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ANN technique for the evaluation of soil moisture over bare and vegetated fields from microwave radiometer data
Published in
Volume: 38
Issue: 5
Pages: 283 - 288
Retrieving information from remotely sensed data is an important task. In the present work, data of L band microwave radiometer has been used to collect the brightness temperature over bare and vegetated fields in two polarizations at different moisture levels. Artificial neural network (ANN) trained with Levenberg-Marquardt algorithm has been used to determine soil moisture from brightness temperatures measured by microwave radiometry. ANN are trained to evaluate the moisture content in the range 0-36% from different sets of data of bare and vegetated fields. Properly trained feed-forward neural network with Levenberg-Marquardt algorithm predicted soil moisture content with less mean absolute error.
About the journal
JournalIndian Journal of Radio and Space Physics
Open AccessNo