Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning

Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning

Large-scale mapping activities can benefit from the vastly increasing availability of earth observation (EO) data, especially when combined with volunteered geographical information (VGI) using machine learning (ML). High-resolution maps of inland surface water bodies are important for water supply...

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Bibliographic Details
Main Authors: Hao Li, Johannes Zech, Christina Ludwig, Sascha Fendrich, Aurelie Shapiro, Michael Schultz, Alexander Zipf
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Volunteered geographical information
Inland surface water
SDG 6
Copernicus
Deep learning
OpenStreetMap
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243421002786

Internet

http://www.sciencedirect.com/science/article/pii/S0303243421002786

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