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ABSTRACT Title of Document: IDENTIFYING LANDSLIDE ABSTRACT Title of IDENTIFYING LANDSLIDE HAZARDS IN A TROPICAL Document: MOUNTAIN ENVIRONMENT, USING GEOMORPHOLOGIC AND PROBABILISTIC APPROACHES José Gregorio Roa-Lobo PhD, 2007 Directed By: Prof. Michael Kearney, Department of Geography The objective of this study is the performance, assessing, comparison and validation of a set of three landslide hazard maps: The geomorphological, the multicriteria evaluation (MCE) and the probabilistic (weights of evidence); in order to evaluate its accuracy, advantages and limitations, and finally state its reliability. These approaches were tested in a tropical mountain environment located in the central Venezuelan Andes, particularly in the Río Chama basin (2820.63 Km²), where the complexity and variety of the landscape provides a special geographical framework to address the landsliding process as natural hazard. The scale of this study is regional. For doing this a GIS data base was built up to collect and manipulate the landslide inventory map and the cartography of the main landslide passive factors found in this study area. The landslide inventory map was generated through the manual interpretation of 300 aerial photographs and by the processing of two sets of Landsat imagery via contrast-widening color composite, given as result the outline of 493 landslide polygons. The landslide passive factors represent the physical features of the study area associated to landslide occurrences, as those found in the topographical, geological and physiographical settings. In that sense, given the main role played for a digital elevation model (DEM) as data input, a DEM for the study area was built through remotely sensed data obtained from the shuttle radar topographical mission (SRTM) and optical stereographic imagery provided by the advanced spaceborne thermal emission and reflection radiometer (ASTER) system. Because of the comparative nature of this study, these data was preliminary processed via density analysis in order to establish a common background on the landsliding process – passive factors relationship, which was used later to set up the criteria applied in the geomorphological and multicriteria evaluation (MCE) approaches. All the three landslide hazard mapping approaches were fully benefited from the use of GIS, improving the processing and manipulation of the spatial information, even in procedures considered subjective as the geomorphological mapping, as well as in the use of non-areal statistics measures for the weights of evidence procedure where the Kappa index proved to be a useful index to assess the level of independence between factor maps. As a way of validation, the accuracy and error rate of the three landslide hazard maps were performed by its comparison to the landslide inventory map. Hence through the use of contingency tables and the success rate curve, was concluded that although the geomorphological approach achieved a better landslide predictive power for this study area at a regional scale, the remaining procedures can play a complementary role, for example the MCE plays a crucial role in an early assessment of landslide hazard which highlights the needs and improving necessary to achieve a better probabilistic approach, which can be later incorporated in a more objective geomorphological assessment. Results also showed that any methodology can be improved and even empowered by the development of better and more integrated standards for geographical data collection rather that the simplification of them, in that sense, satellite data improves the spatial and temporal consistence of data used for landslide hazard purposes, potentially allowing the integration of useful geographical data as those Holdridge life’s zones and geomorphometric generated and used in this study. Hence, further studies at regional scale must explore the remotely sensed imagery capacities for generation of data bases addressing regional susceptibility to landsliding process. IDENTIFYING LANDSLIDE HAZARDS IN A TROPICAL MOUNTAIN ENVIRONMENT, USING GEOMORPHOLOGIC AND PROBABILISTIC APPROACHES By José Gregorio Roa Lobo Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2007 Advisory Committee: Professor Michael Kearney, Chair Professor John Townshend Professor Samuel Goward Karen Prestegaard Luigi Boschetti © Copyright by José Gregorio Roa Lobo 2007 Acknowledgements To Prof. Michael Kearney and his invaluable help. To the University of Maryland, College Park. To the University of Los Andes, Venezuela. To the Watson International Scholars of the Environment, Brown University. To the International Institute for Geo-Information Science (ITC), The Netherlands. To Prof. J. Townshend and the GLCF staff. To Dr. Eric Vermote. To Dr. Ulrich Kamp. To my friends and informal supervisors: Matthew Smith, Julia Skory, Shannon Franks, Jan and Daniela Dempewolf, Svetlana Kotchenova, Diane Davies, Sunghee Kim, Jessica McCarty, Minnie Wong, Enrique Castellanos, Alexander Walzenbach. ii Table of Contents Acknowledgements Table of Contents………………………………………………………………….. iii List of Tables…………………….