Evaluation of a rough soil surface description with ASAR-ENVISAT radar data

被引:45
作者
Zribi, M
Baghdadi, N
Holah, N
Fafin, O
Guérin, C
机构
[1] CNRS, CETP, F-78140 Velizy Villacoublay, France
[2] Bur Rech Geol & Minieres, ARN, ATL, F-45060 Orleans, France
关键词
radar; ENVISAT; ASAR; roughness; backscattering;
D O I
10.1016/j.rse.2004.11.014
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The input roughness parameters for electromagnetic backscattering modelling need to be accurate to estimate radar measurements correctly over bare soils, particularly in agricultural environments. This paper proposes to evaluate the roughness description in terms of several characterisations through a correlation function using a numerical backscattering model. The experimental database used in this study is based on ASAR-ENVISAT experimental campaigns in the Beauce region (France). Two presentations of the surface height correlation function are proposed in this study. The first one, referred to as the "alpha function" fits the experimental correlation functions up to the correlation length, while the second one, the "(a,b) function", fits the correlation function for scales corresponding to positive values. A relationship is proposed between the rms height of soil surface and the shape of the correlation function. Using the a function, comparisons between radar measurements for high incidence angles and simulations based on the numerical backscattering model (moment method) show a good agreement for soil surfaces with an rms height smaller than 2 cm with medium and high soil moisture. (c) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:67 / 76
页数:10
相关论文
共 25 条
[1]  
[Anonymous], 1986, THEORY APPL
[2]   Semi-empirical calibration of the IEM backscattering model using radar images and moisture and roughness field measurements [J].
Baghdadi, N ;
Gherboudj, I ;
Zribi, M ;
Sahebi, M ;
King, C ;
Bonn, F .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2004, 25 (18) :3593-3623
[3]   Retrieving surface roughness and soil moisture from synthetic aperture radar (SAR) data using neural networks [J].
Baghdadi, N ;
Gaultier, S ;
King, C .
CANADIAN JOURNAL OF REMOTE SENSING, 2002, 28 (05) :701-711
[4]  
Boiffin J, 1985, ASSESSMENT SOIL SURF, P210
[5]   A note on the multiple scattering in an IEM model [J].
Chen, KS ;
Wu, TD ;
Tsay, MK ;
Fung, AK .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2000, 38 (01) :249-256
[6]   A STUDY OF THE VALIDITY OF THE INTEGRAL-EQUATION MODEL BY MOMENT METHOD SIMULATION - CYLINDRICAL CASE [J].
CHEN, MF ;
CHEN, KS ;
FUNG, AK ;
CHEN, PM .
REMOTE SENSING OF ENVIRONMENT, 1989, 29 (03) :217-228
[7]   On the characterization of agricultural soil roughness for radar remote sensing studies [J].
Davidson, MWJ ;
Le Toan, T ;
Mattia, F ;
Satalino, G ;
Manninen, T ;
Borgeaud, M .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2000, 38 (02) :630-640
[8]  
Fung A.K., 1994, Microwave Scattering and Emission Models and their Applications
[9]   NUMERICAL-SIMULATION OF SCATTERING FROM SIMPLE AND COMPOSITE RANDOM SURFACES [J].
FUNG, AK ;
CHEN, MF .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 1985, 2 (12) :2274-2284
[10]   BACKSCATTERING FROM A RANDOMLY ROUGH DIELECTRIC SURFACE [J].
FUNG, AK ;
LI, ZQ ;
CHEN, KS .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1992, 30 (02) :356-369