@inproceedings{baraka2020machine,
author = {Baraka, Shimaa and Akera, Benjamin and Aryal, Bibek and Sherpa, Tenzing and Shresta, Finu and Ortiz, Anthony and Sankaran, Kris and Lavista Ferres, Juan M. and Matin, Mir and Bengio, Yoshua},
title = {Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya},
booktitle = {NeurIPS CCAI},
year = {2020},
month = {December},
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.

 },
url = {http://approjects.co.za/?big=en-us/research/publication/machine-learning-for-glacier-monitoring-in-the-hindu-kush-himalaya/},
}