High levels of water-induced erosion in the transboundary Himalayan river basins are contributing to substantial changes in basin hydrology and inundation. Basin-wide information on erosion dynamics is needed for conservation planning, but field-based studies are limited. This study used remote sensing (RS) data and a geographic information system (GIS) to estimate the spatial distribution of soil erosion across the entire Koshi basin. The revised universal soil loss equation (RUSLE) was used in an ArcGIS environment with rainfall erosivity, soil erodibility, slope length and steepness, cover-management, and support practice factors as primary parameters. The estimated annual erosion from the basin was around 42 million tonnes.

High levels of water-induced erosion in the transboundary Himalayan river basins are contributing to substantial changes in basin hydrology and inundation. Basin-wide information on erosion dynamics is needed for conservation planning, but field-based studies are limited. Part of the remote sensing (RS) and a geographic information system (GIS) based soil erosion estimation and spatial distribution of across the entire Koshi basin, a land cover map of 1990 used as a Support practice factor (PL). Land cover data for 1990 were prepared from analysis of the Landsat images using object-based image analysis.

Digital polygon data of Glaciers of Bhutan in 2010. This dataset is created using Landsat TM and ETM+, imageries of 2010. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.

Digital polygon data of Glaciers of Nepal in 1980, 1990, 2000 and 2010. This dataset is created using Landsat MSS,TM and ETM+ imageries of four respective decades. The glacier outlines were derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth. Moreover, the glacier outlines for 2000, 1990 and 1980 were derived manually modifying the glacier outlines of 2010 by overlaying separately the images of respective decades.

Digital polygon data of Glaciers of Nepal in 2010. This dataset is created using Landsat TM, ETM+ imageries of 2010. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.

Digital polygon data of Glaciers of Nepal in 2000. This dataset is created using Landsat MSS, TM imageries of 2000. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.

Digital polygon data of Glaciers of Nepal in 1990. This dataset is created using Landsat MSS, TM imageries of 1990. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.

Digital polygon data of Glaciers of Nepal in 1980. This dataset is created using Landsat MSS, imageries of 1980. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.