). The various circles shown in this web page indicate users’ classifications: small grey circles represent a single user classification; medium green between 2 and 5 user classifications; large red circles are more than 6 user classifications according to a time scale. To assess further information, users can click hyperlinked ‘notes’. The knowledge map is the final resource of this application for documenting, sharing, and reuse among users. All comments between users are saved in a database as a record of personal secure knowledge sharing. Secure knowledge may be transferred and applied to other users’ processes. For example, users

can read previous contributions, and learn about others perspectives on the suitability of locations or may wish to revisit, and possibly revise, their own classifications. Additionally, users that opt to access the knowledge map directly can use the shortcut button to access the web page where they can create their own classification and can access all data introduced by the users. These data are archived and can be processed afterwards because it might be of interest to later investigate how and when users change their minds.

The final step in the process receives users’ opinions through a questionnaire form. This step using the internet (Roth, 2006) involves a survey in the form of a post‐task questionnaire. The questionnaire is divided into three topics: the system concept and interface; system usability; and personal feedback. Survey results collected will be helpful to improve the design and implementation of the prototype and the investigation.

3.2. Workflow mechanism of the prototype application

The workflow process established directed users consecutively through the general overview area, the multi‐criteria spatial decision supporting system, the knowledge map area, and, finally, the post‐task questionnaire. The model supports both users who are logged in and those that are not, as shown in Fig. 8. There is no fundamental need to guide familiar users through the system. The model has a navigation menu that allows users to determine their own workflow through the system. An additional navigation feature allows registered users to proceed to their choice of step directly following log in. All pages in the prototype encourage users to log in. Special attention is paid to returning users that log in: the system automatically loads previously submitted information including decision criteria weights and submitted feedback. This information can be edited at any time.

Fig. 8: The prototype workflow process.

3.3. Further discussions of the proposed model

This model will be successful only if the participants in the process are willing to communicate among the disciplines involved, in order to increase the level of understanding and awareness among all parties, and to work towards a common vision. This will require a change in the approach of participants to an inter‐disciplinary focus. Also, it is important to prevent participants from feeling that they are marginal to a wider interplay of forces and that they consequently have less influence on the outcome of the planning process. Thus, it is important to make clear how the results of this model can benefit from the use of these tools. In general, the acceptance of these tools will improve if there are transparent connections with generally accepted elements of empirical practice, availability of suitable data, and functions that target specific regulations and procedures to be undertaken on a regular basis.

Currently, the system is a proof‐of‐concept implementation by the developer. The suitability tests of the proposed model need to conduct its integrative improvement. A software usability engineering approach (Nielsen, 1994) will be considered during prototype application testing for evaluating both computational capability and a graphical user interface (GUI). After improving a web application prototype, a set of survey and interview will provide numerical data about participants’ performance using this system to realize its true benefits and potentialities. In addition, it will determine whether this system improves users’ learning in the whole process and also will identify appropriate directions for the use of knowledge.

4. Conclusions

A spatial methodology has been presented for the integration of new rural buildings associated with tourism and their landscapes by combining MCE and GIS techniques. The design and implementation of a conceptual web‐based GIS model with the methodology has been described that identifies and formulates spatial models for the spatial planning integration, asynchronous decision making, user perception integration and verification of tourism resources, together with its application to a case study in Hervás, Spain. The proposed prototype incorporates four elements: a general overview area, a multi‐criteria spatial decision supporting area, a knowledge map area and a post‐task questionnaire area. Through the proposed system, users are able to learn interactively and iteratively about the nature of the problem, and their own preferences for desirable characteristics of solution, the knowledge map supports and stimulates the sharing of opinions and, hence the clarification and discussion of interests behind user’s preferences.

Acknowledgements

This research has been carried and carrying out with the financial support from Ministerio de Ciencia e Innovación (BIA 2007‐61166) and Captación y Formación de Recursos Humanos de Excelencia en Investigación, Desarrollo e Innovación (Universidad de Extremadura); the support of both institutions is gratefully acknowledged.

4.1.3. Un modelo WEB para la asistencia en la toma de decisiones en la integración de las construcciones rurales mediante planificación espacial multi‐criterio

Un modelo WEB para la asistencia en la toma de decisiones en la integración de las construcciones rurales mediante planificación espacial multi‐criterio

Informes de la Construcción, aceptado (2013)

Jin Su Jeong, Lorenzo García‐Moruno, Julio Hernández‐Blanco

Este trabajo presenta un modelo web ideado para asesorar en la toma de decisiones en la integración de construcciones turísticas rurales en su entorno, mediante el intercambio de información y colaboración entre los agentes implicados. Se expone el uso de metodologías espaciales para la selección de localizaciones adecuadas a partir de la evaluación de criterios múltiples (ECM) en un marco web. Se emplean cuatro criterios para la evaluación, que se muestran en un mapa final global de idoneidad, basado en cuatro mapas intermedios parciales según los criterios de evaluación. Como resultado se utilizan tres niveles de información: página de información general, página para la toma de decisión espacial multi‐criterio y una página con mapas de intercambio de conocimiento. El modelo propuesto, aplicado al caso práctico de ‘Hervás’, pretende conseguir una discusión esclarecedora entre distintas percepciones de integración de construcciones en su entorno, considerando diferentes alternativas de decisión y posibles contribuciones.

Palabras clave: planificación colaborativa espacial; integración de construcciones rurales; web; análisis multi‐criterio; toma de decisiones.

A decision‐supporting web model for integrating rural buildings with multi‐criteria spatial planning

Informes de la Construcción, accepted (2013)

Jin Su Jeong, Lorenzo García‐Moruno, Julio Hernández‐Blanco

This paper presents an interoperable web‐based model able to interchange information amongst different stakeholders and to use the information as a means of promoting collaborative activities to integrate rural tourism buildings into a landscape with a case study, Hervás (Spain). Preliminary results from a continuing research are explained with a spatial methodology for selecting the suitable locations of rural buildings, coupling multi‐criteria evaluations (MCE) into a web framework. The aim of this methodology is to classify four evaluation criteria and then is to show a final composite suitability map based on the four intermediate maps. The model deals with three types of information: a general overview page; a multi‐criteria spatial decision‐supporting page; and, a knowledge sharing map page. Using the proposed model, the regional spatial planning is intended to discuss different perceptions of building integration with the surroundings from various decision alternatives and to elucidate this model’s contribution.

Keywords: collaborative spatial planning; rural building integration; web; multi‐criteria analysis; decision‐making.

1. Introducción

En las últimas décadas se ha producido una transformación, en muchos casos abrupta y discordante, entre las edificaciones rurales y su entorno (De Vriesa et al., 2012; Mennella, 1997). Actualmente el turismo se considera como una herramienta de gran alcance para el desarrollo, estimulando el crecimiento económico, el aumento de divisas, la inversión a pequeña escala y el empleo local (De Kadt, 1979). Las políticas europeas de ordenación del paisaje establecen códigos para la construcción con el objetivo de proteger la identidad cultural y particularidades de las edificaciones y promover la calidad del paisaje (Council of the European Union, 2001). En muchos casos, el desarrollo del turismo conlleva una mayor protección del medio ambiente y el aumento de los fondos para la conservación (Pigram, 1980). Sin embargo, la adecuada integración de las construcciones en su entorno, no es un factor que se considere habitualmente en la redacción de los proyectos de ingeniería y arquitectura (Jeong et al., 2013; Tassinari et al. 2007). Por lo tanto, es importante que los profesionales propicien una integración respetuosa y tengan presente el emplazamiento para equilibrar armónicamente las construcciones rurales con su entorno paisajístico, todo ello asociado con el turismo (Bell, 1995; Tandy, 1979).

En el sector turístico, el desarrollo sostenible ha sido considerado ampliamente, ya que satisface demandas atractivas para los turistas, protege el entorno y proporciona oportunidades para el crecimiento económico gracias a la coexistencia de un turismo de calidad y la protección del medio ambiente (Eagles et al., 2002). La mayor preocupación existente hacia los aspectos ecológicos y del patrimonio cultural está motivando mejoras en los entornos locales, incrementándose así su atractivo visual, sus valores estéticos y recreativos (Zhang & Lei, 2012). Coincidiendo con un fuerte desarrollo urbanístico en Extremadura a finales del siglo XX, se ha incrementado de forma notable el número de edificaciones en zonas rurales. La incorporación en el entorno rural de estas nuevas edificaciones ha supuesto un impacto en la propia forma de las construcciones, así como en sus relaciones con el entorno rural actual (Dwyer & Childs 2004; Jeong et al., 2013; Van der Wulp, 2009). La planificación regional actual no ha sido efectiva a la hora de considerar la evolución de los entornos rurales. En concreto no se han considerado ciertos criterios que podrían haber mitigado el impacto que han supuesto determinadas construcciones en su entorno rural (Bell, 1995; García et al., 2006; Tandy, 1979). Con buenas prácticas incluso se podría haber enriquecido el entorno.

La modelización espacial, que proporciona la utilización de sistemas de información geográfica (SIG), permite analizar gran cantidad de datos espaciales mostrando mapas basados en datos georreferenciados en las informaciones económicas, sociales, culturales y ecológicas desarrolladas por la sociedad (Böhme & Schön, 2006; Hermann &

Osinski, 1999). Además, el SIG proporciona herramientas para estudiar minuciosamente las diferentes localizaciones teniendo en cuenta limitaciones en la ordenación del territorio, oportunidades o características visuales que tengan en cuenta la escena paisajística general (Domingo‐Santos et al., 2011; García Moruno et al., 1998; Hernández et al., 2004b; Tassinari & Torreggiani, 2006). A partir de los modelos generados, los responsables de la planificación pueden determinar el estado actual y obtener una idea de las condiciones futuras. Incluso se podrán considerar las posibles consecuencias de los planes de ordenación del territorio y las políticas que puedan estar considerando (Blaschke, 2006). La evaluación de criterios múltiples (ECM) es una herramienta que pretende ser útil para la ordenación del territorio y facilitar a los responsables la exploración y resolución de problemas con gran cantidad de variables y datos (Malczewski, 1999). Los problemas de la ordenación del territorio suelen incorporar gran número de partes interesadas con diferentes antecedentes, inquietudes e interpretaciones de las dificultades (Fountas et al., 2006). Por este motivo, el trabajo colaborativo puede ser una opción adecuada para aunar las aportaciones individuales a los problemas asociados con la ordenación del territorio y tomar decisiones que satisfagan sino a la totalidad, al menos a la mayoría de los afectados (Jankowski et al., 1997). En la última década, se han realizado numerosos esfuerzos para desarrollar una herramienta con estas características que integre y sea capaz de tratar “dentro de un marco único” tanto la vertiente analítica como la comunicativa de los procesos de diseño y ordenación del territorio (Jankowski et al., 1997; Voss et al., 2004). La definición de este marco único posee importancia crítica. Se ha demostrado que la utilización de internet proporciona un mecanismo fundamental para garantizar que las partes interesadas tengan la oportunidad de participar en el proceso del diseño y ordenación del territorio en un proceso de colaboración asincrónico y distributivo (Voinov & Bousquet, 2010).

El objetivo del presente trabajo es, por tanto, analizar y examinar cómo la investigación que se propone puede contribuir en los procesos de toma de decisiones entre las partes interesadas para la integración de construcciones turísticas rurales y su entorno, mostrando la funcionalidad de esta propuesta a través del estudio en Hervás, España. Este trabajo se centra en el diseño de una aplicación web basada en sistemas ECM combinados con la ponderación aditiva simple (PAS), con la que se podrá identificar y formular criterios apropiados y modelos espaciales para la correcta integración en la ordenación del territorio, con el objetivo principal de resaltar las interrelaciones entre las construcciones rurales y su entorno. La aplicación desarrollada en este estudio constituye una nueva alternativa que intenta facilitar los procesos de toma de decisiones, cuantificando la percepción de los usuarios, archivando los mapas de conocimiento que podrán ser compartidos y reutilizados posteriormente y verificando el impacto económico de las acciones tomadas sobre el turismo. Así, esta

aplicación podría ser considerada como un vía de colaboración y comunicación entre los usuarios con intereses específicos o particulares en la ordenación del territorio en entornos rurales. La metodología propuesta se ha aplicado a un caso de estudio, mostrándose y discutiéndose los resultados en este trabajo.

2. Materiales y método

2.1. Descripción del área de estudio

Se ha establecido Hervás como área de estudio. Esta población está localizada en la comarca del Valle del Ambroz al norte de la provincia de Cáceres (Extremadura, España), como se indica en la Figura 1. El área de estudio tiene una superficie total de 60 km2. Por su mayor número de habitantes, Hervás es el centro administrativo y comercial de la comarca del Valle del Ambroz. En esta comarca, el terreno tiene un uso multifuncional mediante un sistema agro‐silvestre y de pastoreo centrado en la Dehesa. Constituye un paisaje cultural específico, en el que predominan los bosques caducifolios de castaños, que son la base de un importante conjunto de empresas. Además, este área posee un importante valor biológico, escénico y recreacional, con un gran número de ríos y humedales idóneos para el destino turístico en periodos estivales.

Figura 1: Mapa de situación del área de estudio Hervás.

En el comienzo de la década de los noventa, se produjo un importante cambio en este área hacia un desarrollo rural sostenible, como consecuencia de diferentes iniciativas europeas en Extremadura (Proyectos LEADER y PRODER) (LEADER y PRODER, 2011). Durante las últimas décadas ha crecido el desarrollo de edificaciones en entornos rurales, muchas de ellas segundas residencias con fines vacacionales. También se ha producido un importante desarrollo de las actividades relacionadas con el turismo rural, lo que ha conllevado un incremento en la construcción de hoteles y casas rurales (Jaraíz et al., 2013). Este proceso ha provocado un impacto, algunos estudios ya han resaltado que el continuo desarrollo en entornos urbanos y rurales ha causado importantes cambios en el uso de territorio, lo que se refleja en la pérdida de los entornos tradicionales (Jaraíz et al., 2013; Tassinari et al., 2008). En un corto período de tiempo se han realizado grandes

cambios en la utilización del suelo como consecuencia del enorme desarrollo turístico y urbanístico. La respuesta a la situación actual (LESOTEX, Ley 15/2001 del suelo y ordenación territorial de Extremadura) está vinculada con la ordenación regional del territorio mediante planes, programas y diferentes acciones incluyendo las repercusiones territoriales. Sin embargo no proporciona una respuesta apropiada al problema real planteado (LESOTEX, 2001). De hecho, los cambios que se producen con el desarrollo rural son más rápidos que la capacidad que tiene el legislador para comprenderlos (Wascher et al., 1999). Las actuales políticas fallidas e instrumentos de planeación necesitan modificaciones y/o nuevas alternativas que deben ser desarrolladas e implementadas. Además, el proceso de planificación debe ser sometido a debate público para obtener sugerencias, alternativas, objeciones u otros puntos de vista mediante la colaboración con otras asociaciones y particulares.

