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Computer Science > Computer Vision and Pattern Recognition

arXiv:2012.05013v1 (cs)
[Submitted on 9 Dec 2020]

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
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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.
Comments: Accepted for a spotlight talk and a poster at the Tackling Climate Change with Machine Learning workshop at NeurIPS 2020
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2012.05013 [cs.CV]
  (or arXiv:2012.05013v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2012.05013

Submission history

From: Shimaa Baraka [view email]
[v1] Wed, 9 Dec 2020 12:48:06 UTC (13,562 KB)
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