Back to Search Start Over

Assessment of the SMAP Passive Soil Moisture Product

Authors :
Jeffrey P. Walker
Rajat Bindlish
Fan Chen
Eni G. Njoku
Eric E. Small
M. Thibeault
Michael H. Cosh
Yann Kerr
John H. Prueger
Peggy O'Neill
Xiaoling Wu
Steven Chan
Michael A. Palecki
Dara Entekhabi
Mark S. Seyfried
Thomas J. Jackson
Jean-Christophe Calvet
David D. Bosch
José Martínez-Fernández
Simon Yueh
David C. Goodrich
Jeffrey R. Piepmeier
Aaron A. Berg
Tracy Rowlandson
A. Pacheco
A. Gonzalez-Zamora
Marek Zreda
Scott Dunbar
Wade T. Crow
Andreas Colliander
Patrick J. Starks
Todd G. Caldwell
Heather McNairn
Mariko Burgin
Source :
IEEE Transactions on Geoscience and Remote Sensing. 54:4994-5007
Publication Year :
2016
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2016.

Abstract

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.

Details

ISSN :
15580644 and 01962892
Volume :
54
Database :
OpenAIRE
Journal :
IEEE Transactions on Geoscience and Remote Sensing
Accession number :
edsair.doi...........b48c81e24211b61d309623b0a12c5933
Full Text :
https://doi.org/10.1109/tgrs.2016.2561938