A prototype ann based algorithm for the soil moisture retrieval from l- band in view of the incoming SMAP mission

An algorithm for retrieving soil moisture (SMC) from SMAP acquisitions is presented in this paper. The algorithm is based on Artificial Neural Network (ANN) techniques and takes advantage of the synergy between active and passive SMAP acquisitions. The training was carried out by using both electrom...

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Bibliographic Details
Published in2014 13th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad) pp. 5 - 9
Main Authors Santi, E., Paloscia, S., Pettinato, S., Fontanelli, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2014
Subjects
Artificial neural networks
backscattering coefficient
brightness temperature
Data models
electromagnetic models
microwave
Microwave radiometry
Radar
SMAP
Soil moisture
Temperature measurement
Training
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DOI10.1109/MicroRad.2014.6878897

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Summary:An algorithm for retrieving soil moisture (SMC) from SMAP acquisitions is presented in this paper. The algorithm is based on Artificial Neural Network (ANN) techniques and takes advantage of the synergy between active and passive SMAP acquisitions. The training was carried out by using both electromagnetic forward models based on the Radiative Transfer Theory (RTT) and experimental data from SMEX02 campaign.
DOI:10.1109/MicroRad.2014.6878897