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An Initial Assessment of a SMAP Soil Moisture Disaggregation Scheme Using TIR Surface Evaporation Data over the Continental United StatesThe Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of −0.022 and −0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.
Document ID
20180002110
Acquisition Source
Marshall Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Vikalp Mishra
(University of Alabama in Huntsville Huntsville, Alabama, United States)
W Lee Ellenburg
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Robert E Griffin
(University of Alabama in Huntsville Huntsville, Alabama, United States)
John R Mecikalski
(University of Alabama in Huntsville Huntsville, Alabama, United States)
James F Cruise
(University of Alabama in Huntsville Huntsville, Alabama, United States)
Christopher R Hain
(Marshall Space Flight Center Redstone Arsenal, Alabama, United States)
Martha C Anderson ORCID
(United States Department of Agriculture Washington D.C., District of Columbia, United States)
Date Acquired
March 26, 2018
Publication Date
February 16, 2018
Publication Information
Publication: International Journal of Applied Earth Observation and Geoinformation
Publisher: Elsevier
Volume: 68
Issue Publication Date: June 1, 2018
ISSN: 0303-2434
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
MSFC-E-DAA-TN53221
Funding Number(s)
PROJECT: SCMD-EarthScienceSystem_281945
WBS: WBS 281945.02.80.01.36
CONTRACT_GRANT: NNM11AA01A
CONTRACT_GRANT: NNX15AN58H
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Keywords
Disaggregation
Soil Moisture
Land Surface
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