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Accurate estimation of sigma(exp 0) using AIRSAR dataDuring recent years signature analysis, classification, and modeling of Synthetic Aperture Radar (SAR) data as well as estimation of geophysical parameters from SAR data have received a great deal of interest. An important requirement for the quantitative use of SAR data is the accurate estimation of the backscattering coefficient sigma(exp 0). In terrain with relief variations radar signals are distorted due to the projection of the scene topography into the slant range-Doppler plane. The effect of these variations is to change the physical size of the scattering area, leading to errors in the radar backscatter values and incidence angle. For this reason the local incidence angle, derived from sensor position and Digital Elevation Model (DEM) data must always be considered. Especially in the airborne case, the antenna gain pattern can be an additional source of radiometric error, because the radar look angle is not known precisely as a result of the the aircraft motions and the local surface topography. Consequently, radiometric distortions due to the antenna gain pattern must also be corrected for each resolution cell, by taking into account aircraft displacements (position and attitude) and position of the backscatter element, defined by the DEM data. In this paper, a method to derive an accurate estimation of the backscattering coefficient using NASA/JPL AIRSAR data is presented. The results are evaluated in terms of geometric accuracy, radiometric variations of sigma(exp 0), and precision of the estimated forest biomass.
Document ID
19950027384
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Holecz, Francesco
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Rignot, Eric
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
September 6, 2013
Publication Date
January 23, 1995
Publication Information
Publication: Summaries of the Fifth Annual JPL Airborne Earth Science Workshop. Volume 3: AIRSAR Workshop
Subject Category
Earth Resources And Remote Sensing
Accession Number
95N33805
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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