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Application of Remote Sensing and Geographical Information System for the Study of Mass Movements in Lebanon Chadi Abdallah

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Application of Remote Sensing and Geographical Information System for the Study of Mass Movements in Lebanon Chadi Abdallah Application of remote sensing and geographical information system for the study of mass movements in Lebanon Chadi Abdallah To cite this version: Chadi Abdallah. Application of remote sensing and geographical information system for the study of mass movements in Lebanon. Tectonics. Université Pierre et Marie Curie - Paris VI, 2007. English. NNT : 2007PA066085. tel-00800759 HAL Id: tel-00800759 https://tel.archives-ouvertes.fr/tel-00800759 Submitted on 15 Mar 2013 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ACADÉMIE DE PARIS UNIVERSITÉ PIERRE ET MARIE CURIE PARIS 6 Mémoire des Sciences de la Terre Présenté par M Chadi ABDALLAH Pour obtenir le grade de DOCTEUR DE L’UNIVERSITÉ PARIS 6 Sujet de la thèse : Application de la télédétection et des systèmes d’informations géographiques à l’étude des mouvements de terrain au Liban UFR Des Sciences de la Terre 4, place jussieu – 75252 Paris cedex 05 THESE DE DOCTORAT DE L’UNIVERSITÉ PARIS 6 Spécialité Géosciences et Ressources Naturelles Présenté par M Chadi ABDALLAH Pour obtenir le grade de DOCTEUR DE L’UNIVERSITÉ PARIS 6 Sujet de la thèse : Application de la télédétection et des systèmes d’informations géographiques à l’étude des mouvements de terrain au Liban 11 Juillet 2007 Devant le jury de : (préciser la qualité de chacun des membres) M Jean CHOROWICZ Directeur de thèse Mme Christine KING Rapporteur M Jean Paul DEROIN Rapporteur M Alain TABBAG Examinateur M Mohamad KHAWLIE Co directeur de thèse M Damien DHONT Co directeur de thèse ACKNOWLEGMENTS My sincere thanks to the Authorities of the Lebanese National Council for Scientific Research (LCNRS), who have supported my scholarship. Thanks extend to the Secretary General of the LCNRS Dr. Mouin Hamzé for his aid and support. Special thanks to Prof. Jean Chorowicz who gave me the honor to be his student, supported, supervised and guided this work. To the man who could not pass a day without learning something new from him, deep thanks to Dr. Mohamad Khawlie for his continuous encouragement, support and valuable guidance through my dissertation and all other work. Deep thanks also to my friend and colleague Dr. Rania Boukheir for her enormous help and participation in this work. Thanks also for Dr. Damien Dhont for his help and being a co-advisor of this thesis. Many thanks to Dr. Christine King and Dr. Jean Paul Deroin for accepting reviewing this work. Special thanks for Mr. Souhail Kanaan from the LCNRS for his support and encouragement. Also Thanks extend to Dr. Francisco Gomez (Paco) for hosting me during my visit to The United States and making his Lab at Missouri University and the GPS equipment available and at my disposal. Thanks also to Rani Jaafar and Samer El Hashem for their help in the GPS campaigns. Also special thanks to Dr. Gebran Karam for giving the access to the GPS equipment. Finally, I would like to thank all my colleagues at the Remote Sensing Center for their aid and for being supportive. Dedication To my Family; Mom, Tarek & Ali, with deep & sincere love Abstract Among the various natural hazards, mass movements (MM) are probably the most damaging to the natural and human environment in the Mediterranean countries, including Lebanon which represents a good case study of mountainous landscape. Although affecting vast areas in the country, the phenomenon was not studied at regional scale, and related maps are still lacking. Therefore, this research deals with the use of remote sensing and geographic information system (GIS) techniques in studying MM in Lebanon. In this context, the first part reviews existing knowledge on the topics of mass movements (MM) specifically in the Mediterranean region, and defines research gaps. It exposes the diverse types of MM, their magnitudes, the causative agents and their bad consequences. It clarifies confusions related to MM-terms (hazard, susceptibility, risk, etc.), and compares the efficiencies of the most used methods for MM susceptibility/hazard zonation. It includes also a statement on remote sensing and GIS benefits and constraints in mass movement studies, pointing out possible ways of research. The second part is dedicated to the detailed description of the study area “the Mediteranean slopes of central to north Lebanon” within Lebanon. Physical/morphodynamic and socio- economic characteristics of the area are exposed, as well as the natural hazards, MM