India ranks first in the world in terms of fatal landslides. Large vulnerable area (0.42 million km²), high population density and monsoon rainfall make India’s landslide management and mitigation task difficult. Therefore, an understanding of landslide occurrences and exposure of socio-economic parameters on a national scale is essential to prioritise landslide mitigation efforts. In this paper, a database of 45,334 landslides (polygons) in India mapped by the National Remote Sensing Centre (NRSC) during the 1998–2018 period was compiled and catalogued in a WebGIS platform. High-resolution satellite data such as IRS PAN+LISS-III, Resourcesat LISS-IV Mx, Cartosat, WorldView, Pleiades and GeoEye were used to map landslides as small as 12 m² to as big as 1,390,350 m². GIS analysis using the landslide inventory revealed interesting results about control, exposure and pattern of landslide occurrences in India. The Northwest Himalayas contribute 66.5% of landslides in India, followed by the Northeast Himalayas (18.8%) and the Western Ghats (14.7%). The Greater Himalayan sequence consisting of high-grade metamorphic rocks has a considerable control (32%), and the Main Central Thrust is the major regional structure controlling (12%) landslides in India. In the Northeast Himalayas, the size of landslides and the slope gradient controlling landslide occurrence are less in comparison to the Northwest Himalayas and the Western Ghats. Landslides in the Western Ghats are triggered with a lesser amount of rainfall than the Himalayan regions. Exposure analysis using four key socio-economic parameters in the 145 hilly districts shows that Rudraprayag district is most affected by landslides in India. The understanding derived using the landslide database on a national scale will help to prioritise and strengthen landslide disaster risk reduction strategies in India.

就致命的山体滑坡而言，印度排名世界第一。大型脆弱的地区，（0420000公里²），人口密度高和季风降水使印度的滑坡管理与减灾任务艰巨。因此，在全国范围内了解滑坡的发生和社会经济参数的暴露对于优先考虑减轻滑坡的工作至关重要。在本文中，由国家遥感中心（NRSC）在1998-2018年期间绘制的印度45,334个滑坡（多边形）数据库已编译并编入WebGIS平台。IRS PAN + LISS-III，Resourceat LISS-IV Mx，Cartosat，WorldView，Pleiades和GeoEye等高分辨率卫星数据用于绘制从12 m ²到最大1,390,350 m ^2的滑坡图。使用滑坡清单进行的GIS分析揭示了有关印度滑坡发生的控制，暴露和模式的有趣结果。西北喜马拉雅山占印度滑坡的66.5％，其次是东北喜马拉雅山（18.8％）和西高止山脉（14.7％）。由高级变质岩组成的大喜马拉雅层序具有可控性（32％），而主要中央逆冲是印度控制滑坡的主要区域结构（占12％）。与西北喜马拉雅山和西高止山脉相比，在喜马拉雅东北部，滑坡的大小和控制滑坡发生的坡度较小。与喜马拉雅地区相比，西高止山脉的滑坡是由较少的降雨引发的。使用145个丘陵地区的四个关键社会经济参数进行的暴露分析表明，印度的Rudraprayag地区受滑坡影响最大。在全国范围内使用滑坡数据库得出的理解将有助于优先确定和加强印度的滑坡灾害风险减少策略。