Retrievals of land surface parameters from measured brightness temperatures at 1.4 and 10.65 GHz by a neural network

Y. A. Liou, Shuo-Fang Liu, J. B. Lee, W. J. Wang, J. P. Wigneron

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

Field measurements are utilized to examine the sensitivity of H- and V-polarized radiometric signatures at 1.4 (L-band), 10.65 (X-band) GHz, and their combinations in terms of viewing angles and frequencies to the wheat biomass and soil moisture through an Error Propagation Learning Back Propagation (EPLBP) neural network. The radiometric measurements were taken by the PORTOS radiometer over wheat fields through 3 month growth cycles in 1993 (PORTOS-93) and 1996 (PORTOS-96). Soil moisture content (SMC) profiles were measured into depth of 10 cm in 1993, and 5 cm in 1996. The wheat was sampled daily in 1993 and twice a week in 1996 to obtain its dry and wet biomass. The EPLBP neural network is trained with observations randomly chosen from the PORTOS-93 data, and evaluated by the rest of the very same data set. Then, the trained neural network is further evaluated based on the PORTOS-96 data set for practical concern. During both field campaigns, the L-band radiometer measured brightness temperatures at a wide range of viewing angles from 0 to 50 degrees, while the X-band radiometer was operated at an incident angle of 50 degrees.

Original languageEnglish
Pages12-14
Number of pages3
Publication statusPublished - 2001 Dec 1
Event2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - Sydney, NSW, Australia
Duration: 2001 Jul 92001 Jul 13

Other

Other2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
CountryAustralia
CitySydney, NSW
Period01-07-0901-07-13

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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