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Statistical characteristics of simulated radar imagery from bare soil surfaces: Effects of surface roughness and soil moisture variability

Journal Article · · IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States)
DOI:https://doi.org/10.1109/36.285198· OSTI ID:6956740
;  [1];  [2]
  1. Univ. of Nebraska, Lincoln, NE (United States)
  2. Hughes STX Corp., Lanham, MD (United States)

The potential of high-resolution radar imagery to estimate various hydrological parameters, such as soil moisture, has long been recognized. Image simulation is one approach to study the interrelationships between the radar response and the underlying ground parameters. In order to perform realistic simulations, the authors incorporated the effects of naturally occurring spatial variability and spatial correlations of those ground parameters that affect the radar response, primarily surface roughness and soil moisture. Surface roughness and soil moisture images were generated for a hypothetical 100 x 100 m bare soil surface area at 1 m resolution using valid probability distribution and correlation lengths, These values were then used to obtain copolarized radar scattering coefficients at 2 GHz (L band) and 10 GHz (X band) frequencies using appropriate backscatter models, which were then converted to a digital number within 0--255 gray scale in order to generate radar images. The effect of surface roughness variability causes variability in the radar image, which is more apparent under smooth soil conditions. On the other hand, the inherent spatial pattern in soil moisture tends to cause similar patterns in the radar image under rougher soil conditions. The maximum difference between contrast-enhanced mean values of the radar image digital number due to moisture variations occurs at surface roughness values in the 1.5--2.0 cm range.

OSTI ID:
6956740
Journal Information:
IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States) Vol. 32:1; ISSN 0196-2892; ISSN IGRSD2
Country of Publication:
United States
Language:
English

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