Retrieval of soil moisture using a dynamic learning neural network trained with a 1-dimensional hydrology/radiobrightness model

Yuei An Liou, Y. C. Tzeng, A. W. England

Research output: Contribution to conferencePaperpeer-review

Abstract

A scheme that utilizes satellite radiobrightness to infer surface parameters without losing the nonlinearity between the measured quantities and desired variables is examined. The approach is to incorporate products from the 1-dimensional hydrology/radiobrightness (1dH/R) model into the dynamic learning neural network (DLNN) manages the nonlinear mappings.

Original languageEnglish
Pages1096-1098
Number of pages3
StatePublished - 1997
EventProceedings of the 1997 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'97. Part 3 (of 4) - Singapore, Singapore
Duration: 3 Aug 19978 Aug 1997

Conference

ConferenceProceedings of the 1997 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'97. Part 3 (of 4)
CitySingapore, Singapore
Period3/08/978/08/97

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