events, their socio-economic impacts and mitigation measures. All previous studies about MM hazard in Lebanon are reviewed. The studied area, extending from the Mediterranean coast to around 3000 m elevation, covers ~36% of the total area of Lebanon. It represents the geoenvironmental diversity of this country in terms of geology, soil, hydrography, land cover and climate. It is characterized by problematic human activities (e.g., chaotic urban expansion, artificial recharge of groundwater, overgrazing, forest fire) enhancing environmental decline and inducing MM, with minimal government control. The third part compares the applicability of different satellite sensors (Landsat TM, IRS, SPOT4) and preferred image processing techniques (False Color Composite “FCC”, Pan- sharpen, Principal component analysis “PCA”, Anaglyph) for the mapping of MM recognized as landslides, rock/debris falls and earth flows. Results from the imagery have been validated by field surveys and analysis of IKONOS imagery (1 m) acquired in some locations witnessing major MM during long periods. Then, levels of accuracies of detected MM from satellite imageries were plotted. This study has demonstrated that the anaglyph produced from the two panchromatic stereo-pairs SPOT4 images remains the most effective tool setting the needed 3-D properties for visual interpretation and showing maximum accuracy of 69%. The PCA pan-sharpen Landsat TM-IRS image gave better results in detecting MM, among other processing techniques, with maximum accuracy level of 62%. The errors in interpretation fluctuate not only according to the processing technique, but also due to the difference in MM type. They are minimal once 3D anaglyph SPOT4 is considered, varying between 31% (landslides), 36% (rock and debris falls) and reaching 46% in the case of earth and debris flows. The fourth part explores relationships between MM occurrence and different factor terrain parameters. Parameters expressed by: 1- preconditioning factors, like: elevation, slope gradient, slope aspect, slope curvature, lithology, proximity to fault line, karst type, distance to quarries, soil type, distance to drainage line, distance to water sources, land cover/use, and proximity to roads, and 2- triggering MM factors, like: rainfall quantity, seismic events, i floods and forest fires, were correlated with MM using GIS-approaches. This study indicates, depending on bivariate remote sensing and GIS statistical correlations (Kendall Tau-b correlation), that lithology is the most influencing on MM occurrence, having the highest correlation with other parameters (i.e. 7 times correlated at 1% level of significance and 3 times at 5%). It also shows that statistical correlations to mass movements exist best between parameters at the following decreasing order of importance: soil type/distance to water sources (acting similarly on MM occurrence), karst/distance to quarries/land cover-use, proximity to faults, slope gradient/proximity to roads/floods, seismic events, elevation/slope aspect/forest fires. These correlations were verified and checked through field observations and explained using univariate statistical correlations. Therefore, they could be extrapolated to other Mediterranean countries having similar geoenvironmental conditions. The fifth part proposes a mathematical decision making method – Valuing Analytical Bi- Univariate (VABU) that considers two-level weights for mapping MM susceptibility/hazard (1:50,000 cartographic scale) within the study area. The reliability of this method is examined through field surveys and depending on a GIS comparison with other statistical methods – Valuing accumulation Area (VAA) (depending on one weight level) and Information Value (InfoVal) (requiring detailed measurements of MM areas). Three susceptibility maps were derived using preconditioning parameters, while hazard maps were produced from triggering ones. The coincidence values of overlapping susceptibility maps were found to be equal to 47.5% (VABU/VAA), 54% (VABU/InfoVal) and 38% (VAA/InfoVal). The agreement between hazard maps showed closer values than susceptibility ones, oscillating between 36.5% (VAA/InfoVal), 39% (VABU/VAA), and 44 % (VABU/InfoVal). Field verification indicates that the total precision of the produced susceptibility maps ranges from 52.5% (VAA method), 67.5% (InfoVal method) and 77.5% (VABU method). This demonstrates the efficiency of our method, which consequently can be adopted for predictive mapping of MM susceptibility/hazard in other areas in Lebanon and may be easily extrapolated using the functional capacities of GIS. The sixth part predicts the geographic distribution and
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