………………………………………….……… v List of Figures…………………….……………………………………….………... vi Chapter 1:INTRODUCTION…...…………………………………………..………. 1 Overview………………………………………………………………………… 1 Justification……………………………………………………………………… 2 Research Objectives……………………………………………………………... 4 Outline of the thesis structure…………………………………………………… 5 Chapter 2: THE STUDY AREA...…………………………………………………. 7 Geological aspects………………………………………………………………. 8 Lithological units………………………………………………………………... 9 Fault patterns…………………………………………………………..…….….. 9 Geomorphological aspects………………………………………………………. 10 Climatic aspects…………………………………………….…………..………. 12 Landuse aspects………………………………………………………..………. 14 Typical expressions of landsliding processes in the area…….………………… 16 Chapter 3: METHODOLOGY……………………………………………………... 19 Conceptual background definitions……………………………………………... 19 Review of existing techniques to perform a landslide hazard zonation………… 20 General methodological procedure…………………..…………………….…… 22 The hazard modeling…………………………………..………………..….….. 25 Validation and comparison……………………………………………..….…… 25 Chapter 4: GENERATION OF THE DIGITAL ELEVATION MODEL (DEM) FROM SPACE BORNE SYSTEMS……...…............................. 26 Building the study area DEM from SRTM data and ASTER imagery………….. 26 Chapter 5: LANDSLIDE DISTRIBUTION ANALYSIS. BASIC DESCRIPTIVE STATISTICS………………………………..... 30 The landslide inventory map……………………………….….……………..…. 30 The contrast-widening color composite………………………….…………..…. 31 Landslide geographical occurrence…………………………….…………..…… 33 Landsliding processes and factor/classes. Descriptive statistical .....................… 37 Landslide area - altitudinal ranges relationship…………………………………. 38 Landslide area - slope angle / slope shape / slope aspect relationship…….……. 39 Landslide area - lithology / lithology – slope relationship………….…….…..… 41 Landslide area – drainage buffer / lineaments relationship……………….…..... 43 Landslide area – internal relief relationship……………………….………..…... 45 Landslide area – Geomorphometric classes relationship…………….……..…... 46 Landslide area – Holdridge's life zone system relationship……….…………..... 47 Landslide area – Geomorphological units relationship…………………………. 49 Landslide – Factor maps analysis by area density……………………….…….... 50 iii Chapter 6: THE GEOMORPHOLOGICAL, MULTICRITERIA EVALUATION (MCE), AND THE PROBABILISTIC APPROACHES……………….... 54 The Geomorphological approach. Hierarchical structure and factors................... 54 The Terrain Mapping Complexes………………………………………….………….. 55 The Geomorphological units. Factors………………………………………...………. 56 The Terrain Mapping Units (TMU)………………………………………………….... 57 DEM and geomorphometry. An empirical procedure for Geomorphometric classification……………………………………………………..…………………..... 59 The Terrain Mapping Subunits………………………………………………………... 61 Classification of the Terrain Mapping Subunits into a landslide hazard zonation map…………………………………………………………...... 64 The MCE paradigm. Justification of the MCE for this study…………...………. 66 Integrating MCE into GIS…………………………………………………………...... 66 The Analytical Hierarchy Process (AHP)…….…………………………………...…... 67 Definition of the processes involved in the landsliding process………………...……. 68 Normalizing factor maps to criteria maps………………………………………...…... 69 Compensating weights via Pairwise procedure……………………………………….. 70 Computing the Analytical Hierarchy matrices for the criteria maps………………….. 71 Data output integration and final classification and hazard maps……………………...74 Probabilistic landslide hazard zonation through the Weights of Evidence model………………………………………………………………….…………. 77 Data entry. Test of conditional independence………………………………...………. 78 Computing the weights of evidence. Selection of scenarios……………...…………... 85 Data integration, classification and interpretation……………………….……...…….. 91 Chapter 7: SUMMARY OF THE THREE LANDSLIDE METHODOLOGIES AND CONCLUSIONS……………………………………………...………… 96 Evaluation of the accuracy and error rate……………………………………….. 99 Accuracy and error rate within landslide hazard maps……..…………..……….. 100 Accuracy and error rate within factor maps………………….……...…………... 102 Validation………………………………………………………………………... 104 Success rate curve…………………………………………….………………….. 105 Correlation………………………………………………………………………. 106 Conclusions……………………………………………….………..…………… 109 Summary….……………………………………………….………..…………… 112 Appendices…………………………………………………………………………
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