European Journal of Geography
The publication of the EJG (European Journal of Geography) is based on the European Association of Geographers’ goal to make European higher education a worldwide reference and standard. Thus, the scope of the EJG is to publish original and innovative papers that will substantially improve, in a theoretical, conceptual or empirical way the quality of research, learning, teaching and applying geography, as well as in promoting the significance of geography as a discipline. Submissions should have a European dimension.
Contributions to EJG are welcomed. They should conform to the Notes for authors and should be submitted to the Editor, as should books for review. The content of this journal does not necessarily represent the views or policies of EUROGEO except where explicitly identified as such.
Editor Kostis C. Koutsopoulos Professor, National Technical University of Athens, Greece [email protected]
Assistant Editor Yorgos N. Photis Associate Professor, University of Thessaly, Volos Greece [email protected]
Book Review Editor Gerry O’Reilly Lecturer, St. Patrick’s College, Dublin, Ireland [email protected]
Editorial Advisory Bailly Antoine, Prof., University of Geneva, Geneva Switzerland Board Bellezza Giuliano, Prof., University of Tuscia, Viterbo, Italy Buttimer Anne, Prof., University College Dublin, Ireland Chalkley Brian, Prof., University of Plymouth, Plymouth UK Martin Fran, S. Lecturer, Graduate School of Education Exeter S. Vice President of the Geographical Association Gosar Anton, Prof., University of Primorska, Koper, Slovenia Haubrich Hartwig, Prof., University of Education Freiburg, Germany Nazmiye Ozguc, Prof., Istanbul University, Istanbul Turkey Strobl Josef, Prof., University of Salzburg, Salzburg Austria Van der Schee Joop, Prof., VU University, Amsterdam The Nederlands
© EUROGEO, 2011 ISSN 1792-1341
The European Journal of Geography is published by EUROGEO - the European Association of Geographers (www.eurogeography.eu).
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European Journal of Geography
Volume 2 Number 2 2011
CONTENTS
1 Letter from the Editor
6 DYNAMIC OPPORTUNITY‐BASED MULTIPURPOSE ACCESSIBILITY INDICATORS IN CALIFORNIA Pamela DALAL, Yali CHEN, Konstadinos G. GOULIAS
21 "GLOKAL CHANGE": GEOGRAPHY MEETS REMOTE SENSING IN THE CONTEXT OF THE EDUCATION FOR SUSTAINABLE DEVELOPMENT Markus JAHN, Michelle HASPEL, Alexander SIEGMUND
35 CHILDREN’S MAP READING ABILITIES IN RELATION TO DISTANCE PERCEPTION, TRAVEL TIME AND LANDSCAPE Ekaterini P. APOSTOLOPOULOU, Aikaterini KLONARI
48 USING GIS‐BASED PROJECTS IN LEARNING: STUDENTS HELP DISABLED PEDESTRIANS IN THEIR SCHOOL DISTRICT Ali DEMIRCI, Ahmet KARABURUN, Mehmet ÜNLÜ, Ramazan ÖZEY
62 A MICROECONOMIC ASSESSMENT OF GREECE’S CORE‐PERIPHERY IMBALANCES (1994‐2002): CONFIRMING KRUGMAN’S INITIAL NEW ECONOMIC MODEL Constantinos IKONOMOU
78 STANDARDIZATION OF GEOGRAPHIC DATA: THE EUROPEAN INSPIRE DIRECTIVE Gabor BARTHA, Sandor KOCSIS
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Editorial
Dear Fellow Geographers,
It is a great pleasure as well as an immense satisfaction to see this SPECIAL ISSUE OF THE EJG materialize. Indeed this is a turning point between a process that started several years ago with the formation of the network HERODOTE which was later evolved into EUROGEO, the Association of European Geographers, and a new era whereby our Association has organized its first annual meeting without any outside help or support as well as start publishing the European Journal of Geography.
These new exiting activities became possible because there are many geographers full of new ideas and energy and Geography in Europe is still a young and productive science.
As you know, the European Association of Geographers ‐ EUROGEO is interested in improving the quality of learning, teaching and creating geographic knowledge as well as promoting the significance of Geography as a discipline. Therefore it should not be a surprise that in our Athens conference there were approximately 120 papers presented in 18 sessions ranging from environmental issues, to spatial economics and problems of the Mediterranean region.
Most of these high quality papers were submitted for publication for this special issue of the EJG. Such a massive submission of papers however, on one hand advanced successfully the universally accepted notion that Geography is indeed the best way to study our world we live in, but on the other hand because of their quality created a pleasant but difficult editorial problem of choosing a small number from a set of many excellent papers.
To partially overcome this problem very shortly a new issue of the EJG will appear to provide the scientific community with Geographic knowledge that should be available.
Kostis Koutsopoulos National Technical University of Athens
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European Journal of Geography, 2:2 Copyright © European Association of Geographers, 2011 ISSN 1792-1341
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European Journal of Geography 2 2: 6‐20, 2011. © Association of European Geographers
DYNAMIC OPPORTUNITY-BASED MULTIPURPOSE ACCESSIBILITY INDICATORS IN CALIFORNIA
Pamela DALAL University of California, Santa Barbara, Department of Geography,3625 Ellison Hall, UC Santa Barbara, Santa Barbara, CA 93106-4060 , [email protected], http://geog.ucsb.edu/geotrans
Yali CHEN University of California, Santa Barbara, Department of Geography, 3625 Ellison Hall, UC Santa Barbara, Santa Barbara, CA 93106-4060, http://geog.ucsb.edu/geotrans, [email protected]
Konstadinos G. GOULIAS University of California, Santa Barbara, Department of Geography, 5706 Ellison Hall, UC Santa Barbara, Santa Barbara, CA 93106-4060 http://geog.ucsb.edu/geotrans, [email protected]
Abstract Accessibility, defined as the ease (or difficulty) with which activity opportunities can be reached from a given location, can be measured using the cumulative amount of opportunities from an origin within a given amount of travel time. These indicators can be used in regional planning and modeling efforts that aim to integrate land use with travel demand and an attempt should be made to compute at the smallest geographical area. The primary objective of this paper is to illustrate the creation of realistic space-sensitive and time-sensitive fine spatial level accessibility indicators that attempt to track availability of opportunities. These indicators support the development of the Southern California Association of Governments activity-based travel demand forecasting model that aims at a second-by-second and parcel-by-parcel modeling and simulation. They also provide the base information for mapping opportunities of access to fifteen different types of industries at different periods during a day. The indicators and their maps are defined for the entire region using largely available data to show the polycentric structure of the region and to illustrate this as a method that can be applied in other polycentric regions.
Keywords: hierarchical spatial choice, spatial cluster analysis, multi-scale representation
European Journal of Geography - ISSN 1792-1341
Dalal P.- Chen Y.- Goulias K./ European Journal of Geography 2 2 6-20
1. INTRODUCTION Recent legislation in California aiming at stricter mobile source emissions control and planning for dramatic decreases in Greenhouse Gas (GHG) emissions emphasizes the need for integrated land use policies with transportation policies. This is expected to happen with planning tools such as a Sustainable Communities Strategy (SCS), which among its many objectives also needs to understand residential location and relocation decisions and explain possible futures under different scenarios of policy to a variety of audiences including decision makers and professional planners and engineers (see http://www.ca-ilg.org/SB375Basics). Similar to many European jurisdictions land use planning is in the local level (e.g., the City) and transportation planning is at higher levels. In the US, transportation planning is a foundational activity of Metropolitan Planning Organizations (MPO) that were created in the 1960s to ensure coordinated planning among local jurisdictions. Two of the most important elements of this planning activity are the Long Range Regional Transportation Plan (LRTP), which every 4-5 years creates a vision and a path to reach goals that protect the environment, foster economic growth, and ensure equity and the second is the development of the regional Transportation Improvement Program, which is an multi-billion USD investment plan to satisfy LRTP goals. The recent legislation adds the land use and transportation goal with a SCS to the MPOs. In California the four largest MPOs (their region surrounds Los Angeles, Sacramento, San Diego, and San Francisco) are also required to build simulation models to assess scenarios for meeting specific targets of GHG emissions by 2020 and 2035. At the heart of these urban simulation models are behavioral equations of residence, workplace, and school location choices by households and their members together with activity and travel behavior equations to represent the daily activities and movements of people in the region. All these models and simulation tools are currently developed and often face two major stumbling blocks: a) lack of understanding of the behavioral processes we try to change with the new policies; b) lack of suitable tools to explain spatio-temporal phenomena that emerge from complex interactions among people. The short statement below is indicative of the relationships we should disentangle, understand, and recreate in predictive urban simulation models.
“A household’s decisions of residential location, workplace, activities and travel pattern are an inextricably entangled weave of mutual interdependencies and constraints. Each of these choices is connected to all the others,…” Eliasson, 2010 pg 138.
At the core of this we find spatial structure analysis and particularly the spatial structure analysis of urban environments, which is a key informant about location choices of people. This is becoming extremely important in assessing policy actions that change land use to influence travel behavior and attempts to steer it away from using automobiles. The assessment of these policies, in large metropolitan organizations, is done with urban simulation software that employs discrete choice models (see the review by Waddell, 2002). These models predict location choices (e.g., residence, workplace, school, or possibly other major pegs at which activities take place) using as explanatory variables a variety of location attributes in more or less complex forms of accessibility indicators. In this area we see an increasing sophistication of techniques such as multi-scale approaches that account for spatial and behavioral heterogeneity while attempting to
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Dalal P.- Chen Y.- Goulias K./ European Journal of Geography 2 2 6-20 solve some problems with spatially correlated explanatory variables and counteract potential fallacies. A sample of recent advances are papers by Bhat and Guo, 2004, Guo and Bhat, 2004 and 2007, Mohammadian et al., 2005, Sivakumar and Bhat, 2007, Sener, Bhat, and Pendyala, 2011. In parallel, in policy oriented circles and among advocates of specific land use actions to change travel demand, we also see growing literature offering an emerging typology of spatial structure indicators (e.g., land use density, diversity of land uses, characteristics of the highway infrastructure, proximity to public transportation). The review and meta-analysis of Ewing and Cervero (2010) provide a comprehensive report of the use of these indicators, a link between the policy literature and an estimate of the impact of these indicators on a limited set of travel indicators. As one would expect spatial structure is very important in studies about the historical evolution of settlements (typical example is the urban growth application of Stanilov and Batty, 2010). In all these studies we find accessibility to opportunities for employment and/or activity participation explaining the location choices of households. Accessibility indicators can take a variety of forms but they almost always include some measure of location attractiveness (e.g., amount of activity, number of stores, variety) weighted or buffered by measures of impedance (e.g., travel time to reach activities). Location choice is also a function of a variety of other factors including cost (e.g., price of homes), spatial ethnic segregation (e.g., immigrant ethnic enclaves or other social processes that motivate people of similar cultural traits to co-locate), social exclusion (e.g., specific groups may be excluded from different areas of an urban environment by policy or tradition), or temporary co-location for education or other reasons (e.g., attending a specific college, serving in the military). Underlying all this, a hierarchy exists in the spatial organization of opportunities that characterizes each living environment. In fact, large urban environments are no longer monocentric but show clear emergence of polycentrism (Giuliano and Small, 1991, and the review by Anas et al., 1998). It is important then to identify and describe underlying spatial structures (Hughes, 1993) but this is not a trivial task and should account for transportation infrastructure. Hierarchies are based on geographic space (e.g., region, city, neighborhood, city- block, land parcel), time (e.g., historical time, day of the week, time of day), in-situ social networks (e.g., ethnicity, religious meeting places), and type of activity opportunities (e.g., retail, arts and entertainment, leisure). To the best of our knowledge a method that recognizes this hierarchy explicitly and provides classification of locations using accessibility and segregation, as well as, employs informative opportunity indicators does not exist or it is done in a somewhat ad-hoc opportunistic way. A more systematic approach is useful in developing choice sets, creating new type of explanatory variables for discrete choice models, estimating models tailored to localities of special character, and helps us characterize spatial structure and its evolution for urban simulation models. It may also help us understand, explain, and support the input to and output from urban simulation models. To partially fill this gap we report in this paper findings from a pilot research project with focus on the Southern California five county region (which is also the largest MPO in California) that takes advantage of accessibility indicators computed at a fine level of spatial resolution (the US Census block), for fifteen types of employment, and different times during a day (accounting for opening and closing of businesses and the presence of congestion in different parts of the region at different times of a day). We use these indicators to develop spatial clusters that are able to classify each block based on its own intensity of activity availability and the opportunities available at its adjacent (contiguous) blocks. In this way we derive spatial clusters for a selection
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Dalal P.- Chen Y.- Goulias K./ European Journal of Geography 2 2 6-20 of activity opportunities for each block by first computing this value from each land parcel within the block. These spatial clustering indicators are then used in another clustering process, using Latent Class Cluster Analysis, to classify different parts of Southern California into five categories that range from high accessibility, to medium accessibility, and finally to very low accessibility. We repeat this using the same method for four time periods of a day to describe the evolution of the region during a day and how different localities change in their ability to provide services to their residents. We also study these different groups of blocks in terms of their resident characteristics. In the next section we describe the accessibility indicators used here followed by a section on the spatial cluster analysis and the Latent Class Cluster Analysis together with a description of the time-of-day dynamics. Then we review the findings in the correlation between spatial structure and resident characteristics. The paper concludes with a summary of findings and next steps.
2. ACCESSIBILITY INDICATORS AND THE REGION The block-level accessibility measures described in Chen et al., 2011 are the main source of information to describe the spatial structure of Southern California. These measures are computed at a fine level of spatial disaggregation, which is the US Census block. As described in Chen et al., 2011, we used multiple databases to describe the opportunities available at different levels of spatial aggregation and converted all data into information for each block while rectifying any missing or miscoded information through comparisons of different sources of data. The end result is an account of the number of persons at each block working in any of the fifteen different and mutually exclusive industry types that are: a) Agriculture, forestry, fishing and hunting and mining; b) Construction; c) Manufacturing; d) Wholesale trade; e) Retail trade; f) Transportation and warehousing and utilities; g) Information; h) Finance, insurance, real estate and rental and leasing; i) Professional, scientific, management, administrative, and waste management services; j) Educational; k) Health; l) Arts, entertainment, recreation, accommodation and food services; m) Other services (except public administration); o) Public administration; p) Armed forces. All blocks are connected to a roadway network that includes for each of its links estimated speed for different periods of a day. This network is used to compute shortest paths among all the blocks. There are approximately 203,000 blocks that cover the entire (mega)region surrounding Los Angeles (called the Southern California Association of Governments region). Using these shortest paths we identify for each block all the other blocks that are within 10, 20, and 50 minutes to create travel time buffers. Then, for each period in a day and for each of the fifteen industries we count the number of persons employed by each industry type within each buffer. To account for the different opening and closing times of activity opportunities the number of employees that are reachable in the accessibility indicators changes for each hour in a day. To derive this time of day profile we use information of arrivals and departures from work sites available in a travel survey. In this way the resulting accessibility indicators change with space and time to reflect the rhythms of activity in the region for which they are defined. More details about the method are reported in Chen et al., 2011 and an application to neighborhood analysis in Dalal and Goulias, 2011. Due to the region’s size and vastly varied land use, population for any given block can range from zero to over 7,000 residents. However, the attributes of the built environment described are not equally distributed over the county. For example, the density of transportation
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Dalal P.- Chen Y.- Goulias K./ European Journal of Geography 2 2 6-20 infrastructure increases with population density. This creates different levels of network connectivity and accessibility between urban and rural neighborhoods (Chen, et al, 2011). Other attributes include the distribution of opportunities, which are often more dense in more urban areas of Southern California (Dalal and Goulias, 2011). In this analysis we use accessibility indicators as the core material in developing groups of similar spatial structure. We selected to work with four periods in a day that follow the current SCAG four-step model that provides travel speed and time for each roadway segment for four time periods, AM peak (6 AM to 9 AM), PM peak (3 PM to 7 PM), Midday off-peak hours (9 AM to 3 PM), and Nighttime off-peak hours (7 PM to 6 AM). This allows the calculation of shortest path travel time between blocks for each of these four different periods in a day and analyze blocks in terms of the 10 minute accessibility indicators of all fifteen types of industries. In this way we have fifteen continuous variables for each of the 203,000 blocks covering the entire Southern California. Similarly, the population of Southern California is as varied as the landscape. Within the study region, there exists a certain amount of social and demographic stratification. The average density, age, household income, and household size differ between sub-regions and between neighborhoods as shown in Table 1. One example is in race/ethnicity, which can be very diverse, as in Pasadena, or very homogenous, as in Boyle Heights. Thus, while the built environment varies over space, persons with different socio-demographics populate different spaces.
Table 1. Socio-demographics of selected neighborhoods in Southern California
Region South Bay San Gabriel Valley Westside Southeast Eastside
Rancho Palos Santa Boyle Neighborhood Verdes Inglewood Pasadena Glendale Monica Compton Heights Persons/mi 3,084 12,330 5,366 6,368 9,817 9,199 14,229
Median hh size 2.7 3 2.5 2.7 2 3.9 3.8
Median hh income 128,321 46,574 62,825 57,112 69,013 43,157 32,253
Rented housing 18.1 63.6 54 61.6 70.2 43 75.9
Single parent hh 4.8 26.5 13.4 9.4 12.8 22 21.2
Median age 44 29 34 37 38 24 25
% White 62.8 4 39.1 54.1 71.3 1 2
% Latino 5.6 46 33.3 19.6 13.5 57 94
% Black 2.1 46.4 13.9 1 3.5 40 0.9
% Asian 25.2 1.1 10 16.3 7.1 1 2.4
Source: US Census, 2000
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In our study, we consider the anisotropic spread of environmental attributes and population characteristics as an underlying preference for choice for residences, workplaces, and other activity destinations. This is accomplished by first accounting for the variation in opportunities and persons over space through spatial clustering methods. Second, the clusters of opportunities are associated with persons to describe a probable set of choices based on household survey data.
3. G* ANALYSIS
This study examines spatial clusters of opportunity access aiming at representing subregions within Southern California that display spatial homogeneity, such as a neighborhood of blocks with high accessibility to locations that offer arts opportunities. We account for spatial heterogeneity from large-scale regional effects by using a local indicator of clustering. In addition, we consider spatial dependency in our data. For any spatial outcome, such as land prices, the values in one location are more influenced by the values of nearby locations than values of far locations. However, it is unlikely that any urban phenomenon is spatially independent, so our approach is to describe spatial dependency through spatial clusters. Spatial clusters are built on the concept of spatial dependence, in which things closer to each other are more related than things farther apart (Tobler, 1970). A cluster measures the concentration (or dispersion) of values over space, a simple measure of positive spatial dependence or autocorrelation. In our analysis, a positive cluster specifies when a block which is surrounded by more similar blocks than expected at random. Conversely, a negative cluster specifies when a block is surrounded by dissimilar blocks, more than expected at random, indicating negative spatial autocorrelation. Thus, our first step is to measure the concentration or dispersion of urban attributes by locating and defining the spatial extent of spatial clusters (Jacquez, 2008). However, it is important to note that urban processes, including the distribution of activities, are widely considered to be spatially heterogeneous, in that the outcomes of the processes vary over space (Anselin, 1995; Paez and Scott, 2004; Jacquez, 2008). Spatial heterogeneity is especially true for extensive study areas where large-scale regional effects can influence the mean and variance of spatial processes, thereby biasing spatial clustering analysis of values (Miller, 1999; Buliung and Kanaroglou, 2007). In our study of Southern California, large variation can be found in the number and density of opportunities available to blocks throughout the day (Figure 1 shows box-plots of the sum of all fifteen accessibility indicators). High-density areas such as downtown Los Angeles would affect estimation in a global cluster analysis, such as Moran’s I, thus the use of a local indicator of clustering is highly relevant in a large study area like Southern California. By using a local measure of spatial association, we are able to estimate clusters without large-scale regional bias, and show significant local clusters in rural or outskirt areas (Anselin, 1995).
