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Proceedings Paper

Surface roughness retrieval from radar data
Author(s): Narinder S. Chauhan; Edwin T. Engman
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Paper Abstract

Radar data from the remote sensing technique have been used in conjunction with theoretical microwave modeling to develop a retrieval algorithm for the root mean square height of the rough surface. The algorithm exploits frequency (L and C band) differences in the radar response from a vegetated rough surface. These differences are related back to the Fresnel reflectivity and surface rms height by using a theoretical modeling approach that is based on a discrete scatter random media technique and uses distorted Born approximation to compute backscatter coefficient from a particular scene. Sensitivity analysis shows that the change in surface reflectivity due to the change in frequency from L to C band is dominated by surface rms height, and, the Fresnel reflectivity stays almost constant over this frequency interval. The inversion algorithm based on these sensitivity differences has been applied to the backscatter model data from a plant canopy of soybean. Calculations show that the technique gives accurate results from a model backscatter data set that is corrupted with 80% of noise. The inversion algorithm is also applied to synthetic aperture radar (SAR) data collected over corn fields during the MACHYDRO'90 experiment in Pennsylvania, USA. There is an excellent agreement between the measured and the retrieved rms surface height.

Paper Details

Date Published: 31 January 1995
PDF: 11 pages
Proc. SPIE 2314, Multispectral and Microwave Sensing of Forestry, Hydrology, and Natural Resources, (31 January 1995); doi: 10.1117/12.200734
Show Author Affiliations
Narinder S. Chauhan, NASA Goddard Space Flight Ctr. (United States)
Edwin T. Engman, NASA Goddard Space Flight Ctr. (United States)


Published in SPIE Proceedings Vol. 2314:
Multispectral and Microwave Sensing of Forestry, Hydrology, and Natural Resources
Eric Mougin; K. Jon Ranson; James Alan Smith, Editor(s)

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