Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data

M. M. Rahman, M. S. Moran, D. P. Thoma, R. Bryant, C. D. Holifield Collins, T. Jackson, Barron J Orr, M. Tischler

Research output: Contribution to journalArticle

97 Citations (Scopus)

Abstract

The Integral Equation Model (IEM) is the most widely-used, physically based radar backscatter model for sparsely vegetated landscapes. In general, IEM quantifies the magnitude of backscattering as a function of moisture content and surface roughness, which are unknown, and the known radar configurations. Estimating surface roughness or soil moisture by solving the IEM with two unknowns is a classic example of under-determination and is at the core of the problems associated with the use of radar imagery coupled with IEM-like models. This study offers a solution strategy to this problem by the use of multi-angle radar images, and thus provides estimates of roughness and soil moisture without the use of ancillary field data. Results showed that radar images can provide estimates of surface soil moisture at the watershed scale with good accuracy. Results at the field scale were less accurate, likely due to the influence of image speckle. Results also showed that subsurface roughness caused by rock fragments in the study sites caused error in conventional applications of IEM based on field measurements, but was minimized by using the multi-angle approach.

Original languageEnglish (US)
Pages (from-to)391-402
Number of pages12
JournalRemote Sensing of Environment
Volume112
Issue number2
DOIs
StatePublished - Feb 15 2008

Fingerprint

radar imagery
surface roughness
radar
Soil moisture
Radar
soil moisture
Surface roughness
soil water
Integral equations
roughness
speckle
Backscattering
Speckle
Watersheds
backscatter
moisture content
Moisture
rocks
Rocks
watershed

Keywords

  • Active microwave
  • ENVISAT-ASAR
  • Integral Equation Model
  • Radar
  • Soil moisture
  • Surface roughness

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Earth-Surface Processes
  • Environmental Science(all)
  • Management, Monitoring, Policy and Law

Cite this

Rahman, M. M., Moran, M. S., Thoma, D. P., Bryant, R., Holifield Collins, C. D., Jackson, T., ... Tischler, M. (2008). Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data. Remote Sensing of Environment, 112(2), 391-402. https://doi.org/10.1016/j.rse.2006.10.026

Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data. / Rahman, M. M.; Moran, M. S.; Thoma, D. P.; Bryant, R.; Holifield Collins, C. D.; Jackson, T.; Orr, Barron J; Tischler, M.

In: Remote Sensing of Environment, Vol. 112, No. 2, 15.02.2008, p. 391-402.

Research output: Contribution to journalArticle

Rahman, MM, Moran, MS, Thoma, DP, Bryant, R, Holifield Collins, CD, Jackson, T, Orr, BJ & Tischler, M 2008, 'Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data', Remote Sensing of Environment, vol. 112, no. 2, pp. 391-402. https://doi.org/10.1016/j.rse.2006.10.026
Rahman MM, Moran MS, Thoma DP, Bryant R, Holifield Collins CD, Jackson T et al. Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data. Remote Sensing of Environment. 2008 Feb 15;112(2):391-402. https://doi.org/10.1016/j.rse.2006.10.026
Rahman, M. M. ; Moran, M. S. ; Thoma, D. P. ; Bryant, R. ; Holifield Collins, C. D. ; Jackson, T. ; Orr, Barron J ; Tischler, M. / Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data. In: Remote Sensing of Environment. 2008 ; Vol. 112, No. 2. pp. 391-402.
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