2.2. Evaluación de idoneidad del área

Con objeto de determinar la localización más apropiada para la integración en su entorno de edificaciones rurales con fines turísticos se han aplicado diversos métodos, como la superposición e indexado, considerando diferentes parámetros a través del uso de herramientas de análisis espacial tales como SIG complementado con ECM. Los criterios de evaluación utilizados en esta investigación han sido clasificados en cuatro categorías principales: criterios físicos, ambientales, sociales y económicos. Todos han sido implementados en un proceso computacional y seleccionados a partir de la consulta de literatura relevante, políticas regionales y las directrices de la Unión Europea.

Se han considerado un amplio número de criterios de evaluación que influyen en la integración de las edificaciones turísticas rurales y se han tenido en cuenta diferentes etapas de evaluación que se han identificado con los cuatro criterios principales: físicos, medioambientales, sociales y económicos. Cada uno de estos criterios principales lleva asociado diferentes sub‐criterios. En concreto, se han considerado los 16 sub‐criterios en el proceso computacional como se indica en la Tabla 1: (a) aspecto, (b) elevación, (c) pendiente, (d) visibilidad, (e) la presencia de un ecosistema sensible de acuerdo con la regulación de la Comisión Europea para la naturaleza y la biodiversidad (NATURA 2000), (f) presencia de fuentes agua, (g) presencia de agua superficial, (h) tipo de vegetación, (i) proximidad de áreas residenciales, (j) densidad de población, (k) proximidad a áreas culturales, (l) accesibilidad, (m) proximidad a núcleos urbanos, (n) proximidad a zonas turísticas, (o) proximidad a zonas agrícolas y (p) utilización del territorio y tipo de cubierta. De modo que el criterio principal “físico” incluye los sub‐criterios del (a) al (d), el criterio “medioambiental” incluye los sub‐criterios del (e) al (h); el tercer

criterio “social” incluye los sub‐criterios del (i) al (l) y finalmente, el criterio “económico” incluye los criterios del (m) al (p).

La estructura jerárquica del proceso de decisión consta de cuatro niveles. El primer nivel muestra el objetivo principal: la idoneidad de la edificación turística rural. El segundo nivel representa los criterios que apoyan al objetivo principal. El tercer nivel corresponde los sub‐ criterios de cada uno de los criterios principales. Por último, el cuarto nivel muestra los atributos espaciales de cada sub‐criterio.

La idoneidad de la localización de la construcción turística rural, considerando su entorno, es determinada mediante la combinación de los criterios de evaluación indicados en la metodología propuesta. De este modo, comenzando con el proceso analítico jerárquico (PAJ), se extraen los pesos de importancia relativa con la matriz de comparación por pares (MCP) y los valores de puntuación mediante la evaluación y juicio de la situación actual de los indicadores de cada criterio. En pocas ocasiones se obtendrá la MCP totalmente coherente (Armengou et al., 2012; Saaty, 1996; Zeleny, 1982). La estructura que se establezca en la MCP por parte de los tomadores de decisiones dependerá de la importancia con la que perciban cada uno de los criterios, para ello se establece una escala de puntuación como la indicada en la Tabla 2 (Balana et al., 2010). En este estudio, se ha empleado una escala de nueve puntos que obedece a los siguientes atributos, aii = 1 y aij = 1/aji. El método PAJ incluye un índice denominado Razón de Consistencia (RC) que indica la coherencia global de la MCP (Golden et al., 1989; Vargas & Zahedi, 1993). Según Saaty (1996), la RC debe tener un valor de menos del 10%, para considerar que una matriz sea consistente. El peso calculado de prioridad de todos los criterios y sub‐criterios “una vez establecida la MCP por parte de los autores” se presenta en la Figura 2. Los parámetros PAJ indican las asignaciones de los pesos de importancia relativa final considerados para un primer acercamiento al problema.

Tabla 1: Los cuatros criterios principales y su desglose en sub‐criterios.

Criterio Sub‐criterio Descripción del sub‐criterio Muestra las áreas con buena orientación, desde un punto Aspecto de vista estético. Constituye un parámetro básico junto con la elevación y la pendiente. Muestra las áreas de elevación expresada en metros, Elevación parámetro básico de la superficie del suelo y de los procesos atmosféricos con efecto en los atributos derivados medioambientales. Físicos Muestra las áreas de pendiente expresada en grados, Pendiente parámetro con efecto en los atributos derivados medioambientales y en el aspecto del paisaje de acuerdo a la forma y flujo de la superficie del terreno. Muestra las áreas destinadas a la protección estética Visibilidad utilizando las distancias radiales y visibles desde puntos de acceso a la localización, tales como carreteras (autopistas y carreteras locales) y los ferrocarriles. Ecosistema Muestra las áreas calculadas utilizando funciones de sensible distancia Euclidianas, la distancia radial desde el ecosistema sensible de acuerdo con NATURA 2000. Muestra las áreas calculadas utilizando funciones de Fuentes agua distancia Euclidianas, distancia en línea recta a masas de Medio aguas, manantiales y/o pozos. Muestra las áreas calculadas utilizando funciones de ambientales Agua superficial distancia radial de fuentes de aguas superficiales, lagos y/o ríos con flujos continuos de agua. Tipo de Muestra las áreas que incluyen una evaluación basada en la singularidad ecológica de vegetación y las áreas vegetación deforestadas. Se muestra la extensión natural de estas formaciones naturales. Áreas Muestra las áreas calculadas utilizando funciones de residenciales distancia Euclidianas, la distancia radial desde ciudades y pueblos que representan actividad humana. Densidad de Muestra las áreas de las zonas de influencia alrededor de una ciudad, pueblo o asentamiento humano asociado con población la distancia económica basado en la información facilitada por el instituto nacional de estadística (INE). Sociales Muestra las áreas que poseen aspectos culturales del área Áreas culturales de estudio, que presentan zonas para la protección de herencias culturales de acuerdo con las restricciones legales. Muestra las áreas calculadas mediante funciones de Accesibilidad distancia radial, la distancia directa desde las estructuras de los puntos de acceso, tales como autopistas, carreteras y vías de tren. Muestra las áreas calculadas usando funciones de distancia Núcleos urbanos Euclidianas, la distancia directa desde las zonas urbanas basada en el uso del terreno y el tipo de cubierta. Muestra las áreas en las que se mezclan zonas culturales y Zonas turísticas urbanas, incluyendo zonas de interés arqueológico, mediante el uso de funciones de distancia Euclidianas. Económicos Muestra las áreas con explotaciones agrarias en proceso de Zonas agrícolas cambio de uso de terreno, con la distancia mínima de protección según las restricciones legales. Utilización del Muestra las áreas destinadas al desarrollo económico que territorio incluya el uso de la tierra y los tipos de cobertura basado en modelo de elevación digital (LESOTEX).

Tabla 2: Matriz de comparación por pares para el cálculo numérico de los pesos de los criterios.

Comparación por pares (Escala de valoración continua de 9 puntos) Intensidad muy baja Intensidad muy alta 1/9 1/8 1/7 1/6 1/5 1/4 1/3 1/2 1 2 3 4 5 6 7 8 9

o fuerte fuerte

Extrema Muy Equilibrada Moderada Fuerte Muy Fuerte Moderada Igual Extrema

Finalmente, la aplicación de la PAS se utiliza con una escala de 9 puntos para extraer la información de los cálculos del índice de aptitud. Así se calculan los valores de clasificación finales en problemas con criterios múltiples basándose en la escala de clasificación utilizada en el presente trabajo para el índice de idoneidad comprendido entre 0 y 10, el cual establece la zona menos o más apropiada según se indica en la Ecuación [1] (Hwang & Yoon, 1981; Yoon & Hwang, 1995). Cada indicador muestra una puntuación, que puede ser comparada respecto al estado actual del indicador para alguna condición deseada. De esta forma, la puntuación 9 establece la condición de rendimiento excelente, la 7 establece un rendimiento bueno, la 5 establece un rendimiento aceptable, la 3 establece un rendimiento razonable y la puntuación 1 indicaría una condición de rendimiento desfavorable para cada condición deseada. Indicadores con valores intermedios, 2, 4, 6 y 8 se emplean para puntuar cada condición deseada (Balana et al., 2010).

Figura 2: Organización jerárquica del proceso de decisión mediante los criterios de evaluación planteados.

∑ [1] donde Vi es el índice de idoneidad del área i, wj es el peso de importancia relativa para el criterio j, vij corresponde al valor de evaluación para el área i bajo el criterio j, n es el número total de criterios. Los criterios de evaluación se combinan en una rejilla que incluye a todas las puntuaciones para cada una de las rejillas por separado. Cada uno de los valores de los criterios de evaluación es combinado en una rejilla compleja en el campo del atributo apropiado.

2.3. El modelo web implementado

Para el caso de estudio seleccionado, el entorno web implementa la información con el servicio de información de internet (SII), habilitando a los participantes para la toma de decisiones. La aplicación web implementada, descrita en este trabajo, se propone como una solución para la mejor integración de las edificaciones rurales en su entorno, como una herramienta para apoyar la toma de decisiones, para evaluar la percepción de los usuarios que tienen sobre la integración de dichas edificaciones, para compartir y reutilizar los mapas personales de conocimiento entre los usuarios y como un índice para verificar el impacto económico de las acciones tomadas sobre el turismo. La aplicación consta básicamente de un área de información general, un área para la toma de decisión espacial multi‐criterio y un área con mapas de intercambio de conocimiento, tal como se muestra en la Figura 3. Aunque el prototipo cuenta con estas tres etapas, puede considerarse como un entorno holístico y continuo con una barra de navegación superior y otros componentes visualmente coherentes con una página web.

Figura 3: Despliegue del proceso del flujo de trabajo de e‐shift.

El modelo web, denominado e‐shift, dirige a los usuarios de forma consecutiva hacia el área de visión general, seguidamente a la zona de apoyo para la toma de decisión espacial multi‐criterio y finalmente hacia el área de mapa de conocimiento. Los usuarios pueden navegar por este modelo de flujo de trabajo utilizando los botones de “siguiente” y “atrás” situados en la parte superior del área de trabajo principal.

Además, e‐shift cuenta con un menú de navegación en la parte superior, lo que permite a los usuarios diseñar su propio flujo de trabajo a través del sistema. En primer lugar, la zona de visión general proporciona información introductoria, un manual de usuario, información de contacto y el formulario de registro a través del cual el usuario pude acceder de forma completa al sistema y simplificar el acceso a otros recursos. En segundo lugar, el sistema de soporte para la toma de decisión espacial multi‐criterio ayuda al usuario a la selección de la localización de la edificación considerando las complejidades del proceso espacial como se ha mencionado anteriormente en la sección 2.2. Así, cada etapa tiene su propia función para documentar sus conocimientos a través de la transcripción de comentarios en la parte inferior del área de trabajo principal. Se debe esperar que una única persona no se encuentre en posesión de todos los detalles y del conocimiento profundo para la integración total o parcial de una edificación. En tercer y último lugar, el área del mapa de conocimiento aglutina todas las partes de la aplicación incluyendo las transcripciones de los comentarios y el conocimiento tácito personal (Polanyi, 1996) y representa el recurso final para compartir y reutilizar la información generada por todos los usuarios. De este modo, los usuarios ven incrementada sus propias experiencias y su conocimiento a través del proceso de generación del mapa de conocimiento.

La aplicación web e‐shift es funcional tanto con usuarios registrados en el sistema como aquellos que no lo estén. Todas las funciones del sistema están disponibles para aquellos usuarios que están debidamente autentificados. A aquellos usuarios que no se han registrado se les permite navegar por el sistema y leer toda aquella información que esté disponible, incluyendo las clasificaciones proporcionadas por otros usuarios, pero no se les permite participar activamente en el proceso de planificación espacial regional en su etapa segunda. Además, estos usuarios, no podrán clasificar los procesos de integración viables o contribuir a compartir y/o reutilizar los mapas de conocimiento. Para evitar este inconveniente, todas las páginas en el prototipo animan al usuario a registrarse. El sistema web diseñado detecta a los usuarios que regresan al sistema, cargando automáticamente la información enviada previamente, incluyendo los pesos de los criterios de decisión y las retroalimentaciones enviadas. Esta información puede ser editada en cualquier momento por parte del usuario.

3. Resultados y discusión

El modelo web implementado e‐shift, permite la identificación del área más apropiada para la localización de la construcción rural con fines turísticos en Hervás. La utilización de la segunda etapa del modelo (el área de apoyo para la toma de decisión espacial multi‐criterio), ilustra el posible escenario de agrupamiento utilizando cuatro criterios principales, los cuales se han combinado con dieciséis sub‐criterios

como en la etapa previa (Figura 4). Para obtener los posibles resultados alternativos, en primer lugar los usuarios exploran el área piloto para las construcciones rurales y otros componentes de integración del entorno y seguidamente expresan sus preferencias sobre dónde podría o no localizarse en función de los dieciséis sub‐criterios. La asignación dada por este usuario sirve para establecer la importancia relativa del criterio de decisión que determina la asignación de los sitios viables para las categorías. Una vez evaluados todos los criterios de decisión, la última página muestra la clasificación de los resultados seleccionados para las localizaciones viables. A partir de este momento, los usuarios son más conscientes de la tarea en la que están involucrados y, sin duda, están en mejores condiciones para juzgar las relaciones de la zona de integración.

Figura 4: Selección de páginas web que muestran el proceso de toma de decisión espacial multi‐criterio.

El mapa mostrado en la Figura 4a presenta una alternativa al escenario generado cuando el usuario ha asignado diferentes pesos a los criterios y sub‐criterios establecidos. Esta alternativa aplica pesos iguales a los cuatro criterios. Además, este resultado muestra que la bondad del terreno se incrementa cuando el índice de idoneidad aumenta. Zonas con índices de idoneidad en el rango de 0 a 4 pueden considerarse, de forma general, como no idóneas para localizar una edificación rural con fines turísticos. Áreas con valores de índices de 9 a 10 pueden considerarse como las más apropiadas para la localización de la

edificación rural con fines turísticos. En la Figura 4b, se muestra el resultado del porcentaje de área categorizada; en este caso la zona más apropiada es aquella con un 8.44%. El resultado de agrupamiento también tiene interés para señalar los patrones espaciales diferenciadores generados mediante la asignación de pesos a los criterios y para indicar que la metodología presentada es capaz de revelar la zona más apropiada para la integración de las edificaciones rurales con fines turísticos en su entorno, así como proporcionar una escala inicial de zonas más apropiadas. De este modo, modelos integrados en un entorno web para la toma de decisión espacial multi‐ criterio, como el modelo “e‐shift” presentado en este trabajo, pueden ser de gran utilidad para tomar la decisión final.