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Fig.1 Total opportunities during different time periods for Southern California study regions
In our spatial cluster analysis, we use the G statistic, developed by Getis and Ord (1992), to quantify local spatial autocorrelation and dependency and reveal block-level. This measure was selected for its attractive properties and based on a preliminary pilot study using Los Angeles county data alone. The output of the repeated application of G* to each of the fifteen accessibility indicators are fifteen continuous variables of z-scored spatial cluster accessibility indicators. These are in turn used as criteria variables to identify latent classes (LC) using Latent GOLD® 4.5 software (Vermunt and Magdison, 2005), which is a model-based latent class cluster model building system. The analysis starts with a 1-dimensional LC baseline model (one cluster), followed by fitting successively LC models by adding one dimension (additional cluster) each time. The goodness of model fit is assessed using the Bayesian Information Criterion (BIC) value which is a penalizing statistic for excessive estimated parameters and it is a function of the log-likelihood statistic (LL). The final cluster spatial structure is defined as the model with a low BIC value and less parameters. Taking into account parsimony and model fit statistics a 5-class latent cluster model is estimated with the accessibility indicators for each time of day. Figure 2 shows the mean (in z-scores) spatial clustering values of industries for the five clusters and Table 2 shows the cluster sizes during the AM, MD, PM, and NT. The largest cluster is Cluster 1 (Crimson), which accounts for a third of all blocks in the study region. Cluster 1 shows high accessibility for all industry types except agriculture and armed forces. It is lowest during the night time which may be explained by store operating hours. Cluster 2 (Orange) is the second largest class and shows an average accessibility to all industry types. The third largest class is Cluster 3 (Gold) and has lowered access to all industries over all times of day. Cluster 4 (Cyan) experiences very low access to all industries and is fourth in size. This cluster is largest during midday, but then shrinks during the PM peak. The smallest cluster is Cluster 5 (Blue) which experiences very low accessibility to all industries except agriculture and armed forces. This cluster expands during the night time and may include blocks that have
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Dalal P.- Chen Y.- Goulias K./ European Journal of Geography 2 2 6-20 higher accessibility in other time periods. This outcome shows the temporal variability of accessibility that is captured by the LCCA outcome.
Fig.2 Latent Class Cluster Characteristics
Table 2. Size of Latent Class Clusters for time of day
Cluster Size Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5
AM 35.84 20.12 18.13 16.07 9.83
MD 33.1 22.7 18.3 18.3 7.6
PM 36.07 21.86 18.5 13.06 10.5
NT 29.3 20.81 18.4 17.76 13.73
In Figure 3 a map of the blocks classified by cluster membership shows a much clearer spatial structure. There is a clearly definable region in Southern California of high accessibility that stretches along the Pacific Ocean and east to west to the center of the city of Los Angeles.
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Accessibility is in fact enhanced by the presence of freeways as backbone to this structure. In addition, these maps show the polycentric/multimodal character of the spatial organization of the SCAG region (recall this region includes 190 cities). The four maps together also show that the role of these centers (nodes) is for some centers dynamically homogeneous and for some other centers heterogeneous. For example, the coast has many centers that provide high accessibility throughout the day and even at night time (lower right hand map) it maintains good accessibility but for a smaller number of industries than in the day time. Similarly, some areas in the far northeast of the region have poor accessibility all the time. In contrast, there are groups of blocks (e.g., North Orange County) that have dramatic changes of accessibility at night.
Fig.3 Map of Latent Class Cluster Output for Time of Day
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Another reason that clusters show significantly different patterns of accessibility during the night time is also the inclusion of a large portion of zero opportunities for industries at this time, which can bias the clustering outcomes. This is likely why the clusters show a major shift in pattern during the NT, as shown in Figure 3. Cluster 1 is found where clusters of high opportunities are found, with the exception of armed forces and agricultural industries. Cluster 1 is found in the downtown Los Angeles region and a few locations in the east. When comparing the time periods, Cluster 1 is more pronounced in the east in the PM peak, though public and manufacturing opportunities decline. Cluster 2 experiences more heterogeneity in opportunity access with neither high clustering nor high dispersion. In space, Cluster 2 is largely found in the suburban Central Valley extending until the eastern deserts. Importantly, Cluster 2 represents the average heterogeneity in the distribution of opportunities based on the local and global mean in the study region. Cluster 3 shows low levels of dispersed opportunities and is found in small pockets consistent with locations of outer rural towns. Cluster 4 is found in clusters of high dispersion, seen in the Central Valley exurbs and along outer transportation networks. Similarly, Cluster 5 experiences high dispersion, with the exception of high clustering of armed and agricultural opportunities. Near the coast, Cluster 1 clearly represents mixed land use in high density urban areas. However, Cluster 1 also represents high clustering, or rural centers, when found near areas of dispersed armed and agricultural lands in the east. The dynamics in accessibility are more pronounced in these rural areas, with more high clusters in the AM and PM peak than during work hours. Next, Cluster 3 experiences much more dispersion in the PM peak than in earlier time periods. Translated on a map, the exurbs of Los Angeles Valley lose access to many opportunities during the PM peak possibly from congestion or early store closing hours. This is in contrast to Cluster 4 in rural areas which show no change in low clustering values. These clusters can be related to socio-demographic characteristics of the resident populations. As shown in Figure 4, high accessibility clusters have the highest level of percent renters, black, asian, and foreign born residents (which is an indication of the different immigration waves in this area). In contrast, low accessibility clusters are higher in home owners living in areas with high levels of vacant housing. The contrast between these two clusters suggests high accessibility may not be an immediate proxy for desirability, and low accessibility may not describe undesirability. In fact, we find an 11.31% to 13.80% of poverty level residents in all clusters with the highest percentage in the two best access clusters. Interestingly, Cluster 3 with low levels of dispersion has the highest percentage of home owners and lowest minority and poverty rates. These are the areas in the outer rim of Los Angeles which experience a decrease in accessibility into the PM peak. Cluster 3 may describe an older, white population that has moved to the exurbs far away from the urban core and then services followed them but did not reach the same high levels as along the coast.
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Fig.4 Cluster Socio-demographic characteristics
4. SUMMARY AND CONCLUSIONS In this paper we present one way to analyze complex spatial systems enhancing our understanding of the dynamics of polycentric cities and of residential, job, and school location choice processes. We first classify a large region into a multilevel nested spatial structure using information from regional models, US Census blocks, and networks. We also employ multiple sets of indicators including resident population and its characteristics, infrastructure provision, activity opportunities by type of opportunities, and housing supply, and synoptic measures of activity and travel behavior. We also introduce time of day as a fundamental element in classifying spatial units at different observation levels. The primary objective of this paper, to illustrate the creation of realistic space-sensitive and time-sensitive fine spatial level accessibility indicators that attempt to track availability of opportunities, is met using largely available data. These indicators support the development of the Southern California Association of Governments activity-based travel demand forecasting model that aims at a second-by-second and parcel-by- parcel modeling and simulation. They also provide the base information for mapping opportunities of access to fifteen different types of industries at different periods during a day reflecting clearly the polycentric nature of the urban landscape of this region. To accomplish this task classification of units within each level is performed in two distinct ways: a) cluster analysis using observed variables to derive groups and their taxonomy; and b) cluster analysis using a set of latent constructs to derive groups and their taxonomy. In our spatial analysis, we include the spatial dependency and homogeneity attributes as latent descriptors of the environment, which are then used to classify Southern California into block clusters. The method used and our findings improve center identification techniques of the type found in McMillen (2001) and Redfearn and Giuliano (2008).
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The methods here reduced a complex spatial environment into groups that share similar attributes but also share spatial patterns and provided new insights. What is uncertain is the appropriate scale of the spatial analysis, as the scale of our spatial units and the scale of neighborhood definitions. In our analysis, we use the Census block which varies in size over Southern California. To compensate for resident population size, urban blocks are quite small while parks and rural areas are much larger. Smaller blocks often have more neighbors within a given distance. Likewise, the shape of rural blocks is rarely regular resulting in more contiguous neighbors. The size and shape affect the value of the local mean derived from ‘neighboring’ blocks of neighbors in the spatial clustering analysis. This is a classic geographic concern known as the Modifiable Unit Problem (MAUP) in which spatial analysis is inherently biased by the data. The MAUP effect is most clearly seen during the nighttime when most blocks report no open businesses. The nighttime clusters are unusual in their size, spatial distribution, and industry characteristics. Interpretation is aided with more descriptive statistics on block-specific attributes like socio-demographics. We need to expand the research reported here and test the use of land parcels as spatial units to reduce the bias from MAUP. However, when applied as a way to describe the environment and identify subcenters of activity during multiple time points, we find spatial structures related to the hierarchy of transportation networks and industry agglomeration. The next steps in continued research are to enhance the inventory of land use, expand travel modes to transit, account for public lands, and add other indicators that describe the built environment. We also used the spatial indicators in a multi-equation study addressing the relationship between travel behavior and land use patterns using a Structural Equations Modeling framework that is an ongoing study to compare location choices and travel behavior choices among residents of different regions such as the Lisbon metropolitan area in Portugal, The Montreal region in Canada and the Los Angeles region in Southern California (de Abreu, Goulias, and Dalal, 2011). While the context of this study is in Southern California, we believe the method can be extended outside the United States. Similar to Southern California, the geographic region of the European Union contains many major and minor cities, creating a polycentric and complex built environment. Examples include the RhineRuhr, Randstad, Central Belgium, as well as the regions surrounding Paris, Zurich, and London (Taylor, Evans, and Pain, 2006). In fact, this analysis parallels European studies such as POLYNET (http://www.polynet.org.uk) and could support the data analysis in the ESPON 2013 Programme. Aided by improved transportation networks and relaxed border controls, increased connectivity throughout the region results in a continuous but hierarchical landscape in which opportunity accessibility is likely found at multiple spatial scales. Using the spatial clustering method described in this study, insights into the local, regional, and continental organization of the environment can inform policy decisions regarding the continued integration and collaboration of multiple international entities.
Acknowledgments Funding for this research was provided by The Southern California Association of Governments, The University of California Transportation Center (funded by the US Department of Transportation and the California Department of Transportation) , and the University of California Office of the President (Multicampus Research Program Initiative on Sustainable Transportation and the US Lab Fees Program). This paper does not constitute a policy or regulation of any Local, State, or Federal agency.
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REFERENCES Anas, A., Arnott, R. and Small, K. 1998. Urban spatial structure. Journal of Economic Literature: 36: 1426-1464. Anselin, L. 1995. Local indicators of spatial association-LISA. Geographical Analysis: 27 (2): 93-115. Bhat, C. R., Guo, J.Y. 2004. A Mixed Spatially Correlated Logit Model: Formulation and Application to Residential Choice Modeling. Transportation Research Part B: 38 (2): 147- 168. Buliung, R. N., Kanaroglou, P. S. 2007. Activity–Travel Behaviour Research: Conceptual Issues, State of the Art, and Emerging Perspectives on Behavioural Analysis and Simulation Modelling. Transport Reviews: 27(2): 151-187. Chen,Y., Ravulaparthy, S., Deutsch, K., Dalal, P., Yoon, S.Y., Lei, T., Goulias, K.G., Pendyala, R.M., Bhat, C.R. and Hu, H-H. 2011. Development of Opportunity-based Accessibility Indicators. Transportation Research Record: Journal of the Transportation Research Board (in press). Dalal,P., Goulias, K.G. 2011. Geovisualization of Opportunity Accessibility in Southern California: an exploration of spatial distribution patterns using geographic information systems for equity analysis, GEOTRANS Technical paper, Department of Geography, University of California-Santa Barbara. Accepted for presentation at the 90th Annual Transportation Research Board Meeting, Washington D.C., January 23-27. de Abreu e Silva, J., Goulias, K.G. and Dalal, P. 2011. A structural Equations Model of Land Use Patterns, Location Choice, and Travel Behavior in Southern California. Paper 12-3422 to be presented at the 91st Annual Meeting of the Transportation Research Board, Washington, D.C., January 22-26. Doling, J. 1975. The Family Life Cycle and Housing Choice. Urban Studies: 13: 55-58. Eliasson, J. 2010. The Influence of Accessibility on Residential Location. In Residential Location Choice: Models and Applications, eds. F. Pagliara, J. Preston, and J. Simmonds, 137-164. Berlin: Springer. Ewing, R., Cervero, R. 2010. Travel Behavior and Built Environment. Journal of American Planning and Association: 76 (3): 265-294. Getis, A., Ord, J. 1992. The analysis of spatial autocorrelation by use of distance statistics. Geographical Analysis: 24 (3): 189-206. Giuliano, G., Small, K. A. 1991. Subcenters in the Los Angeles Region, Regional Science and Urban Economics: 21(2): 163-182. Guo, J.Y., Bhat, C.R. 2004. Modifiable Areal Units: Problem or Perception in Modeling of Residential Location Choice? Transportation Research Record: Journal of the Transportation Research Board: 1898: 138-147. Guo, J.Y., Bhat,. C.R. 2007. Operationalizing the Concept of Neighborhood: Application to Residential Location Choice Analysis. Journal of Transport Geography: 15 (1): 31-45.
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Hughes, H. L. 1993. Metropolitan Structure and the Suburban Heirarchy. American Sociological Review: 58 (3): 417-433. Jacquez, G. M. 2008. Spatial cluster analysis. The Handbook of Geographic Information Science, eds. S. Fotheringham and J. Wilson, 395-416. Oxford: Blackwell Publishing. Litman, T. 2002. Evaluating transportation equity. World Transport Policy & Practice: 8 (2): 50- 65. McMillen, D. P. 2001. Nonparametric Employment Subcenter Identication. Journal of Urban Economics: 50 (3): 448-473. Miller, H. 1999. Potential contributions of spatial analysis to geographic information systems for transportation (GIS-T). Geographical Analysis: 31 (4): 373-399. Mohammadian A., Haider, M. and Kanaroglou, P. S. 2005. Incorporating Spatial Dependencies in Random Parameter Discrete Choice Models. Paper submitted for presentation at the 84th Annual Transportation Research Board Meeting, January 23-27, Washington D.C. Páez, A., Scott, D. 2004. Spatial statistics for urban analysis: A review of techniques with examples. GeoJournal: 61 (1): 53-67. Pagliara, F., Timmermans, H.J.P. 2009. Choice set generation in spatial contexts: a review. Transportation Letters: 1 (3): 181-196. Redfearn C., Giuliano, G.. 2008. Network Accessibility and the Evolution of Urban Employment. METRANS Project 06-16, Draft Report, University of Southern California, Los Angeles, CA. Sener I., Pendyala, R. and Bhat, C.R. 2011. Accommodating Spatial Correlation Across Choice Alternatives in Discrete Choice Models: An Application to Modeling Residential Location Choice Behavior. Journal of Transport Geography: 19: 294-303. Sivakumar, A., Bhat, C.R. 2007. A Comprehensive, Unified, Framework for Analyzing Spatial Location Choice. Transportation Research Record: Journal of the Transportation Research Board: 2003: 103-111. Stanilov K., Batty, M. 2010. Exploring the Historical Determinants of Urban Growth through Cellular Automata. UCL – CASA paper. http://www.casa.ucl.ac.uk/working_papers/paper157.pdf Taylor, P. J., Evans, D.M. and Pain. K. 2006. The Organisation of Europolis: Corporate Structures and Networks, The Polycentric Metropolis, 53-64. London: Earthscan. Thill, J.C. 1992. Choice set formation for destination choice modelling, Progress in Human Geography: 16 (3): 361-382. Tobler, W. 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography: 46: 234-240. Van Gent, W. P. C. 2010. Housing Context and Social Transformation Strategies in Neighborhood Regeneration in Western European Cities. International Journal of Housing Policy: 10 (1): 63–87. Van Kempen, R., Ozuekren, A. 1998. Ethnic Segregation in Cities: New Forms and Explanations in a Dynamic World. Urban Studies: 35 (10): 1631–1656.
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Vermunt, J.K., Magidson, J. 2002. Latent class cluster analysis. In Applied Latent Class Analysis, eds. Hagenaars, J.A., McCutcheon, A.L. , 89-106. Cambridge: Cambridge University Press. Vermunt, J.K., Magdison, J. 2005. Technical Guide for Latent GOLD 4.0: Basic and Advanced. Belmont Massachusetts: Statistical Innovations Inc. Waddell, P. 2002. UrbanSim: Modeling Urban Development for Land Use, Transportation and Environmental Planning. Journal of the American Planning Association: 68 (3): 297-314.
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European Journal of Geography 2 2: 21‐34, 2011. © Association of European Geographers
"GLOKAL CHANGE": GEOGRAPHY MEETS REMOTE SENSING IN THE CONTEXT OF THE EDUCATION FOR SUSTAINABLE DEVELOPMENT Markus JAHN University of Education Heidelberg, Department of Geography – rgeo, Czernyring 22/11-12, 69115 Heidelberg, Germany, http://www.ph-heidelberg.de/en/home.html, [email protected]
Michelle HASPEL University of Education Heidelberg, Department of Geography – rgeo, Czernyring 22/11-12, 69115 Heidelberg, Germany, http://www.ph-heidelberg.de/en/home.html, [email protected]
Alexander SIEGMUND University of Education Heidelberg, Department of Geography – rgeo, Czernyring 22/11-12, 69115 Heidelberg, Germany. http://www.ph-heidelberg.de/en/home.html, [email protected]
Abstract The web-based learning platform "GLOKAL Change" (www.glokalchange.de), which is currently developed at the University of Education Heidelberg, Germany, highlights four topics of environmental changes in terms of sustainable development. In interactive learning modules, adolescents aged 10 to 16 years learn to evaluate economic, ecological and social impacts of recent environmental changes occurring in different geographic areas worldwide and in Germany. Information is provided by remote sensing data and other media. Users compare, visually analyze and interpret satellite imagery to obtain spatial information on the development of the three dimensions of sustainability. Subsequent to the example areas in the modules, learners examine their individual local surroundings at home on a satellite image mosaic of Germany as well as by performing geo-scientific fieldwork on site. "GLOKAL Change" supports an original encounter by providing worksheets and methodology papers on various fieldwork methods, and by the application of a micro-drone for taking their own aerial imagery.
