Review of Machine Learning Approaches for Biomass and Soil Moisture Retrievals from Remote Sensing Data

Review of Machine Learning Approaches for Biomass and Soil Moisture Retrievals from Remote Sensing Data

The enormous increase of remote sensing data from airborne and space-borne platforms, as well as ground measurements has directed the attention of scientists towards new and efficient retrieval methodologies. Of particular importance is the consideration of the large extent and the high dimensionali...

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Bibliographic Details
Main Authors: Iftikhar Ali, Felix Greifeneder, Jelena Stamenkovic, Maxim Neumann, Claudia Notarnicola
Format: Article
Language:English
Published: MDPI AG 2015-12-01
Series:Remote Sensing
Subjects:
remote sensing
soil moisture
biomass
retrieval algorithms
machine learning
artificial neural networks
SVM
regression
biophysical parameters
Online Access:http://www.mdpi.com/2072-4292/7/12/15841

Internet

http://www.mdpi.com/2072-4292/7/12/15841

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