Finalmente, en la última etapa, la clasificación conseguida se archiva en el mapa de conocimiento y se comparte y/o reutiliza para facilitar la comunicación entre los usuarios. El mapa de conocimiento es el último recurso de esta aplicación para la documentación, intercambio de información y reutilización por parte de los usuarios. Todos los comentarios de los usuarios se almacenan en una base de datos como registros personales del conocimiento tácito compartido. Esta información será accesible para todos los usuarios participantes en momentos posteriores y podrá utilizarse para intercambiar el conocimiento implícito generado anteriormente. Por ejemplo, los usuarios podrán leer las contribuciones aportadas con anterioridad y aprender sobre las perspectivas propuestas por otras personas sobre la idoneidad de una localización para albergar o construir elementos, así podrán modificar o revisar sus propias clasificaciones mediante el conocimiento de esta información.

4. Conclusiones

En este trabajo se describe el diseño e implementación de un modelo web con metodología espacial, el cual permite afrontar y facilitar la integración de edificaciones rurales con fines turísticos en su entorno mediante la toma de decisión asincrónica. La percepción de integración de los usuarios, la elaboración de mapas de conocimiento y verificación económica de los recursos turísticos. Para mostrar la aplicabilidad de este modelo, se ha desarrollado un caso práctico, utilizando el área de Hervás (Extremadura, España) como ejemplo. Particularmente, el caso de estudio ha presentado una aproximación de los procedimientos de agrupación mediante PAJ/PAS para generar un amplio rango de decisiones alternativas para abordar la problemática de la integración de edificaciones rurales con fines turísticos. A través del modelo web propuesto, los usuarios son capaces de aprender de forma interactiva e iterativa sobre la naturaleza del problema y además permite al usuario establecer sus preferencias para la solución deseada. El mapa de conocimiento generado, apoya y estimula el intercambio de opiniones y, por lo tanto, la discusión de intereses propios de cada usuario. Así, estos resultados preliminares

muestran la flexibilidad del marco metodológico implementado en el modelo web, e‐shift, más allá de la evaluación de todos los posibles criterios y sub‐criterios.

Sin embargo, este modelo sólo será exitoso si todos los participantes en el proceso están dispuestos a poner en común sus conocimientos con objeto de incrementar el entendimiento y comprensión por todas las “partes” trabajando así hacia una visión común. Actualmente, el sistema se implementa como un concepto‐prueba por parte de los autores. Será necesario llevar a cabo pruebas de idoneidad para la mejora del sistema. Se determinará si este sistema mejora el aprendizaje de los usuarios en todo el proceso y también se identificarán las instrucciones apropiadas para el uso del conocimiento. Durante las pruebas de evaluación de la aplicación prototipo, se tendrá en cuenta la usabilidad del software (Nielsen, 1994) para evaluar tanto la capacidad computacional como la interfaz gráfica del usuario (GUI). Una vez mejorada la aplicación prototipo, se llevarán a cabo un conjunto de encuestas y entrevistas para obtener información numérica sobre el rendimiento que los participantes han obtenido al utilizar el sistema, comprobando de este modo el beneficio potencial del modelo web propuesto.

Agradecimientos

Los autores agradecen al Ministerio de Ciencia e Innovación (Proyecto BIA 2007‐61166) por su financiación. Jin Su Jeong agradece a la Universidad de Extremadura por su contrato FPI del programa de Captación y Formación de Recursos Humanos de Excelencia en Investigación, Desarrollo e Innovación.

4.1.4. Approaches to validating a mutual participatory web‐planning interface in rural Extremadura (Spain)

Approaches to validating a mutual participatory web‐planning interface in rural Extremadura (Spain)

Land Use Policy, under review (2013)

Jin Su Jeong, Julio Hernández‐Blanco, Lorenzo García‐Moruno

Decision‐making in the process of spatial planning usually concerns multiple stakeholders with conflicting views. In this article, a mutual participatory web‐planning interface is developed to support rural tourism building integrations into a landscape that combine multi‐criteria decision analysis (MCDA); an application of the proposed interface for Hervás (northern Extremadura region), Spain, is further presented. Through the web interface with the methods, stakeholders can reflect their individual experience to achieve desirable planning outcomes by the asynchronous and distributed collaboration with the increased public participation. Based on the qualitative and quantitative content and survey data set, this study examines the identification of spatial models for the different perceptions and knowledge sharing of building integrations into a rural landscape, the certification of the possible impact on tourism and the definition of interface usability. To strengthen data interpretation, these hypotheses are analyzed by four different clusters with the aid of ANOVA and PCA test: weak ties, socially linked, roots and resources, and dedicated to the place in social and emotional terms. In general, most participants revealed positive responses to the questionnaires and an interesting fact amongst the findings is the difference between roots and resources (positive to building integrations) and dedicated to the place (negative to building integrations). Thus, the analyzed results demonstrate that the web interface can achieve consensus on recommendations for the spatial planning with the implementation of decision alternatives and understanding of the other interest groups’ preferences.

Keywords: participatory web; collaborative planning; rural building integration; tourism; user perceptions; knowledge sharing.

1. Introduction

In many organizations, participants see opportunities to achieve individual goals through collective action (Craig et al., 2002; Olson, 1965). Public participation has different organization size from small ones, engaging in neighbourhood problems, to large ones, solving sophisticated regional problems. Particularly, decision‐makers pay attention to public participation and community organizations due to the importance of community inputs for defining local concerns (Jones, 1990). In the spatial planning sense, a large number of stakeholders (experts and non‐experts) with different backgrounds, interests, authorities and interpretations of their issues incorporate to achieve the community‐developed solutions which are feasible because they tend to be reasonable, realistic and sustainable (Fountas et al., 2006). The spatial modelling allows to analyzing large volumes of spatial data with the aid of geographic information system (GIS) which give geographical expression to the economical, social, cultural ecological policies of societies (Böhme and Schön, 2006; Hermann and Osinski, 1999). A collaborative process, therefore, is the correct manner to reconcile the individual approaches and to make decisions satisfying all or most participants (participants: stakeholders and the public) (Jankowski et al., 1997).

During computer and internet technology are becoming mainstream in the last decade, efforts have been made to extend an integrative tool capable of dealing with both the analytical and communicative side of spatial planning within a unique framework (Jankowski et al., 1997; Ruiz and Fernández, 2009; Voss et al., 2004). Some researchers have mentioned that the internet offers a new way to allow and facilitate participatory decision‐making processes and to generate a new public sphere supporting interaction and debate amongst participants (Batty, 1998; Kingston et al., 2000). Decision‐makers (planners and local authorities) develop manners to use these technologies to work effectively and efficiently with the participants and to grant opportunities to some interested stakeholders using asynchronous and distributed collaboration (Al‐Kodmany, 2001; Voinov and Bousquet, 2010). Thus, multi‐criteria decision analysis (MCDA) incorporating with the technology provides ways to help decision‐makers explore and solve multiple and complicated decision problems (Hwang and Yoon, 1981; Keefer et al., 2004; Malczewski, 1999; Roy, 1996). One of widely accepted decision‐making methods is the analytic hierarchy process (AHP) that is an effective approach to take out the relative importance weights of the criteria in a specific decision‐making situation (Gemitzi et al., 2006; Saaty, 1977). Typically, the criteria have different significance which shows participants’ preference as the alternatives for them on each criterion (Saaty, 1996, 2005).

In Southern Europe, an important translation has occurred in many instances, the discordant relationship between rural buildings and a

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landscape for the past few decades (Jeong et al., 2013; Jaraíz et al., 2013; Mennella, 1997). Tourism as a powerful tool has long been identified for development, spurring economic growth, increasing foreign exchange, smallholder investment, and local employment and results in increased environmental protection and funds for environmental conservation in some cases (De Kadt, 1979; Pigram, 1980). The importance of rural tourism also has been recognized by the world tourism organization (WTO, 2005) as analyzing its current situation and prospects (Díaz Martín and Vázquez Casielles, 1998; Gascón Linares, 1993). European landscape planning policy has its particular building codes issued for protecting their cultural identity and for promoting landscape quality (Council of the European Union, 2001). The suitable rural buildings’ integration into a landscape is not a general consideration of planning processes yet (De Vriesa et al., 2012; Jeong et al., 2012; Tassinari et al., 2007). The presented research describes the implementation of a mutual participatory web‐based planning interface coupled with methods which can identify and formulate suitable criteria and spatial models for the right spatial planning integration, with the primary aim of highlighting the interrelations between rural tourism buildings and their landscapes. The methodology explains the determination of rural tourism buildings’ site suitability with the AHP and constraints for MCDA and the simple additive weighting (SAW) based on the understanding of the existing regional planning and policies (Eastman, 2003). The general goal of this paper is to examine how the research can contribute to support stakeholders’ decision‐making, together with its application to an empirical case study in Hervás, Spain. The implemented web application allowed us to calibrate the method, measuring users’ perception and knowledge sharing about building integration, defining the interface adequacy, and certifying the possible impact associated with tourism suitable carried out the content and statistics analyses through the qualitative and quantitative database set. The next section provides background information about the study area and how different methods applied to the study. Section 3 presents the data set results obtained from the application of the proposed web interface with the methodology and its statistical analysis, as well as the discussion of the proposed objectives. Finally in Section 4, conclusions from this approach are described.

2. Materials and methods

The study region, Hervás (60 km2) located in the mid‐west part of Spain, accords with high biological, scenic and recreational value such as rivers and wetlands where are tourist places for the summer season. The major motive to visit rural areas is contact with the way of rural life and/or environment that tourists’ stays which are short, often for only a weekend. Because of these reasons, rural developments have been rapidly growing with their consequent impacts, the loss of traditional landscapes and substantial change of land use, although the

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definition of rural area may differ amongst countries or even regions within a country (Jeong et al., 2013). Specifically, the development of rural tourism buildings has been increased on the account of holiday residences’ growth and area’s nature characteristics (Hernández et al., 2007). Despite the response as a regional law in Extremadura, Spain (LESOTEX, Law 15/2001 for Land and Landscape Planning of Extremadura), it does not give coherent answers for the Extremadura land use and planning problems. For that reason, we suggest an approach to site a sound rural tourism building into a landscape with the considerations of extensive criteria and evaluation steps. A multi‐ disciplinary evaluation process framed in the web interface is applied through the spatial analysis tools with the MCDA, based on certain evaluation criteria (physical, environmental and socio‐economic) and constraints. As the last step, it represents participants’ utilization intermediate and final results as analyzing the content and statistical survey questionnaire based on four different clusters.

2.1. Application of multi‐criteria decision‐makings

There are many different means to carry out the modelling of the stakeholders’ preferences. The MCDA gives transparent ways to systematically organize and analyze complicated decision‐making problems and to support the elicitation of preferences in participatory decision‐making within a structured framework (physical, environmental, socio‐economic and constraints) (Hwang and Yoon, 1981; Keefer et al., 2004; Malczewski, 1999). Extensive criteria and evaluation processes are considered and classified into three main criteria with each four sub‐criteria and six constraints involved in the computation process as the follow (Jeong et al., 2013):

 Evaluation criteria: 1. Factors relevant to physical evaluations: the following four factors related with the physical evaluation of the selected study area were analyzed; (1) morphology: having an important role for environmental attributes’ derivation along with slope, aspect and specific catchment area and plan (Gallant and Wilson, 2000); (2) orientation: showing a better aspect for aesthetical reason not for any legal restrictions and having environmental attributes’ derivation; (3) land use: resolving public conflicts over the acceptance of unwanted buildings integration to consider the current land development from the Landsat bands of the digital elevation model (DEM); (4) visibility: aiming to preserve the aesthetic protection of inhabited areas from the designated points but not based on any legal restrictions. 2. Factors relevant to environmental concerns: the following four factors related with the environmental concern of the selected study area were analyzed; (1) sensitive ecosystem: dealing with the potential pollution or degradation

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of natural environments of unique ecological and/or aesthetic interest based on legal restrictions (NATURA, 2000); (2) water source: including springs and/or groundwater wells calculated using Euclidean distance functions using ArcGIS 9.3; (3) surface water: relating with lakes and rivers with continuous water flows which have a potential final receiver of treated or even untreated pollution; (4) vegetation type: including the ecological uniqueness of the forested and deforested vegetation and spatial spread of these natural formations based on the normalized difference vegetation index (NDVI). 3. Factors relevant to socio‐economic parameters: the following four factors related with the socio‐economic evaluation of the selected study area were analyzed; (1) site access infrastructure: including the existing transport networks, the main routes for tourists, such as highways, local roads and train railways; (2) population density: considering an influence zone around city, town and human settlement associated with economic activities; (3) residential area: relating with towns and villages representing a high concentration of human activities associated the surrounding resources’ demands besides the presence of urban centres; (4) tourism resource area: including tourist, cultural and urban area examined by the various distance calculations from each zone and by the legal restrictions based on land use and cover type.

 Constraints: the following six constraints limit the analysis to the particular geographic areas: (1) environmentally protected areas, sensitive ecosystem following European commission regulation for nature & biodiversity policy (NATURA, 2000); (2) important aquifers such as springs and/or ground water wells with high groundwater pollution risk; (3) surface water bodies to prevent water surface pollution; (4) specific vegetation and land use types with the dense vegetation formation; (5) highways and railways followed by legal limits for minimum distance; (6) areas prohibited to construct commercial buildings by the regional building ordinance.

In the final step of the MCDA, the various methods were applied to combine the mentioned criteria establishing the most suitable areas for integrating rural tourism buildings into a landscape. The AHP, the first approach, makes the relative importance weight and grades values as examining the indicators’ condition with the aid of the pair‐wise comparison matrix (PCM) under each criterion and sub‐criterion. Finally, the SAW method was used for the evaluation of the final suitability index, 1 to 10, which is, respectively, from the least to the most suitable area to solve the multiple criteria problem (Hwang and Yoon, 1981).

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2.2. Use of a web‐based spatial planning interface, aka ‘e‐shift’

Although the web still does not yet provides equal possibilities to participate, the use of the web offers new chances, an alternative to traditional way as communications channel, to support participatory processes (Jeong et al., 2011; Kangas and Store, 2003). The potentials to make an interactive application using MCDA methods will be a take‐ off to develop sophisticated web tools. With these web tools, each user can participate as the most suitable way and can express their individual experiences that can be saved into the data, turned to knowledge mapping and sharing.

