# Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya

**Authors:** Shimaa Baraka, Benjamin Akera, Bibek Aryal, Tenzing Sherpa, Finu Shresta, Anthony Ortiz, Kris Sankaran, Juan Lavista Ferres, Mir Matin, Yoshua Bengio  
**arXiv:** [2012.05013](https://arxiv.org/abs/2012.05013)  
**Date:** 2020-12-09  
**Summary page:** https://www.summarizepaper.com/fr/paper/2012.05013v1/

## Abstract

Glacier mapping is key to ecological monitoring in the hkh region. Climate change poses a risk to individuals whose livelihoods depend on the health of glacier ecosystems. In this work, we present a machine learning based approach to support ecological monitoring, with a focus on glaciers. Our approach is based on semi-automated mapping from satellite images. We utilize readily available remote sensing data to create a model to identify and outline both clean ice and debris-covered glaciers from satellite imagery. We also release data and develop a web tool that allows experts to visualize and correct model predictions, with the ultimate aim of accelerating the glacier mapping process.