Keywords: Web-based Learning Platform, Remote Sensing Data, Geography, Education for Sustainable Development, Geoscientific Fieldwork
1. INTRODUCTION Human society needs resources for its economic prosperity and social well-being. In the last century, the combination of global population rise and continuous growth of the world economy caused an ever increasing consumption of resources. At the same time, spatial needs for different land-use types such as living space, industry, services, infrastructure and
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agriculture diminished the area of natural ecosystems on earth. Both processes, provision of resources and reshaping of natural landscapes, have led to profound interventions into the earth's natural state all over the world. Many of these interactions between human society and environment are very complex in structure as they have simultaneous impacts on economic prosperity, ecological equilibrium and social well-being in a geographic region. In 1987, the Report of the World Commission on Environment and Development Our Common Future (available at http://www.un-documents.net/wced-ocf.htm), known as the Brundtland Report, highlighted the environmental and developmental concerns of present human-environment-interactions, whose characteristics are not sustainable regarding the future. As a reaction to the report the United Nations Conference on Environment and Development (UNCED) launched Agenda 21 in 1992. This comprehensive political action program aims at implementing a more sustainable development in the 21st century. To achieve this objective increasing economic effectiveness needs to be combined with more ecologic compatibility and growing social equity as prerequisite to give future generations the same chances to meet their material needs (UN 1993, UNESCO 2011). One of the most important keys to more sustainable behavior in our society may be a „…reorientation of the education towards more sustainable development…” (Gross & Friese 2000, Bahr 2007). The importance of Education for Sustainable Development (ESD) has been emphasized in chapter 36 of the Agenda 21 (UN 1993). Education for Sustainable Development enables people to „…apply their knowledge on sustainable development and to be aware of the problems of non-sustainable development…”, i.e. to identify the mutual dependency of the three dimensions of sustainability as well as to make decisions and act sustainable oneself based on this awareness (cf. Programm Transfer-21 2007, de Haan & Gerhold 2008). In the Lucerne Declaration on Geographic Education for Sustainable Development drafted by Haubrich et al. (2007) the authors stress the necessity „…for the paradigm of sustainable development to be integrated into the teaching of geography at all levels and in all regions of the world.”. For Gross & Friese (2000), Hemmer (2006a, 2006b) and Bahr (2007) the subject geography is of importance in the context of ESD due to the analyses of human-environment-interactions and their implications on a geographic area conducted in the subject. Hence, the subject geography is bound to teach for sustainability, i.e. to comprise the concept of ESD in its subject-specific education (DGfG 2010), as almost all topics of the UN Decade of Education for Sustainable Development (UNDESD) 2005- 2014 possess a geographic dimension (cf. Haubrich et al. 2007). In the concept of ESD, education represents a notion of individual competences (BLK 1998, de Haan & Gerhold 2008). Evaluation and media competences for example are both necessary for individuals to comprehend and practice sustainability comprehensively (de Haan & Gerhold 2008, Programm Transfer-21 2007). In Germany, the national educational standards for the school subject geography demand the promotion of both competences: students should be able to obtain information from different media, e.g. satellite imagery, and to evaluate human interventions into the environment concerning their economic, ecologic and social/political compatibility (DGfG 2007). The web-based learning platform (LP) "GLOKAL Change" has been developed to focus on fostering both competences: learners are requested to evaluate environmental changes in terms of sustainable development by analyzing given information such as remote sensing (RS) data.
2. THE LEARNING PLATFORM "GLOKAL CHANGE" Fostering students' abilities to comprehend and evaluate the impact of environmental changes on sustainability is the overall aim of the web-based LP "GLOKAL Change". Its development has been conducted in the Department of Geography at the University of Education Heidelberg, Germany, as an integral part of the research project "GLOKAL Change –
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Evaluating global environmental changes locally". The LP is still open for use free of charge at www.glokalchange.de and addresses primarily German students from grades 5 to 10 as well as adolescents from extracurricular environmental education aged 10 to 16 years (both described as adolescents later on). Due to its contribution to the ESD from the viewpoint of geography, the entire project "GLOKAL Change" has been marked out as an official project of the UNDESD by the German UNESCO Commission in 2010. The adolescents learn to evaluate environmental changes in terms of sustainability by dealing with each of the three modules of the educational concept of "GLOKAL Change" shown in Figure 1. In interactive learning modules (see section 3) they get to know the impacts of environmental change occurring in different geographic areas on the global (worldwide) and local (in Germany) scale using satellite imagery (see chapter 4). Afterwards, they use a map server containing satellite imagery of Germany to virtually discover their individual home area (see chapter 5). Subsequently, they perform geo-scientific fieldwork on site to explore their local surroundings more comprehensively (see chapter 6). In this context, a micro-drone may be applied assisting the adolescents in the acquisition of further information on their geographic area of interest through taking high resolution aerial imagery (see chapter 6.1).
Fig.1 Educational concept of the learning platform "GLOKAL Change" to foster adolescents' ability to evaluate environmental changes in terms of sustainability.
3. LEARNING CONTENT AND STRUCTURE OF THE LP "GLOKAL Change"
As environmental changes studied in many geographic topics are often complex in structure due to extensive economic, ecologic and social interactions among each other, "GLOKAL Change" concentrates on certain geographic topics of human-environment-relationships that are also important to sustainable development. Each topic is presented as an interactive learning module, which has been designed for adolescents in terms of established teaching methods being used in the didactics of geography. Altogether, the LP "GLOKAL Change" contains the following four learning modules:
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a) The module "Land use" deals with spatial conflicts between economic, ecological and social needs of using space, which have primarily been caused by urban processes, such as the growth of the city of Las Vegas, or suburbanization tendencies in the city of Berlin. b) The impacts of the cultivation of energy crops and their subsequent transformation to biofuels are discussed in the module "Biofuels from Agriculture", for example the deforestation of the Amazonian tropical rainforest for growing sugarcane to produce ethanol fuel. c) In "Ecosystem Forest and its Management" the consequences of non-sustainable forest management and forest replacement on ecosystem services have been picked out as a central theme, e.g. the impacts of the deforestation at the airport of Frankfurt am Main, Germany, to build a new runway, or the implications of deforestation in the Congolese rainforest. d) The effects of mining resources in vast open pits on the economy, environment and society are given attention to in the module "Mining Resources in Open-Cast Mining", for example in the lignite mining area of the Rhineland, Western Germany, or in the Athabasca Oil Sands Area in Alberta, Western Canada.
Each learning module can be accessed from the first page of the LP (Fig. 2), they present four examples of non-sustainable environmental change in different geographic areas. In each case, two examples are located on the global scale (worldwide) and at the local scale (in Germany; Fig. 3). For every example presented in the modules, the adolescents get to know the recent development to the economic, ecological and social dimension on site as a result of the environmental changes occurring there. They learn to make statements on the dimensions' impact on sustainability. Finally, they are asked to evaluate the whole situation concerning its effects on sustainable development. Users can switch between the learning modules and geographic examples at any time. Each module begins with a short web trailer, which presents the module's topic cinematographically and introduces a set of problems related to the environmental changes occurring within the topic. After the web trailer, general information on the topic is given before users can deal with one of the geographic examples.
Fig.2 First page of the web-based learning platform "GLOKAL Change". Users can enter the four learning modules by clicking on the four images in the middle of the page as well as a map server by clicking on the earth symbol or the small satellite.
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Fig. 3 Technical structure of the learning platform "GLOKAL Change".
For each example worksheets are available on the LP free of charge. Adolescents can use them as a basis for gathering information on the economic, ecological and social circumstances in the area they deal with. At the same time the worksheets are an opportunity for teaching staff to control the learning progress.
4. UNDERSTANDING SPATIAL IMPACTS BY USING RS DATA IN LEARNING MODULES Young people can learn about recent economic, ecological and social changes that have occurred in the geographic examples of "GLOKAL Change" using a variety of media such as texts, charts, graphics, images, maps and RS data. Satellite imagery is used in the LP for two reasons: first of all, it visualizes spatial relations and changes in the geographic area of interest, which may help learners to understand the impacts on the economy, environment and society. Secondly, the use of satellite imagery induces high motivation and interest by the learners as an international comparative study conducted by Siegmund (2011) revealed. In this study, younger students especially were highly motivated and interested although their specialist knowledge about satellite imagery was generally lower when compared with older participants (Siegmund 2011). In general, factors such as image coloring, image complexity, image ambiguity and general difficulties in image understanding (Gerber & Reuschenbach 2005) often prevent inexperienced users such as younger adolescents from reading and interpreting satellite imagery successfully. For that reason, Beckel & Winter (1989) point to the importance of a gradual image analysis following instruction and/or the provision of additional information, e.g. describing image content. In the LP "GLOKAL Change", satellite imagery is embedded into a framework of additional information, which is thought to help
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users understand and and more deeply interpret the imagery. Moreover, the worksheets described earlier (cf. section 3) contain different exercises in terms of reading and interpreting the imagery correctly. Thus, users are guided step by step towards a comprehensive image interpretation in "GLOKAL Change" in order to exhaust the full potential of using RS data in learning situations. Since the start of the Landsat program in 1972, satellite imagery of the earth's surface is available for more than 30 years, which allows for a time series analysis to get a deep insight into the spatio-temporal development of a geographic area. While Landsat imagery has a low spatial resolution of 30 m × 30 m per pixel, particular RS data such as IKONOS or QuickBird as well as aerial imagery (all less than 1 m × 1 m per pixel) provide detailed information on a geographic area, and permit spatial analysis at a small scale. As a satellite image displays an area covering at least 100 km² or more, depending on the satellite sensor that has been chosen, „…large spatial structures and environmental changes…” (Kollar et al. 2008: 70) can be identified when using these data. Furthermore, satellite imagery displays the earth's structures in its natural appearance in contrast to maps, since no artificial entries or modifications in the imagery have been carried out (Gerber & Reuschenbach 2005, Siegmund & Menz 2005). This is especially true for real color imagery displaying the earth in its natural colors (RGB). False color imagery provides image information on specific subjects of interest such as geologic/geomorphologic features or soil and vegetation properties, and allows for the differentiation of urban and non-urban areas. In general, satellite imagery can help users to make statements on single image objects, connections between these objects as well as on image structures. Thus, reading and interpreting an image correctly can provide a lot of information on the geographic area that has been mapped. The German Educational Standards in Geography for the Intermediate School Certificate point to satellite and aerial imagery as sources for geographic information, which students should be able to acquire (DGfG 2010). Brucker (2006, 178) and Doering & Veletsianos (2007) refer to RS data as suitable tools for the analysis and evaluation of alterations in economic, ecological and social dimensions. This suggests the usefulness of RS data as valuable media in terms of communicating learning content on sustainable development. According to the explanations made here, the interpretation of RS data is an important method in "GLOKAL Change" for gathering spatial information on the kind and extent of changes in the field of the three dimensions of sustainability. The imagery in "GLOKAL Change" primarily consists of Landsat TM and ETM+ data. Besides the analysis of single images in real and false color, users can detect spatio-temporal developments or changes within the mapped area by comparing imagery of different temporal origin (Fig. 4). In the geographic example "Mining Lignite in the Rhineland, Western Germany", which belongs to the module "Mining Resources in Open-Cast Mining", spatio-temporal changes in this area can be observed in all three dimensions using satellite imagery (Figure 5): for example, the shifting of open-cast mining (economy), the loss of land due to excavation followed by reclamation processes (environment) as well as resettlement activities (social dimension). After the use of the imagery shown in Figure 5, a group of 22 sixth graders (about 12 years old) was asked "Did the satellite imagery help you to understand the topic?" Seventeen answered with "Yes.", five said "It was ok." and none of them answered "No.". In the modules "Biofuels from Agriculture" and "Ecosystem Forest and its Management", the loss of forest areas due to deforestation and transformation into other land-use types, e.g. agricultural area, infrastructure or residential area, can be detected using near-infrared (NIR) or the Normalized Difference Vegetation Index (NDVI). Both, NIR and NDVI generally allow visual conclusions to be reached about the vegetation's distribution, composition, productivity and vitality (cf. Campbell 2002, Lillesand et al. 2004). Spatio-temporal changes in urban
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areas (module "Land Use") are visualized using imagery with different band combinations, especially involving NIR and mid-infrared (cf. Campbell 2002, Lillesand et al. 2004).
Fig.4 The comparison of satellite imagery of different temporal origin allows users to detect developments or changes within the mapped area in space and time like in the geographic example "City Development of Las Vegas" in the module "Land Use".
Altogether, RS data provide valuable spatial information about a geographic area including local economy, environment and society. In "GLOKAL Change", satellite imagery of different temporal origin and different band combinations is used for visualization purposes. Image interpretation and comparison, in combination with additional information on the topic (texts etc.), are thought to enable the young users to make a well-founded evaluation about the impacts on sustainable development.
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Fig.5 When comparing satellite imagery of the lignite mining area in Western Germany from different time slots, spatial changes in the economic, ecologic and social dimension are observable owing to the mining activity can be observed.
5. USING RS DATA ON A MAP SERVER TO EXPLORE THE INDIVIDUAL HOME AREA
In addition to the satellite imagery provided in the learning modules, "GLOKAL Change" comprises a map server containing pre-processed Landsat TM and ETM+ imagery of the entire territory of Germany (Fig. 6). Users can access the map server either from the first page of the LP (cf. Fig. 2) or from the learning modules. Imagery is available for three time slots, 1985, 2000 and 2007. For each of these slots, one real color and two false color images of Germany, e.g. imagery showing the NDVI, have been processed. Using an overlay function, two images can be viewed at the same time by setting one of them to transparency mode. In this format, the transparent image is on top of the other one, enabling users to compare the images and allowing them to recognize similarities and differences, i.e. changes in the landcape.
Fig.6 The map server of "GLOKAL Change" contains real and false color satellite imagery of Germany for three time slots.
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As in Google Earth, users can zoom in/out or navigate on the map server surface using a pan function. Beyond that, users are able to search for certain settlements by name, zip code or geographic coordinates as well as measure distances and areas. Image details that 6. PERFORMING GEOSCIENTIFIC FIELDWORK TO EXPLORE THE INDIVIDUAL HOME AREA When users deal with the learning modules of "GLOKAL Change", they get to know some non-sustainable effects of environmental changes on the economy, environment and society in various geographic areas worldwide and in Germany. In the course of the modules, they also learn to analyze information and evaluate it in terms of their impacts on sustainability (cf. chapter 3). They have to pay attention to all three dimensions owing to the complex interactions between them as a prerequisite to make a well-founded, holistic evaluation. When the adolescents are in the field in the context of an original encounter they require all these abilities to investigate the economic, environmental and social issues in their local surroundings. Coming from the classroom into the field, they have to transfer the knowledge they acquired in the virtual world of the learning modules and using the map server to real situations outside. According to Kirch (1999), students will not really gain geographic knowledge and build comprehension for a geographic area without exposure to fieldwork. Obtaining primary, i.e. non-filtered, information in the field during an original encounter is an important part of the learning process as information from mass media and information systems is filtered by the authors (Haubrich 1997). Furthermore, learners gain individual experience in the field by actively observing or performing fieldwork (cf. Haubrich 1997). Bland et al. (1996, 165) once summarized the overall importance of an original encounter (fieldwork) for learning in geography as follows: „Geography without fieldwork is like science without experiments.” The LP "GLOKAL Change" supports adolescents in gaining individual experience and primary information on site by making worksheets available for module-specific, action- orientated geo-scientific fieldwork, e.g. interview guidelines or mapping instructions. For the accurate execution of the fieldwork, "GLOKAL Change" also provides papers on background knowledge concerning different geo-scientific fieldwork methods. Using these worksheets and methodology papers the learners can examine the economic, environmental and social situations to some extent, and comment upon their implications, for example regarding the impact of a small gravel pit nearby, or the construction of a road through a forested area. Once the studetns have studied the international examples and those from Germany in the modules, they can also explore their home area in terms of sustainability. In our view, the personal reference to the home area where the original encounter takes place will be a motivating factor for them. However, they may need assistance on how to obtain meaningful on-site information on the three dimensions. This support is provided by the worksheets and methodology papers. Sometimes, specific information may be needed, which can only be 29 Jahn M.- Haspel M.- Siegmund A./ European Journal of Geography 2 2 21 - 34 provided using up-to-date aerial imagery. In this case, a micro-drone (see section 6.1) could be applied in the context of "GLOKAL Change". 6.1. Using a micro-drone for the generation of specific aerial information When the learners are in the field they will presumably be able to gather answers to most questions in their geo-scientific fieldwork. However, in some circumstances specific questions may only be answered by using special equipment. During field examinations in the context of "GLOKAL Change" a low-flying micro-drone can be used to gather real-time high resolution aerial imagery (Fig. 7). As part of the project, the micro-drone can be operated by teachers who take a training course to support adolescents in need of specific information from aerial imagery. The micro-drone's multi-spectral camera can map small areas such as razed forests or damage in cornfields (Thamm & Judex 2005). The micro-drone can be applied to generate information in terms of all four topics presented in "GLOKAL Change": open-cast mining of different size, entire forests or small forested areas, agricultural land where energy crops or other crops are grown, and several other uninhabited land-use types, e.g. building sites. Fig.7 During the fieldwork in the context of "GLOKAL Change" a low-flying micro-drone, which is equipped with a multi-spectral camera, can be applied to take real-time high resolution aerial imagery (image on the right). Beyond the practical benefit of taking aerial imagery for generating information, the micro-drone has an educational function. Before and during its application the adolescents get to know the basics of remote sensing as well as the principles and difficulties of producing RS data. For example, when they learn how an aerial image is taken they may, at the same time, start to understand the process of generating satellite imagery. Thus, the micro-drone is also thought to be an educational learning object. As the youngsters are involved in flight preparation, data acquisition, conditioning and evaluation, they may likely be more motivated and interested in performing fieldwork compared to regular field examinations. 7. CONCLUSIONS AND OUTLOOK The LP "GLOKAL Change" is a multi-dimensional learning environment. By using it in school as well as during extra-curricular environmental education, adolescents can firstly obtain information on economic, ecological and social issues through analyzing and interpreting different types of media including RS data. Secondly, they can get to know examples of non-sustainable development at global and local scales before subsequently examining their own individual local surroundings, a multi-perspective approach. Thirdly, the combination of computer-assisted learning (learning modules and map server) and original encounter (fieldwork) is thought to add to the entire learning process as a multi-sensory approach covering various human sensory channels. Moreover, RS data, fieldwork and the application of a micro-drone are thought to increase adolescents' motivation and their interest 30 Jahn M.- Haspel M.- Siegmund A./ European Journal of Geography 2 2 21 - 34 to learn effectively in the context of "GLOKAL Change". Following the first application of the geographic example "Mining Lignite in the Rhineland, Western Germany" ("Mining Resources in Open-Cast Mining") in school, 14 from a total of 22 sixth graders answered with "Yes." while eight said "Maybe again." when they were asked: "Would you like to learn again with GLOKAL Change, maybe in terms of another example or topic?". The overall objective of the LP, which can be used in school as well as in extra- curricular environmental education free of charge, is to foster German adolescents' evaluation and media competence. In the learning modules, adolescents' overall task is to evaluate the impact of various environmental changes on sustainable development. In this context, the comparison and visual analysis of RS data is thought to be an important method in "GLOKAL Change" to gain spatial information on economic, ecological and social changes, improving the adolescents' competence to read and interpret satellite imagery simultaneously. Altogether, dealing with a LP like this may bring adolescents one step closer to the aims of ESD, namely (i) to apply knowledge on sustainable development, (ii) be aware of the problems of non-sustainable development, and (iii) act sustainable oneself (cf. section 1), as was intended by the developers. Thinking of the future, interactive learning environments such as "GLOKAL Change" may become increasingly frequent in the study of geographic/geo-scientific content, including content on sustainable development. Haubrich et al. (2007: 248) stated that information and communication technologies (ICT) „… can contribute meaningfully to the aims of education for sustainable development in Geography teaching and learning described in this Declaration [on Geographical Education for sustainable Development] by helping students to acquire knowledge and develop competencies necessary for lifelong learning and active citizenship.” Besides "GLOKAL Change", various RS-based online LPs have been developed or are still in development in the Department of Geography at the University of Education Heidelberg, Germany (Ditter et al., accepted), e.g. "BLiF – Blickpunkt Fernerkundung" (www.blif.de). These LPs follow established teaching methods being used in the didactics of geography, general pedagogy and computer sciences. They have been or are being designed to foster the acquisition of knowledge on and individual competences in geography/RS effectively through modern-day computer-assisted learning. ICT are promoted by the European Union as an important key to improve education and training (cf. European Commission 2010a). The interactive LP "GLOKAL Change" belongs to the ICT. A review of several studies of ICT impact on schools has shown „…that ICT impacts on competency development – specifically team work, independent learning and higher order thinking skills…” (ICT Impact Report 2006). "GLOKAL Change" aims at fostering several of the adolescents' higher order thinking skills (see section 1) and basically allows users to deal with its learning content either by oneself or in team work. Thus, the LP "GLOKAL Change" follows guidelines that have been made by the European Commission to „…develop innovative education and training practices…” (cf. European Commission 2010b). Beyond that, it deals with several sustainability-related topics, which have a European dimension, for example energy supply, use of biofuels and sustainable management of forests. Acknowledgements The authors wish to acknowledge the Deutsche Bundesstiftung Umwelt (DBU) for supporting the project "GLOKAL Change – Evaluating global environmental changes locally". 31 Jahn M.- Haspel M.- Siegmund A./ European Journal of Geography 2 2 21 - 34 REFERENCES: Bahr, M. 2007. Bildung für eine nachhaltige Entwicklung – ein Handlungsfeld (auch) für den Geographieunterricht?!. Praxis Geographie: 9/2007: 10-12. Beckel, L. & Winter, R. (eds.) 1989. Satellitenbilder im Unterricht. Einführung und Interpretation. Bonn: Orbit-Verlag Reinhard Maetzel. Bland, K., Chambers, B., Donert, K. & Thomas, T. 1996. Fieldwork. In Geography Teachers' Handbook, eds. P. Bailey & P. Fox, 165-175. Sheffield: The Geographic Association. Brucker, A. 2006. Luft- und Satellitenbilder. In Geographie unterrichten lernen. Die neue Didaktik der Geographie konkret, ed. H. Haubrich. 178-179. München: Oldenbourg Verlag. Bund-Länder-Kommission (BLK) 1998. 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Accessed Dec. 2011. 33 European Journal of Geography 2 2: 35-47, 2011. © Association of European Geographers CHILDREN’S MAP READING ABILITIES IN RELATION TO DISTANCE PERCEPTION, TRAVEL TIME AND LANDSCAPE Ekaterini P. APOSTOLOPOULOU University of the Aegean, Department of Geography, University Hill, Mytilene, 81100 [email protected] Aikaterini KLONARI University of the Aegean, Department of Geography, University Hill, Mytilene, 81100 [email protected] Abstract Children’s cognition of distance is influenced by functional distance and estimations of travel time which increases with the presence of natural or artificial barriers. In this paper we investigate pupil’s associations of landscape and travel time in a map reading task of equal distance target cities. More than 330 11 year old pupils attending the fifth grade from 18 public primary schools located in city and rural areas participated in a research with the use of a 3D relief map of central Greece for decision making activities relating travel time to geomorphologic barriers. We hypothesized that pupils from city areas would design straight line routes regardless of the physical landscape influenced by the linear and rectangular outlines of city environments in opposition to pupils living in rural areas that would design curved routes according to the landscape. The results indicate that children relate landforms with travel time by identifying physical obstacles on the map. Pupils that selected the city of destination correctly justified their answers by identifying geomorphologic features on the map. However, the performance of urban pupils outpaces rural pupils’ performance postulating that the quality and quantity of educational resources in city areas may influence positively spatial cognition. Keywords: route selection, route depiction, morphological barriers, 3D relief map 1. INTRODUCTION Wayfinding is an everyday task, essential to survival, that has been accomplished by people since they evolved and by other organisms before that, using their eyes and bodies and minds (Tvesrky, 2000, p. 24) It is argued (Kosslyn et al., 1974) that children’s spatial representations rely on functional distance and their estimations of traveled distance increases with the presence of natural or European Journal of Geography - ISSN 1792-1341 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 artificial barriers. Functional distance is described as the length of traveled route while moving between locations (Cohen et al, 1978). According to the route segmentation hypothesis (Allen, 1981) traveled routes segmented by features are considered longer than unsegmented routes. Barriers influence the cognitive spatial organization by chunking the space into local subspaces (Newcombe & Liben, 1982) leading to distorted estimations. Both preschoolers and adults were found to overestimate the distance between locations separated by opaque barriers, but children focused on the required effort to move from one location to another, while adults were influenced by visual distance information (Kosslyn et al., 1974). Cohen and his colleagues’ research (1978) on distance estimations of 9-10 year old children and adults demonstrated the consistent effect of hills and sloping pathways as a factor of added effort, which resulted in overestimation of distances. Circuit routes between locations revealed similar overestimations of actual inter-object distances contrary to direct tracks by kindergartners (Anooshian & Wilson, 1977). Increased experience, exposure and interaction with the physical environment improve environmental awareness (Golledge & Stimson, 1997; Thorndyke & Hayes-Roth, 1982). Visits to rivers by upper primary school children aged 9-11 from four different schools living in outer urban London areas had a positive effect on their perceptions of rivers (Tapsell et al. 2001). Mackintosh (2005) underlines the importance of providing children with experience of rivers and fieldwork, as they reinforce landscape visualization and the development of three- dimensional constructions of rivers that supports classroom activities on associations and terminology. Children’s perception of the third dimension on maps (altitude) is influenced by their natural surroundings (Labrinos, 2009, Trend et al. 2000). Research based on findings from more than 2000 12 year old primary pupils in more than 100 Central Macedonian schools, Greece on the representation of the third dimension on maps found that children living in mountainous and semi-mountainous regions had better understanding of relief in comparison with children living in coastal or plain areas (Lambrinos et al., 2000). Klonari et al. (2011) studied the perceptions and interpretations of terraces in terms of various uses and values between more than 360 primary and secondary students and more than 90 geography teachers and found that responders from rural areas had a better understanding of terraces than those from urban areas. On the contrary, restrictions on children’s spatial mobility as a result of adult concerns over their use of public space and the extended privatization of rural space question the previous line of thought (Smith & Barker, 2001). Furthermore, the increased engagement with computer games reduces the chances of outdoor activities (Subrahmanyam et al, 2000; Palmer, 2006). However Chen & Michael (2005) supported that electronic games provide possibilities for the transformation of the process of knowledge construction and Buckingham (2007) argues that computer games can provide powerful learning experiences when effective learning principles are employed. Uttal (2000) supports that understanding the symbolic nature and abstract representations of maps is less likely to be spontaneously developed than learned and children’s spatial conception limitations may rely on restricted understanding of the functions and uses of maps, calling for the nurturing of special visual literacy skills (Kemp, 2008) and spatial literacy (Gryl et al., 2010). Enriching environmental experiences with map uses contributes to spatial competence. Parental map use and map resources available in the home improves children’s map reading abilities and other spatial skills (Liben & Myers, 2007). “Meaningful verbal annotations” provided by parents during travel positively influences the quality of pupils’ representations of the landscape (Hart, 1981). 36 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 These studies provide evidence that morphologic barriers, environmental experience, engagement with electronic games and parental map uses influence spatial awareness and map reading abilities. Spatial thinking is a domain of great scientific interest within the disciplines of child psychology (Gersmehl & Gersmehl, 2007), geography, earth and environmental sciences (GEES) (King, 2006) and a key organizing principle for geography education (Bednarz et al. 2009). Gersmehl (2005) suggested a taxinomy of spatial-thinking concepts to geography instruction at all levels, while Jo & Bednarz (2009) proposed a taxonomy of spatial thinking as a tool to select spatial questions in schools (Jo et al., 2010). Research on concepts of space, tools of representation and the processes of reasoning indicate they dynamically influence geography curricula and didactical methologies. In this research the aim was to examine pupils’ distance perception and their ability to design a route traveled by car according to the physical landscape. Therefore we used 3D maps as a research tool in our methodology. The challenge was for them to identify elements of the landscape such as mountains and plains and relate these features to the design of a route. The second aim was to explore whether familiarity with mountainous environments influenced their perception of geomorphologic features on the map and the selection of a route that would be traveled by car in the shortest period of time. We analyzed children’s argumentation as well as their designs of selected routes according to the landscape. It was hypothesized that pupils from city areas would design straight line routes regardless of the physical landscape as they are influenced by the linear and rectangular outlines of city environments in comparison with rural pupils who would design more curved routes based on the “contours” of the natural landscape. 2. EXPERIMENTAL METHOD 2.1. Sample A total of 339 pupils aged 11 attending the fifth grade from 18 public primary schools in Greece participated in the research. 80,5% of the pupils lived in city and inner-city areas and 19,5% lived in rural areas, following the distribution of the Greek population (NSSG, 2008). Over 70% of the children lived in coastal and plain areas (altitude < 250m) and 23,9% in semi-mountainous areas (altitude > 250m) and 5,6% in mountainous areas (altitude > 500m). 2.2. Materials Pupils individually completed a questionnaire, which contained closed and open ended questions based on a 3D relief map of central Greece retrieved by the educational software “Traveling with maps in Greece and around the World” (Figure 1). The criteria for the selection of the map were the display of an area that contained three cities with equal road distance (110km) from the city-point of departure. It was also mentioned to the children that the quality of the road system was similar in all three routes. The Euclidian distance between (i) Amfissa and Lamia was 5cm, between (ii) Karpenisi and Lamia 7cm and between (iii) Livanates and Lamia 7,5cm. In the first option, two thirds of the route would be traveled through mountainous areas, in the second option one fifth of the route would be traveled through mountainous areas and in the third option the majority of the route was traveled through plain areas. 37 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 Fig.1. 3D relief map of Sterea Ellada. Source: Traveling with maps in Greece and in the World. (Source: Talent S.A.) 2.3. Procedure The research was conducted during the third trimester of studies in Greek public primary schools by pupils attending the fifth grade. Permission was issued by the Pedagogical Institute and the schools’ directors. The questionnaire was completed with the presence of the experimenter within a didactical hour (50 min) during the Geography class. Pupils were informed about the purpose of the study and were presented with the questionnaire. Finally it was mentioned that their performance would not influence their grades. After observing the 3D map of southern Sterea Ellada on their questionnaires, the task was to select which of the three cities could be reached in the shortest period of time by driving a car. Then they were asked to justify their selection and design on the map the route they would follow by car. 2.4. Data analysis City selections were scored as correct or false. A chi-square analysis was conducted to reveal statistical significance separately between the score and pupils’ sex, the categories of engagement with electronic games (frequent, seldom, rare-none) and pupils’ city or rural allocation. The data were categorical. The level of significance was p<.05 (Pathak, 2008). We developed three level descriptors (Martin, 2008) and allocated each map combined with pupils’ explanations to one of the three categories. Relief associations. Pupils in this category selected Livanates as the city of destination, designed the route according to the landscape using curved lines between hills and mountains and produced explanations demonstrating a clear understanding of the physical landscape. 38 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 Linear associations. In this category pupils designed straight-line routes regardless of the landscape. The majority chose Karpenisi as the city of destination and produced explanations that revealed misunderstanding of the symbology of the point symbol of cities. In their explanations they demonstrated partial understanding of the landscape represented on the map. Straight lines were used to link the city of departure with the city of destination. Naive theories. Pupils’ designed either straight line or curved routes on the map regardless of the landscape. Their explanations were focused on prior visits to the city of destination and acquaintance with the region, personal impressions and environmental affordances (Tapsell et al., 2001) without further justification (eg. I chose Amfissa because I think so) or irrelevant responses (eg. We reach Livanates easier by boat). 3. RESULTS 3.1. City selection Pupils’ selection of cities on the map was scored as correct for Livanates and incorrect for Karpenisi and Amfissa. 64,3% of pupils answered correctly, while 35,7% answered incorrectly or gave no answer. 71,8% of the boys and 57,4 % of the girls selected correctly the city of destination. A chi-square analysis of these frequencies point that their distribution was significantly different to that expected by chance, χ2 (1,339) = 0.006, p < .05. Significantly more boys made correct city selections. Frequent engagement with electronic games is not related to high scores in the city selection task. 56% of the pupils who gave correct answers were occupied with electronic games more then three times per week. 8,3% of pupils were occupied with electronic games once a month and 35,7% had scarce or no involvement at all, χ2 (2,339) = 0.231, p>.05, ns. Urban pupils presented better performance in the city selection task than rural population (Table 1). This proved to be highly significant, χ2 (1,339) = 0.001, p < .05. Table 1. Gender and route design Route design Straight line According to the landscape NA Total Gender Boy Count 42 95 26 163 % within sex 25,8% 58,3% 16,0% 100,0% Girl Count 63 85 28 176 % within sex 35,8% 48,3% 15,9% 100,0% Total Count 105 180 54 339 % within sex 31,0% 53,1% 15,9% 100,0% 39 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 3.2. Route design More than half the participants designed the route according to the landscape (Figure 2). This is consistent with previous researches on river depiction on maps, where less then 60% of pupils designed the river flow on a 3D map according to the landscape (Apostolopoulou & Klonari, 2011) and on children’s understanding of the physical landscape with maps, where more than 10% of pupils ignored the landform and drew routes in straight lines across mountains (Apostolopoulou et al., 2009). Fig.2. Route design 10% more boys more than girls designed on the map routes according to the landscape (Table 2), but the difference is not statistically important, χ2 (2,339) = 0.114, p >.05, not significant. Among the pupils that designed routes according to the landscape 50,6% stated frequent engagement with electronic games, 10% were seldom engaged and 39,4% had rare or no involvement. There was no significant difference, χ2 (4,339) = 0.673, p>.05, ns. Children living in city areas designed routes according to the landscape on their maps in significantly greater frequency than children living in rural areas. City pupils presented better performance in the route design task (54, 6% designs according to the landscape), than rural population (47% designs according to the landscape). This proved to be highly significant, χ2 (2,339) < 0.001, p <.05. Some pupils (14, 2%) selected the city of destination correctly but drew straight line routes. This implies that they may understand the relief as it is represented on the map, but they find it difficult to design the route according to the landscape. Teachers should therefore combine map reading and map drawing activities to bridge this cognitive gap. Table 2. Types of responses in justification of route design task Urban population Rural population A. There are more/less mountains/plains, 65,9% 45,5% the route is smooth, less natural obstacles B. The route is in straight line, it’s closer 18,3% 41,0% C. It’s easier to reach 4,8% 4,5% D. I have been there, I have traveled there 1,1% 0,0% E. I like it, I think so 5,9% 4,5% F. NA 4,0% 4,5% Total 100,0% 100,0% 40 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 3.3. Levels of understanding Children were asked to justify city selections in an open ended question. Their answers were categorized in relief associations, linear associations and naïve theories as analyzed on the section Experimental Method. Relief associations presented the highest frequency among the other levels of understanding (Figure 3). The majority of pupils mentioned geomorphologic features in their explanations that were identified on the map. However some children’s explanations were influenced by familiarity with the region, aesthetic or leisure criteria. “I chose Amfissa because it is closer to my village” (Dimitra) “I chose Karpenis because I have been there and it is wonderful” (Ageliki) “I want to go to Amfissa, because I like the city” (Antonis) “I will go to Karpenisi to do climbing” (Nikos) “In the other places there is a lot of climbing and I get dizzy” (Eleni). These justifications highlight a potential drawback on allocentric representations that, according to Piaget & Inhelder (1969), develop after the age of 8. 70,6% of the boys and 60,2% of the girls made relief associations justifying city selection and route design. Frequent engagement with electronic games was related to relief associated explanations, although no statistical significant difference was derived from a chi- squared analysis. 55,2% of pupils presenting relief associations in their answers noted a frequent engagement with electronic games, 8,1% rare engagement and 36,7% rare or no engagement at al. χ2 (4,339) = 0.694, p>.05, ns. Significantly more pupils in urban areas presented scientific oriented associations linking landscape with travel time and distance perception. 70% of the pupils living in city areas and 45, 5% pupils in rural regions identified geomorphologic features. 21, 2% of the city pupils explained city selection by postulating that it was closer or in straight line with the city of departure. The equivalent rural population reached 47%. Naïve theories were 8, 8% for city pupils and 7, 6% for rural pupils. This data is significant, χ2 (2,339) < 0.001, p < .05. Fig.3. Levels of understanding 41 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 3.4. Odds ratio analysis The results of the study indicate that urban pupils performed better in the city selection task, they designed routes on the map according to the landscape and justified city selections by identifying geomorphologic features. According to the logistic regression statistical technique we proceeded to an odds ratio analysis between the urban and rural pupil populations. j, k the two categories of the variable pupils from urban and rural areas, where j = urban and k = rural. j = 1, 2, 3 …n the criteria of route selection where 1 = geomorphologic features, 2, 3 …n are the other criteria (ex. linear etc) F (xj1) odds j = F (xj2+xj3+…xjn) F (xk1) odds k = F (xk2+xk3+…xkn) odds j 1,22 1,47 Oddsratio = = = odds k 0,83 1 Therefore an urban pupil was more likely to use geomorphologic features in justifying answers than a pupil from rural regions. These findings are supported by Blades’ et al. (1998) research showing that urban pupils demonstrate developed map reading abilities. In addition Matthews et al. (1999) claimed that for many young people, rural childhoods and closer affinity to nature is on dispute. Research findings by Klonari et al. (2011) indicate that terraces escape the attention of rural students and teachers, suggesting that the apparent is not at all evident, even for the locals where terraces constitute a very common landscape feature. Even children living near to the River Thames have little sense of it (Taylor, 1995). Environmental experiences of children living in rural regions do not reflect on the better understanding of physical landscape on maps. Our research findings contradicted the nativist viewpoint that children’s ability to understand maps is innate or acquired in early ages (Blaut 1991). 