The architecture of web interface takes advantages of the web implementation feasibilities to support decision‐making processes, to identify spatial models for the different perceptions and knowledge sharing for building integration and to certify the possible impact on tourism. The general structure of this interface is a client/server system, defining the collaboration and communication between clients and servers (Umar, 1997). The interface has been established directed for users consecutively through the general overview section, the MCDA section, the knowledge map section, and, finally, the post‐task questionnaire section which is compatible with any web browser (but Internet Explorer needs to be at least version 9.0) as shown in Fig. 1. To be object‐oriented system, we applied the system architecture pattern, model‐view‐controller (MVC) which the programming language Smalltalk first defined the MVC concept it in the 1970’s. Although the interface supports both users who are logged in and not logged in, all pages in the interface encourage users to log in. To perform the proper execution of the interface, we followed some requirements, functional and technical support such as real‐time data acquisition, user‐side operation and low maintenance cost that give heterogeneous computing environments for functional ones and hardware, software, internet connection and development tools for technical ones, need to be classified (Haklay et al., 2008). Thus, to understand different types of website users and their cognitive factors, we adopted the user analysis which guided to design the web model according to five usability measures: easy to learn; efficient for the user; easy to remember; be equipped with built‐in error protection; and, subjectively pleasing (Nielsen, 1994; Sawasdichai and Poggenphol, 2003). The general aim of web interface is a multi‐criteria application with the selected case study area, especially suitable for rural tourism buildings integrations and their elements for decision‐makings in a sense of both supporting the analysis of participants’ different aspects, and presents an interface for remote participation via the web.

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Fig. 1: The workflow deployment process of the web interface, named ‘e‐shift’.

2.3. Measurement of variables

The study data were collected via the implemented web‐based interface, e‐shift (www.e‐shift.eu). Through the interface, users have participated two variables which are the MCDA ranking weighting and post‐task survey questionnaire. Both variables were first tested in a pilot study and then developed further. Altogether, these comprised 258 participants who were categorized into items related with socio‐ demographic background. The MCDA ranking process yielded a total 243 responses from the sample, amounting to 94% of the total number of the actual participants to the web interface. On the other hand, the web‐based post‐task questionnaire survey gave a total 212 responses from the sample, amounting to 82% of the total number of the actual participants to the web tool. Two sample data were analyzed using content and statistics analysis approaches.

2.3.1. MCDA ranking weights and survey questionnaire

The process to select locations for rural building integrations using the MCDA, here users can explore the study area and then express their preferences on three main decision criteria, namely physical, environmental and socio‐economic criteria and equal weight depending on users’ preference, depicted in Fig. 2. Users must log in and select one criterion out of three available which is given the maximum score and the remaining criteria are weighted with respect to this or can select the equal weight for three criteria. Easton (1973) and Malczewski (1999) have described this simplification technique based on the ratio estimation procedure. Then, in the following pages, users need to weight sub‐criteria showing the relative importance of

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the decision criteria at the same time (see Fig. 3a). The relative importance, using a drop down menu that displays the exact value, assigns 1 to the least suitable and 10 to the most suitable. After evaluating all decision criteria and sub‐criteria, a final page displays the classification of the selected feasible site results and in this page users can decide to apply constraints into the final map and categorized suitability area as simply checking a radio button (see Fig. 3b). At this point, users are more aware of the task that they are involved in and, arguably, are better able to judge the parameters of location integration (Jeong et al., 2012).

Fig. 2: Web page that shows the criteria selection process that users must select one of three criteria and equal weight option, after logged in the system.

The expected scope, design, validation, analysis and use of the preference survey need to be described as shown in Fig. 4. First, a web‐ based survey questionnaire have been designed as clear manner using up‐to‐date standards which will perform individual preference elicitations due to the large number of participants to be surveyed (Reips, 2002). To get as many respondents as possible, it is based on an interactive web‐based survey which will not only provide a qualitatively better elicitation of preferences but will directly store the results in a data server. The technical implementation was achieved to generate dynamic web‐pages, the online questionnaire and to save the transferred data to database server. Thus, it did not contain additional plug‐ins or special software on the clients’ side computer. Another important factor for ensuring the acceptance of web‐based survey was the validation of intended participants’ requirements. As a

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confirmatory step, personal interview have been conducted to validate the survey as designed by conducting a limited number to check any difference in preferences revealed by the survey. In the other way, we can do a follow‐up after the full survey.

2.3.2. Measures

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attitude toward rural tourism buildings integration, perceived quality, and interface satisfaction employ five‐point scales ranging from (1) completely disagree to (5) completely agree, respectively since the AHP scales are from 1 to 10 which are too fine. The remaining survey grades are interpolated from the minimum to maximum values.

Fig. 4: The flow diagram of the web‐based post‐task survey questionnaire.

2.3.3. Data analysis

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providing a valuable incentive to complete the survey which will assure a consistency between the specified preferences and the resulting, Pareto‐efficient solution.

3. Results and discussion

The web interface as currently implemented uses the information to enable participants to make decisions on the issues of integrating rural tourism buildings and their components within landscapes. First, an open and participatory planning process was conducted to be necessary in order to gain participants’ opinions for the project and to find a consensus solution for further planning strategy. Then, a detailed analysis of the participants’ content and survey results was done to judge the sample representativeness and provide a statistical basis for the subsequent analyses reported in Sections 3.2 to 3.6.

3.1. Profile of the participants

The number of participants who visited the web site from different backgrounds and ages amounted to 258, further introduced the MCDA ranking process with feedback comments, yielding a total 243, and finished the online post‐task questionnaire, amounting a total 212 responses. The response rate for the MCDA ranking was 94% and for the online survey was 82% (number of people who evaluated at least one step weighting process and answered at least one question of the online survey). With the survey data, the typical socio‐demographic profile was analyzed to support their interpretation. Socio‐ demographic background information on the survey respondents is presented in Table 1. The gender distribution was quite equal, with a slight bias towards men. The age of the participants ranged from 18 to more than 65 years, with an average age of just under/over 35 years. Almost half of respondents (101, 47.7%) have physical territorial relation with the study area. About one in five not lives in the area but have a strong emotional attachment due to their personal reasons (41, 19.4%) and 70 respondents (32.9%) do not have any relationship with this region. Much more than half have at least a bachelor’s degree (136, 64.1%) and more than half have the related occupations associating with the proposed objectives (110, 51.7%). The participants, therefore, had enough qualification to rate the MCDA weighting ranking and following post‐task questionnaires.

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Table 1: Socio‐demographic background variables of the participants in survey (n=212).

Registration Questionnaires Frequency % Gender Female 99 46.7 Male 113 53.3

Age More than 65 8 3.8 50‐64 24 11.4 35‐49 81 37.5 34 or younger 99 47.3

Relationship with the case study area Live permanently in the study area 39 18.6 Live in the study area’s close vicinity 46 21.7 Part‐time residents or vacationers in the 16 7.4 study area Not live but have strong attachment with 41 19.4 the study area Not have any relationship with the study 70 32.9 area

Education Comprehensive education 39 18.3 Secondary level (high school or vocational 37 17.6 education) Tertiary level (university or polytechnic) 136 64.1

Occupation Related one with the proposed objectives 110 51.7 Entrepreneurs/Professionals/specialists 5 4.9 White‐collar workers 37 34.1 Blue‐collar workers 11 10.4 Others 57 50.6 Not related one with the proposed 102 48.3 objectives Entrepreneurs/Professionals/specialists 24 23.5 White‐collar workers 34 33.3 Blue‐collar workers 15 14.4 Others 29 28.8

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Additionally, to strengthen the interpretation of the survey data, the typical socio‐demographic profile were divided and analyzed within the four clusters according to the attachments of the case study area social and emotional terms: the respondents in the first cluster were the most indifferent to the place, named weak ties; the second cluster had social connections but not emotional attachments within the region, named socially linked; the third cluster of participants had strong roots in the region and some attachment to the place in emotional terms, named roots and resources; and, the final cluster was strongly attached to the place in emotional terms but weakly in social terms, named dedicated to the place.

3.2. Perception of building integration into a landscape

The empirical results of the MCDA ranking process by the participants are shown in Fig. 5, criteria and sub‐criteria distribution, respectively. The horizontal axis is the criteria and sub‐criteria name, and the vertical axis is the fraction of respondents selecting each choice shown in different colours. Among three criteria, namely physical, environmental and socio‐economic including the equal weight, most often (65%), the participants had selected the environmental criteria. Then, they had chosen sub‐criteria as follows: land use factor got the highest ranking point (55%) in the physical criteria; vegetation type factor got the highest point (43%) in the environmental criteria; and, in the socio‐economic criteria, site access factor got the highest point (46%). Regarding the selected suitable map layer, the appropriate areas were identified for new rural building siting of Hervás (the northern Extremadura region), Spain. The methods of SAW were selected as the proper way to dissolve the multiple criteria problem of rural tourism building with landscapes as presenting the final suitability area map.

Fig. 5: The MCDA weighting ranking results of criteria and sub‐criteria.

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The perceptions of building integration differed according to four cluster groups related with the study area attachment in social and emotional terms. As shown in Table 2, the perception of landscape elements is surely accepted by the all clusters (all mean 4.13, on a five‐ point scale), which roots and resources cluster presented less positive result (mean 3.90) comparing with the other clusters and especially having a distinguished difference with dedicated to the place cluster as seeing the denotation letters A and C. The perceptions about the constructed elements in the study area showed the opposite result against the question about landscape elements. In the case of the building integration results and its future contribution, the final suitable mapping process is surely accepted by the most participants and all clusters expressed the positive results (all mean 4.16 and 4.13, respectively) as showing slightly difference between roots and resources and dedicated to the place cluster. Therefore, respondents who have more attached to the place in emotional terms gave the negative responses than others who do have attachment to the place in social terms for building integration. Even the latter group demonstrated more positive attitude than indifferent group, weak ties.

Table 2: Perceptions of building integration amongst the cluster groups, showing significant (p≤0.1) differences.

Average score (Five‐point scale, minimum 1 . . . 5 maximum) Roots Dedicated Questionnaires Weak Socially p‐ and to the All ties linked value resources place Building integration

perceptions I generally feel natural landscape elements in the 4.25A,B 4.04B,C 3.90C 4.34A 4.13 0.002 study area are important The constructed elements in the study area are 3.96A,B 4.15A,B 4.31A 3.83C 4.06 0.002 acceptable I have positive thought for the possible integration 4.09A,B 4.19A,B 4.33A 4.02B 4.16 0.070 results I am willing to contribute to 4.05A,B 4.22A,B 4.28A 3.95B 4.13 0.048 its future integration

Mean 4.09 4.15 4.20 4.03 Note. The letters A, B and C in the same row denote clusters with significant differences at the 0.1 significance level.

3.3. Certification of possible impact on tourism

The stakeholders had large differences in the perceptions of the importance of the ecological, social and economic impacts, which naturally affected the preference order of the planning alternatives (Mustajoki et al., 2004). When asked to rate of possible impact on tourism (see Table 3) based on the previous cluster groups, survey

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respondents generally felt that the study area has quite a lot of rural character (all mean 4.08), and that rural character preservation is very important for tourism (all mean 4.09). These responses establish consistency in respondents’ attitudes towards maintaining rural character, and indicate an acknowledgement that rural character is worthy of attention. Specifically, people who have more attachment in emotional terms (dedicated to the place, mean 4.33 and 4.36, respectively) gave the positive responses than one who have more attachment in social terms (roots and resources) (mean 3.90 and 3.85, respectively).

Table 3: Perceptions of possible impact on tourism amongst the cluster groups, showing significant (p≤0.1) differences.

Average score (Five‐point scale, minimum 1 . . . 5 maximum) Roots Dedicated Questionnaires Weak Socially p‐ and to the All ties linked value resources place Possible impact perceptions on

tourism I generally feel that the study area has quite a lot of rural 4.03B 4.06A,B 3.90B 4.33A 4.08 0.005 character Rural character preservation 4.22A 3.93B 3.85B 4.36A 4.09 0.000 is very important for tourism I believe the local government generally support tourism 4.18A 3.89B 3.96A,B 4.17A,B 4.05 0.037 activities The model well presented where this new development 4.05 4.24 4.24 3.97 4.12 0.066 should occur for tourism

Mean 4.12 4.03 3.99 4.21 Note. The letters A and B in the same row denote clusters with significant differences at the 0.1 significance level.

Thus, there were two survey questions that focused on participants’ attitude toward planning issues, including general support of planning, resource protection, and specific planning strategies. First, survey participants were asked how much they believe the local government support tourism activities for the study area generally. Overall, scores revealed that the participants supported the idea but according to the attachment in social terms the results differed in the denotation letters A and B. Though about 22% of the respondents rated their support for the local government involvements as average or low (scores between 1 and 3), the 28% respondents rated their support for the local government as “a great deal” (score 5). An earlier question in the survey asked participants about their attitude towards the final suitable map the model well presented where new development should occur for tourism. The results showed the most participants agreed the final suitable map which depicted the suitable development map (all

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mean 4.12) but cannot find the significant difference amongst cluster groups.

3.4. Examination of knowledge sharing

To test the knowledge sharing through the proposed web interface, e‐ shift, and its results, frequent users’ classification results count and online survey had been conducted. As the first step, a knowledge map step which is after the MCDA ranking process presents a data archive of all users’ classification results and from this developer can check users’ sharing activities through the accessing data. Here, the knowledge map is the final resource of this application for documenting, sharing, and reuse among users. All comments between users are saved in a database as a record of personal secure knowledge sharing. Secure knowledge may be transferred and applied to other users’ processes. For example, users can read previous contributions, and learn about others perspectives on the suitability of locations or may wish to revisit, and possibly revise, their own classifications

Table 4: Perceptions of knowledge sharing amongst the cluster groups, showing significant (p≤0.1) differences.

Average score (Five‐point scale, minimum 1 . . . 5 maximum) Roots Dedicated Questionnaires Weak Socially p‐ and to the All ties linked value resources place Knowledge sharing perceptions The communication interface in the planning process is 4.32A 4.11A,B 3.96B 4.28A 4.17 0.004 important I generally feel that the knowledge map is quite useful and effective step to share and 4.29A 4.09A,B 4.00B 4.24A,B 4.16 0.047 reuse the other participants’ experiences I checked other participants’ classification at least once 4.26 4.07 3.97 4.26 4.14 0.056 when I use this model A shortcut button to directly access the knowledge map is 4.33A 4.11A,B 4.03B 4.24A,B 4.18 0.036 useful

Mean 4.30 4.10 3.99 4.25 Note. The letters A and B in the same row denote clusters with significant differences at the 0.1 significance level.

From the results of the online survey (see Table 4), respondents generally felt that the communication interface in the planning process is important (all mean 4.17). Then, the knowledge map is quite useful and effective step to share and reuse the other participants’ thoughts which were archived in the database server (all mean 4.16). In these two questions, roots and resources cluster showed less positive

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response than the others. For the questions to check the actual use of the knowledge map, users presented their opinions that they checked other participants’ classifications and due to change their minds then processed new classification to see the different results in the all cluster groups. The respondents checked other participants’ classification at least once when they are using the model (all mean 4.14). Additionally, they showed that the direct shortcut button is useful to access the knowledge map with the less positive response in roots and resources cluster.

