Tests of the SMAP Combined Radar and Radiometer Algorithm Using Airborne Field Campaign Observations and Simulated Data

被引:157
作者
Das, Narendra Narayan [1 ]
Entekhabi, Dara [2 ]
Njoku, Eni G. [1 ]
Shi, Jiancheng J. C. [3 ]
Johnson, Joel T. [4 ]
Colliander, Andreas [1 ]
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA
[2] MIT, Dept Civil & Environm Engn, Cambridge, MA 02139 USA
[3] Univ Calif Santa Barbara, ICESS, Santa Barbara, CA 93106 USA
[4] Ohio State Univ, Electrosci Lab, Columbus, OH 43212 USA
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2014年 / 52卷 / 04期
基金
美国国家航空航天局;
关键词
Active-passive; L-band radiometer; L-band SAR; satellite; SMAP; soil moisture; SOIL-MOISTURE RETRIEVAL; OCEAN SALINITY; L-BAND; MISSION;
D O I
10.1109/TGRS.2013.2257605
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
A soil moisture retrieval algorithm is proposed that takes advantage of the simultaneous radar and radiometer measurements by the forthcoming NASA Soil Moisture Active Passive (SMAP) mission. The algorithm is designed to downscale SMAP L-band brightness temperature measurements at low resolution (similar to 40 km) to 9-km brightness temperature by using SMAP's L-band synthetic aperture radar (SAR) backscatter measurements at high resolution (1-3 km) in order to estimate soil moisture at 9-km resolution. The SMAP L-band SAR and radiometer instruments are designed to provide coincident observations at constant incidence angle, but at different spatial resolutions, across a wide swath. The algorithm described here takes advantage of the correlation between temporal fluctuations of brightness temperature and backscatter observed when viewing targets simultaneously at the same angle. Surface characteristics that affect the brightness temperature and backscatter measurements influence the signals at different time scales. This feature is applied in an approach in which fine-scale spatial heterogeneity detected by SAR observations is applied on coarser-scale radiometer measurements to produce an intermediate-resolution disaggregated brightness temperature field. These brightness temperatures are then used with established radiometer-based algorithms to retrieve soil moisture at the intermediate resolution. The capability of the overall algorithm is demonstrated using data acquired by the airborne passive and active L-band system from field campaigns and also by simulated global dataset. Results indicate that the algorithm has the potential to retrieve soil moisture at 9-km resolution, with the accuracy required for SMAP, over regions having vegetation up to 5-kg/m(2) vegetation water content. The results show a reduction in root mean square error of > 0.02 cm(3)/cm(3) volumetric soil moisture (40% improvement in the statistics) from the minimum performance defined as the soil moisture retrieved using radiometer measurements re-sampled to the intermediate scale.
引用
收藏
页码:2018 / 2028
页数:11
相关论文
共 16 条
[1]  
[Anonymous], 2007, EARTH SCI APPL SPACE, P428
[2]  
Bindlish R., 2009, IEEE GEOSCI REMOTE S, V6, P326
[3]   An Algorithm for Merging SMAP Radiometer and Radar Data for High-Resolution Soil-Moisture Retrieval [J].
Das, Narendra N. ;
Entekhabi, Dara ;
Njoku, Eni G. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2011, 49 (05) :1504-1512
[4]   The Soil Moisture Active Passive (SMAP) Mission [J].
Entekhabi, Dara ;
Njoku, Eni G. ;
O'Neill, Peggy E. ;
Kellogg, Kent H. ;
Crow, Wade T. ;
Edelstein, Wendy N. ;
Entin, Jared K. ;
Goodman, Shawn D. ;
Jackson, Thomas J. ;
Johnson, Joel ;
Kimball, John ;
Piepmeier, Jeffrey R. ;
Koster, Randal D. ;
Martin, Neil ;
McDonald, Kyle C. ;
Moghaddam, Mahta ;
Moran, Susan ;
Reichle, Rolf ;
Shi, J. C. ;
Spencer, Michael W. ;
Thurman, Samuel W. ;
Tsang, Leung ;
Van Zyl, Jakob .
PROCEEDINGS OF THE IEEE, 2010, 98 (05) :704-716
[5]   PASSIVE MICROWAVE SENSING OF SOIL-MOISTURE UNDER VEGETATION CANOPIES [J].
JACKSON, TJ ;
SCHMUGGE, TJ ;
WANG, JR .
WATER RESOURCES RESEARCH, 1982, 18 (04) :1137-1142
[6]   VEGETATION EFFECTS ON THE MICROWAVE EMISSION OF SOILS [J].
JACKSON, TJ ;
SCHMUGGE, TJ .
REMOTE SENSING OF ENVIRONMENT, 1991, 36 (03) :203-212
[7]   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
[8]   A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data [J].
Kim, Yunjin ;
van Zyl, Jakob J. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (08) :2519-2527
[9]   High-resolution change estimation of soil moisture using L-band radiometer and radar observations made during the SMEX02 experiments [J].
Narayan, Ujjwal ;
Lakshmi, Venkataraman ;
Jackson, Thomas J. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2006, 44 (06) :1545-1554
[10]   Soil moisture retrieval from AMSR-E [J].
Njoku, EG ;
Jackson, TJ ;
Lakshmi, V ;
Chan, TK ;
Nghiem, SV .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (02) :215-229