Improved Landsat-Based Water and Snow Indices for Extracting Lake and Snow Cover/Glacier in the Tibetan Plateau

Abstract

Identifying water and snow cover/glaciers (SCG) accurately is of great importance for monitoring different water resources in the Tibetan Plateau. However, discriminating between water and SCG remains a difficult task because of their similar spectral characteristic according to the physical principles of remote sensing. To efficiently distinguish different kinds of water resources automatically, here we proposed two new indices including: (i) the normalized difference water index with no SCG information (NDWIns) to extract lake water and suppress SCG: and (ii) the normalized difference snow index with no water information (NDSInw) to extract SCG and suppress lake water. Both new water and snow indices were tested in the Tibetan Plateau using Landsat series, showing that the overall accuracies of NDWIns and NDSInw were in the range of 94.6–97.0% and 94.9–97.0% in mapping the lake water from SCG and mapping the SCG from lake water, respectively. Further comparisons suggest that these new two indices improved upon the previous normalized difference snow index/modified normalized difference water index (NDSI/MNDWI) in mapping the water body and SCG. While the present study only focuses on the validation over certain areas in Tibetan Plateau, the newly proposed NDWIns and NDSInw have the potential for better monitoring the lake water and snow/glacier areas over other cold regions around the globe.