Estimation of the moisture content of bare soil from RADARSAT-1 SAR using simple empirical models

• Published in: International journal of remote sensing Vol. 24; no. 12; pp. 2575 - 2582
• Main Authors: Sahebi, M. R., Bonn, F., Gwyn, Q. H. J.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 20.06.2003; Taylor and Francis
• Subjects: Applied geophysics; Earth sciences; Earth, ocean, space; Exact sciences and technology; Internal geophysics; Soils; Surficial geology; Canada; models; soil moisture; Space remote sensing; accuracy; cartography; North America; backscattering; frequency; synthetic aperture radar; interpretation; roughness; polarization; errors
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/0143116031000072948

Synthetic Aperture Radar (SAR) provides a remote sensing tool to estimate soil moisture. Mapping surface soil moisture from the grey level of SAR images is a demonstrated procedure, but several factors can interfere with the interpretation and must be taken into account. The most important factors are surface roughness and the radar configuration (frequency, polarization and incidence angle). This Letter evaluates the influence of these variables for estimation of bare soil moisture using RADARSAT-1 SAR data. First, the parameters of two linear backscatter models, the Ji and Champion models (Ji et al . 1995, Champion 1996), were tested and the constants recalculated. rms error based on the backscattering coefficient was reduced from 6.12 and 6.48 dB to 4.28 and 1.68 dB for the Ji and Champion models respectively. Secondly, a new model is proposed which had an rms error of only 1.21 dB. The results showed a marked increase in accuracy compared with the previous models.