Soil moisture estimation from ERS/SAR data:: Toward an operational methodology

被引:122
作者
Le Hégarat-Mascle, S
Zribi, M
Alem, F
Weisse, A
Loumagne, C
机构
[1] Ctr Etude Environnements Terr & Planetaires, Ctr Natl Rech Sci, F-78140 Velizy Villacoublay, France
[2] Ctr Etude Machinisme Agr & Genie Rural Eaux & For, Antony, France
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2002年 / 40卷 / 12期
关键词
agriculture surfaces; image processing; moisture measurement; radar imaging; soil;
D O I
10.1109/TGRS.2002.806994
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
Previous studies have shown the possibility of using European Remote Sensing/synthetic aperture radar (ERS/SAR) data to monitor surface soil moisture from space. The linear relationships between soil moisture and the SAR signal have been derived empirically and, thus, were a priori specific to the considered watershed. In order to overcome this limit, this study focused on two objectives. The first one was to validate over two years of data the empirical sensitivity of the radar signal to soil moisture, in the case of three agricultural watersheds with different soil compositions and land cover uses. The slope of the observed relationship was very consistent. Conversely, the off set could change, making the soil moisture retrieval only relative (and not absolute). The second one was to propose an "operational" methodology for soil moisture monitoring based on ERS/SAR data. The implementation of this methodology is based on two steps: the calibration period and the operational period. During the calibration period, ground truth campaigns are performed to measure vegetation parameters (to correct the SAR signal from the vegetation effect), and the ERS/SAR data is processed only once a field land cover map is established. In contrast, during the operational period, no vegetation field campaigns are performed, and the images are processed as soon as they are available. The results confirm the relevance of this operational methodology, since no loss of performance (in soil moisture retrieval) is observed between the calibration and operational periods.
引用
收藏
页码:2647 / 2658
页数:12
相关论文
共 21 条
[11]   Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission [J].
Kerr, YH ;
Waldteufel, P ;
Wigneron, JP ;
Martinuzzi, JM ;
Font, J ;
Berger, M .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2001, 39 (08) :1729-1735
[12]   Land cover discrimination from multitemporal ERS images and multispectral Landsat images:: a study case in an agricultural area in France [J].
Le Hégarat-Mascle, S ;
Quesney, A ;
Vidal-Madjar, D ;
Taconet, O ;
Normand, M ;
Loumagne, C .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2000, 21 (03) :435-456
[13]   Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing [J].
LeHegaratMascle, S ;
Bloch, I ;
VidalMadjar, D .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1997, 35 (04) :1018-1031
[14]  
LEHEGARATMASCLE.S, 2000, P EUSAR2000 MUN GERM, P679
[15]   ESTIMATING CROP WATER-DEFICIT USING THE RELATION BETWEEN SURFACE-AIR TEMPERATURE AND SPECTRAL VEGETATION INDEX [J].
MORAN, MS ;
CLARKE, TR ;
INOUE, Y ;
VIDAL, A .
REMOTE SENSING OF ENVIRONMENT, 1994, 49 (03) :246-263
[16]   AN EMPIRICAL-MODEL AND AN INVERSION TECHNIQUE FOR RADAR SCATTERING FROM BARE SOIL SURFACES [J].
OH, Y ;
SARABANDI, K ;
ULABY, FT .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1992, 30 (02) :370-381
[17]  
Quesney A, 2001, IAHS-AISH P, P495
[18]   Estimation of watershed soil moisture index from ERS/SAR data [J].
Quesney, A ;
Le Hégarat-Mascle, S ;
Taconet, O ;
Vidal-Madjar, D ;
Wigneron, JP ;
Loumagne, C ;
Normand, M .
REMOTE SENSING OF ENVIRONMENT, 2000, 72 (03) :290-303
[19]  
TACONET O, 1986, J CLIM APPL METEOROL, V25, P284, DOI 10.1175/1520-0450(1986)025<0284:EOAARU>2.0.CO
[20]  
2