Accurate and automatic mapping of complex debris‐covered glacier from remote sensing imagery using deep convolutional networks
Author:
Affiliation:
1. School of Engineering and Technology China University of Geosciences (Beijing) Beijing China
2. Institute of Geosafety China University of Geosciences (Beijing) Beijing China
Funder
National Natural Science Foundation of China
Publisher
Wiley
Subject
Geology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/gj.4615
Reference49 articles.
1. Machine-learning classification of debris-covered glaciers using a combination of Sentinel-1/-2 (SAR/optical), Landsat 8 (thermal) and digital elevation data
2. An inventory of Norway's glaciers and ice-marginal lakes from 2018–19 Sentinel-2 data
3. Ayma V. Beltran C. Happ P. Costa G. A. &Feitosa R. Q.(2019)Mapping Ausangate glacier changes using clustering techniques on cloud computing infrastructure. Proceedings of the 7th international conference on remote sensing and Geoinformation of the environment (RSCy) Cyprus Remote Sensing Soc Paphos CYPRUS.
4. Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning
5. Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification
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