4. DISCUSSION In this research we studied middle school children’s map reading abilities in relation to distance perception, route traveling time and landscape with the use of a 3D relief map of Sterea Ellada. The findings contradict our research hypothesis that pupils living in rural areas have a better perception of the landscape. Urban pupils presented better performance in the city selection task, they drew routes on the map according to the landscape and supported their city selections identifying geomorphologic features. Map reading abilities tend to be more advanced among urban children, a conclusion that is consistent with research findings of Blades et al. (1998) that map reading abilities are present in urban communities with relatively high adult-literacy rates. Boys performed slightly better than girls in map reading tasks, while statistical significance was reported only in the city selection task, evidence supported by the studies of 42 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 Johnson and Meade (1987). Linn & Petersen (1985) suggested that spatial visualization presents less consistent pattern of sex differences. Boardman (1990) claimed that boys, as they grow older perform better then girls of the same age in drawing tasks and Maccoby & Jacklin (1974, in Liben, 2006, p. 208) agreed that sex related differences in spatial skills do not emerge until adolescence. Frequent engagement with electronic games related to a better visualization of landscape with maps. However the difference was not statistically significant and our research hypothesis was not confirmed. A number of studies indicate that electronic games enhance learning (Chen & Michael, 2005; Cordova & Lepper, 1993). Further research should be conducted aiming at the investigation of the role of educational electronic games in learning with maps and how to translate learning objectives into gameplay with educational implementations. Anagnostou (2010) suggests that educators should experiment with simple electronic games applying concepts that support learning objectives and evaluating the results of using game-based learning in educational environments. Naïve theories linking distance perception with the acquaintance of a place are still present at the age of 11. This implies that egocentric representations (Siegel, 1998) are not yet abandoned. The factor of acquaintance with a place is dominant in children’s mental representations of the environment and the feeling of security that derives from using for example home as a reference point may lead to systematic distortions of spatial representations (Biel, 1982). A few pupils based their selections on prior visits to a city and familiarity with a place or incorporated explanations that are significant in their everyday lives, such as safety parameters or easier access by boat, showing inability to conceptualize relief with the use of a 3D map. Some route depictions showed errors or distortions. The connecting route was interrupted either before the display of mountainous regions or at the edges of the word of the selected city. This relates to problems with symbology (DeLoache, 1989, Liben & Downs, 1992). A few pupils confused the point symbol of the city with the word of the city name. Teachers should clarify that the location of a city is represented by point symbols defined on the map legend and not by the word of the city name. Cartographers should also consider better placements of city names on maps, as they might produce confusion during map related tasks. The following areas of further study can be suggested from this research. Firstly, even though the research sample was representative of the ratio of Greek urban and rural population, it is proposed that further investigation should be conducted in mountainous regions about children’s landscape conceptualization and distance perception. The quality of environmental experience should be analyzed in more detail and correlated with pupils’ performance in mapping activities. Everyday geographies of rural pupils with rich environmental experiences should be utilized in map reading activities. We agree with Martin (2008) that primary geography teachers should be aware of the distinction between everyday and academic geographies and comprehend how to enable connections between the two. Educational resources and training are more easily accessible to teachers living in cities and that reflects on children’s map reading abilities. Lifelong learning with the use of educational platforms, such as Moodle, could bridge the difference of educational opportunities between city and rural regions. We advocate that these new technologies will enhance geography and should be implemented in national or European networks. Such efforts have started in Greece in the field of environmental education for secondary teachers and should expand to primary teachers including map work in this context. 3D maps are a useful tool applied successfully in this research. Therefore further research should be conducted to investigate the use of 3D maps combined with GIS applications and navigation tools for the improvement of pupils’ abilities to understand relief. 43 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 Acknowledgments We would like to thank Professor N. Soulakellis (Laboratory of Cartography and Geoinformatics) for the provision of the maps utilized, Lecturer V. 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What do we know about social and psychological effects of computer games? A comprehensive review of the current literature. Playing video games: 46 Apostolopoulou E-Klonari A./European Journal of Geography 2 2 35-47 Motives, responses, and consequences, eds. P. Vorderer, & J. Bryant, Mahwah, 325— 346. NJ: Lwarence Erlbaum. 47 European Journal of Geography 2 2: 48‐61, 2011. © Association of European Geographers USING GIS-BASED PROJECTS IN LEARNING: STUDENTS HELP DISABLED PEDESTRIANS IN THEIR SCHOOL DISTRICT Ali DEMIRCI Fatih University, Department of Geography, 34500, Buyukcekmece, Istanbul, Turkey, http://www.geography.fatih.edu.tr/, [email protected] Ahmet KARABURUN Fatih University, Department of Geography, 34500, Buyukcekmece, Istanbul, Turkey, http://www.geography.fatih.edu.tr/, [email protected] Mehmet ÜNLÜ Marmara University, Atatürk Faculty of Education, 34722, Kadıköy, Istanbul, Turkey, http://aef.marmara.edu.tr/, [email protected] Ramazan ÖZEY Marmara University, Atatürk Faculty of Education, 34722, Kadıköy, Istanbul, Turkey, http://aef.marmara.edu.tr/, [email protected] Abstract This study outlines a GIS-based project conducted in a public high school in Istanbul, Turkey with the support of the Scientific and Technological Research Council of Turkey (TÜBİTAK) in 2010. Fifteen 9th and 10th grade students worked as a group to determine how livable their district was for disabled pedestrians. The project lasted for one and a half years and students investigated the 251 kilometers of sidewalks in the district of Sisli. The students mapped all the objects that occupied the sidewalks, measured the widths and heights of the sidewalks at more than three thousand points, and located all the ramps constructed at each end of the sidewalks for those who use wheelchairs. At the end of the project, the students produced a map showing where disabled pedestrians can travel on sidewalks by themselves in the district. The project revealed that GIS is an important learning and teaching tool for schools and an important platform to bring school and other institutions together to solve social problems. Keywords: GIS, GIS-based projects, Project Based Learning, Geography education, Secondary education 1. INTRODUCTION Project-based learning (PBL) is a learning model in which students learn by completing projects. PBL focuses on teaching by engaging students in different activities, including asking and refining questions, discussing ideas, making predictions, conducting interviews, designing plans, collecting data in the field and laboratory, analyzing data, drawing European Journal of Geography - ISSN 1792-1341 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 conclusions, and presenting the results to others (Blumenfeld, et al., 1991). Projects should have some certain criteria to be considered within the framework of PBL. As described by Thomas (2000), projects in PBL; (1) should be central to the curriculum, (2) should focus on questions or problems, (3) should involve students in a constructive investigation, (4) should be student-driven, and (5) should be realistic by focusing on real-life topics and activities. PBL is a beneficial and effective instructional method that enhances the quality of learning and provides students with many practical skills, such as planning, communicating, problem solving, and decision making (Thomas, 2000). The use of technology has become an integral part of PBL in schools (ChanLin, 2008). As been one the powerful technological tools in schools, Geographic Information Systems (GIS) are used in combination with PBL to produce, store, display, manipulate, and analyze data on computers. Being a location-based system, GIS provides the opportunity for student-centered and standards-based education (Kerski, 2003), facilitates Problem-Based, Inquiry-Based, and Project-Based Learning (Johansson, 2003; Landenberger et al., 2006; Demirci, 2011), and empowers students to become active users of spatial data and active learners of geography (William, 2001). GIS has a big potential to be easily integrated into PBL. Since storing, representing, and analyzing data are the main functions of GIS, it encourages students and teachers to work on real life issues as project in their lessons. Various methods are used in incorporating GIS into classrooms across the world, such as implementing GIS-based exercises and conducting GIS projects (Malone et al., 2003; Demirci, 2008a, b; Demirci et al., 2011). The number of examples of GIS projects in secondary schools has increased in recent years across the world (Demirci et al. 2011). For example, the Geographical Information Systems Applications for Schools (GISAS) project, completed in 2006 (Johansson, 2006), is a GIS project that is conducted in schools in seven European countries. Similar GIS-based projects have been conducted in various academic subjects at schools in many countries across the world, including the US, UK, Canada, and Singapore (Wilder et al., 2003; Wigglesworth, 2003; Shin, 2006; Milson, et al., 2012). In schools in Turkey, GIS is primarily used to implement GIS-based exercises in the classroom. Only a few examples illustrate the use of GIS as a tool to conduct projects in Turkish high schools, and many of these cases are part of doctoral studies (Karatepe, 2007; Tuna, 2008). Although many different materials, lesson plans, and digital data are available to teachers allowing them to implement GIS-based exercises in Turkish high schools, a lack of good examples prevents teachers from incorporating GIS projects into their lessons. The problem has been illustrated in a project that was initiated in 2009 in Turkey. The project, titled “Using GIS to Develop Social Sensitivity among Students: Implementation of GIS- based Projects at Secondary School Geography Lessons,” identified the main obstacles to conducting GIS-based projects in schools. It lasted for 18 months from September 2009 to March 2011, and was conducted in three pilot public high schools in Istanbul, Turkey with the support of The Scientific and Technological Research Council of Turkey (TÜBİTAK). During the first stage of the project, students from each school conducted a survey of people in their school district. The survey included 24 questions that asked about the school district’s main social, economic, and environmental problems from other people’s point of view. Students in each school then selected three important problems and developed solutions in cooperation with related governmental agencies that use GIS. Nine GIS-based projects were conducted in three schools. This study outlines one of the GIS-based projects, which was conducted by Sisli High School students in Istanbul in 2010, and describes its effect on students, teachers, and the school. The project, titled “How accessible is the Sisli district for 49 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 disabled people? Analyzing the sidewalks for people with wheelchair,” was conducted in the Sisli district, which is located in the central part of Istanbul. 2. THE AIM OF THE GIS-BASED PROJECT IN SISLI HIGH SCHOOL Sisli is one of the most populated districts in Istanbul and is located in the central part of the city. Rapid urbanization and population growth have resulted in many problems in the district, such as traffic congestion, lack of parking areas, air pollution, and the development of illegal housing. Although this is a serious problem for the entire community, disabled people are among those who suffer the most from these inconvenient conditions in the district. When approximately 126 students at Sisli High School conducted a survey of 1,250 people in their district, they found that the state of the sidewalks, the roadway for pedestrians, received one of the highest numbers of complaints. Many people thought that the sidewalks in the Sisli district did not have proper standards and were mainly occupied by cars, stands, billboards, and trees that make it very difficult for normal pedestrians to walk. When discussing this problem, students thought that the lack of proper sidewalks in the district may cause further stress to disabled pedestrians, especially those who use wheelchairs. To understand the extent of the problem, students visited the Association for the Visually Impaired in the district. Authorities in the association told students how unbearable the situation was for them and demonstrated the difficulties they had while walking on sidewalks (Figure 1). After the visit and a long discussion of other possible project topics, the students decided to study the sidewalks in one of their GIS-based projects to understand the extent to which they were suitable for disabled pedestrians using wheelchairs in the district of Sisli. Fig.1 Students visited the Association for the Visually Impaired in the district of Sisli and walked with them on pedestrian ways to understand their problems 3. METHOD A number of activities were developed for the students participating in the project (Figure 2). Students helped with planning different stages of the project. They reviewed the existing literature to understand the problem and the main concepts regarding the project topic, conducted interviews in state and private institutions, studied GIS to learn how to use it in their project, collected and stored data in computers, used GPS, analyzed data with GIS, and prepared and disseminated the results of their project through conferences, newspapers and magazines. Before starting the project, the students walked through the streets in the district to understand the problems facing the use of the pedestrian areas. The following major problems were identified: (1) there were no sidewalks along some of the streets, (2) sidewalks were very 50 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 narrow along many streets, (3) there was no curb ramp at each end of many sidewalks, and (4) a majority of the sidewalks were occupied by objects such as trees, cars, billboards, stands, and even stone mushrooms that were built to prevent car parking. Fig.2 Activities targeted for the students in the project Fifteen students worked on the project during their 9th and 10th grade years at the age of 14 and 15, along with their geography teachers and a project assistant who was a graduate student studying geography. All the processes in the project were discussed and organized together with the project members under the supervision of an academic council included four geographers from two universities. Twenty neighborhoods located in the southern half of the district were identified as the study area, which covered 7.8 square kilometers (Figure 3). Students obtained the maps of the study area, which came in 46 pieces at a scale of 1:1.000, from the Map Directorate of the Istanbul Metropolitan Municipality. Students then walked through all the sidewalks in the study area to identify the locations and types of objects that occupied the sidewalks. They also recorded whether the objects prevented the passage of people on sidewalks, the locations of curb ramps along the sidewalks, the heights and widths of the sidewalks at certain locations, and the locations where there are no sidewalks. Students also identified broken surfaces on the sidewalks in the study area. 51 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 Fig.3 Location of the study area The project team collected all the data in the field over a two month period. The data collection took approximately 300 hours during April and May of 2010. The section on the sidewalks which can be walked through uninterruptedly was called a pedestrian segment in the study. A total of 3,018 pedestrian segments were studied in the study area and the total length of the sidewalks students walked through was 251,122 meters. Students first documented their findings on paper maps and then transferred them to computers (Figure 4). Basic layers of the study area, including streets and buildings, were obtained from the GIS department in the Istanbul Metropolitan Municipality in a GIS format. ArcGIS 9.3 was used for storing, manipulating, and analyzing data on the computer. Students first identified the streets that did not include properly constructed sidewalks. The objects occupying the sidewalks were classified with different symbols on GIS (Figure 5). Students also identified whether the objects prevented the passage of a person with a wheelchair by measuring the distance between the object and each end of the sidewalks. After locating the broken surfaces and curb ramps on GIS, students produced the final map of the study, which indicates the sidewalks through which disabled people can pass with their wheelchair. Students then produced the project report in an MS Word document and presented their findings at a conference organized by their schools. 52 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 Fig.4 Students collecting data in the field and transferring them into GIS environment Fig.5 Objects occupied the pedestrian ways were shown on GIS with different symbols 53 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 4. RESULTS 4.1. What did students find out from their project The project provided an in-depth analysis of the sidewalks in the Sisli district for disabled people using wheelchairs. As identified in the Figure 6, 26.7% of the pedestrian segments did not have proper sidewalks dedicated to walking. The total length of these segments is 67,075 meters. Fig.6 Streets with and without sidewalks Obstacles on sidewalks can make walking difficult and even impossible especially for people using wheelchairs and crutches. A total of 14,594 objects were identified on the sidewalks in the study area. As shown in the Table 1, 46% of these objects were trees. Almost 24% and 16% of the objects were electric poles and mushrooms, respectively. Mushrooms are the small mushroom-shaped stones that are built on sidewalks to prevent car parking. Various types of motor vehicles, such as cars and motorcycles, accounted for 7.9% of all the objects on the sidewalks. Table 1. The objects occupying the pedestrian ways in the study area Objects on the pedestrian ways Number % Tree 6719 46 Electric pole 3453 23,7 Mushroom 2365 16,2 Motor vehicle 1152 7,9 Stand 391 2,7 Billboard 120 0,8 Buffet 101 0,6 Trush Bin 36 0,3 Others 257 1,8 54 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 The objects were also analyzed to understand whether they create obstacles for passage on sidewalks. 2,904 objects (19.9% of all the objects) were found to obstruct people’s passage on the sidewalks. The pedestrian segments, along with the objects that create obstacles for people’s passage, are presented in the Figure 7. Fig.7 The pedestrian segments including objects that prevent people’s passage The widths of all the pedestrian segments were measured from 3,183 points in the study area. The classification of the pedestrian segments according to their width is given in the Table 2. As can be seen in the table, 82.4% of the pedestrian segments were less than two meters wide. As identified in some studies, two meters is accepted as the ideal width in Turkey for the sidewalks; it should be at least 3 meters at bus stops and 3.5 meters in front of stores (BÖİB, 2010; ÖZIDA, 2008). Only 17.6% of the sidewalks are more than two meters in width in the study area. Students also detected broken surfaces on the sidewalks. They identified 299 locations that needed maintenance in the study area (Figure 8). Table 2. The width of the pedestrian segments in the study area Width (m) The number of pedestrian segments % 0 - 2 2485 82,4 2 ve üzeri 533 17,6 55 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 Fig.8 The broken surfaces on the sidewalks that needed maintenance One of the most important features of sidewalks is whether they have a curb ramp properly constructed at each end. All the ramps on the sidewalks in the study area are shown in the Figure 9. A total of 264 curb ramps were identified. Only 9 out of 3,018 pedestrian segments included a ramp at each end. The final map (Figure 10) produced for the project indicated the sidewalks on which disabled pedestrians can move by themselves with wheelchairs. It was produced using two criteria: 1) whether objects found on the sidewalks prevented passage and 2) whether there were two curb ramps, one at each end of the sidewalks. The study revealed that only two pedestrian segments out of 3,018 had curb ramps at both ends that were properly constructed. The total length of the sidewalks through which disabled pedestrians can move by themselves with wheelchairs is only 273 meters in the study area (the approximate length of the whole pedestrian ways is 251 kilometers). Fig.9 Ramps on the sidewalks Overall, the project revealed that the sidewalks in the study area were not suitable for the needs of the disabled pedestrians who used wheelchairs. It confirmed that reconstructing all the sidewalks to meet certain standards was impossible, particularly in the places where the streets were very narrow. Some of the main streets, however, which crossed the study area 56 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 from south to north, could be modified to better serve disabled pedestrians. Buyukdere, Halaskargazi, and Cumhuriyet streets were the most important streets in the study area connecting Mecidiyekoy and Taksim. The sidewalks on both sides of these streets were at least two meters wide and contained no objects that prevented the passage of people. These streets could be made suitable for pedestrians using wheelchairs by constructing ramps at each end of their sidewalks. The survey showed that disabled pedestrians would then be able to walk approximately six kilometers by themselves using sidewalks. Fig.10 The sidewalks disabled pedestrians with a wheelchair could navigate by themselves 4.2. Effects of the project on students, teachers, and schools The GIS-based project conducted in the district of Sisli was the first project in which GIS was used in Sisli high school. The project had many positive effects on students, teachers, and the school. It provided students with opportunities to experience activities such as conducting a survey and interviews, visiting government agencies, collecting data in the field, using GPS and GIS and giving presentations at conferences and meetings. Through these activities, students gained an appreciation for the importance of geographic studies for society. They learned how to use GIS to solve social problems. Before the project, the students had only an abstract understanding of the usefulness of GIS. The project provided them an opportunity to learn how to use the main tools of GIS to produce, manipulate, analyze, and visualize data for specific purposes. The project was also useful for the students’ personal development. Students experienced increased confidence in their ability to communicate with people from different segments of society and to achieve something that improves society. The manager of the school and geography teacher who involved in the project in the school explained that the project changed the attitudes of students towards geography lessons and school in a positive way by considering the results of many interviews with the students. As they commented further, the project motivated students to participate in other school activities and to give further consideration to their post-graduation plans. Only one geography teacher actively participated in the project at Sisli high school. The teacher did not have sufficient GIS knowledge, skills, and experience before the project started. For this reason, the role of the teacher was restricted to organizing, communicating, and motivating students to conduct different activities in the project. The project was useful for the teacher in many ways. It helped the teacher understand the role and potential of GIS in 57 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 his lessons and also to recognize his lack of knowledge and skills about GIS. One of the most important benefits of the project for the teacher was that he realized the importance of GIS as an effective teaching tool for his geography lessons. The teacher coordinated the activities and connections between students, the school manager, and other project partners such as the municipality, Governor of Sisli, and Fatih University. All his activities and meetings with these partners increased the visibility and credibility of his geography lessons both inside and outside the school. The project was also useful for the school. Two conferences have been organized at Sisli high school to disseminate the results of the project. The governor of Sisli district, deputy mayor of the district, district director of national education, district police chief, researchers from two major universities in Istanbul, managers of the schools in the district, students, teachers, parents, and some journalists participated in these conferences. The project was useful for promoting the school and publicizing the needs of the school to related institutions. The GIS- based project brought together the school, public-private institutions and society and proved that schools can play an important role in society to solve problems and create unity. The project was also an opportunity to highlight inadequacies in the school. At the beginning of the project, there were no project rooms in the school where students could work together collaboratively. A room was eventually dedicated to this project’s activities at the school. The project received very positive feedback from different segments of society. The students who worked on the project received their certificates from the Deputy Director of Istanbul Provincial Directorate of National Education at a conference held at Fatih University (Figure 11). The findings from the project have also been covered in some newspapers. Fig.11 Student conference presentation and receiving their certificates from Ahmet Sait Güler, Deputy Director of Istanbul Provincial Directorate of National Education 5. CONCLUSION GIS can be regarded as a new subject for secondary schools in Turkey. It found a place in the secondary school geography curriculum in 2005 (Karabag, 2005). Different activities were carried out in the country over the last seven years to make GIS a common educational tool in schools, such as publishing the book “GIS for Teachers” in Turkish and providing teachers with GIS software, digital data, and lesson plans (Demirci, 2008b). The facilities and support for using GIS in schools are better now compared to previous years. Teachers can easily find GIS software, digital data, and lesson plans to use in their lessons. The number of teacher training programs using GIS has increased. Despite all of these positive developments, however, the number of schools in which GIS is used in classroom situations is far from satisfactory. This is why it is important to implement additional GIS projects that make teachers aware of GIS and motivate them to incorporate it into their lessons. 