Soil moisture mapping and AMSR-E validation using the PSR in SMEX02

被引:87
作者
Bindlish, Rajat
Jackson, Thomas J.
Gasiewski, Albin J.
Klein, Marian
Njoku, Eni G.
机构
[1] USDA, ARS, SSAI, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA
[2] NOAA, Environm Technol Lab, Boulder, CO 80303 USA
[3] Jet Propuls Lab, Pasadena, CA USA
基金
美国国家航空航天局;
关键词
microwave remote sensing; soil moisture; AMSR; PSR;
D O I
10.1016/j.rse.2005.02.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Field experiments (SMEX02) were conducted to evaluate the effects of dense agricultural crop conditions on soil moisture retrieval using passive microwave remote sensing. Aircraft observations were collected using a new version of the Polarimetric Scanning Radiometer (PSR) that provided four C band and four X band frequencies. Observations were also available from the Aqua satellite Advanced Microwave Scanning Radiometer (AMSR-E) at these same frequencies. SMEX02 was conducted over a three-week period during the summer near Ames, Iowa. Corn and soybeans dominate the region. During the study period the corn was approaching its peak water content state and the soybeans were at the mid point of the growth cycle. Aircraft observations are compared to ground observations. Subsequently models are developed to describe the effects of corn and soybeans on soil moisture retrieval. Multiple altitude aircraft brightness temperatures were compared to AMSR-E observations to understand brightness temperature scaling and provide validation. The X-band observations from the two sensors were in reasonable agreement. The AMSR-E C-band observations were contaminated with anthropogenic RFI, which made comparison to the PSR invalid. Aircraft data along with ancillary data were used in a retrieval algorithm to map soil moisture. The PSR estimated soil moisture retrievals on a field-by-field comparison had a standard error of estimate (SEE) of 5.5%. The error reduced when high altitude soil moisture estimates were aggregated to 25 km resolution (same as AMSR-E EASE grid product resolution) (SEE similar to 2.85%). These soil moisture products provide a validation of the AMSR retrievals. PSR/CX soil moisture images show spatial and temporal patterns consistent with meteorological and soil conditions. The dynamic range of the PSR/CX observations indicates that reasonable soil moisture estimates can be obtained from AMSR, even in areas of high vegetation biomass content (similar to 4-8 kg/m2). (c) 2005 Elsevier Inc. All rights reserved.
引用
收藏
页码:127 / 139
页数:13
相关论文
共 50 条
[21]   Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches [J].
Im, Jungho ;
Park, Seonyoung ;
Rhee, Jinyoung ;
Baik, Jongjin ;
Choi, Minha .
ENVIRONMENTAL EARTH SCIENCES, 2016, 75 (15)
[22]   Near-surface soil moisture estimation using AMSR-E brightness temperature [J].
Al-Shrafany, D. ;
Han, D. ;
Rico-Ramirez, M. A. .
REMOTE SENSING AND HYDROLOGY, 2012, 352 :11-15
[23]   Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches [J].
Jungho Im ;
Seonyoung Park ;
Jinyoung Rhee ;
Jongjin Baik ;
Minha Choi .
Environmental Earth Sciences, 2016, 75
[24]   Remotely Sensed Soil Moisture over Australia from AMSR-E [J].
Draper, C. S. ;
Walker, J. P. ;
Steinle, P. J. ;
de Jeu, R. A. M. ;
Holmes, T. R. H. .
MODSIM 2007: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION: LAND, WATER AND ENVIRONMENTAL MANAGEMENT: INTEGRATED SYSTEMS FOR SUSTAINABILITY, 2007, :1756-1762
[25]   Retrieval of Bare Surface Soil Moisture from AMSR-E Data [J].
Han, Nianlong ;
Chen, Shengbo ;
Wang, Zijun .
2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 2, 2010, :67-72
[26]   A comparison of in situ precipitation with soil moisture retrieved from AMSR-E [J].
Mikai, H ;
Arai, Y ;
Mutoh, T ;
Imaoka, K ;
Shibata, A .
IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, :3460-3461
[27]   Evaluation of AMSR-E——Derived Soil Moisture over Northern China [J].
ZHANG AnZhi JIA GenSuo WANG HeSong ZHAO TianBao FENG JinMing and MA ZhuGuo Key Laboratory of Regional ClimateEnvironment Research for Temperate East AsiaInstitute of Atmospheric PhysicsChinese Academy of SciencesBeijing China Graduate University of Chinese Academy of SciencesBeijing China .
AtmosphericandOceanicScienceLetters, 2011, 4 (04) :223-228
[28]   A New Evapotranspiration Model Accounting for Advection and Its Validation during SMEX02 [J].
Yang, Yongmin ;
Su, Hongbo ;
Zhang, Renhua ;
Wu, Jianjun ;
Qi, Jianwei .
ADVANCES IN METEOROLOGY, 2013, 2013
[29]   Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe [J].
Brocca, L. ;
Hasenauer, S. ;
Lacava, T. ;
Melone, F. ;
Moramarco, T. ;
Wagner, W. ;
Dorigo, W. ;
Matgen, P. ;
Martinez-Fernandez, J. ;
Llorens, P. ;
Latron, J. ;
Martin, C. ;
Bittelli, M. .
REMOTE SENSING OF ENVIRONMENT, 2011, 115 (12) :3390-3408
[30]   Retrieval of soil moisture from passive and active L/S band sensor (PALS) observations during the Soil Moisture Experiment in 2002 (SMEX02) [J].
Narayan, U ;
Lakshmi, V ;
Njoku, EG .
REMOTE SENSING OF ENVIRONMENT, 2004, 92 (04) :483-496