Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya

• URL: http://arxiv.org/abs/2012.05013v1
• Date: Wed, 9 Dec 2020 12:48:06 GMT
• Title: 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
• Abstract summary: 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. We present a machine learning based approach to support ecological monitoring, with a focus on glaciers.
• Score: 54.12023102155757
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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