Saurabh Kaushik

Saurabh Kaushik

Postdoctoral Researcher, Geospatial Data Science, Machine Learning, Computer Vision, Geo-foundational Models, Transfomers, Data Fusion

Mapping Glaciers from Space Using Artificial Intelligence

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Mapping Glaciers from Space Using AI

This blog provides a step-by-step implementation of deep learning using multisource remote sensing data for extracting glacier boundaries (specifically supraglacial debris, which is referred to as glacier boundary throughout the post, as mapping of clean ice is quite straightforward using NDSI) in parts of the Himalaya-Karakoram (HK). This blog is equally relevant to all GeoAI enthusiasts who are interested in Earth Observation (EO) applications using deep learning. The code and explanation provided here are easy to adapt for other EO applications. The original data and code of this work can be accessed via Repository Link.

Glacier Mapping Using AI
Figure: Example of deep learning-based glacier mapping using multisource remote sensing data.

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A Step-by-Step Guide to Acquiring Multisource Remote Sensing Data Using Python

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Read full blog here guide The intersection of computer vision, remote sensing, and earth observation has proven to be highly effective in monitoring and predicting Earth surface processes. These tasks often require combining multisource remote sensing data to provide complementary information to deep learning models. Since these models are data-intensive, performing large-scale analyses necessitates a sophisticated pipeline for downloading and processing multisource remote sensing data efficiently.