Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling

被引:118
作者
Baghdadi, Nicolas [1 ]
Cerdan, Olivier [1 ]
Zribi, Mehrez [2 ]
Auzet, Veronique [3 ]
Darboux, Frederic [4 ]
El Hajj, Mahmoud [1 ]
Kheir, Rania Bou [5 ]
机构
[1] Bur Rech Geol & Minieres, French Geol Survey, Dev Planning & Nat Risks Div, F-45060 Orleans 2, France
[2] CETP CNRS, F-78140 Velizy Villacoublay, France
[3] Univ Strasbourg, IMFS, CNRS, UMR 7507, F-67000 Strasbourg, France
[4] INRA, Sci Sol, F-45166 Olivet, France
[5] Lebanese Natl Council Sci Res, Beirut, Lebanon
关键词
synthetic aperture radar (SAR) sensors; soil surface; hydrological modelling; erosion modelling;
D O I
10.1002/hyp.6609
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Synthetic aperture radar (SAR) sensors are often used to characterize the surface of bare soils in agricultural environments. They enable the soil moisture and roughness to be estimated with constraints linked to the configurations of the sensors (polarization, incidence angle and radar wavelength). These key soil characteristics are necessary for different applications, such as hydrology and risk prediction. This article reviews the potential of currently operational SAR sensors and those planned for the near future to characterize soil surface as a function of users' needs. It details what it is possible to achieve in terms of mapping soil moisture and roughness by specifying optimal radar configurations and the precision associated with the estimation of soil surface characteristics. The summary carried out for the present article shows that mapping soil moisture is optimal with SAR sensors at low incidence angles (<35 degrees). This configuration, which enables an estimated moisture accuracy greater than 6% is possible several times a month taking into account all the current and future sensors. Concerning soil roughness, it is best mapped using three classes (smooth, moderately rough, and rough). Such mapping requires high-incidence data, which is possible with certain current sensors (RADARSAT-1 and ASAR both in band C). When L-band sensors (ALOS) become available, this mapping accuracy should improve because the sensitivity of the radar signal to Soil Surface Characteristics (SSC) increases with wavelength. Finally, the polarimetric mode of certain imminent sensors (ALOS, RADARSAT-2, TerraSAR-X, etc.), and the possibility of acquiring data at very high spatial resolution (metre scale), offer great potential in terms of improving the quality of SSC mapping. Copyright (C) 2007 John Wiley & Sons, Ltd.
引用
收藏
页码:9 / 20
页数:12
相关论文
共 100 条
[1]   Retrieving soil moisture over bare soil from ERS 1 synthetic aperture radar data: Sensitivity analysis based on a theoretical surface scattering model and field data [J].
Altese, E ;
Bolognani, O ;
Mancini, M ;
Troch, PA .
WATER RESOURCES RESEARCH, 1996, 32 (03) :653-661
[2]  
[Anonymous], 1991, THEORY WAVE SCATTERI
[3]   THEORETICAL-STUDY OF THE SENSITIVITY OF THE MICROWAVE BACKSCATTERING COEFFICIENT TO THE SOIL SURFACE PARAMETERS [J].
AUTRET, M ;
BERNARD, R ;
VIDALMADJAR, D .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1989, 10 (01) :171-179
[4]   RILL EROSION AS A FUNCTION OF THE CHARACTERISTICS OF CULTIVATED CATCHMENTS IN THE NORTH OF FRANCE [J].
AUZET, AV ;
BOIFFIN, J ;
PAPY, F ;
LUDWIG, B ;
MAUCORPS, J .
CATENA, 1993, 20 (1-2) :41-62
[5]   Surface characterisation for soil erosion forecasting [J].
Auzet, AV ;
van Dijk, P ;
Kirkby, MJ .
CATENA, 2005, 62 (2-3) :77-78
[6]   Relationship between profile length and roughness variables for natural surfaces [J].
Baghdadi, N ;
Paillou, P ;
Grandjean, G ;
Dubois, P ;
Davidson, M .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2000, 21 (17) :3375-3381
[7]   Soil moisture estimation using multi-incidence and multi-polarization ASAR data [J].
Baghdadi, N. ;
Holah, N. ;
Zribi, M. .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2006, 27 (9-10) :1907-1920
[8]   Calibration of the Integral Equation Model for SAR data in C-band and HH and VV polarizations [J].
Baghdadi, N ;
Holah, N ;
Zribi, M .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2006, 27 (04) :805-816
[9]   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
[10]   Potential of ERS and Radarsat data for surface roughness monitoring over bare agricultural fields: application to catchments in Northern France [J].
Baghdadi, N ;
King, C ;
Bourguignon, A ;
Remond, A .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (17) :3427-3442