Snow, Glacier, and Glacier Lake Mapping and Monitoring Using Remote Sensing Data

Nowadays, remote sensing (RS) technology under the space programs of the world’s leading agencies provides multispectral optical and microwave data for natural resource mapping of the Earth’s surface. Snow and glacier mapping are critical for the accurate assessment of water resource availability on the Earth’s cryosphere and to quantify the impact of climate change on these cryosphere components. At present, the availability of multispectral remote sensing data is a major source for studying the snow and glaciers from space. The RS approach provides data visualization, interpretation, and assessment of the time series scenario of both snow cover change and glacier dynamics. The mapping of snow is comparatively easier than glacier mapping. Most commonly, the normalized difference snow index (NDSI) band ratio technique has been adopted for snow cover mapping and monitoring. There are various remote sensing-derived snow cover area products available. To overcome the limitations of optical data in terms of cloud presence, the microwave RS data is highly useful for snow cover mapping and snow physical parameters retrieval. However, for snow physical parameters such as snow water equivalent, the scatterometer data incorporating the synthetic aperture radar (SAR) data was used. Recently, semi-automated algorithms are used for glacier mapping separating clean ice and debris cover area. For the Indian Himalayan region, glacier mapping was primarily based on Survey of India (SoI) and Geological Survey of India (GSI) topographic maps ranged on the scale 1:250,000 to 1: 50,000. The innovation of novel geospatial approaches for glacier mapping like manual delineation, band ratios, image segmentation, and classification is based on the multispectral/panchromatic data. However, mapping clean-ice and debris cover of the glacier still has some limitations for automated methods. Automated approaches for glacier mapping dealt with the comparison of different datasets, measurement of glacier change in length, volume, and snout positions by multi-temporal satellite imagery, and digital elevation model. Further, the high-resolution RS data has been extensively used for glacier lake mapping and monitoring. The regular study of glacier lakes is critical for any possible glacier lake outburst flood. In this way, the critical glacier lakes may be identified. It is concluded that geospatial technology plays a significant role in cryosphere studies and analysis from a climate change perspective.