3.5. Assessment of web interface’ usability

All computer software has limitations; these limitations are important measures of functionality. The software developer must analyze the limitations in light of the constraints of the operating environment and the typical problems solved in the course of the organization’s business ‐ another indication that the developer needs to be highly skilled (Hand, 1989).The evaluation process must include a complete review of how well the program functions on your computer hardware. The functionality must be tested on all equipment. Then, the usability requirement evaluation involves assessing software components to see if they must comply with the guide for evaluation engineering software (Nielsen, 1994). Moreover, the system interface which is included in these features is a significant element which could influence the functionality of software and the efficiency of users.

Before executed the online public use, we verified that this system can perform all tasks properly, system capabilities had been tested. Then, to test the usability of the web interface, we had the online survey’s results, 212 participants were involved to fill in the questionnaire. With these data (see Table 5), we found out some results about a series of questions: respondents felt the system is self‐explanatory which explains web browser gives understandable user interface (all mean 4.17); the most participants responded that the interface allowed for the proper graphical results and interface methods, describing menu, sub‐menus, image formats and tabular forms (all mean 4.28); results showed that the system does not need additional software or plug‐ins to execute it properly (all mean 4.27); and, results presented that the system can detect error messages when input data is not proper format or invalid for the system and needs to be corrected before continuing the process (all mean 4.24). Not like previous three perception tests, statically these series of questions do not have any particular difference amongst the cluster groups.

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Table 5: Perceptions of usability testing amongst the cluster groups, showing significant (p≤0.1) differences.

Average score (Five‐point scale, minimum 1 . . . 5 maximum) Roots Dedicated Questionnaires Weak Socially p‐ and to the All bonds connected value resources place Usability testing perceptions I feel that the system is self‐ explanatory which explains web browser gives 4.28 4.11 4.01 4.29 4.17 0.073 understandable user interface The interface allows for the proper graphical results and interface methods, 4.32 4.11 4.00 4.29 4.28 0.024 describing menu, sub‐ menus, image formats and tabular forms The system does not need additional software or plug‐ 4.26 4.09 4.00 4.31 4.27 0.090 ins to execute it properly The system can detect error messages when input data is not proper format or invalid 4.33 4.29 4.15 4.28 4.24 0.088 for the system

Mean 4.30 4.08 4.04 4.28

3.6. PCA test for all survey variables

To understand the participants’ opinions on the web interface, the web‐based post‐task questionnaires were distributed to the participating users to collect quantitative data and analyzed in the previous steps. The results from the survey are expressed as means ± standard deviation and were analyzed using a one‐way analysis of variance (ANOVA). When ANOVA detected significant differences between mean values, means were compared using Turkey’s test at the p≤0.1 significance level with the aid of SPSS 15.0 software. Thus, to understand the characteristics and relationships of samples, the principal component analysis (PCA) test was applied to analyze the questionnaire data. The PCA is a linear transformation of a set of original data to a set of uncorrelated components in such a way that only a few of the resulting variables account for the majority of the variability observed in the original data (Calvo et al., 2011; Leite et al., 2010). We carried out the PCA test in order to find the specific correlations of all variables in the issues of rural tourism building integration, particularly between all groups and questions. Therefore, a reduction in dimensionality is achieved with minimal loss of information. This reduction is significant in the evaluation of large datasets, containing many interrelated variables.

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Visualization of the results of the PCA is usually achieved by plotting pairs of the first few PCs. In our study, the principal component 1 (PC1) and principal component 2 (PC2) represented the system variance. Figures 6 and 7 represent the scores (analyzed samples) and loading (variables) plot for all the studied groups and questions. From the scores plot (see Figure 6) it can be observed how roots and resources cluster group (Group 3) formed different clustering separated from the rest of samples (Group 1, 2 and 4) according to PC1. According to the loading plot, three questions amongst 16 ones showed the different clustering which presented dissimilar results in question 2, 3 and 4 (see Figure 7). These tree questions are related with the building integration perceptions and roots and resources cluster group relating with the previous figure demonstrated the different clustering towards the raised problem. Apart from that, all questions are grouped without differencing participants’ responses according to the loading plot.

Fig. 6: Score plot after PCA of the individuals in the four cluster groups defined by the two first PCs, PC1 and PC2.

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Fig. 7: Loading plot after PCA of the variables in the questions defined by the two first PCs, PC1 and PC2.

4. Conclusions

A mutual participatory web‐based spatial planning interface, named e‐ shift, is described in the support of rural tourism building integration decision‐making. The study presents an efficient web interface in the Hervás area (Extremadura region), Spain. We implemented and tested an approach the AHP/SAW clustering procedures for generating a wide range of decision alternatives based on this web interface. Thus, with the qualitative and quantitative database set using the content and survey analysis of participants’ data, we were able to clarify the views of the participants, and consensus on the proposed research hypotheses: the identification of spatial models for the different perception and knowledge sharing of building integrations into the rural landscape; the certification of the possible impact on tourism; and, the definition of interface usability.

The factor analyses of four different groups in the relation with the study area, weak ties, socially linked, roots and resources, and dedicated to the place, revealed that the clusters differed by each characteristic and their attachment in social and emotional terms. The interesting finding based on the ANOVA and PCA test is roots and resources cluster group differed most of the other groups in some perception examinations. Especially, the question 2, 3 and 4 of the PCA test in building integration category revealed more different than other ones, more positive responses to this category. In the ANOVA test, this group showed also more positive to building integration and tourism impact compared with dedicated to the place group, revealed more

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negative to the same issues. Additionally, we found the difference among clusters in social and emotional terms, especially the categories of knowledge sharing and usability testing based on the ANOVA test. Not or less socially attached clusters, dedicated to the place and weak ties, revealed more positive responses. In general, however, the differences between the clusters were relatively small. Thus, the relevant of an emotional attachment to the place and willingness to participate future integration did not differ significantly although it is often assumed to their close interrelation.

The objective was that with an exhaustive analysis that involves all the interest groups, public acceptance and commitment to the decisions to be made could be achieved. The overall objective was to achieve consensus on the recommendations for the web‐based spatial planning through improved understanding of the complex nature of the current problems and of the other interest groups’ preferences. Thus, the results present that the application is spatial, simple and flexible to facilitate the different methodology implementations from decision alternatives involved in the decision‐making process.

Video abstract

This work is a video instruction made by ScreenFlow, a screencasting and video editing software for the Mac OS X operating system, to guide users to use a proposed web‐based application, named e‐shift. With this video, each user can be more perceptible for this web application while participating at the most suitable way and then can express his/her individual experiences. Thus, to perform the proper execution of the interface, they will go consecutively through the general overview section, the MCDA section, the knowledge map section, and, finally, the post‐task questionnaire section which is compatible with any web browser.

Acknowledgements

This research has been carried and carrying out with the financial support from Captación y Formación de Recursos Humanos de Excelencia en Investigacioón, Desarrollo e Innovación (Universidad de Extremadura) and Ministerio de Ciencia e Innovación (BIA 2007‐61166); the support of both institutions is gratefully acknowledged.

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CONCLUSIONS AND FUTURE WORK

5. This chapter summarizes and discusses the findings obtained during the research for this dissertation and proposes possible future works. Consisting of three sections, this chapter is discussed with the outcome with respect to research motivations and objectives phrased in the previous chapters. Then, the limitations of the research are discussed in the next section, followed by an outlook on future researches in the last section of this chapter.

5.1. Summary and discussion

The goal of this dissertation was to develop a novel approach for a mutual participatory web‐planning interface to support rural tourism building integrations into a landscape that combine geographic information system (GIS) and multi‐criteria evaluation (MCE). The data presented and analyzed in the preceding chapters of this study have been revisited first and have answered the research objectives addressed in Chapter 2 as follows:

Research objective 1. Describe a spatial methodology for determining the location/site suitability of rural tourism building based on the understanding the limitations of the existing regional planning in the northern Extremadura region, Hervás (Spain), using the analytical hierarchy process (AHP) for multi‐criteria evaluations (MCE) combined with fuzzy standardization and the simple additive weighting (SAW) (Eastman, 2003) in a GIS environment: As the first part of the dissertation, the results has shown the process of the identification and application of GIS‐based MCE for characterizing and assessing suitable sites of rural tourism buildings into a landscape in the Hervás area (the Extremadura region), Spain. In particular, the case study has presented an approach of the AHP/SAW clustering procedures for generating a wide range of decision alternatives for these rural building suitability problems, considered to eliminate subsequent impacts and adverse long‐term effects which affect to choose it. The MCE was utilized to form the siting problem into a decision structure of four hierarchical levels: the goal, evaluation criteria, sub‐criteria and spatial attributes. Then, the AHP method was utilized to extract the relative importance weights of the evaluation criteria and the SAW method was utilized to calculate the suitability indexes, in order to solve the rural building integration problem with its landscape. The selection of criteria presented in this work was limited to only currently available data from public sources in accordance to Extremadura (LESOTEX, Law 15/2001 of land and landscape planning of Extremadura), European Union (EU) legislation

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and relevant literatures. Thus, as an analytical procedure, a group discussion session with the experts was considered to reduce authors’ subjectivity, to identify the weights generated, and to reach a consensus for weights. With the possible clustering scenarios based on three major criteria which were combined with fifteen sub‐criteria, the results presented that land suitability increases as the suitability index increases as an initial ranking of the suitable areas. Areas with suitability indexes from 0 to 4 can be generally considered as unsuitable for new rural tourism building siting. Sites with grades ranging from 9 to 10 are expected to be the best sites for new rural tourism building siting in the proposed study area. Thus, the methodology presented is flexible as far as criteria’ determination is concerned and can easily extend as taking other parameters of criteria and sub‐criteria which could yield different decision alternatives. The main goal of these preliminary results, therefore, is the flexible methodology implementation rather than all possible criteria and sub‐ criteria evaluation. The study results demonstrate that the goal of the approach is not to find a single suitable solution, but to explain the weighting flexibility strengths of the application. Likewise, the methodology discussed in this part can be very useful not only in the final decision but also in the decision‐making process.

Research objective 2. Demonstrate design and implementation of web GIS application with the proposed spatial methodology which can help decision‐makers learn interactively and iteratively about the nature of the problem and their own preferences for desirable characteristic of solution and solve complex spatial problems reflected in the functionality with the associated system and which can identify and formulate suitable criteria and spatial models for the right rural tourism buildings’ integration into their landscapes: In the second part of this work’s results, we have dealt with the fact that the web prototype design and implementation based on the previous methodologies was developed to support a decision‐making processes for asynchronous and distributed collaboration. The design and implementation of a conceptual web‐based GIS model with the methodology has been described that identifies and formulates spatial models for the spatial planning integration, asynchronous decision making, user perception integration and verification of tourism resources, together with its application to a case study in Hervás, Spain. The proposed prototype implemented on the internet information server (IIS) incorporates four elements: a general overview area, a multi‐criteria spatial decision supporting area, a knowledge map area and a post‐task questionnaire area. Although the prototype has four steps, it is intended to be a holistic and seamless environment with a top navigation bar and other components as visually consistent web pages. Thus, an analysis of each step’s functionality and capability will produce more specific design requirements of the prototype. Through the proposed system, users are able to learn interactively and

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iteratively about the nature of the problem, and their own preferences for desirable characteristics of solution, the knowledge map supports and stimulates the sharing of opinions and, hence the clarification and discussion of interests behind user’s preferences. This model, however, will be successful only if the participants in the process are willing to communicate among the disciplines involved, in order to increase the level of understanding and awareness among all parties, and to work towards a common vision. This will require a change in the approach of participants to an inter‐disciplinary focus. Thus, in general, the acceptance of these tools will improve if there are transparent connections with generally accepted elements of empirical practice, availability of suitable data, and functions that target specific regulations and procedures to be undertaken on a regular basis. In this step, the system was a proof‐of‐concept implementation by the developer. The suitability tests of the proposed model need to conduct its integrative improvement. A software usability engineering approach (Nielsen, 1994) will be considered during prototype application testing for evaluating both computational capability and a graphical user interface (GUI). After improving a web application prototype, a set of survey and interview will provide numerical data about participants’ performance using this system to realize its true benefits and potentialities. In addition, it will determine whether this system improves users’ learning in the whole process and also will identify appropriate directions for the use of knowledge.

Research objective 3. Test and observe the effect of the process of how the research can contribute to support consensus on stakeholders’ decision‐making, allowed them to calibrate the method, measuring users’ perception and knowledge sharing about building integration, defining the interface adequacy, and certifying the possible impact on tourism resource suitable carried out the analyses through the qualitative and quantitative database set: The third and last part of this research’s results has dealt with the mutual participatory web‐planning interface implemented to enabling participants to make decisions on the issues of integrating rural tourism buildings and their components within landscapes and their content and statistics analyses based on multi‐criteria decision analysis (MCDA) ranking weighting, frequent classification result count for knowledge sharing and post‐task survey questionnaire. Herein, we tested an approach the AHP/SAW clustering procedures for generating a wide range of decision alternatives for an open and participatory planning process and finding a consensus solution for further planning strategy based on this web interface. Then, with the qualitative and quantitative database set using the content and survey analysis of participants’ data, we were able to clarify the views of the participants, and consensus on the proposed research hypotheses. The empirical results in the most selected of the MCDA ranking process by the participants are shown as the following: environmental criterion (65%); land use in physical criterion (55%);

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vegetation type in environmental criterion (43%); and, site access in socio‐economic criterion (46%). To check the knowledge sharing, frequent classification result count was used from all users’ classification results showing that at least a user read and commented two different classifications per day. And, for the survey analysis, the factor analyses of four different cluster groups, weak ties, socially linked, roots and resources, and dedicated to the place, revealed that the clusters differed by each characteristic and their attachment in social and emotional terms in the relation with the study area. The interesting finding based on the analysis of variance (ANOVA) and principal component analysis (PCA) test is roots and resources cluster group differed most of the other groups in some perception examinations. Especially, the question 2, 3 and 4 of the PCA test in building integration category revealed more different than other ones, more positive responses to this category. In the ANOVA test, this group showed also more positive to building integration and tourism impact compared with dedicated to the place group, revealed more negative to the same issues. Additionally, we found the difference among clusters in social and emotional terms, especially the categories of knowledge sharing and usability testing based on the ANOVA test. In general, however, the differences between the clusters were relatively small. Thus, the relevant of an emotional attachment to the place and willingness to participate future integration did not differ significantly although it is often assumed to their close interrelation. The overall objective in this part was to achieve consensus on the recommendations for the web‐based GIS spatial planning through improved understanding of the complex nature of the current problems and of the other interest groups’ preferences. Thus, the results present that the application is spatial, simple and flexible to facilitate the different methodology implementations from decision alternatives involved in the decision‐making process.

