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Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya

Authors :
Baraka, Shimaa
Akera, Benjamin
Aryal, Bibek
Sherpa, Tenzing
Shresta, Finu
Ortiz, Anthony
Sankaran, Kris
Ferres, Juan Lavista
Matin, Mir
Bengio, Yoshua
Publication Year :
2020

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.<br />Comment: Accepted for a spotlight talk and a poster at the Tackling Climate Change with Machine Learning workshop at NeurIPS 2020

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2012.05013
Document Type :
Working Paper