Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application

Title
Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application
Authors
Keywords
Soil moisture, SMOS, Soil moisture deficit, Artificial intelligence, Support vector machine, Relevance vector machine, Artificial neural network, Generalized linear models
Journal
WATER RESOURCES MANAGEMENT
Volume 27, Issue 8, Pages 3127-3144
Publisher
Springer Nature
Online
2013-04-17
DOI
10.1007/s11269-013-0337-9

Ask authors/readers for more resources

Reprint

Contact the author

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation