Sentinel-1 soil moisture at 1 km resolution: a validation study

被引:58
|
作者
Balenzano, Anna [1 ]
Mattia, Francesco [1 ]
Satalino, Giuseppe [1 ]
Lovergine, Francesco P. [1 ]
Palmisano, Davide [1 ]
Peng, Jian [2 ,13 ,14 ]
Marzahn, Philip [2 ]
Wegmuller, Urs [3 ]
Cartus, Oliver [3 ]
Dabrowska-Zielinska, Katarzyna [4 ]
Musial, Jan P. [4 ]
Davidson, Malcolm W. J. [5 ]
Pauwels, Valentijn R. N. [6 ]
Cosh, Michael H. [7 ]
McNairn, Heather [8 ]
Johnson, Joel T. [9 ]
Walker, Jeffrey P. [6 ]
Yueh, Simon H. [10 ]
Entekhabi, Dara [11 ]
Kerr, Yann H. [12 ]
Jackson, Thomas J. [7 ]
机构
[1] CNR, Natl Res Council Italy, Inst Electromagnet Sensing Environm IREA, Uos Bari, Italy
[2] Ludwig Maximilians Univ Munchen LMU, Dept Geog, Munich, Germany
[3] Gamma Remote Sensing Res & Consulting AG GAMMA, Gumlingen, Switzerland
[4] Inst Geodesy & Cartog IGiK, Remote Sensing Ctr, Warsaw, Poland
[5] European Space Agcy, Mission Sci Div, Noordwijk, Netherlands
[6] Monash Univ, Dept Civil Engn, Clayton, Vic, Australia
[7] USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD USA
[8] Agr & Agri Food Canada AAFC, Ottawa, ON, Canada
[9] Ohio State Univ, Dept Elect & Comp Engn, Columbus, OH 43210 USA
[10] CALTECH, Jet Prop Lab JPL, Pasadena, CA USA
[11] MIT, Civil & Environm Engn, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[12] Ctr Etud Spatiales BIOsphere CESBIO, Toulouse, France
[13] UFZ Helmholtz Ctr Environm Res, Dept Remote Sensing, Leipzig, Germany
[14] Univ Leipzig, Remote Sensing Ctr Earth Syst Res, Leipzig, Germany
关键词
Soil moisture; High resolution; Sentinel-1; Synthetic Aperture Radar (SAR); Spatial representativeness error (SRE); Validation; BAND SAR DATA; TIME-SERIES; TEMPORAL STABILITY; LINEAR-REGRESSION; SPATIAL SCALES; SURFACE; RADAR; RETRIEVAL; CLIMATE; VARIABILITY;
D O I
10.1016/j.rse.2021.112554
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study presents an assessment of a pre-operational soil moisture product at 1 km resolution derived from satellite data acquired by the European Radar Observatory Sentinel-1 (S-1), representing the first space component of the Copernicus program. The product consists of an estimate of surface soil volumetric water content Theta [m(3)/m(3)] and its uncertainty [m(3)/m(3)], both at 1 km. The retrieval algorithm relies on a time series based Short Term Change Detection (STCD) approach, taking advantage of the frequent revisit of the S-1 constellation that performs C-band Synthetic Aperture Radar (SAR) imaging. The performance of the S-1 Theta product is estimated through a direct comparison between 1068 S-1 Theta images against in situ Theta measurements acquired by 167 ground stations located in Europe, America and Australia, over 4 years between January 2015 and December 2020, depending on the site. The paper develops a method to estimate the spatial representativeness error (SRE) that arises from the mismatch between the S-1 Theta retrieved at 1 km resolution and the in situ point-scale Theta observations. The impact of SRE on standard validation metrics, i.e., root mean square error (RMSE), Pearson correlation (R) and linear regression, is quantified and experimentally assessed using S-1 and ground Theta data collected over a dense hydrologic network (4-5 stations/km(2)) located in the Apulian Tavoliere (Southern Italy). Results show that for the dense hydrological network the RMSE and correlation are similar to 0.06 m(3)/m(3) and 0.71, respectively, whereas for the sparse hydrological networks, i.e., 1 station/km(2), the SRE increases the RMSE by similar to 0.02 m(3)/m(3) (70% Confidence Level). Globally, the S-1 Theta product is characterized by an intrinsic (i.e., with SRE removed) RMSE of similar to 0.07 m(3)/m(3) over the Theta range [0.03, 0.60] m(3)/m(3) and R of 0.54. A breakdown of the RMSE per dry, medium and wet Theta ranges is also derived and its implications for setting realistic requirements for SAR-based Theta retrieval are discussed together with recommendations for the density of in situ Theta observations.
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页数:20
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