Spatial statistical characteristics of radar imagery from bare soil surfaces

Ram M. Narayanan, Rajan Pardipuram, Donald C. Rundquist

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

1 Scopus citations

Abstract

The potential of high resolution radar imagery to estimate various hydrological parameters, such as soil moisture, has long been recognized. Various Synthetic Aperture Radar (SAR) sensors have been developed to acquire and analyze data over terrain surfaces. As a parallel effort, several modeling approaches have also been used to simulate radar imagery for comparison with measured data. In order to perform realistic simulations, it is essential to incorporate the effects of. naturally-occurring spatial variability and spatial correlations of those ground parameters that affect the radar response. In the past, such simulations have largely neglected the use of spatial statistical characteristics of soil physical properties, with the result that it has not been possible to meaningfully interpret field-acquired data. In this paper, we specifically address the incorporation of the spatial characteristics of soil properties into radar image simulation models.

Original languageEnglish (US)
Title of host publicationIGARSS 1992 - International Geoscience and Remote Sensing Symposium
Subtitle of host publicationInternational Space Year: Space Remote Sensing
EditorsRuby Williamson, Tammy Stein
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages498-500
Number of pages3
ISBN (Electronic)0780301382
DOIs
StatePublished - Jan 1 1992
Event12th Annual International Geoscience and Remote Sensing Symposium, IGARSS 1992 - Houston, United States
Duration: May 26 1992May 29 1992

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume1

Other

Other12th Annual International Geoscience and Remote Sensing Symposium, IGARSS 1992
Country/TerritoryUnited States
CityHouston
Period5/26/925/29/92

All Science Journal Classification (ASJC) codes

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

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