DocumentCode :
1358813
Title :
Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S.
Author :
Jackson, Thomas J. ; Bindlish, Rajat ; Cosh, Michael H. ; Zhao, Tianjie ; Starks, Patrick J. ; Bosch, David D. ; Seyfried, Mark ; Moran, Mary Susan ; Goodrich, David C. ; Kerr, Yann H. ; Leroux, Delphine
Author_Institution :
Hydrol. & Remote Sensing Lab., U.S. Dept. of Agric., Beltsville, MD, USA
Volume :
50
Issue :
5
fYear :
2012
fDate :
5/1/2012 12:00:00 AM
Firstpage :
1530
Lastpage :
1543
Abstract :
Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn, support the widespread utilization of the data. This is especially important since SMOS utilizes a new sensor technology and is the first passive L-band system in routine operation. In this paper, we contribute to the validation of SMOS using a set of four in situ soil moisture networks located in the U.S. These ground-based observations are combined with retrievals based on another satellite sensor, the Advanced Microwave Scanning Radiometer (AMSR-E). The watershed sites are highly reliable and address scaling with replicate sampling. Results of the validation analysis indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with the in situ data and AMSR-E retrievals. The overall root-mean-square error of the SMOS soil moisture estimates is 0.043 m3/m3 for the watershed networks (ascending). There are bias issues at some sites that need to be addressed, as well as some outlier responses. Additional statistical metrics were also considered. Analyses indicated that active or recent rainfall can contribute to interpretation problems when assessing algorithm performance, which is related to the contributing depth of the satellite sensor. Using a precipitation flag can improve the performance. An investigation of the vegetation optical depth (tau) retrievals provided by the SMOS algorithm indicated that, for the watershed sites, these are not a reliable source of information about the vegetation canopy. The SMOS algorithms will continue to be refined as feedback from validation is evaluated, and it is expe- ted that the SMOS estimates will improve.
Keywords :
atmospheric boundary layer; atmospheric precipitation; hydrological techniques; moisture; radiometry; remote sensing; soil; statistical analysis; vegetation; water resources; AMSR-E retrieval; SMOS; USA; advanced microwave scanning radiometer; algorithm performance; passive microwave sensor; precipitation flag; retrieval method; sensor technology; soil moisture; statistical metrics; validation analysis; vegetation canopy; vegetation optical depth retrieval; watershed networks; Accuracy; Microwave radiometry; SMOS mission; Satellite broadcasting; Satellites; Advanced Microwave Scanning Radiometer (AMSR-E); Soil Moisture and Ocean Salinity (SMOS); passive microwave; soil moisture; validation;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2011.2168533
Filename :
6058645
Link To Document :
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