Abstract
Abstract. The 2005 Kashmir earthquake has triggered thousands of landslides which devastated most of the livelihood and other infrastructure in the area. Landslide inventory and subsequently landslide susceptibility mapping is one of the main prerequisite for taking mitigation measure against landslide effects. This study has focused on developing most updated and realistic landslide inventory and Susceptibility mapping. The high resolution data of Worldveiw-2 having spatial resolution of 0.4 m is used for landslide inventory. Support Vector Machine (SVM) classifier was used for landslide inventory developing. Total 51460 number of landslides were classified using semi-automatic technique with covering area of 265 Km2, smallest landslide mapped is covering area of 2.01 m2 and the maximum covered area of single landslide is 3.01 Km2. Nine influential causative factors are used for landslide susceptibility mapping. Those causative factors include slope, aspect, profile curvature, elevation, distance from fault lines, distance from streams and geology. Logistic regression model was used for the Landslides susceptibility modelling. From model the highest coefficient was assigned to geology which shows that the geology has higher influence in the area. For landslide susceptibility mapping the 70 % of the data was used and 30% is used for the validation of the model. The prediction accuracy of the model in this study is 92 % using validation data. This landslide susceptibility map can be used for land use planning and also for the mitigation measure during any disaster.
Highlights
Landsliding is one of the most frequent and destructive natural hazards in the mountainous regions
Landslide susceptibility mapping is the distribution of the area into different zones on the basis of the probability of the occurrence of the landslide according to the factors which are taken during the modelling
To develop landslide susceptibility map different influential factors are used by different researchers with landslide inventory and those factors varying on geographical region
Summary
Landsliding is one of the most frequent and destructive natural hazards in the mountainous regions. For developing landslide inventory different techniques are applied by different researchers like manual digitization, Pixel based classification of landslides and the Object based image classification techniques (Martha et al 2010; Lodhi 2011; Basharat et al 2016). Different spatial resolution data has been used for this study area for developing landside susceptibility map like ASTER has been used by (Kamp et al 2010) Landsat is used by (Lodhi 2011). Landslide susceptibility mapping is the distribution of the area into different zones on the basis of the probability of the occurrence of the landslide according to the factors which are taken during the modelling. To develop landslide susceptibility map different influential factors are used by different researchers with landslide inventory and those factors varying on geographical region.
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