58 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 The GIS-based project conducted in Sisli high school is a good example of how GIS can bring students, schools, and society together to solve problems. In the project, students identified one of the most important problems in their society and worked as a group to develop a solution using GIS. The GIS-based project showed that GIS is a versatile tool in education for teachers, students, the school and society. It motivates teachers to learn how to use GIS effectively in their lessons. In addition to being an efficient learning tool, GIS helps students realize the importance of geography and the role of GIS in this science. Because it encourages students, schools, and different public and private institutions to work together to solve social problems, GIS is an important and effective tool for societal improvement. A number of obstacles continue to hinder the use of GIS-based projects in schools. In this project, schools were provided with GIS software, GPS, digital data, and all the necessary technical assistance. These resources, however, are not available to all schools. The biggest challenge for this project was the teachers’ lack of GIS knowledge and skills. Further, the school manager’s lack of interest and support for the project, a lack of time at the school for teachers to organize students for field work, a lack of PBL activities in lessons, and low levels of student interest in learning new things were among the main obstacles faced by the school while conducting this project. Conducting similar GIS-based projects at secondary schools is crucial. Teachers should be the primary means by which GIS-based projects are introduced into schools. Organizing teacher training programs for existing teachers, developing more efficient curricula for teacher education programs at universities, motivating teachers to spend extra time learning GIS and conducting GIS-based projects with their students, convincing school managers to change their attitudes towards geography lessons and the use of GIS in education, and encouraging decision-makers to take bold steps to develop more effective strategies for bringing GIS into schools are some of the steps that should be taken in order to incorporate GIS into geography lessons more successfully in schools. Whole segments of society should understand that GIS is not a luxury but a necessity to create a better world. Acknowledgment The project outlined in this paper was supported by TUBİTAK (The Scientific and Technological Research Council of Turkey) with the project number 109K271. 59 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 REFERENCES BÖİB. 2010. Yerel yönetimler için ulaşılabilirlik temel bilgiler teknik el kitabı. Ankara: T.C Başbakanlık Özürlüler İdaresi Başkanlığı. Blumenfeld, P.C., Soloway, E., Marx, R.W., Krajcik, J.S., Guzdial, M., and Palincsar, A. 1991. Motivating Project-Based Learning: Sustaining the doing, supporting the learning. Educational Psychologist: 26 (3&4): 369 – 398. Milson, A.J., Demirci, A., and Kerski, J.J. 2012. International perspectives on teaching and learning with GIS in secondary schools. (eds.) New York: Springer. ChanLin, L.J. 2008. Technology integration applied to project-based learning in science. Innovations in Education and Teaching International: 45 (1): 55 – 65. Demirci, A. 2011. 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Using Geographic Information System (GIS) to improve fourth graders' geographic content knowledge and map skills. Journal of Geography: 105 (3): 109–120. 60 Demirci A.- Karaburun A.- Unlu M.- Ozey R./European Journal of Geography 2 2 48-61 Thomas, J.W. 2000. A Review of research on project-based learning. The Autodest Foundation, http://www.ri.net/middletown/mef/linksresources/documents/researchreviewPBL_07022 6.pdf, Tuna, F. 2008. Taking the advantages of Geographic Information Systems (GIS) to support the project based learning in high school geography lessons. Unpublished doctoral dissertation, Marmara University, Institute of Education Sciences, Istanbul. William J.L. 2001. Integrating GIS into the undergraduate learning environment. Journal of Geography: 100: 158-163. Wilder, A., Brinkerhoff, J. D., and Higgins, T. 2003. Geographic information technologies + project-based science: A contextualized professional development approach. Journal of Geography: 102(6): 257-261. Wigglesworth, J. 2003. What is the best route? Route-finding strategies of middle school students using GIS. Journal of Geography: 102(6): 282-291. 61 European Journal of Geography 2 2: 62‐78, 2011. © Association of European Geographers A MICROECONOMIC ASSESSMENT OF GREECE’S CORE-PERIPHERY IMBALANCES (1994-2002) CONFIRMING KRUGMAN’S INITIAL NEW ECONOMIC GEOGRAPHY MODEL Constantinos IKONOMOU Department of Economics, Law School, Department of Economics, 5 Stadiou Street, 10562 Athens, Greece [email protected] Abstract This paper contributes to the literature of economic geography by providing a first empirical confirmation of Krugman’s initial new economic geography model, in the Greek economy. A sample of Greek SMEs, drawn from four selected regions having different levels of centrality and five major industries in the 1995 – 2002 period, is found to be representative of the Greek business population, by the use of non-parametric tests. A cross-sectional model associates logarithmic SME employment growth with proxies used for capital, labour, land, industrial infrastructure, policy support, firm size, manufacturing and distance from Athens. The significance of the last three factors captures the operation of a microeconomic core-periphery model, as suggested by Krugman (1991) and agrees with a discussion on core-periphery imbalances in Greece. The latter however have not yet been diagnosed in literature by the use of models. Policy implications concerning Europe 2020 strategy relate to the need for manufacturing growth in peripheries, its interregional and inter-industrial diffusion. Keywords: Core-Periphery Imbalances Economic Geography NEG Microeconomic Growth 1. INTRODUCTION The 2020 strategy for Europe and its regions, introduced under the headings of “smart”, “sustainable” and “inclusive” growth, discusses the need to exploit resources and wealth in the EU regions, benefiting from all available European assets (COM (2010) 2020). The targets are to achieve regional restructuring both at the national and EU level, resolve the most substantial structural problems in the EU regional economies and help regions to become resource efficient, by enhancing their growth potential (COM (2010) 2020). This strategy however and related guiding documents (e.g. Barca, 2009) have neglected the role of manufacturing for achieving economic growth and the need to support its diffusion in peripheral economies through the production of new varieties of goods, as discussed in readings from new economic geography (Combes et al, 2008). Manufacturing and its spread in peripheries was emphasized for a long period in regional economics and Ikonomou C./European Journal of Geography 2 2 62-78 economic geography to be a principal cause for peripheral growth and a reason for creating, sustaining, strengthening or even reversing core-periphery imbalances (Myrdal, 1957; Chapman and Walker, 1987; Weber, 1929; Hoover, 1948; Losch, 1954; Greenhut, 1956; Isard, 1956; Smith, 1971; Armstrong and Taylor, 1999; Pitfield, 1978; Needleman and Scott, 1964). At the same time, the assessment of the effects of EU Cohesion policies both at the national and the EU level remains rather inconclusive. Some studies have referred to club, σ or β-convergence highlighting policy success (Dall’erba and Gallo, 2008; Curaresma et al, 2008; Siano and D’uva, 2006; Mora et al, 2005; Badinger et al, 2004; Benos and Karagiannis, 2008; Alexiadis and Tomkins, 2006; Michelis et al,, 2004), while other referred to divergence (e.g. in Dall’erba and Gallo, 2008; Cappellen et al., 2003; Dall’ebra and Gallo, 2004, Tsionas, 2002). More recently, the need to combine macro with micro approaches was discussed, given the limited attention on microeconomic models (Bradley et al., 2006; Bradley, 2005). The present is a microeconomic study investigating the causes of business growth in Greece, in the 1995-2002 period. While evidence is provided on the factors associating with the growth of small and medium sized enterprises (SMEs) in a particular environment, their significance highlights existing microeconomic approaches in suggesting core-periphery imbalances (Krugman, 1991). 2. MICROECONOMIC MODELLING, THE NEW ECONOMIC GEOGRAPHY AND THE ASSESSMENT OF CORE-PERIPHERY IMBALANCES Microeconomic models are increasingly being developed to explain spatial growth agglomeration and imbalances, in studies from new economic geography (Krugman, 2010; Combes et al., 2008). Though similar models were developed before in economic geography for the study of agglomeration and spatial concentration of phenomena, a new path for their general inference was offered by the use of general equilibrium modelling. This path helped to better integrate geography to economic thinking (Krugman, 2010). Historically, it coincided with an expressed criticism on the limitations of neoclassical thinking and other growth models to fully explain growth and its spatial agglomeration (Temple, 1999). Microeconomic models such as those developed by Weber, Moses, Losch and Pallander emphasized demand, economies of scale and transportation costs for the location of manufacturing firms (see McCann, 2001). The role of these factors was explored in a model developed by Krugman (1991) that gave birth to the field of New Economic Geography and a subsequent debate on the subject. This model sought to explain circular causation and the conditions for core-periphery imbalances, by reference to manufacturing; whenever “some index that takes into account transportation costs, economies of scale and the share of non- agricultural goods in expenditure crosses a critical threshold, population will start to concentrate and regions to diverge; once started this process will feed itself” (Krugman, 1991; p. 487). The original 1991 two-sector, two-region model, suggested two opposing spatial configurations likely to occur: a core-periphery pattern where the centre benefits mostly and a symmetric spatial equilibrium, with growth being equally distributed among regions (Krugman, 1991). Starting from these configurations, the economy remains in the same state and is, in macroeconomic terms, at a steady-state. If transportation costs are low and the share of manufacturing expenditure and the absorption of new varieties large, labour mobility among regions leads to concentration in the more advantaged regions, and core-periphery imbalances are formed in a circular causation process (Mossay, 2006). Short-run equilibriums can also be formed, based on the current labour distribution across regions (Mossay, 2006). 63 Ikonomou C./European Journal of Geography 2 2 62-78 The use of transportation costs in the model acknowledges the role of trade in the creation of core-periphery imbalances. Both trading with other nations and among national regions is likely to affect the degree of spatial agglomeration (Schmutzler, 1999; Ohlin, 1933). Spatial agglomeration would also relate to inter-industrial association and the forward and backward linkages among industries (Hirschman, 1963; Hoover, 1948). But trade would also depend on particular physical conditions and barriers and the transportation infrastructure and activity. Despite the interest expressed in Krugman’s 1991 model, scanty empirical evidence has been provided to support these views. The absence of studies empirically confirming at least the main growth conditions prioritised in this model and discussed to cause spatial agglomeration, make its use highly suggestive. Even Krugman himself referred to a picture of growth and agglomeration mostly found at the beginning of the last century, limiting its general predictive value (Krugman, 2010). Hence, the task to empirically confirm this model or at least the factors composing it can be a valid precondition for studying its more general inference and usefulness and provide a focus for new economic geography research. Identifying the statistical significance of the model’s factors in the case of a single economy, does not provide, from a geographical perspective, general evidence for all economies, as discussed in Martin (1999). But is a reason to further acknowledge how geography affects the economy, shapes growth agglomeration and the core-periphery imbalances. Macroeconomic growth is generally discussed to have microeconomic foundations (Janssen, 2006; Hoover, 2008; Da Silva, 2009). Microeconomic models are concerned with the development of micro actors, such as consumers, NGOs or firms. As principal growth actors among others, firms and their growth are the subject of a large variety and heterogeneity of models. Microeconomic modelling is progressively associated with the role of increasing business returns highlighted in microeconomic theory and the need to better assess the role of policies, which reminds of the Lucas critique of macroeconomic analyses (Lucas, 1976). Studies using models of businesses investigate the effects of various factors associating with business growth in terms of size or numbers, business survival, death or their general operation (see in Hart and McGuiness, 2003; Smallbone et al., 1983; Curran and Storey, 1983; Storey, 1983; Vaessen and Keeble, 1995 and many other). Some of these models focus on surviving firms only, while other refer to both surviving and non-surviving firms. The growth of businesses and SMEs in size terms is subject to various growth factors (Penrose, 1959; Cosh and Hughes, 2003; Hart and McGuiness, 2003) Business growth factors may derive from the business environment, general or specific to firm. They may also be internal to firm or the outcome of interaction between internal and external to firm factors. Internal to firm factors causing business growth are very broad in nature and relate to the role of entrepreneurs, human resources, training, administration and management, the absorption of R&D and many other issues influencing growth. The specific environment surrounding the firm, local or regional, is studied through factors such as those referring to capital availability, human capital and labour resources, infrastructure development or the land and its value (e.g. in Hart and McGuiness, 2003; Curran and Storey, 1983; Vaessen and Keeble, 1995; Cosh and Hughes, 2003). Many factors need to be included in a model to provide higher coefficients of determination, including internal to firm growth causes. Similar studies developing cross- sectional business growth models focus mostly on the significant associations captured in these models and the respective levels of significance, as a way to diagnose which particular factors contribute to business growth, the direction of their association with business growth and to offer a policy prescription (e.g. Bennett and Robson, 2000). The general expectations in regional studies and economic geography are that firms in central locations and regions will grow faster due to their better access to markets, other businesses, services, high-skilled labour, capital, income resources, information sources, 64 Ikonomou C./European Journal of Geography 2 2 62-78 networks and reduced transactions costs that help them to overcome growth barriers and problems (Friedman and Alonso, 1964). If physical geography acts as a barrier, then it should be removed or turned into a competitive advantage, for example through new infrastructure and transportation projects or investment at the periphery. On the contrary, in theory, businesses in geographically isolated and peripheral areas were expected to face physical barriers and thrive less and, as a result, to seek re-location to central regions. Suffering from information asymmetry, firms in these places need telecommunication, transportation or other infrastructure projects to expand their economic activity and reduce the gap when compared with more central and advanced regions. Low labour costs and wages in peripheral regions can help firms to reduce costs, increase profits and benefit from the use and application of new varieties of products (Combes et al., 2008). These general expectations are not confirmed in studies testing the effects of various local and regional environments of firm growth. The latter do not present uniform results. For example SMEs in peripheral, disadvantaged regions were found to achieve higher growth rates in comparison to central (Vaessen and Keeble, 1996). Furthermore such outcomes may be subject to particular policy conditions and environments (Hart and McGuiness, 2003). To conclude, the assessment of core-periphery imbalances can be made by using applied microeconomic analysis that confirms Krugman’s 1991 model (or any other new economic geography model tested). Furthermore such assessments are subject to various theoretical expectations, which however may not be necessarily confirmed at the microeconomic level. 2.1 The focus on Greece: An international example of domestic geographical imbalance and its role in affecting the growth of the Greek economy This study focuses on the growth of a sample of SMEs in Greece, which have survived between 1995 and 2002 and investigates the factors associating with their growth in size terms, in different geographical levels. The focus is given on a period before Greece’s entrance at the Euro-zone, in 2002. Inside the common currency area core-periphery imbalances in Greece are likely to be affected (as discussed in Martin, 2001). Recently the Greek economy has become the focus of considerable international attention. Various discussions have been held concerning its growth prospects and its increasing debt. In the period before joining the Euro-zone in 2002, Greece underwent numerous structural adjustments, such as the reduction of inflation and that of interest rates from more than 20% (in early 1990s) to less than 5% (in early 2000s) and what appeared at the time a steady economic growth rate (O.E.C.D., 2007). The Greek economy is a peripheral EU economy, such as the economies of Spain, Portugal, Ireland or the Southern Italy. Located far away from EU economic centres, it has been physically isolated by land and its firms suffered from higher transportation costs to EU markets. But the country actually suffers from a double peripherality, not only within the EU but also inside its own territory. Greece’s physical geography is characterised by imbalances in its economic geography, which are difficult to overcome. Some of its regions are more central than others, while the most peripheral regions are physically very isolated. The most peripheral throughout the 1990’s are those physically isolated by sea1 and, in the mainland, those isolated by mountains and the absence of infrastructure. Approximately two-thirds of Greece’s physical environment is an archipelago composed of islands, while the main part of the mainland is covered by mountains. This creates a permanent character of physical 1 It may take more than a full calendar month to transport labour or products from the islands to the mainland. 