Spatial probabilistic approach on landslide susceptibility assessment from high resolution sensors derived parameters

8th International Symposium of the Digital Earth

地球科学;计算机科学

Aman, S.N.A.^1 ; Latif, Z Abd^1 ; Pradhan, B.^2

Centre of Studies Surveying Science and Geomatics, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA, Shah Alam, Malaysia^1

Department of Civil Engineering, Faculty of Engineering, UPM 43400, Serdang, Malaysia^2

关键词: Airborne remote sensing;    Environmental factors;    Frequency ratio models;    High resolution sensors;    Landslide susceptibility;    Landslide susceptibility assessments;    Probabilistic approaches;    Topographic wetness index;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/18/1/012057/pdf
DOI  :  10.1088/1755-1315/18/1/012057

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Landslide occurrence depends on various interrelating factors which consequently initiate to massive mass of soil and rock debris that move downhill due to the gravity action. LiDAR has come with a progressive approach in mitigating landslide by permitting the formation of more accurate DEM compared to other active space borne and airborne remote sensing techniques. The objective of this research is to assess the susceptibility of landslide in Ulu Klang area by investigating the correlation between past landslide events with geo environmental factors. A high resolution LiDAR DEM was constructed to produce topographic attributes such as slope, curvature and aspect. These data were utilized to derive second deliverables of landslide parameters such as topographic wetness index (TWI), surface area ratio (SAR) and stream power index (SPI) as well as NDVI generated from IKONOS imagery. Subsequently, a probabilistic based frequency ratio model was applied to establish the spatial relationship between the landslide locations and each landslide related factor. Factor ratings were summed up to obtain Landslide Susceptibility Index (LSI) to construct the landslide susceptibility map.