Title :
Joint statistical properties of RMS height and correlation length derived from multisite 1-m roughness measurements
Author :
Davidson, Malcolm W J ; Mattia, Francesco ; Satalino, Giuseppe ; Verhoest, Niko E C ; Le Toan, Thuy ; Borgeaud, Maurice ; Louis, Jérôme M B ; Attema, Evert
Author_Institution :
Eur. Space Res. & Technol. Center, Eur. Space Agency, Noordwijk, Netherlands
fDate :
7/1/2003 12:00:00 AM
Abstract :
This paper aims to establish the joint roughness statistics for rms height s and correlation length l for agricultural bare soil fields and a variety of tillage conditions. To do so, we make use of a unique pan-European database of profile measurements covering five different sites and containing approximately 1.5 km of profile data. A preliminary assessment of the validity of the derived roughness statistics for electromagnetic scattering models is also carried out by comparing σ0 predictions obtained using the integral equation model with derived roughness statistics and European Remote Sensing 1 and 2 (ERS 1/2) synthetic aperture radar observations. The results are then summarized within the overall context of roughness description and we discuss the implications in terms of forward modeling and inversion. The limitations of s and l parameters as roughness descriptors are also underlined.
Keywords :
agriculture; backscatter; geophysical techniques; radar cross-sections; radar theory; remote sensing by radar; rough surfaces; soil; synthetic aperture radar; terrain mapping; Europe; RMS height; SAR; agricultural land; agriculture; backscatter; bare soil; correlation length; electromagnetic scattering models; field; geophysical measurement technique; integral equation model; joint statistical properties; land surface; multisite observations; radar remote sensing; radar scattering; rough surface; statistics; surface roughness; synthetic aperture radar; terrain mapping; tillage conditions; Databases; Electromagnetic measurements; Electromagnetic modeling; Electromagnetic scattering; Integral equations; Length measurement; Predictive models; Remote sensing; Soil measurements; Statistics;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2003.813361