65 Ikonomou C./European Journal of Geography 2 2 62-78 peripherality within Greece’s territory that, until today, has been difficult for firms to overcome2. The same Greek geography imposes significant growth barriers. Economies of scale in the islands are enhanced through tourism, which can create inter-industrial linkages for all islands, taken together. There are almost three hundred populated islands which each add considerable public expenditure required to support education, public health, airports, sea transportation and other public services. The cyclical nature of tourism and economic activity in the islands affects the overall Greek economy, following any periodic interruptions. This is sustained both directly through various jobs in tourism and indirectly, as the labour force from islands moves towards the two main centres, Athens and Thessaloniki, seeking for permanent or part-time jobs during the non-touristic seasons. On the mainland, business and economic growth is restricted by accessibility barriers and concentrated in some specific areas. The western region of Greece, Ipiros, is one of the most peripheral at the EU. For centuries it has lacked the necessary infrastructure to be accessed by land or sea and only remained partially integrated in the road and train infrastructure developed in the country at the north-south axis. This peculiar physical environment has contributed strongly to the location of economic activity at the coastal zone, providing multiple equilibriums for minimising trade and business costs from cities to more than 100 main islands/destinations. Similarly, Greece’s international trade and the related shipping activity has affected the location of cities-ports by the coastal zone, especially in what is known as the S-axis3, where two-thirds of economic activity is located. Climatic conditions, especially in the summer season, also strongly affect economic activity and reinforce its location close to the coastal zone. Overall Greece’s economic and physical geography pose various barriers to growth and substantially increase transportation costs, bringing insufficient economies of scale and limiting growth. Various studies of the Greek economy that take a macroeconomic perspective highlight the presence of geographical imbalances in the period before Greece’s entrance at the Euro-zone, referring to a geographical dualism between the North and the South (Asteriou et al., 2002; Tsionas, 2002; Siriopoulos and Asteriou, 1996). However the Greek regional convergence/divergence literature is not clear about the presence of substantial core-periphery imbalances, despite the fact that more than half of the population lives and commutes in the two main centres, in Attiki and Kentriki Makedonia, where the cities of Athens and Thessaloniki and the majority of economic activity are located (see for example the views held by Asteriou et al., 2002; Tsionas, 2002; Siriopoulos and Asteriou, 1996; Benos and Karagiannis, 2008). On the contrary, some studies -even from earlier periods- appear to suggest the presence of regional convergence or limited divergence (Michelis et al, 2004; Benos and Karagiannis, 2008). Beyond the macroeconomic perspective, the growth of Greek firms is discussed to relate to their investment patterns and their performance to be higher in central locations, in Athens and Thessaloniki (Fillipaios and Kottaridi, 2004) and subject to locational choices (Liargovas and Skandalis, 2008). EU regional policy assistance appears to affect new plant formation by changing the wider economic environment and boosting economic development. The location of manufacturing firms relates to market size, advanced infrastructure, human capital, labour cost and spatial proximity (Filippaios and Kottaridi, 2004). Hence, an interesting theoretical and empirical direction lies in investigating the presence of core-periphery imbalances in Greece from a microeconomic perspective and the factors associated to it. 2 As an indicative index of the particularity of Greece’s geographical environment, the length of the coastal zone is comparable to that of the rest of the EU. 3 From Thessaloniki to Patras all along the coastal zone that seems to create an S-axis. Most recent developments in road infrastructure attempts to overcome this problem by reducing the degree of peripherality in a way that changes the latin S to the Greek sigma (Σ-axis), to a certain extent (Skayannis, 2009). 66 Ikonomou C./European Journal of Geography 2 2 62-78 2.2 The selection of the sample This study focuses on business and SME growth in the 1994-2002 period, in different industries and regions of Greece. The sample was selected from the 1995 Greek V.A.T. database and the firms in the sample have been traced through the same database, in 2002. The Greek V.A.T. database is the largest Greek business database and the most accurate approximation of the business population. A simple scale of centrality was created for the country’s general core-periphery pattern by categorising regions from more central to more peripheral. Such rankings can be based on GDP per capita or other regional economic indexes. But the present study has made use of a broader composite ranking index, by using of several economic variables. Similar rankings for the Greek regions are found in other studies (Petrakos and Psycharis, 2004). This method was used to select four out of the thirteen Greek regions: two central Greek regions, Attiki and Kentriki Makedonia (where the capital, Athens, and the “capital” of the north, Thessaloniki, are located respectively), a region of moderate peripherality, Thessaly and the most peripheral region in Greece and one of the most peripheral in the EU at the time, Ipiros, located at the North-West of Greece. Hence the sample of firms was spread randomly across different regions, a method which is followed in other circumstances (e.g. Cosh and Hughes, 2003) to avoid reaching conclusions only on central areas, because of the relatively very large size of business population in the most central areas. In this research, the sample was limited geographically to the Greek mainland, given the strong geographical imbalances in the islands and the bias towards firms of certain activities (e.g. in maritime activities), smaller sizes and high transportation costs. The choice of regions removes the problem of spatial autocorrelation, as business growth is studied in regions distant to each other, of different levels of centrality. The sample was limited to five industries: construction, manufacturing, tourism, trade, and services. These are dynamic industries of the Greek economy and belong to the two main sectors of production, manufacturing and services that represented approximately 90% of the Greek GDP in the late 1990s. The construction and manufacturing industries are comprised in the secondary (manufacturing) sector whose importance is high in the Greek economy. As in Krugman’s 1991 model, the sample comprises two main sectors and is drawn from four regions of different peripherality, two of which are central and the rest can be seen as non-central. The spatial configuration is that of core-periphery imbalances that already appears in the Greek territory (more than half of the population lives in the regions of Attiki and Kentriki Makedonia) and, following Krugman’s (1991) model the factors causing this configuration should relate to transportation costs, economies of scale and the role of manufacturing production in the total expenditure. Such factors should be found to be significant for the growth of SMEs. A stratified simple random sampling method was used, with quotas for the regions and industries selected. First, stratification was made for the employment variable only, using employment bands provided by the Statistical Services of Greece (EL.STAT). Only firms of initial employment size from 5 to 200 employees were selected. Employment thresholds were in agreement with the E.U. definition of SMEs and the pattern of employment size distribution found in the Greek economy, skewed to lower employment bands. Turnover thresholds were more than €0.15M and less than €50M, again in agreement both with the E.U. definition of SMEs and the pattern of turnover size distribution in Greece (2003/361/EC). The number of firms calculated in each employment band was allocated to the preselected four regions and five industries. The allocation of the sample to the regions was made using the regional variance provided by EL.STAT. Each region and each industry had to contain a minimum of 50 firms, sufficient for econometric purposes (as discussed in 67 Ikonomou C./European Journal of Geography 2 2 62-78 Barkham et al., 1996). This threshold is important for reaching conclusions at the regional level concerning business growth. Simple random sampling was used to select each combination of employment band, region and industry. Overall, simple random sampling was undertaken for a total of one hundred combinations of employment, regions and industries. Quotas for the regions and industries were imposed to ensure that, in every region, a sufficient proportion of firms was allocated, as in the national population. Overall 1,380 firms were identified for 1995 and were traced until the final year of the research, 2002. Those among them having a zero size in 2002 both for employment and turnover, were considered as inactive, having ceased operation and removed from the sample. Firms containing either final zero turnover or final zero employment were contacted to double-check the validity of their size values and, on several occasions, to correct it4. A total of 1,089 firms was finally selected, which, successfully passed the non- parametric tests, and they were found to be representative of both the full sample of 1,380 firms and the Greek business population. Representation was found for employment bands, regions and industries. Further data correction was undertaken to ensure the robustness of results. As there was a limited extension of information on mergers and acquisitions in the Greek economy in the study period, all firms were assumed to be proper firms5. Data on employment in the construction industry for the final study year (2002) revealed the presence of partnerships (double-checked with information on legal status). Having removed the majority that had a zero value both in their final employment and final turnover, the remainder (only one quarter) were assumed to act as firms, given also that existing studies on SMEs in the construction industry at the study period had provided evidence of their underperformance. Firm relocation was assumed not to take place, given the very limited number of firms relocating from one region to another and the principal significance of the initial regional environment for taking such a growth-oriented decision . Hence only changes of the initial regional environment were tested upon firm growth. Information contained in the sample was used to create variables (of size, industry and region) that were introduced as categorical and further broken down into several dummy variables. Initial employment size dummies were used to differentiate among micro, small and medium firms. The local and regional dummies were used to associate the sample with selected proxy-variables for the local and regional environment, using the regional and local accounts, available from the EL.STAT. (enlisted in Table 1). These variables, reflecting a variety of changes in economic factors at the local and regional level, such as financial capital and savings, population, labour, infrastructure and land, were grouped under the following headings: capital, labour, land, industrial infrastructure for services and manufacturing-based variables. The role of the geographical environment was introduced both by the use of regional and local dummies and by their association with regional and local variables. Further to these geographical variables, the distance of firms from Athens (DIST) was also added, as a numerical variable, based on road distance data. The particular role of manufacturing firms was tested through the respective variables on manufacturing sales, manufacturing value added and manufacturing investments of SMEs and 4 The correction was based on additional information provided by EL.STAT with respect to the law on confidentiality. Managers and accountants of the firms’ contacted have traced data in their officially declared V.A.T. documents, using, in practice, the same source of information as that used in the V.A.T. database. 5 It is mainly in the following years that mergers and acquisitions were intensified in the Greek economy. 68 Ikonomou C./European Journal of Geography 2 2 62-78 larger firms, which are more likely to achieve economies of scale (MANFSMLSAL, MANFSMLINV and MANFSMLVA). The number of manufacturing firms was also introduced (MANFSML). Table 1: The variables used in the study LEVEL NAMES of CATEGORY DESCRIPTION PROXIES USED REGION1 – MOST CENTRAL REG1_95 REGION, ATTIKI REGION2 - CENTRAL REGION, REG2_95 KENTRIKI MAKEDONIA REGION BUSINESS REGION3 - MIDDLE REG3_95 PERIPHERAL, THESSALIA REGION4 - PERIPHERAL REG4_95 REGION, IPIROS IND1_95 INDUSTRY1 - CONSTRUCTION IND2_95 INDUSTRY2 – MANUFACTURING INDUSTRY BUSINESS IND3_95 INDUSTRY3 – SERVICES IND4_95 INDUSTRY4 - TOURISM IND5_95 INDUSTRY5 – TRADE MICRO95 Initial micro size INITIAL SIZE BUSINESS SMALL95 Initial small size MEDIUM95 Initial medium size REGION ACTIVE Changes in activity rates, 1991-2001 LABOUR Changes in population density, LOCAL POPDENS_9401 1994-2001 Changes in private investment in LAND LOCAL PRHSINV_9401 housing, 1994-2001 Change in the number of SMEs and MANFSML_9401 large manufacturing firms (more than 10 employees), 1994-2001 Change in manufacturing MANFSMLINV_9401 SME and large firms investment, 1994-2001 MANUFACTURING LOCAL Change in manufacturing MANFSMLVA_9401 SME and large firms value added, 1994-2001 Change in manufacturing MANFSMLSAL_9401 SME and large firms sales, 1994-2001 SAVINGS_9400 Change in savings, 1994-2000 Change in declared income, INCDECL_9401 1994-2001 CAPITAL LOCAL INDTAX_9401 Change in indirect taxes, 1994-2001 DIRTAX_9401 Change in direct taxes, 1994-2001 Change in the number of tax payers, TAXPAY_9401 1994-2001 INDUSTRIAL Change in the number of hotel beds, INFRASTRUCTURE LOCAL HOTELBED_9401 1994-2001 (for services) Distance from the centre of Athens DISTANCE BUSINESS DIST (km) POLICY STATUS BUSINESS POLSTAT Policy support status (dummy) The role of policy is introduced in two ways. As Greek state policies are scheduled and applied within the context of EU Cohesion Policy, the latter is automatically integrated into 69 Ikonomou C./European Journal of Geography 2 2 62-78 the study. Hence, local and regional level growth factors are the outcome of changes brought by the EU Cohesion Policy. To better clarify policy influences, the study of policy support at the firm level is introduced. The sample was matched with the largest dataset on policy supports from EU Regional Policy, available from the Greek Ministry of Finance. Overall, 315 firms were found to match the sample, a reasonable proportion, which was sufficient to draw conclusions on the effects of policy on SME growth and found to be representative of the overall policy dataset used. A dummy variable was introduced on the policy status of firms (POLSTAT), taking positive values for those SMEs in the sample that have received support. Other variables from the local and regional environment were included and tested in the model and found not to be significant. These are some industrial proxies, education variables, variables-proxies for the financial activity status and unemployment status and are presented in Table 1, Appendix. Business and SME growth is measured as a change of employment size over the study period. The study focuses on surviving firms only, in practice emphasizing the question of growth (more intensified in surviving firms). 3. ANALYSIS 3.1. Developing the growth models The growth outliers were identified and removed, before models were built for the sample without outliers. Removing outliers is a standard practice in statistical analysis. Tracing the growth outliers was considered necessary in order to isolate the study of firms only to those more regular growth and was made with the help of the scattergram of employment and turnover growth (Diagram 1). Firms were ranked in terms of their employment growth and those with extreme increases or decreases in employment were removed. Similarly this was done for turnover growth outliers, taking into account that growth outliers overall should be a reasonable proportion of the full sample. Overall, 66 growth outliers were removed, reducing the sample to 1,023 firms. Diagram 1: Scattergram of employment growth and turnover growth for the full sample (1089 firms) Notes: 1. Employment growth is measured as employees and turnover growth in M€. 2. Turnover values are deflated (TURNGRdfl) 70 Ikonomou C./European Journal of Geography 2 2 62-78 As in related works (e.g. in Hart and McGuiness, 2004) SME growth modelling followed a consecutive reiteration method. First all explanatory variables are introduced in the model and then, the most significant among them (at the highest level of significance, p≤0.001), are selected and re-introduced. All variables, apart from one exception, are found to be significantly associated with SME growth at a very high level of significance. This method limits multi-collinearity and allows including numerous explanatory variables. Only highly significant associations are included in the final model. The use of logarithmic models (as in Hart and McGuiness, 2004) was preferred, to reduce the levels of heteroscedasticity. Modelling results are presented in Table 2. Table 2: Model of logarithmic SME employment growth in Greece (for the sample 1023 firms without outliers) LogEMPLGR Model F-value 6.49 (16, 927) REG2_95 0.842*** IND1_95 -0.073** MEDIUM95 -0.2*** POPDENS -0.53*** PRHSINV 0.008*** HOTELBEDS -0.001*** INCDECL 0.004*** INDTAX 0.012*** DIRTAX -0.023*** TAXPAY -0.001*** MANFSMLINV 0.000*** MANFSML -1.672*** MANFSMLVA -0.001** MANFSMLSAL -0.001*** DIST -0.001*** POLSTAT 0.109*** Cons -4.467* R-square 0.1008 Adj R-square 0.0853 N 944 Degrees of Freedom (df) Model df 16 Residual df 927 Total df 943 Note: *, ** and *** indicate significance at the 90%, 95% and 99% level respectively SME growth was found to associate with the central region of Kentriki Makedonia (REG2) and the distance from Athens (DIST). The latter is a negative association. Both associations highlight the significance of central locations on SME growth and the centripetal forces exercised on SMEs. The model also provides evidence on the association of SME growth with numerous variables at the geographical level: population density (POPDENS), private housing investments (PRHSINV), the number of hotel beds (HOTELBEDS), declared income (INCDECL), direct and indirect taxes (INDTAX and DIRTAX), the number of taxpayers (TAXPAY), investment, value-added and sales of firms in the manufacturing industry 71 Ikonomou C./European Journal of Geography 2 2 62-78 (MANFSMLINV, MANFSMLVA, MANFSMLSAL) as well as the number of large-sized manufacturing firms (MANFSML). Since all these geographical variables were used as proxies for capital, labour, land, infrastructure and the manufacturing industry variables, their role for SME growth is highlighted. For example the negative highly significant association with the construction industry (IND1) and the significant associations with numerous proxies for manufacturing relate to the role of the manufacturing (secondary) sector on SME growth. The general form of the model can be expressed with the function: SME Growth = f (centrality, capital, labour, Policy Status, land, infrastructure, manufacturing sector, size) The last four variables, namely land, infrastructure, manufacturing sector and the size of firms all related to firms’ locational choices. The significant association of SME growth with land prices (PRHSINV) reveals the role of land. The significant association with SME growth highlights the role of firm sizes and that of their economies of scale. The proxy for industrial infrastructure in tourism (HOTELBEDS) is a part of the regional capital. Manufacturing variables-proxies are found to negatively associate, revealing the negative association of sizes, value added and number of manufacturing firms with business and SME growth. The latter should relate with limitation in sizes, value added and number of firms in manufacturing and a reduced capacity to deliver growth. The variables-proxies for distance (for transportation costs), size (for economies of scale) and the variables of manufacturing (for share in manufacturing) were all found to significantly associate with SME growth. Therefore, it can be argued that the final microeconomic model of SME growth for surviving firms between 1995 and 2002 in Greece reveals the significance of the variables that are discussed in Krugman (1991). In that respect it confirms the presence of a core-periphery configuration at the national level, empirically confirming the significance laid on Krugman’s model for the growth of firms and SMEs. The association with central areas (seen at the significance and sign of the variables REG2 and DIST) emphasises the association of SME growth with central Greek regions rather than with the periphery, strengthening the picture of the significance of centrality. What is more, the model contains significant variables for regional and local capital and labour. Hence, in its original functional form of the model incorporates the two main factors discussed in neoclassical growth theory: SME growth = f (capital, labour) A conclusion therefore can be reached that business and SME growth in Greece, in the period under study was a function not only of capital and labour, as in the neoclassic-type function, but also of the conditions discussed by Krugman (1991), the land, the policies implemented and the industrial infrastructure. The empirically produced model was found to hold for surviving firms only and the model provided (with low levels of R-square) cannot be used for predictive but rather for suggestive purposes, while reference needs to be made on the particular policy environment promoting changes at the local and regional level, through EU Cohesion Policy and the business supports. 72 Ikonomou C./European Journal of Geography 2 2 62-78 4. DISCUSSION AND MORE GENERAL CONCLUSIONS This study has developed a model that shows which factors from the geographical and internal environment of the Greek SMEs significantly associate with their growth, in the 1995-2002 period. The findings have revealed a model that is, in its initial form, neoclassical and contains proxy-variables for both capital and labour. The model also contains significant proxies for the factors discussed in Krugman (1991): transportation costs, economies of scale and numerous proxies for the manufacturing industry. Furthermore, it reveals the significance of land prices, centrality and policy support. Given the sample’s representativeness of the Greek business population and the representativeness of all levels of centrality, the model gains a more general value. Results can be suggested to hold at the national level, highlighting the importance of the particular factors in the geographical Greek environment and their changes for SME growth, at the study-period. Krugman’s initial model in new economic geography (Krugman, 1991) that reveals a core-periphery pattern is further strengthened by the association found with capital and labour (discussed in neoclassical and classical economics) and the significance of the land (discussed in the classics and the economic geography studies). The present model bridges the neoclassical view with that on growth agglomeration in space. While neoclassical theory hypothesis is that capital and labour movements bring business growth at the national and non-national (regional or local) level, such business growth also agglomerates in space. This process associates to the geographical environment and to land values. The results do not seem to be a surprising outcome, due to the intensity of Greece’s geographical imbalances, especially core-periphery imbalances that create imperfect markets and information asymmetries. Important policy concerns are raised from the empirical validation of a Krugman’s model. The first is whether geographically disadvantaged, peripheral EU regions are capable to avert their expected demise as peripheral regions. A limited level of manufacturing production, higher transportation costs, a less adequate infrastructure in many respects and the lower economies of scale are likely to enhance the causes of Greece’s peripherality at the EU level and the spatial configuration of its domestic core-periphery imbalances. Furthermore, the EU 2020 strategy should promote peripheral European growth by investing in manufacturing industries, in ways that could unlock growth potential across industries. On the basis of manufacturing development, a progressive integration of other industries can take place through an achieved enhanced inter-regional and intra-regional mobility of capital and labour. This could help to reach the aim to better exploit and use regional resources. In the Greek case study that suffers from a double peripherality, the conclusion reached relates to the basic economic wisdom hitherto addressed for a long period in regional studies and economic geography on the need to better spread manufacturing across the EU. The present text has taken a microeconomic view on growth, by focusing on SME growth in representative Greek regions. While providing a consistent account of Krugman’s model (1991), it also revealed a realistic problem for the sustaining of core-periphery patterns in Greece, by testing indirectly the role of factors discussed in economic theory. Acknowledgments This research was funded by the Greek State Scholarship Foundation. 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Uber den Standort der Industrien. 