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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #286555

Title: Refinement of SMOS multi-angular brightness temperature toward soil moisture retrieval and its analysis over reference targets

Author
item ZHAO, TIANJIE - Chinese Academy Of Sciences
item SHI, JIANCHENG - Chinese Academy Of Sciences
item BINDLISH, RAJAT - Science Systems, Inc
item Jackson, Thomas
item KERR, YANN - Collaborator
item Cosh, Michael
item CUI, QIAN - Chinese Academy Of Sciences
item LI, YUNQING - Chinese Academy Of Sciences
item XIONG, CHUAN - Chinese Academy Of Sciences
item CHE, TAO - Chinese Academy Of Sciences

Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/12/2014
Publication Date: 2/1/2015
Publication URL: https://handle.nal.usda.gov/10113/59883
Citation: Zhao, T., Shi, J., Bindlish, R., Jackson, T.J., Kerr, Y., Cosh, M.H., Cui, Q., Li, Y., Xiong, C., Che, T. 2015. Refinement of SMOS multi-angular brightness temperature toward soil moisture retrieval and its analysis over reference targets. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 8:589-603.

Interpretive Summary: The baseline soil moisture retrieval algorithm under consideration for operational use by the Soil Moisture Active Passive (SMAP) satellite was implemented and validated through an innovative use of another satellite that is currently in operation. Although SMAP and the Soil Moisture Ocean Salinity (SMOS) satellite utilize vastly different technologies, by using the techniques developed here it is possible to use SMOS as a simulator of SMAP. This real world data allowed thorough examination of the SMAP baseline algorithm under consideration. As a result, the SMAP project can now select this baseline algorithm and focus research and development on other priorities. Having simulated SMAP products prior to launch will allow the project to advance development of applications in agricultural hydrology, drought, flood, and climate analyses.

Technical Abstract: The Soil Moisture Active Passive (SMAP) satellite is scheduled for launch in 2014. It will provide global measurements of soil moisture with a 3-day revisit time and accuracy of 0.04 m3/m3 at three spatial resolutions; 40 km, 10 km and 3 km. Of these, the 40 km resolution soil moisture product, which is primarily based on the passive microwave observations, is the only one with heritage from other satellite instruments. Several soil moisture retrieval algorithm approaches are under consideration for the SMAP radiometer product. In this paper we exploit the heritage and availability of the L-band brightness temperature now being provided by the Soil Moisture Ocean Salinity (SMOS) satellite to evaluate the baseline SMAP algorithm that is referred to as the Single Channel Algorithm (SCA). A challenge to this objective was the restructuring of the brightness temperature data of SMOS to simulate SMAP data. Output of the potential radiometer-only SMAP SCA algorithm was compared to in situ measurements from established validation sites. Because of its unique configuration, SMOS is able to implement a soil moisture algorithm that is not compatible with SMAP. However, the SMOS soil moisture retrievals are also a valuable tool in assessing the alternative SMAP simulated products on a global scale than in situ sites allow. The global soil moisture patterns from the SMOS and SCA retrievals are consistent with each other and are able to capture the climatological patterns. The SMOS and SCA retrievals differ significantly over forested areas. Over the forested areas SMOS retrievals are significantly lower than the SCA soil moisture retrievals. The SMOS soil moisture product, which exploits multiple incidence angle observations, compares well with the ground-based observations (Root Mean Square Error-RMSE 0.043 m3/m3 (ascending) and 0.047 m3/m3 (descending)). The alternative SMAP compatible algorithm also performed well (RMSE 0.040 m3/m3 (ascending) and 0.043 m3/m3 (descending)). These results indicate that SMAP will be able to meet its accuracy requirements. This study will contribute to both the selection and refinement of the SMAP radiometer level 2 pre-launch algorithms for soil moisture.