Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine

Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine

Satellite remote sensing plays an important role in mapping the location and extent of surface water. A variety of approaches are available for mapping surface water, but deep learning approaches are not commonplace as they are ‘data hungry’ and require large amounts of computational resources. Howe...

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Bibliographic Details
Main Authors: Timothy Mayer, Ate Poortinga, Biplov Bhandari, Andrea P. Nicolau, Kel Markert, Nyein Soe Thwal, Amanda Markert, Arjen Haag, John Kilbride, Farrukh Chishtie, Amit Wadhwa, Nicholas Clinton, David Saah
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:ISPRS Open Journal of Photogrammetry and Remote Sensing
Subjects:
Image segmentation
Synthetic aperture radar
Surface water mapping
Deep learning
U-net
Google earth engine
Online Access:http://www.sciencedirect.com/science/article/pii/S2667393221000053

Internet

http://www.sciencedirect.com/science/article/pii/S2667393221000053

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