Analysis of Local Variation of Soil Surface Parameters With TerraSAR-X Radar Data Over Bare Agricultural Fields

被引:58
作者
Anguela, Thais Paris [1 ]
Zribi, Mehrez [2 ]
Baghdadi, Nicolas [3 ]
Loumagne, Cecile [4 ]
机构
[1] Observat Spatiales Ctr Natl Rech Sci, Atmospheres Lab, F-78140 Velizy Villacoublay, France
[2] CNRS, Ctr Etud Environm Terrestre & Planetaires, F-78140 Velizy Villacoublay, France
[3] Ctr Etud Machinisme Agr & Genie Rural Eaux & Fore, Unite Mixte Rech Terr Environm Teledetect & Infor, F-34196 Montpellier, France
[4] Ctr Etude Machinisme Agr & Genie Rural Eaux & For, Hydrosyst & Bioproc Res Unit, F-92163 Antony, France
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2010年 / 48卷 / 02期
关键词
Modeling; roughness; soil moisture; soil texture; TerraSAR-X; MOISTURE ESTIMATION; ROUGHNESS; MODEL; BACKSCATTERING; RETRIEVAL; SIMULATION; VALIDITY; SAR;
D O I
10.1109/TGRS.2009.2028019
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The objective of this paper is to analyze the sensitivity of very high resolution TerraSAR-X radar data taken over bare soils to surface soil parameters and to study the spatial variability of these parameters at a fine scale (within a field plot). The relationship between the backscattering coefficient and the soil's parameters (moisture, surface roughness, texture, and local topography) was examined by means of four satellite images, as well as ground truth measurements, of each of the three agricultural plots, recorded during several field campaigns in the winter and spring of 2008. TerraSAR images demonstrate high potential for the identification of local variations of roughness and texture. An approach for the estimation of local moisture is proposed using an empirical method adapted to the scale of an individual field. The results show that, by using TerraSAR-X data to study bare agricultural fields, local variations in soil moisture can be retrieved with a root-mean-square error of 0.05 cm(3) . cm(-3).
引用
收藏
页码:874 / 881
页数:8
相关论文
共 46 条
[1]   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
[2]   Analysis of TerraSAR-X data and their sensitivity to soil surface parameters over bare agricultural fields [J].
Baghdadi, Nicolas ;
Zribi, Mehrez ;
Loumagne, Cecile ;
Ansart, Patrick ;
Anguela, Thais Paris .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (12) :4370-4379
[3]   Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: application to hydrological and erosion modelling [J].
Baghdadi, Nicolas ;
Cerdan, Olivier ;
Zribi, Mehrez ;
Auzet, Veronique ;
Darboux, Frederic ;
El Hajj, Mahmoud ;
Kheir, Rania Bou .
HYDROLOGICAL PROCESSES, 2008, 22 (01) :9-20
[4]   Surface soil moisture estimation over the AMMA Sahelian site in Mali using ENVISAT/ASAR data [J].
Baup, F. ;
Mougin, E. ;
de Rosnay, P. ;
Timouk, F. ;
Chenerie, I. .
REMOTE SENSING OF ENVIRONMENT, 2007, 109 (04) :473-481
[5]  
BEVEN KJ, 1996, SCALING HYDROLOGY US
[6]   Multifrequency soil moisture inversion from SAR measurements with the use of IEM [J].
Bindlish, R ;
Barros, AP .
REMOTE SENSING OF ENVIRONMENT, 2000, 71 (01) :67-88
[7]   Parameterization of tillage-induced single-scale soil roughness from 4-m profiles [J].
Callens, M ;
Verhoest, NEC ;
Davidson, MWJ .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2006, 44 (04) :878-888
[8]   Accuracy of top soil moisture simulation using a mechanistic model with limited soil characterization [J].
Chanzy, A. ;
Mumen, M. ;
Richard, G. .
WATER RESOURCES RESEARCH, 2008, 44 (03)
[9]  
CHANZY A, 1993, REMOTE SENSING REV, V7, P303, DOI DOI 10.1080/02757259309532183
[10]  
CHANZY A, 2003, P IGARSS TOUL FRANC, P1414