5.2. Limitations

Despite the contributions and promising outcomes achieved, a number of challenges still need to be overcome as follows:

 The analysis of some responses from open‐ended feedback equipments revealed improvements that can be made in the web application to create more comprehensive GUI design, spatial planning application and knowledge communications. Several participants, mostly middle aged and older, commented that some part of web application was not easy to go through although each part has own instruction. It might be a solution to make a visual workflow which will makes users less confusion to use a system not normally accessed.

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 In the sense of spatial planning and knowledge communications, several reviewers pointed out that participation would have been greater and the measurable contribution could have been much greater, if the project could be collaborated with the actual planning courses or bigger sample size, in which more specified groups, participated to provide unfiltered tacit experience and knowledge.

 The maturity of the projects discussed in the knowledge map area was a major barrier of one particular case study. There were a few suggestions on the time schedule for the knowledge map area. The participants describe as being useful but found it difficult to arrange timely knowledge map. They prefer to arrange more knowledge map with specified time frames to form a more cohesive group.

 In the case of the coding system, it would be better to refine and differentiate some sub‐categories. At this point, the techniques of coding are heavily dependent upon the human coder and upon the training of the computer. A future project could significantly benefit from this training and might be able to achieve higher coder reliability. The difficulty in this study was that there were no documented studies of this scale to compare the results of the coding book and the coder reliability. The baseline of comparison was derived from theories and techniques from related fields outside rural spatial planning.

5.3. Future research

Upon completion of this study, what should come next? The findings of this research led to a proposition that will direct future researches:

 What become very apparent in this study that the overall the socio‐technical aspects in the rural planning need to be studied in more depth. They cannot remain anecdotal; they need to be qualitatively and quantitatively researched, since their impact on the successful planning is vital.

 To increase the generalizability of the findings, a broader data sample would be very helpful. Additional samples that span the entire planning cycle would be able to support the modeling of planning information and a decision path model within both of the academic and industrial fields.

 The same content and statistics analysis methodology, with improved definitions of sub‐categories, could be applied to the wider sample. Parallel with improved sub‐categories, other theories or coding schemes other than the ones used could be

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tested for applicability. This would foster the development of more computer–supported coding schemes for the rural planning studies.

 With the different aspects, the same data and platform can be useful to adapt a planning tool for some academic courses. This future project should include more developed communication tool in depth to be coordinated by professors, students and external experts. Thus, it would be possible to apply this application to the other case studies or including buildings’ design criteria evaluation to the same or different case studies.

Therefore, a future study should include a wider spectrum of data sample and categories to increase the generalizability of the research. Carrying this further, the ultimate goal would be to have projects, which are tracked and captured from the project initiation to the final location selection and further design criteria application. This could help to complete the picture of a whole planning and design process and cycle of information flow.

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REFERENCES

Adnan, M., Singleton, A.D., Longley, P.A., 2010. Developing efficient web‐based GIS applications. Working Progress Papers 153, Department of Geography and Centre for Advanced Spatial Analysis, UCL, London, UK.

Alavi, M., Leidner, D., 2001. Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Quarterly, 25, 107–136.

Al‐Ghassani, A.M., 2002. Literature review on KM tools. Technical Report, Department of Civil and Building Engineering, Loughborough University, UK.

Al‐Kodmany, K., 2001. Supporting image ability on the world wide web: Lynch's five elements of the city in community planning. Environment and Planning B: Planning and Design, 28, 805–832.

Anumba, C.J., Ruikar, D., Aziz, Z., Carrillo, P.M., Bouchlaghem, N., 2003. Towards a web of construction knowledge and services. In: 4th ASCE International Joint Symposium on IT in Civil Engineering, Nashville, TN.

Anumba, C.J., Ugwu, O.O., Newnham, L., Thorp, A., 2002. Collaborative design of structures using intelligent agents. Automation in Construction, 11(1), 89–103.

Aoidh, E., Bertolotto, M., Wilson, D.C., 2008. Understand geospatial interests visualizing map interaction behavior. Geo Visualization of Dynamics, Movement and Change, 7(3), 275–286.

Appleton, K., Lovett, A., Sunnenberg, G., Dockerty, T., 2002. Rural landscape visualisation from GIS databases: a comparison of approaches, options and problems. Computers, Environment and Urban System, 26, 141–162.

Armengou, J., Aguado, A., Ormazábal, G., 2012. Sistema integrado para toma de decisiones en el diseño de estructuras de hormigón (An integrated decision‐making methodology for the design of concrete structures). Informes de la Construcción, 64(527), 391–400.

Armstrong, M.P., Densham, P.J., Rushton, G., 1986. Architecture for a microcomputer based spatial decision support system. In: Second International Symposium on Spatial Data Handling, International Geographic Union, Washington.

127

Ayuga, F., 1989. Evolution of agricultural buildings in Spain. Its influence in rural landscape. In: Proceedings of the 11th International Congress on Agricultural Engineering, Dublin.

Ayuga, F., 2001. Gestión Sostenible de Paisajes Rurales. Técnicas e Ingeniería (Sustainable management of rural landscapes. Techniques and Engineering). Mundi‐Prensa, Madrid.

Balana, B.B., Mathijs, E., Muys, B., 2010. Assessing the sustainability of forest management: an application of multi‐criteria decision analysis to community forests in northern Ethiopia. Journal of Environmental Management, 91, 1294–1304.

Barnard, C.I., 1968. The functions of the executive. Harvard University Press, Cambridge, MA.

Batty, M., Dodge, M., Jiang, B., Smith, A., 1998. GIS and urban design. Working Paper, No. 3, Centre for Advanced Spatial Analysis, University College London, London.

Bell, S., 1995. Elements of visual design in the landscape. E&FN Spon, London.

Bishop, I.D., Lange, E., 2005. Visualization in landscape and environmental planning: technology and applications. Taylor and Francis, New York.

Blaschke, T., 2006. The role of the spatial dimension within the framework of sustainable landscapes and natural capital. Landscape and Urban Planning, 75, 198–226.

Böhme, K., Schön, P., 2006. From Leipzig to Leipzig: territorial research delivers evidence for the new territorial agenda of the European Union. disP, 165(2), 61–70.

Brail, R.K., Klosterman, R.E., 2001. Planning support systems. ESRI Press, Redlands, CA.

Calvo, P., Castaño, A.L., Lozano, M., González, D., 2011. Micro‐ encapsulation of refined olive oil: influence of capsule wall components and the addition of antioxidant additives on the shelf life and chemical alteration. Journal of the Science of Food and Agriculture, 92, 2689–2695.

Cañas, I., Ayuga, F., Ortiz, J., 1996. Visual impact assessment for farm building projects. In: Proceedings of the International Conference Agricultural Engineering, Madrid.

128

Carver, S., 2001. Participation and geographical information: a position paper. In: Position paper for the ESF‐NSF Workshop on Access to Geographic Information and Participatory Approaches Using Geographic Information, Spoleto, Italy.

Carver, S., Evans, A., Kingston, R., Turton, I., 2001. Public participation, GIS and cyberdemocracy: evaluating on‐line spatial decision support systems. Environment and Planning B: Planning and Design, 28(6), 907–921.

Carver, S., Kingston, R., Turton, I., 1998. Accessing GIS over the web: an aid to public participation in environmental decision‐making. In: Proceedings of EASST’98, Lisbon, Portugal.

CEMAT, 2006. Glossary of key expressions used in spatial development policies in Europe. In: Proceedings of 14th Session of the European Conference of Ministers Responsible for Spatial/Regional Planning, Lisbon, Portugal.

Chambers, C., Harrison, B., Vlissides, J., 2000. A debate on language and tool support for design patterns. In: Proceedings of the 27th ACM SIGPLAN‐SIGACT Symposium on Principles of Programming Language, New York.

Chen, S.J., Hwang, C.L., 1992. Fuzzy multiple attribute decision making: methods and applications. Springer‐Verlag, New York.

Collins, M.G., Steiner, F.R., Rushman, M.J., 2001. Land‐use suitability analysis in the United States: historical development and promising technological achievements. Environmental Management, 28(5), 611–621.

Council of the European Union, 2001. Council resolution on architectural quality in urban and rural environments (2001/C 73/04). Official Journal of the European Communities, C73, 6/3/2001.

Craig, W.J., Harris, T.M., Weiner, D., 2002. Community participation and geographic information system. Taylor & Francis, London & New York.

Daft, R., Robert, L., Lengel, H., 1986. Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571.

Daft, R., Robert, L, Linda, R., 1997. Message equivocality, media selection, and manager performance: implications for information systems. MIS Quarterly, 11(3), 355–366.

129

Damm, T., 1982. Gute gestaltung muss nicht mehr kosten. In kostengünstige gebäude für die landwirtschaft (Good design does not have to cost more. Cost in agricultural buildings). In: Proceedings of the CIGR Second Technical Section, Braunschweig, Germany.

Davenport, T.H., 2005. Thinking for a living. How to get better performance and result from knowledge workers. Harvard Business School Press, Boston, MA.

Davenport, T.H., Prusak, L., 1998. Working knowledge: how organizations manage what they know. Harvard Business School Press, Boston, MA.

Davison, E., Cotten, S.R., 2003. Connection discrepancies: unmasking further layers of the digital divide. First Monday, 8(3), 9–19.

De Kadt, E., 1979. Tourism: passport to development? Oxford University Press, Oxford.

De Vriesa, S., de Grootb, M., Boersb, J., 2012. Eyesores in sight: quantifying the impact of man‐made elements on the scenic beauty of Dutch landscapes. Landscape and Urban Planning, 105, 118–127.

Deng, Z., LI, H., Tam, C., Shen, Q., Love, P., 2001. An application of internet‐based project management system. Automation in Construction, 10, 239–246.

Densham, P.J., 1991. Spatial decision support systems. In: Maguire, D.J., Goodchild, M.F., Rhind, D.W., (Eds.), Geographical information systems: principles and applications. Longman, London.

DeSanctis, G., Gallupe, R.B., 1987. A foundation for the study of group decision support systems. Management Science, 33(5), 3–10.

DeSanctis, G., Marshall, S.P., 1994. Capturing the complexity in advanced technology use: adaptive structuration theory. Organization Science, 5(2), 121–147.

Di Facio, J., 1989. Designing argricultural buildings in relation to the landscape. In: Proceedings of the 11th International Congress on Agricultural Engineering, Dublin.

Di Fazio, S., 1988. La progettazione dell’edilizia rurale nei suoi rapporti con il paesaggio (The design of rural buildings in its dealings with the landscape). Rivista di Ingegneria Agraria, 10, 379–385.

130

Díaz Martín, A. M., Vázquez Casielles, R., 1998. La calidad de servicio percibida por los clientes y por las empresas de turismo rural (The quality of service perceived by clients and rural tourism enterprises). Revista Española de Investigación de Marketing, 2(1), 31–54.

Dodge, M., Kitchin, R., 2001. Mapping cyperspace. Routledge, London.

Domingo‐Santos, J.M., Fernández de Villarán, R., Rapp‐Arrarás, I., Corral‐Pazos de Provens, E., 2011. The visual exposure in forest and rural landscapes: an algorithm and a GIS tool. Landscape and Urban Planning, 101(1), 52–58.

Dretske, F., 1981. Knowledge and the flow of information. MIT Press, Cambridge, MA.

Drucker, P.F., 1994. Post‐capitalist society. Butterworth Heinemann, Oxford.

Dwyer, J.F., Childs, G.M., 2004. Movement of people across the landscape: a blurring of distinctions between area, interests, and issues affecting natural resource management. Landscape and Urban Planning, 69, 153–164.

Eagles, P.F.J., McCool, S.F., Haynes, C.F., 2002. Sustainable tourism in protected areas: guidelines for planning and management. International Union for the Conservation of Nature, Gland, Switzerland.

Earl, M., 2001. Knowledge management strategies: toward a taxonomy. Journal of Management Information Systems, 18, 215–233.

Eastman, J.R., 2003. IDRISI Kilimanjaro: guide to GIS and image processing. Clark Laboratories, Clark University, Worcester.

Eastman, J.R., Kyem, P.A.K., Toledano, J., Jin, W., 1993. GIS and decision making, United Nations Institute for training and research. Explorations in geographic information systems technology, vol. 4. The Clarks Labs for Cartographic Technology and Geographic Analysis, Clark University, Worcester, MA.

Easton, A., 1973. Complex managerial decision involving multiple objectives. John Wiley & Sons, New York, NY.

Egbu, C.O., 1999. The role of knowledge management and innovation in improving construction competitiveness. Building Technology and Management Journal, 25, 1–10.

131

Español, I., 1995. Impacto ambiental (Environmental impact). E.T.S.I. CamCos, Canales y Puertos, Madrid.

Faraji Sabokbar, H., 2005. Siting commercial services units with using the AHP method (Case study of Torghabeh in Mashahd Iran). Geographical Researches, 51, 125–138.

Fichera, C.R., Di Fazio, S., 1989. Architettura rurale e paesaggio: un rapport da ristabilire (Rural architecture and landscape: to reestablish a close relationship between them). Genio‐Rurale, 52(1), 35–42.

Fountas, S., Wulfsohn, D., Blackmore, B.S., Jacobsen, H.L., Pederson, S.M., 2006. A model of decision‐making and information flows for information‐intensive agriculture. Agricultural Systems, 87, 192–210.

Forman, E.H., Selly, M.A., 2001. Decision by objectives. How to convince others that you are right. World Scientific Publishing Co. Pte. Ltd, London.

Fotache, M., 2006. Why normalisation failed to become the ultimate guide for database designers? Social Science Research Network Working Paper Series. http://papers.ssrn.com/sol3/papers.cfm?abst ract_id=905060 (accessed 11.07.12).

Fowler, S., Stanwick, V., 2004. Web application design handbook: best practices for web‐based software (Interactive technologies). Morgan Kaufmann, San Francisco, CA.

Fricke, C., Faust, B., 2006. Knowledge transfer: acquiring implicit knowledge. International Journal of Nuclear Knowledge Management, 2(1), 46–56.

Fulk, J., Schmitz, J., Steinfield, C.W., 1990. A social influence model of technology use. In: Fulk, J., Steinfield., C.W. (Eds.), Organization and communication technology. Sage Publications, Thousand Oaks, CA.

Gallant, J.C., Wilson, J.P., 2000. Primary topographic attributes. In: Wilson, J.P., Gallant, J.C. (Eds.), Terrain analysis principles and applications. John Wiley & Sons, Inc., New York, pp. 51–85.

García, L., Hernández, J., Ayuga, F., 2003. Analysis of the exterior color of agroindustrial buildings: a computer aided approach to landscape integrations. Journal of Environmental Management, 69(1), 94–103.