77 Ikonomou C./European Journal of Geography 2 2 62-78 Appendix Table 1, Appendix: List of variables not significantly associating with business and SME growth in the model CATEGORY LEVEL NAMES of DESCRIPTION PROXIES USED BUSINESS LGST1_95 Unlimited liability firms BUSINESS LGST2_95 Mixed liability firms LEGAL STATUS BUSINESS LGST3_95 Limited liability firms BUSINESS LGST4_95 Sole traders BUSINESS LGST5_95 Other legal statuses Changes in Higher technical REGION HTE education1991-2001 Changes in higher vocational REGION HvcE education1991-2001 Changes in university-level REGION UnE EDUCATION education1991-2001 Changes in secondary-level REGION SE education1991-2001 Changes in Compulsory secondary REGION CmplSE Education, 1991-2001 REGION IL Change of Illiteracy, 1991-2001 Change of financial activity, 1991- REGION FINACT 2001 REGION ACTIVE Change of Activity rates, 1991-2001 Change of self-employment per 100 FINANCIAL REGION SelfEMPL inhabitants, 1991 – 2001 ACTIVITY STATUS Change of salaried employment, REGION SalEMPL 1991-2001 Change of self-employment in REGION SelfEMPLMNF manufacturing 1991-2001 EMPLOYMENT REGION UNEMPL Change in unemployment, 1991-2001 INDUSTRIAL TELLINES_9400, Change of telephone lines per100 INFRASTRUCTURE LOCAL _9401 inhabitants, 1994 – 2000 (for services) 78 European Journal of Geography 2 2: 79-89, 2011. © Association of European Geographers STANDARDIZATION OF GEOGRAPHIC DATA: THE EUROPEAN INSPIRE DIRECTIVE Gabor BARTHA University of Miskolc, H3515 Miskolc-Egyetemvaros, Hungary. [email protected] , [email protected] Sandor KOCSIS University of Miskolc, H3515 Miskolc-Egyetemvaros, Hungary. [email protected] , [email protected] Abstract The global geo-observation systems in the last decades have produced tremendous number of spatially dependant data sets claiming connections to a standardized Spatial Data Infrastructure defined as the technologies, policies, and people necessary to promote sharing of geospatial data throughout all levels of government, the private and non-profit sectors, and the academic communities. The legal and technical response of the European Union to this request is the INSPIRE Directive (Infrastructure for Spatial Information in the European Community - 2007/2/EC). The Directive ensures the compatibility with adaptation of common Implementing Rules (IR) in specific areas as Metadata, Data Specifications, Network Services, Data and Service Sharing, Monitoring and Reporting. This paper provides an overview of the Directive, IRs and the technical support of their implementation illustrated with some examples. It concludes with some important issues for European geography to consider and address. Keywords: spatial data infrastructure, INSPIRE, metadata, ISO 1900 standards 1. INTRODUCTION Spatial information data relating to local, regional or global scales are the basis of geography. Due to the recent developments in space technology the emphasis has been shifted to global data which are available for everybody in unbelievable abundance. Only the modern means of information technology and the task sharing could help to handle the large quantity of data. Obviously it generated a need for a unified and standardized Spatial Data Structure (SDI). The aim of SDI was clear (Dutch national stimulation program on SDI, 2010): 1) to share data evaluation and eliminate duplicated efforts in data evaluation; 2) to make geographic data worldwide easily accessible; 3) to support seamless integration of geographic data from different sources. Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 The US Geographic Data Committee was one of the first bodies that has been legally mandated to set up a national Spatial Data Infrastructure (Executive Order 12906, 1994 p.1) which contains the following definitions of SDI: (a) ‘‘National Spatial Data Infrastructure’’ (‘‘NSDI’’) means the technology, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of geospatial data. (b) ‘‘Geospatial data’’ means information that identifies the geographic location and characteristics of natural or constructed features and boundaries on the earth. This information may be derived from, among other things, remote sensing, mapping, and surveying technologies. Statistical data may be included in this definition at the discretion of the collecting agency. (c) The ‘‘National Geospatial Data Clearinghouse’’ means a distributed network of geospatial data producers, managers, and users linked electronically Throughout Europe there have been a number of national and regional initiatives to establish Spatial Data Infrastructures, most of them are driven by public administration or by public-private partnerships (Masser, 2007). Prominent examples include: Nomenclature des unités territoriales statistiques (NUTS) Arrangements on European Map Projections Draft Arrangements on an European Vertical Reference Systems Draft Arrangements on an European Reference Grid IMAGE 2000 and CORINE Landcover 2000 European Soil Atlas EuroBoundaryMap EuroRegionalMap Unfortunately, spatial information in Europe can be described as fragmentations of datasets and sources, with gaps in availability, lack of interoperability or harmonization between datasets at different geographical scales and duplication of information collection. Therefore SDI initiatives in Europe lacked a coherent, Europe wide framework on for instance which standards should be used, how to formulate data sharing policies, and more important which general feature models (i.e. for example attribute names, common spatial reference models, etc.) to follow. The multilingual nature of the European Union increases further this complexity. However, awareness has grown at national and at EU level about the need for quality geo-referenced information to support our understanding of the complexity and interactions between human activities and environmental pressures and impacts. Initiatives to establish a European Spatial Data Infrastructure are therefore timely and relevant but do also face major challenges given the general situation outlined above and the many stakeholder interests to be addressed. Thanks to this awareness, in September 2001 an E-ESDI Expert group, representing geoinformation experts of the European Commission, the European Environmental Agency, and Member States’ environmental and national mapping bodies started the elaboration of a proposal for a European directive to establish an European Spatial Data Infrastructure (ESDI). The adoption of the proposal for a directive on establishing an Infrastructure for Spatial Information in the European Community (INSPIRE) by the European Commission in July 2004 marked the first important step on the way to a European-wide legislative framework to achieve an European Spatial Data Infrastructure. 80 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 The first overview of an organizational and a process model for INSPIRE was elaborated in a preparatory phase (2005-06). Five drafting teams were nominated, each being mandated to draft implementation rules according to the following five components of INSPIRE: . Interoperability of Spatial Data Sets and Services - enlisting 34 data topics that shall be made available in the final infrastructure (see later ISO 19100 series). . Metadata - to allow the discovery and evaluation of INSPIRE relevant data sets and services in Europe (see later provision for Metadata). . Network Services - to make it possible to discover, transform, view and download spatial data and to invoke spatial data and e-commerce services (see later provision for Network Services). . Data Sharing - to allow an ‘as easy as possible’ data exchange between public bodies and to allow third parties, especially citizens to have an as much as possible free and easy access to spatial information covered by INSPIRE (see later provision for data policy). . Coordination and Complementary Measures – to monitor the organizational and management aspects of the INSPIRE implementation. The five components above are illustrated on Fig.1. Fig.1 The five components of INSPIRE In March 2007 the INSPIRE proposal was adopted as Directive 2007/2/EC of the European Parliament and of the Council, the Directive was published in the official Journal on the 25th April 2007. The INSPIRE work programm was updated to address the INSPIRE transposition phase (2007-09). The overall implementation was planned to take more than 10 years, thus by 2019 INSPIRE can be expected to be fully implemented. The shortest implementation time frame is given for the provision of metadata, with first parts to be implemented in 2010, followed by the Network Services being operational (~2011) and then by having a full set of Implementing Rules for INSPIRE Data Specifications (~ up to 2012) and their full implementation (~ up to 2019). The full roadmap of INSPIRE is depicted on Fig.2. 81 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 Fig.2 Roadmap of INSPIRE 2. ISO 19100 SERIES – THE TECHNICAL GROUND The standardization process usually has three levels in EU Member State. The standards are established at international level, then adopted in European level and finally implemented national level. The structure of this process is shown in Fig. 3. Fig.3 The structure of standardization process In the case of INSPIRE the ISO 19100 series was selected as international standard for the technical base. The standards are summarized in Table 1. This series has been elaborated by ISO Technical Committee (TC) 211 as Geographic information/Geomatics standard based on the proposals of Open Geospatial Consortium (OGC) , World Wide Web Consortium (W3C), Object Management Group (OMG), Organization for the Advancement of 82 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 Structured Information Standards (OASIS) (ISO/TC 211 Advisory Group on Outreach, 2009). The standardization has been started at 2001 and still is in process. Table 1. ISO 19100 series of standards from ISO 19100 SERIES OF GEOGRAPHIC INFORMATION STANDARDS p. 9 www.wmo.int/pages/prog/.../5(2)_ISO.doc 6709 - Standard representation of latitude, longitude 19122 - Qualifications and Certification of personnel and altitude for geographic point locations 19101 - Reference model 19123 - Schema for coverage geometry and functions 19101-2 - Reference model - Part 2: Imagery 19124 - Imagery and gridded data components 19125-1 - Simple feature access - Part 1: Common 19103 - Conceptual schema language architecture 19104 - Terminology Introduction 19125-2 - Simple feature access - Part 2: SQL option 19105 - Conformance and testing 19126 - Profile - FACC Data Dictionary 19106 - Profiles 19127 - Geodetic codes and parameters 19107 - Spatial schema 19128 - Web Map server interface 19129 - Imagery, gridded and coverage data 19108 - Temporal schema framework 19130 - Sensor and data models for imagery and 19109 - Rules for applicaiton schema gridded data 19110 - Methodology for feature cataloguing 19131 - Data product specifications 19111 - Spatial referencing by coordinates 19132 - Location based services possible standards 19133 - Location based services tracking and 19112 - Spatial referencing by geographic identifiers navigation 19134 - Multimodal location based services for 19113 - Quality principles routing and navigation 19135 - Procedures for registration of geographical 19114 - Quality evaluation procedures information items 19115 - Metadata 19136 - Geography Markup Language 19115-2 - Metadata - Part 2: Extensions for imagery 19137 - Generally used profiles of the spatial schema and gridded data and of similar important other schemas 19116 - Positioning services 19138 - Data quality measures 19117 - Portrayal 19139 - Metadata - Implementation specification 19140 - Technical amendment to the ISO 191** 19118 - Encoding Geographic information series of standards for harmonization and enhancements 19119 - Services 19120 - Functional standards 19121 – Imagery and gridded data The standards specify the IT and the geographic aspects of Spatial Data Infrastructure and fall into five categories: . Standards that specify the infrastructure for geospatial standardization. . Standards that describe data models for geographic information. . Standards for geographic information management. . Standards for geographic information services. 83 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 . Standards for encoding of geographic information. . Standard for specific thematics. The ISO 19100 series of standards was adopted as the technical base for INSPIRE by the European standardization organization Comité Européen Normalisation - CEN TC/211. Their implementation included 34 themes. The themes are subdivided into three groups and included into the INSPIRE directive in three appendices. Member States should make the metadata available for the themes in Appendices I and II in 2010, and for the themes in Appendix III in 2013: Appendix I 1. Reference systems using coordinates 2. Geographical grid system 3. Geographical names 4. Administrative units 5. Addresses 6. Land Registry plots 7. Transport networks 8. Hydrography 9. Protected areas Appendix II 1. Height 2. Soil use 3. Ortho-image production 4. Geology Appendix III 1. Statistical units 2. Buildings 3. Soil 4. Land use 5. Human health and safety 6. Utilities and public sector services 7. Environmental protection services 8. Facilities for manufacture and industry 9. Facilities agriculture and aquaculture 10. Population distribution — demography 11. Area management, areas where limitations apply, regulated areas and reporting units 12. Areas with risks to the natural environment 13. Atmospheric conditions 14. Meteorological and geographic characteristics 15. Oceanographic, geographic characteristics 16. Maritime regions 17. Bio-geographic areas 18. Habitats and biotopes 19. Distribution of species 20. Energy sources 21. Mineral sources 84 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 2. PROVISION FOR METADATA - THE FIRST STEP OF IMPLEMENTATION Spatial information in Europe has no harmonization between datasets at different geographical scales and there are several duplications in the information collections as it has been pointed out before. What is worse, there is no clear picture on the obstacles. Therefore the first step is to establish standardized metadata system i.e. to make data about data. Metadata describe geographic datasets that search commands can focus on questions such as ‘who, what, where, when, why and how’. Metadata contains details about the owner of the geographic data, quality, validity, etc., and how it can be traced and used. The ISO 19115 International Standards, summarized in Table 2., defines metadata elements, provides a schema and establishes a common set of metadata terminology, definitions, and extension procedures. This International Standard defines the schema required for describing geographic information and services. It provides information about the identification, the extent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic data. This International Standard is accomplished with two other ones, namely ISO 19118 and ISO/TS 19139 concerning metadata encoding. ISO 19118 describes the requirements for creating encoding rules based on Unified Modeling Language (UML) schemas while ISO/Technical Specification 19139 defines Extensible Markup Language (XML) as selected encoding language for geographic metadata. INSPIRE adopted these standards and recognizing the importance of metadata put forward their implementation plan (c.f. Roadmap of INSPIRE on Fig.2). The European Commission established a web site INSPIRE-Geoportal (www.inspire-geoportal.eu) to promote this process The opening page of this portal is shown on Fig.4. The site has four functional modules to help editing, finding and using European metadata. . Metadata Editor module is an online editor for creating metadata xml files; . Metadata Validator module validates ready metadata files; . Discovery module to locate metadata files via a graphic interface; . Viewer module to display/edit maps from digital data pointed out by metadata. The use or implement of the functional modules is rather simple and straightforward. Detailed descriptions can be found in Technical Guides (Grasso,Craglia, 2010),(NSDT,2009), (IOCTFNS,2011). They can be downloaded from the portal. Fig.4 European Geoportal web site: opening page from: http://www.inspire-geoportal.eu 85 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 Besides the INSPIRE-Geoportal, the community of geologists are also preparing an Internet based metadata searcher, editor service called MICKA (one.geology.cz/metadata) tailored for geology in the framework of an international project, OneGeology Europe. Dataset title (M) Spatial representation type (O) (MD_Metadata > MD_DataIdentification.citation > (MD_Metadata > CI_Citation.title) MD_DataIdentification.spatialRepresentationType) Dataset reference date (M) Reference system (O) (MD_Metadata > MD_DataIdentification.citation > (MD_Metadata > MD_ReferenceSystem) CI_Citation.date) Dataset responsible party (O) Lineage (O) (MD_Metadata > MD_DataIdentification.pointOfContact (MD_Metadata > DQ_DataQuality.lineage > > CI_ResponsibleParty) LI_Lineage) Geographic location of the dataset (by four coordinates On-line resource (O) or by geographic identifier) (C) (MD_Metadata > MD_Distribution > (MD_Metadata > MD_DataIdentification.extent > MD_DigitalTransferOption.onLine > EX_Extent > EX_GeographicExtent > CI_OnlineResource) EX_GeographicBoundingBox or EX_GeographicDescription ) Dataset language (M) Metadata file identifier (O) (MD_Metadata > MD_DataIdentification.language) (MD_Metadata.fileIdentifier) Dataset character set (C) Metadata standard name (O) (MD_Metadata > MD_DataIdentification.characterSet) (MD_Metadata.metadataStandardName) Dataset topic category (M) Metadata standard version (O) (MD_Metadata > MD_DataIdentification.topicCategory) (MD_Metadata.metadataStandardVersion) Spatial resolution of the dataset (O) Metadata language (C) (MD_Metadata > (MD_Metadata.language) MD_DataIdentification.spatialResolution > MD_Resolution.equivalentScale or MD_Resolution.distance) Abstract describing the dataset (M) Metadata character set (C) (MD_Metadata > MD_DataIdentification.abstract) (MD_Metadata.characterSet) Distribution format (O) Metadata point of contact (M) (MD_Metadata > MD_Distribution > MD_Format.name (MD_Metadata.contact > CI_ResponsibleParty) and MD_Format.version) Additional extent information for the dataset (vertical Metadata date stamp (M) and temporal) (O) (MD_Metadata.dateStamp) (MD_Metadata > MD_DataIdentification.extent > EX_Extent > EX_TemporalExtent or EX_VerticalExtent) Table 2. Core metadata for geographic datasets from: ISO/DIS 19115 https://www.seegrid.csiro.au/.../GeologicMetadata/19115_DIS200108 “M” indicates that the element is mandatory. “O” indicates that the element is optional. “C” indicates that the element is mandatory under certain conditions 3. NETWORK SERVICES: LINKING TOGETHER The INSPIRE Directive aims to build upon infrastructures for spatial information established and operated by the Member States. As a result, Member States shall establish and operate a network of the following services for the spatial data sets and services for which metadata has been created in accordance with this Directive: 86 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 . Discovery services making it possible to search for spatial data sets and services on the basis of the content of the corresponding metadata and to display the content of the metadata; . Viewing services making it possible, as a minimum, to display, navigate, zoom in/out, pan, or overlay viewable spatial data sets and to display legend information and any relevant content of metadata; . Downloading services, enabling copies of spatial data sets, or parts of such sets, to be downloaded and, where practicable, accessed directly; . Transformation services, enabling spatial data sets to be transformed with a view to achieving interoperability; . Invoking services enable a user or client application to run them without requiring the availability of a GIS services allowing spatial data services to be invoked; . Registry is in fact not a standard service, but obviously all INSPIRE based services should provide a kind of registry for the stored data. Those services shall take into account relevant user requirements and shall be easy to use, available to the public and accessible via the Internet or any other appropriate means of telecommunication. The INSPIRE network services are depicted in Fig.5. Fig.5 INSPIRE network services from NSDT: INSPIRE Infrastructure for Spatial Information in Europe http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/network/D3_5_INSPIRE_NS_Architecture_ v3-0.pdf INSPIRE networks are web based services therefore they use HTTP (HyperText Transfer Protocol). The data is structured according to the rules of UML (Unified Modeling Language). UML is a graphical planning frame to establish the structure of problem solving, or datasets, respectively. The data are described in XML (eXtensibel Markup Language). XML an object oriented, generalized markup language. The well known HTML (Hypertext Markup Languge) is a specialized form of XML. The objects are predefined in HTML, while in XML the developer is free to define any object. Therefore it is very convenient to describe datasets in a standardized form. The XML datasets are accessed in SOAP (Simple Object Access Protocol) frame. SOAP defines a simple and extensible XML messaging framework that can be used over multiple protocols with a variety of different programming models 87 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 (Villa at al, 2008). The defined framework is a higher-level application protocol that offer increased interoperability in distributed, heterogeneous environments. The characteristic features of the INSPIRE network services and data management are summarized in Table 3. and Table 4., respectively. Table 3. INSPIRE Network Services Service Description Discovery locating metadata files via graphic interface View displaying and edit maps Download supporting to download a part or complete datasets Transformation not completely clear yet, the goal is to support schema and coordinate transformation to enable a user or client application to run them without requiring the availability of a Invoke GIS Registry registry for data files is not a standardized but necessary part of service Table 4. INSPIRE Data Management Data Associated Language/Frame Structuring UML (Unified Modeling Language) – graphic data structuring language XML (eXtensible Markup Language) – generalized object definition language for data Description description on Web SOAP (Simple Object Access Protocol) - messaging framework used over multiple Access protocols to access XML schemes 4. CONCLUDING REMARKS There are both positive and negative conclusions to the INSPIRE Directive initiative and its implementation. Positively, the INSPIRE Directive is an important and necessary initiative to establish a unified standard for Spatial Data Infrastructure in Europe. The recognition of the importance of unified metadata for the fragmented European spatial data sets and to put forward in the implementation has been a crucial step to start INSPIRE. The central services (discovery, view, download, translation, invoke) and metadata editor and validator provide strong support to establish and use the metadata background for the European SDI. Several EU projects, publications help to implement and popularize INSPIRE. However from a negative perspective there remain big differences in the legal, technical and administrative treatment of spatial data among EU countries that will probably delay the implementation beyond expectations. As concerning to geographers: they should elaborate their own metadata classes and metadata editors similar to the above mentioned MICKA for geologists. According to their experiences this work needs an international team working in a frame of a European project. The concept of INSPIRE Directive should be included in the geographical education probably in context with GIS. The connected teaching materials also should be elaborated parallel to the development of metadata editor. 88 Bartha G.-Kocsis S./ European Journal of Geography 2 2 79-89 Acknowledgements The described work was carried out as part of the TÁMOP 4.2.1.B 10/2/KONV 2010 0001 project in the framework of the New Hungarian Development Plan. The realization of this project is supported by the European Union, co-financed by the European Social Fund. REFERENCES Directive INSPIRE, 2007. Official Journal of the European Union L 108/1. Dutch national stimulation program on SDI, 2010. http://geostandards.geonovum.nl/index.php/Main_Page Executive Order 12906, 1994. 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SOAP Primer for INSPIRE Discovery and View Services EUR 23704 EN. Luxembourg: OPOCE;. JRC49175 2.2 JRC Scientific and Technical Reports. Masser,I. 2007. Building European Spatial Data Infrastructures Readland,Calif.:ESRI Press. NSDT, 2008. INSPIRE Infrastructure for Spatial Information in Europe. http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/network/D3_5_INSPIRE_NS_ Architecture_v3-0.pdf NSDT, 2009. Technical Guidance to implement INSPIRE View services. inspire.jrc.ec.europa.eu/...Services/TechnicalGuidance_ViewServices_v3.0.pdf 89 © EUROGEO, 2011 ISSN 1792-1341 The European Journal of Geography is published by EUROGEO - the European Association of Geographers (www.eurogeography.eu).