Platforms and Image Processing Techniques for Descriminating Mass Movements in Lebanon

Chadi Abdallah(1), Rania Bou Kheir(1), Jean-Paul Deroin(2) and Damien Dhont(3)

(1) National Council for Scientific Research, Blvrd. Sport City, Bir Hassan, 11-8281 Beirut, Lebanon
(2) Université Paris-Est, boulevard Descartes, 77454 Marne la Vallée cedex Fr, France
(3) Université de Pau et des pays d’Adour, CNRS-FRE 2639: Imagerie Géophysique/CURS-IPRA, Avenue of the University, 64013 Pau cedex France, France


Mass movements (MM) represent a serious threat to human life and activities in most mountainous areas. However, due to the rugged nature of such terrain, it is often difficult to detect such phenomena in remote areas. Hence, satellite imagery offers many attractions for the examination of MM in such environments, especially in less developed nations in which resources are stretched and levels of environmental information limited. There is a need to ensure that the techniques and images used are effective, reliable, and cheap in terms of the amount and accuracy of data that can be extracted. Nevertheless, satellite images have been used worldwide to visually identify large landslides without differentiating other types of MM. Moreover, the reliability in detecting mass movements can differ to a wide extent according to the processing technique used and the sensor chosen in addition to the overall mapping errors of visual image interpretation may vary between 60 and 90% when different surveyors are making the interpretation and judgment, even of the same area. Taking Lebanon as a case study, this paper compares the applicability of different satellite data sensors (Landsat (Thematic Mapper), IRS, SPOT(4), ALOS (AVNIR-2)) and preferred image-processing techniques (False Colour Composite ‘FCC’, pan-sharpen, principal-component analysis ‘PCA’, Anaglyph) for the mapping of MM recognized as landslides, rock and debris falls, and earth flows. Results from the imagery have been validated by field surveys and analysis of IKONOS imagery 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 3D properties for visual interpretation and showing a maximum accuracy level of 61%. The PCA ALOS and the pansharpened Landsat TM-IRS image gave better results in detecting MM, among other processing techniques, with a maximum accuracy level of 57%.



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