132

García, L., Hernández, J., Ayuga, F., 2006. Analysis of the materials and exterior texture of agro‐industrial buildings: a photo‐analytical approach to landscape integration. Landscape and Urban Planning, 74(2), 110–124.

García Moruno, L., Hernández Blanco, J., Ayuga Téllez, F., García Navarro, J., 1998. Localizacion de las construcciones en el ámbito rural ante la protección del paisaje (location of buildings in the rural area and the protection of the countryside). Informes de la Construcción, 50(458), 61–70.

García, L., Montero, M., Hernández, J., López, S., 2010. Analysis of lines and forms in buildings to rural landscape integration. Spanish Journal of Agricultural Research, 8(3), 833–847.

Gascón Linares, M.A., 1993. Turismo rural en España (Rural tourism in Spain). Secretaría General Técnica, Ministerio de Agricultura, Pesca y Alimentación, Madrid.

Gemitzi, A., Petalas, C., Tsihrintzis, V., Pisinaras, V., 2006. Assessment of groundwater vulnerability to pollution: a combination of GIS, fuzzy logic and decision making techniques. Environmental Geology, 51, 797–811.

Golden, B., Harker, P., Wasil, E., 1989. The analytic hierarchy process: applications and studies. Springer Verlag, The Netherlands.

Gómez Orea, D., 1994. Ordenación del territorio. Una aproximación desde el medio físico (Territory ordination. A physical environmental approach). Editorial Agrícola Española, Instituto Tecnológico Geominero de España, Madrid.

Gordon, T., Karacapilidis, N., Voss, H., Zauke, A., 1997. Computer‐ mediated cooperative spatial planning. In: Timmermans, H. (Ed.), Decision support systems in urban planning. E & FN SPON, London.

Gorman, G.E., Clayton, P., 1997. Qualitative research for the information professional: a practical handbook. The Library Association, London, UK.

Grunwald, S., Reddy, K.R., Mathiyalagan, V., Bloom, S.A., 2003. Florida’s wetland WebGIS. In: Proceedings of the ESRI User Conference, San Diego, CA.

133

Guba, E.G., Lincoln, Y.S., 1988. Do inquiry paradigms imply inquiry methodologies? In: Fetterman. D.M. (Ed.), Qualitative approaches to evaluation in education: the silent scientific revolution. Praeger, London, UK.

Haklay, M., Singleton, A., Parker, C., 2008. Web mapping 2.0: the neogeography of the GeoWeb. Geography Compass, 2(6), 2011–2039.

Haldin‐Herrgard, T., 2000. Difficulties in diffusion of tacit knowledge in organizations. Journal of Intellectual Capita, 1(4), 357–365.

Hall, C.L., 1994. Technical foundation of client/server systems. John Wiley & Sons Inc., New York.

Hand, T., 1989. Guide for evaluation engineering software. The American Society of Civil Engineers, New York.

Healey, P., 1997. Collaborative planning – shaping places in fragmented societies. Macmillan Press, London.

Hearn, P., Bradier, A., Jubert, A., 2002. Building communities: organisational KM within the European commission's information society technologies programme. ITcon, Special Issue ICT for KM in Construction, 7, 63–68.

Hellerstein, J.M., Stonebraker, M., Hamilton, J., 2007. Architecture of a database system. Foundations and Trends in Databases, 1(2), 141– 259.

Hendriks, P., Vriens, D., 2000. From geographical information systems to spatial group decision support systems: a complex itinerary. Geographical and Environmental Modelling, 4(1), 83–104.

Hermann, S., Osinski, E., 1999. Planning sustainable land use in rural areas at different spatial levels using GIS and modelling tools. Landscape and Urban Planning, 46, 93–101.

Hernández, J., García, L., Aguga, F., 2004a. Assessment of the visual impact made on the landscape by new buildings: a methodology for site selection. Landscape and Urban Planning, 68(1), 15–28.

Hernández, J., García, L., Ayuga, F., 2004b. Integration methodologies for visual impact assessment of rural building by geographic information system. Biosystems Engineering, 88(2), 255–263.

134

Hernández, J., García, L., Montero, M., Sánchez, A., López, S., 2007. Determinación de impactos producidos en los humedales de Extremadura para su defensa y protección ambiental (Determination of impacts produced in wetlands in Extremadura for its environmental defense and protection). Universidad de Extremadura, Plasencia, Spain.

Hollan, J., Stornetta, S., 1992. Beyond being there. CSCW, 119–125.

Holz, L., Kuczera, G., Kalma, J., 2006. Multiple criteria decision making: facilitating a learning environment. Journal of Environmental Planning and Management, 49(3), 455–470.

Hopkins, L., 1977. Methods for generating land suitability maps: a comparative evaluation. Journal for American Institute of Planners, 34(1), 19–29.

Horanont, T., Tripathi, N., Raghavana, V., Santitamnont, P., 2002. A comparative assessment of internet GIS server systems. In: Map Asia, Bangkok, Thailand.

Horn, R.E., 1965. Developmental testing. University of Michigan, Ann Arbor.

Hsu, S.K., Tan, L.T., 1999. Agroindustry location under output price uncertainty. The Annals of Regional Science, 33(3), 289–303.

Huang, W.W., Kwok‐Kee, W., Watson, R.T., Tan, B.C.Y., 2003. Supporting virtual team‐building with a GSS: an empirical investigation. Decision Support Systems, 34(4), 359–367.

Hwang, C.L., Yoon, K.L., 1981. Multiple attribute decision making: methods and applications. Springer‐Verlag, New York.

INE, 2011. Instituto nacional de estadística (National statistical institute). http://www.ine.es/jaxi/menu.do?type=pcaxis&path=%2F t20%2Fe260%2Fa2011%2F&file=pcaxis&N=&L=0 (accessed 22.03.12).

Innes, J.E., Booher, D.E., 2000. Public participation in planning: new strategies for the 21st century (Working paper 2000‐07). Institute of Urban and Regional Development, University of California, Berkeley.

Inyang, H.I., Fisher, G.F., Mbamalu, G.E., 2003. A quantitative methodology for indexing environmental sensitivity and pollution potential. Environmental Monitoring and Assessment, 84, 159–173.

135

Jackson, A., 2000. Consultation for the 21st century. Arts Council of Northern Ireland, Belfast, UK.

Jankowski, P., Nyerges, T., Smith, A., Moore, T.J., Horvath, E., 1997. Spatial group choice: a SDSS tool for collaborative spatial decision‐ making. International Journal of Geographical Information Systems, 11(6), 577–602.

Jaraíz, F.J., Mora, J., Gutiérrez, J.A., Jeong, J.S., 2013. Comparison of regional planning strategies: countywide general plans in USA and territorial plans in Spain. Land Use Policy, 30(1), 758–773.

Jeong, J.S., García‐Moruno, L., Hernández‐Blanco, J., 2011. Web‐based interoperability system: a collaborative method to integrate rural buildings with their surroundings. In: Proceedings of International Conference on Urban Planning, Regional Development and Information Society, Essen, Germany.

Jones, B., 1990. Neighborhood planning: a guide for citizens and planners. Planners Press, American Planning Association, Chicago and Washington, D.C.

Jovanovic, M.N., 2003. Spatial location of firms and industries: an overview of theory. Economia Internazionale, 1(56), 23–82.

Kangas, J., Store, R., 2003. Internet and teledemocracy in participatory planning of natural resources management. Landscape and Urban Planning, 62, 89–101.

Kangas, J., Store, R., Leskinen, P., Mehtätalo, L., 2000. Improving the quality of landscape ecological forest planning by utilizing advanced decision‐support tools. Forest Ecology and Management, 132, 157–171.

Kapetsky, J.M., Nath, S.S., 1997. A strategic assessment of the potential for freshwater fish farming in Latin America. COPESCAL Technical Paper, Rome, no. 10.

136

Keßler, C., 2004. Design and implementation of argumentation maps. Diploma Thesis, Westfälische Wilhelms‐Universitäty Münster, Münster, Germany.

Keefer, D.L., Kirkwood, C.W., Corner, J.L., 2004. Perspective on decision analysis applications, 1990‐2001. Decision Analysis, 1, 4–22.

Kingston, R., 1998. Web based GIS for public participation decision making in the U.K. paper submitted for the NCGIA specialist meeting on “empowerment, marginalisation, and public participation GIS”. In: National Centre for Geographic Information and Analysis, Santa Barbara, California.

Kingston, R., 2002. The role of e‐government and public participation in the planning process. In: Proceedings of the 16th AESOP Congress, Volos, Greece.

Kingston, R., Carver, S., Evans, A., Turton, I., 2000. Web‐based public participation geographical information systems: an aid to local environmental decision‐making. Computers, Environment and Urban Systems, 24, 109–125.

Kraut, R.E., Fussell, S.R., Brennan, S.E., Siegel, J., 2002. Understanding effects of proximity on collaboration: implication for technologies to support remote collaborative work. In: Hinds, P., Kiesler, S. (Eds.), The MIT Press, Cambridge, MA.

Lahdelma, R., Salminen, P., Hokkanen, J., 2002. Locating a waste treatment facility by using stochastic multicriteria acceptability analysis with ordinal criteria. European Journal of Operational Research, 142(2), 345–356.

Laiserin, J., 2002. Hey buddy, can you spare some change. Laiserin Letter. http://www.laiserin.com (accessed 03.06.11).

LEADER and PRODER, 2011. Las políticas europeas LEADER y PRODER en Extremadura (España): el desarrollo rural en Extremadura: las políticas europeas y el impacto de los programas LEADER y PRODER (European policies LEADER and PRODER in Extremadura (Spain): the rural development in Extremadura: European policies and the impact of LEADER and PRODER program). Editorial Académica Española, Mérida, Spain.

Leite, A.L., Filho, R.B.P.G., Vicente, J.V.M. 2010. Forecasting the yield curve: a statistical model with market survey data. International Review of Financial Analysis, 19, 108–112.

137

LESOTEX, 2001. Guía práctica de aplicación de la Ley 15/2001 del suelo y ordenación territorial de Extremadura (Practical guide of the Law 15/2001 application of the soil and land in Extremadura). http://sitex.juntaex.es/sias/Documentacion/guiapractica.pdf (accessed 26.01.12).

Lin, X., 1997. Map displays for information retrieval. Journal of the American Society for Information, 48(1), 40–54.

Lin, Y., Wang, L., Tseng, H.P., 2006. Enhancing knowledge exchange through web mapbased knowledge management system in construction: lessons learned in Taiwan. Automation in Construction, 15, 693–705.

Lorenz, A.D., Mauksch, L.B., Gawinsky, B.A., 1999. Models of collaboration. Primary Care, 26, 401–410.

Maguire, D.J., 1991. An overview and definition of GIS. Geographical information systems: principles and applications. Longman, London.

Makowski, D., Hendrix, E.M., van Ittersum, M.K., Rossing, W.A.H., 2000. A framework to study nearly optimum solutions of linear programming models developed for agricultural land use exploration. Ecological Modelling, 131, 65–77.

Malczewski, J., 1999. GIS and multicriteria decision analysis. John Wiley & Sons, New York.

Marinez‐Moyano, I.J., 2006. Exploring the dynamics of collaboration in interorganizational settings. In: Schuman, S. (Ed.), Creating a culture of collaboration. Jossey‐Bass, San Francisco.

Martinnez‐Falero, E., Trueba, I., Cazorla, A., Alier, J.L., 1998. Optimization of spatial allocation of agricultural activities. Journal of Agricultural Engineering, 69, 1–13.

McAfee, A.P., 2006. Enterprise 2.0: the dawn of emergent collaboration. MIT Sloan Management Review, 47(3), 21–28.

McCall, M.K., 2003. Seeking good governance in participatory‐GIS: a review of processes and governance dimensions in applying GIS to participatory spatial planning. Habitat International, 27(4), 549–573.

McHarg, I.L., 1969. Design with nature. Wiley, New York.

138

Mennella, V., 1997. Qualita´dell ambiente e sviluppo delle aree rurali. (Quality of the environment and the development of rural areas). Genio Rurale, Edagricole, Perugia.

Mertins, K., Heisig, P., Vorbeck, J., 2001. Knowledge management. Best practice in Europe. Springer, Berlin, Germany.

Microsoft, 2009. Stored procedures. http://msdn.microsoft.com/en‐ us/library/aa214299(SQL.80).aspx (accessed 19.06.12).

Miller, E., 2008. How to create website wireframes. http://graphicaldesi gn.about.com/od/effectivewebsites/sswireframes.htm (accessed 10. 05.12).

Montero, M.J., López‐Casares, S., García‐Moruno, L., Hernández‐ Blanco, J., 2005. Visual impact on wetlands: consequence of building sprawl in rural areas of the west of Spain. In: Proceedings of International Congress on Modelling and Simulation, Melbourne, Australia.

Munkvold, B.E., 2003. Implementing collaboration technologies in industry: case examples and lessons learned. Computer supported cooperative work. Springer Verlag, London.

Mustajoki, J., Hämäläinen, R.P., Marttunen, M., 2004. Participatory multicriteria decision analysis with Web‐HIPRE: a case of lake regulation policy. Environmental Modelling & Software, 19, 537–547.

Namahn, D. 2000. Information mapping: a research note. http://www.namahn.com/resources/docments/note‐IM.pdf (access ed 26.07.11).

NATURA, 2000. European commission environment for nature & biodiversity policy. http://ec.europa.eu/environment/nature/natur a2000/index en.htm (accessed 27.10.11).

Newell, S., Bresnen, M., Edelman, L., Scarbrough, H., Swan, J., 2006. Sharing knowledge across projects: limits to ICT‐led project review practices. Management Learning, 37, 67–185.

Nielsen, J., 1994. Usability engineering. Academic Press Inc, Boston.

Nieto Masot, A.G., Gurría, J.L., 2001. SIG para el análisis de la población de los programas de desarrollo rural en Extremadura en la última década (1991–2001) (GIS for the population analysis of rural development programs for the last decade in Extremadura (1991– 2001)). Universidad de Extremadura, Badajoz, Spain.

139

Nonaka, I.O., Takeuchi, H., Umenmoto, K., 1996. A theory of organizational knowledge‐creation. International Journal of Technology Management, 11(7‐8), 833–845.

Ofek, E., Sarvary, M., 2001. Leveraging the customer base: creating competitive advantage through knowledge management. Management Science, 47(11), 1441–1456.

Olson, G.M., 1965. The logic of collective action; public goods and the theory of groups. Harvard University Press, Cambridge, MA.

Olson, G.M., Olson, J.S., 2000. Distance matters. Human‐Computer Interaction, 15, 139–179.

Olson, J.S., Teasley, S., Covi, L., Olson, G.M., 2002. The (currently) unique advantages of collocated work. In: Hinds, P., Kiesler, S. (Eds.), The MIT Press, Cambridge, MA.

