Landslide Susceptibility and Risk Mapping in the Tectonic Ensemble Comprising of Eastern Himalayan Zone, Northeast India and Bhutan using Logistic Regression and Random Forest Techniques

Abstract

Abstract The mountainous terrain of the East-Northeast tectonic ensemble covers an approximate area of 3,11,420 km2 comprising the Eastern Himalayan zone, Northeast India and Bhutan is prone to mass movements. The increasing trend of landslide occurrences in the last few decades sets loud alarm bells for mapping the landslide hotspot zones in terms of Landslide Susceptibility and Risk. Initially, a landslide inventory of around 9751 landslides has been prepared, of which 6826 (70%) has been randomly picked as training dataset and the remaining 2925 (30%) as the testing dataset. Thereafter, Random Forest (RF) and binary Logistic Regression (LR) based Landslide Susceptibility Zonation (LSZ) have been prepared through twelve predictor layers viz. Slope Angle, Slope Aspect, Slope Curvature, Distance to Drainage, Distance to Lineament, Landform, Surface Geology, Distance to Road, Normalized Difference Vegetation Index (NDVI), Landuse/ Landcover (LULC), Rainfall and Epicentre Proximity. Both the Landslide Susceptibility Index (LSI) maps are divided into five classes, viz. ‘low’, ‘moderate’, ‘high’, ‘very high’ and ’severe’, which are then validated statistically by drawing a comparison with the 30% testing chronological landslide inventory database. The statistical index based accuracy assessment in terms of Area Under the Curve (AUC) exhibits an LR model AUC of 0.776 and RF model AUC of 0.820. However, it has been observed that the RF model strongly correlates with the testing inventory dataset exhibiting that around 46% of the landslide-prone terrain is classified in the ‘high to severe’ zones with 41% inventory landslides occurring in these zones. Integrating the Random Forest (RF) based LSI thematic layer with the socio-economic vulnerability layers like the Number of Households and Population Density have demarcated around 20.78% of the region under ‘very high to severe’ socio-economic risk as convoluted by landslide susceptibility in the terrain. The present findings are expected to be useful in urban development and town planning with appropriate slope management and land-use planning.