Explicit inverse of soil moisture retrieval with an artificial neural network using passive microwave remote sensing data

Soo See Chai, Bert Veenendaal, Geoff West, Jeffrey P. Walker

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

2 Citations (Scopus)

Abstract

Soil moisture is an important variable that controls the partition of rainfall into infiltration and run-off. This plays an important role in the prediction of erosion, flood or drought. Passive microwave remote sensing data has great potential for providing estimates of soil moisture. This is mainly due to the minimal weather influence on passive microwave data and its ability to penetrate through clouds. The Artificial Neural Network (ANN) is a method that tries simulates human intelligence by crudely imitating the way a human brain learns. This method has been especially useful for mapping non-linear and ill-posed problems. Soil moisture retrieval is an example of a non-linear problem. An explicit inverse of the physical process can be built using an ANN to map the passive microwave measurements into land surface parameters such as soil moisture. For this paper, the ANN method used to create the explicit inverse function is divided into (i.) single parameter retrieval of the soil moisture value given the passive microwave measurements, and (ii.) multi-parameter retrieval of a number of land surface parameters, i.e. soil temperature, surface roughness, together with soil moisture value given the passive microwave measurements. This paper examines these methods in the context of retrieving surface soil moisture values given microwave radiometric data and discusses key issues that will need to be addressed to improve mapping performance and to produce operational systems.

Original languageEnglish
Title of host publication2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Edition1
DOIs
Publication statusPublished - 1 Dec 2008
Event2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, United States of America
Duration: 6 Jul 200811 Jul 2008

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Number1
Volume2

Conference

Conference2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
CountryUnited States of America
CityBoston, MA
Period6/07/0811/07/08

Keywords

  • Inverse problems
  • Neural networks
  • Review
  • Soil moisture

Cite this

Chai, S. S., Veenendaal, B., West, G., & Walker, J. P. (2008). Explicit inverse of soil moisture retrieval with an artificial neural network using passive microwave remote sensing data. In 2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings (1 ed.). [4779086] (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2, No. 1). https://doi.org/10.1109/IGARSS.2008.4779086