Orr, J., 2004. Extranet news: the list. Cyon Research. http://www.extranetnews.com (accessed 27.08.11).

Page, T., Heathwaite, A.L., Thompson, L.J., Pope, L., Willows, R., 2012. Eliciting fuzzy distributions from experts for ranking conceptual risk model components. Environmental Modelling & Software, 36, 19–34.

Painho, M., Peixoto, M., Cabral, P., Sena, R., 2001. WebGIS as a teaching tool. In: Proceedings of the ESRI UC 2001, San Diego, CA.

Peng, Z.R., 1999. An assessment framework of the development strategies of Internet GIS. Environmental Planning B: Planning and Design, 26(1), 117–132.

Peng, Z.R., Tsou, M.H., 2003. Internet GIS. John Whiley & Sons, Hoboken, New Jersey.

Pigram, J., 1980. Environmental implications of tourism development. Annals of Tourism Research, 7, 554–583.

Pillay, A., 2007. Object oriented programming using Java: notes for the computer science module object oriented programming comp200. School of Computer Science, University of Kwazulu‐Natal, Durban.

Pinto‐Correia, T., 2000. Future development in Portuguese rural areas: how to manage agricultural support for landscape conservation? Landscape and Urban Planning, 50, 95–106.

140

Pinto‐Correia, T., Mascarenhas, J.M., 1999. Contribution to the extensification/intensification debate: new trends in the Portuguese Montado. Landscape and Urban Planning, 46(1), 125–131.

Plewe, B., 1997. GIS Online: information retrieval, mapping and the internet. OnWord Press, SantaFe, NM.

Polanyi, M., 1996. The tacit dimension. Doubleday Broadway Publishing Group, New York.

Poyhonen, A., 2005. KM‐factor: a method for analyzing the renewal capability of organizations. In: Proceedings of the 6th International CINet Page 2 Conference: Continuous Innovation‐(Ways of) Making Things Happen, Brighton, UK.

Preiss, K., Goldman, S.L. Nagel, R.N., 1996. Cooperate to compete: building agile business relationships. Wiley, New York.

Reips, U.D., 2002. Standards for internet‐based experimenting. Journal of Experimental Psychology, 49, 243–256.

Renger, M., Kolshoten, G., Devreede, G., 2008. Challenges in collaborative model – a literature review and research agenda. International Journal of Simulation and Process Modelling, 4, 248– 263.

Reyes‐Rodríguez, A.M., 2009. Criterios de diseño de las construcciones rurales atendiendo a los costes de sus acabados y a su integración en el paisaje (Rural constructions’ design criteria serving their finishes costs and their integration into a landscape). Ph.D. Thesis, Universidad de Extremadura, Badajoz, Spain.

Rice, R.E., 1992. Task analyzability, use of new media, and effectiveness: a multisite exploration of media richness. Organization Science, 3(4), 475–500.

Rittel, H.W.J., Weber, M.M., 1973. Dilemmas in a theory of planning. Policy Sciences, 4(2), 155–169.

Roth, M., 2006. Validating the use of internet survey techniques in visual landscape assessment – an empirical study from Germany. Landscape and Urban Planning, 78, 179–192.

Roy, B., 1996. Multicriteria methodology for decision aiding. Kluwer Academic Publishers, Dordrecht.

141

Ruikar, K., Anumba, C.J., Egbu, C., 2007. Integrated use of technologies and techniques for construction knowledge management. Knowledge Management Research & Practice, 5, 297–311.

Ruiz, M.C., Fernández, I., 2009. Environmental assessment in construction using a spatial decision support system. Automation in Construction, 18(8), 1135–1143.

Saaty, T.L., 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15, 234–281.

Saaty, T.L., 1996. The analytic hierarchy process. McGraw‐Hill, New York.

Saaty, T.L., 2005. Theory and applications of the theory of the analytic network processes. Decision making with benefits, opportunities, costs and risks. RWS Publications, Pittsburgh.

Sawasdichai, N., Poggenpohl, S., 2003. User analysis framework: thoughts on cognitive factors for information design on web‐based media. Visible Language, 37(1), 91–95.

Scarbrough, H., Swan, J., Preston, J., 1999. Knowledge management: a literature review. Institute of Personnel and Development, London, UK.

Schrage, M., 1990. Shared minds: the new technologies of collaboration. Random House, New York.

Schmitt, H., 2003. Landschaftbezogenes bauen in Baden‐Wüttemberg. (Landscape‐related buildings in Baden‐Wüttemberg). Landtechnik, 2, 88–89.

Schultze, U., 1998. Investigating the contradictions in knowledge management. In: IFIP Conference on Information Systems, Helsinki, Finland.

Seppelt, R.,Voinov, A., 2002. Optimization methodology for land use patterns using spatially explicit landscape models. Ecological Modelling, 151, 125–142.

Shafer, E.L., 1969. Perception of natural environment. Environmental Behavior, 1, 71–82.

Shenk, D., 1998. Data smog: surviving the information glut. Harper San Francisco, New York.

142

Shklar, L., Rosen, R., 2009. Web application: principles, protocols and practices. Wiley, Glasgow, UK.

Simão, A., Densham, P., 2004. Designing a web‐based public participatory decision support system: the problem of wind farms location. In: Proceedings CORP 2004 and Geomultimedia, 9th International Symposium on ICT in Urban and Regional Planning, Wien, Austria.

Simão, A., Densham, P.J., Haklay, M., 2009. Web‐based GIS for collaboration planning and public participation: an application to the strategic planning of wind farm sites. Journal of Environmental Management, 90, 2027–2040.

Smardon, R.C., 1979. Prototype visual assessment manual. State University of New York, Syracuse.

Smith, L.G., 1993. Impact assessment and sustainable resource management. Longman, Harlow, UK.

Smith, E.A., 2001. The role of tacit and explicit knowledge in the workplace. Journal of Knowledge Management, 5, 311–321.

Smith, C., 2006. Introduction to database indexes. http://www.interspire.com/content/articles/34/Introduction‐ toDatabase‐Indexes (accessed 29.09.11).

Stuart, K.C., Jock, D., Shneiderman, B., 1999. Readings in information visualization: using vision to think. Morgan Kaufmann Publishers, Academic Press, San Diego.

Switzer, C., 2008. Time for change: empowering organisations to succeed in the knowledge economy. Journal of Knowledge Management, 12(2), 18–28.

Tandy, C., 1979. Industria y Paisaje (Industry and Landscape). Ed Leonard Hill Books, Madrid.

Tang, M.Y., 2006. Design and implementation of a GIS. GIS‐enabled online discussion forum for participatory planning. Technical Report, University of New Brunswick, Canada.

Tassinari, P., Carfagna, E., Benni, S., Torreggiani, D., 2008. Wide‐area spatial analysis: a first methodological contribution for the study of changes in the rural built environment. Biosystems Engineering, 100, 435–447.

143

Tassinari, P., Torreggiani, D., 2006. Location planning: a methodological approach for agro‐industrial buildings in rural territory. Transactions of ASAE, 49(2), 505–516.

Tassinari, P., Torreggiani, D., Paolinelli, G., Benni, S., 2007. Rural buildings and their integration in landscape management. Agricultural Engineering International: The CIGR Ejournal, 9, Manuscript LW 07 020.

Teece, D., 1998. Capturing value from knowledge assets: the new economy, markets for know‐how, and intangible assets. California Management Review, 40, 55–79.

Terluin, I.J., 2003. Differences in economic development in rural regional of advanced countries: an overview and critical analysis of theories. Journal of Rural Studies, 19, 327–344.

Thysen, I., 2000. Agriculture in the information society. Journal of Agricultural Engineering Research, 76, 297–303.

Tsai, W., Ghoshal, S., 1998. Social capital and value creation: the role of intrafirm networks. Academy of Management Journal, 41, 464–476.

Tveit, M., Ode, A., Fry, G., 2006. Key concepts in a framework for analysing visual landscape character. Landscape Research, 31(3), 229‐255.

Umar, A., 1997. Object‐oriented client/server internet environments. Prentice Hall Press, Upper Saddle River, NJ.

USDA Forest Service, 1974. National forest landscape management. United States Department of Agriculture. Agriculture Handbook, Washington.

Van der Wulp, N.Y., 2009. Verrommeling van het landschap, de rol van storende elementen (Landscape clutter: the role of disturbing elements). Landschap, 26, 132–144.

Vance, D.M., 1997. Information, knowledge and wisdom: the epistemic hierarchy and computer‐based information system. In: The Third Americas Conference on Information Systems, Indianapolis, IN.

Vargas, L., Zahedi, F., 1993. Analytic hierarchy process and its applications. Mathematical and Computer Modeling, 17, 4–5.

Venters, W., 2001. Review of literature on knowledge management (C‐ sand working paper). http://www.c‐sand.org.uk/Documents/WP10 01‐02‐KMLitRev.pdf (accessed 22.03.11).

144

Voinov, A., Bousquet, F., 2010. Modeling with stakeholders. Environmental Modelling & Software, 25(11), 1268–1281.

Voloshyn, A., Gnatienko, G., Drobot, E., 2003. Fuzzy membership functions in a fuzzy decision making problem. International Journal of Information Theories and Applications, 10, 243–247.

Voss, A., Denisovich, I., Gatalsky, P., Gavouchidis, K., Klotz, A., Roeder, S., Voss, H., 2004. Evolution of a participatory GIS. Computers, Environment and Urban Systems, 28(6), 635–636.

Wascher, D., Múgica, M., Gulinck, H., 1999. Environmental indicators and agricultural policy. In: Brouwer, F., Crabtree, B. (Eds.), Establishing targets to assess agricultural impacts on European landscapes., Wageningen, pp. 73–87.

WFD, 2000. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for community action in the field of water policy. http://eur‐ lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32000L0060:E N:NOT (accessed 18.07.12).

Wiedemann, P.M., Femers, S., 1993. Public participation in waste management decision making: analysis and management of conflicts. Journal of Hazardous Materials, 33(3), 355–368.

Wilcox, D., 1994. The guide to effective participation. The Joseph Rowntree Foundation, London.

World Tourism Organization, (2005). WTO World tourism barometer, 3(2). http://www.world‐tourism. org/statistics/index.htm (accessed 11.09.12).

Yoon, K., Hwang, C.L., 1995. Multiple attribute decision making: an introduction. Sage Publications, Inc., London.

Zeleny, M., 1982. Multiple criteria decision making. McGraw‐Hill, New York.

Zhang, H., Lei, S.L., 2012. A structural model of residents’ intention to participate in ecotourism: the case of a wetland community. Tourism Management, 33, 916–925.

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APPENDIX A

Related publications published or in process

The following publications are related with and continuing from the ideas and fragments of this dissertation:

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1. An operational method to supporting siting decisions for sustainable rural second home planning towards ecotourism in Spain

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An operational method to supporting siting decisions for sustainable rural second home planning towards ecotourism in Spain

Land Use Policy, under review (2013)

Jin Su Jeong, Lorenzo García‐Moruno, Julio Hernández‐Blanco, Francisco Javier Jaraíz‐Cabanillas

12,1

Sustainable ecotourism development is under increasing pressure of urban sprawl with growing recreational and tourist awareness. This paper describes a spatial planning methodology using multi‐attribute decision‐making (MADM) based on the understanding of all possible aspects and implications for siting second home countryside in the study area, La Vera, Spain. Accordingly, this study explores criteria using the analytical hierarchy process (AHP) with the primary screening and supporting opportunities of environmental conservation and economic growth as well which strongly emphasize benefits to the local community and effective management of tourism. To reach a consensus criteria weight, a field survey to local residents and group discussion with a panel of experts are conducted for an analytical procedure, making them more objective. Then, it evaluates the suitability of the study area in order to optimally site a rural second home based on the previous constraints and criteria with the aid of the ordered weighted averaging (OWA) operator weighing functions with constant value of orness and maximum entropy. The assessment results provide a new empirical approach and valuable management tool to evaluating the existing infrastructure and environment and to predicting their future improvements which can be reapplied to other destinations. Particularly, this model analysis proposes a method to enhance the participatory attitudes of local residents in the sustainable assessment management.

Keywords: rural second home; tourism development; multi‐attribute decision‐making; residents' attitude; AHP/OWA.

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2. Decision‐makers’ spatial reasoning for rural tourism building siting

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Decision‐makers’ spatial reasoning for rural tourism building siting

Proceedings on VII Iberian Congress of Agricultural Engineering and Horticultural Sciences (2013)

Jin Su Jeong, Lorenzo García‐Moruno, Julio Hernández‐Blanco, Francisco Javier Jaraíz‐Cabanillas

12,1

In the 20th century, human movements with recreational potential to rural areas are growing and coinciding with the urban sprawl, especially many man‐ made constructions’ cluttering. This paper presents a systematic spatial regional planning approach that utilizes a structured multi‐criteria decision analysis framework to evaluate rural tourism buildings into their landscape, with an empirical case study, La Vera, Extremadura (Spain). Intelligent spatial siting for decision‐makers’ reasoning can capitalize on the multiple benefits of practical actions and can achieve various resource management objectives more efficiently. The focus of the study first determines the evaluation criteria and sub‐criteria based on European planning policy and regional planning law on Extremadura (LESOTEX, Law 15/2001 of land and landscape planning of Extremadura) and the relevant literature review. Then, an expert group discussion is achieved to validate the criteria weights more objective. Evaluation criteria identify a spatial data treatment with a grading system based on constraints, tourism resource, environmental and socio‐economic aspects. The proposed methodology herein uses the analytical hierarchy process (AHP) and the ordered weighted averaging (OWA) functions of multi‐criteria decision modeling evaluating the entire study region using a common grading scale in a GIS environment. The main goal of the preliminary results, therefore, is to show this methodology’s flexibility as exploring different decision alternatives and patterns. In addition, the study results demonstrate that the approach is not to find a single suitable solution as the final decision, but to explain the decision‐making process.

Keywords: location planning; rural tourism building integration; multi‐ criteria evaluation; decision‐making reasoning; flexibility and alternative.

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APPENDIX B

Supplementary materials

1. The following document gives the proof of research collaboration accorded with the European Doctoral Mention:

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2. The following document shows the proof of publication’s acceptance mentioned in the previous section:

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3. The following document describes the whole workflow made by Microsoft Office Visio 2007 mentioned in the previous section:

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VITA

Name: Jin Su Jeong

Current Address: Calle José María Pemán, 51, 1‐B, 28019 Madrid, Spain

E‐mail: [email protected]

Education: Ph.D. with European Mention in Graphic Engineering, Geomatics and Projects, University of Extremadura, 2013 M.S. in Architecture, Texas A&M University, 2006 B.E. in Architecture, Chonnam National University, 2002

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