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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 #364901
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: An L-band brightness temperature disaggregation method using S-band radiometer data for the Water Cycle Observation Mission (WCOM)

Author
item YAO, P. - Tsinghua University
item SHI, J.C. - Chinese Academy Of Sciences
item Cosh, Michael
item BINDISH, R. - Goddard Space Flight Center
item LU, H. - Hohai University

Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/27/2019
Publication Date: 6/28/2019
Citation: Yao, P., Shi, J., Cosh, M.H., Bindish, R., Lu, H. 2019. An L-band brightness temperature disaggregation method using S-band radiometer data for the Water Cycle Observation Mission (WCOM). IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(9):3184-3193. https://doi.org/10.1109/JSTARS.2019.2922780.
DOI: https://doi.org/10.1109/JSTARS.2019.2922780

Interpretive Summary: The radiometric spectrum contains valuable information for estimating surface soil moisture via remote sensing platforms. The L and S bands specifically have demonstrated that they can produce an accurate soil moisture product, hence several future satellite platforms plan to make use of these bands for higher resolution land surface monitoring, including the Water Cycle Observation Mission (WCOM) in China and the NASA-ISRO Synthetic Aperture Radar (NISAR) mission. There is a need to develop algorithms for blending these two bands for optimal soil moisture estimation. Using experimental data, a study was initiated to develop a joint L and S band soil moisture algorithm over agricultural fields. It was demonstrated to be feasible within the errors which are currently acceptable in the remote sensing community and this study will help to spur the further development of dual band microwave remote sensing products.

Technical Abstract: The Water Cycle Observation Mission (WCOM) will build upon previous L and C band passive microwave soil moisture satellite missions. WCOM will consist of a passive microwave synthetic aperture radiometer operating at L, S, and C bands. The WCOM requirements for passive soil moisture are to estimate soil moisture in the top 5 cm of soil layer with an error less than 0.04 m3/m3, at 15 km resolution and with a 3-day revisit. A new set of algorithms for these multi-frequency platforms will need to be developed for estimating the data products at the desired resolution. To accomplish this, a brightness temperature (TB) downscaling methodology is developed that uses passive S-band TB (30 km) to downscale L-band TB (50 km) and to estimate soil moisture at a 30 km resolution, based on the linear relationships between the passive signals of L-band and S-band. To test this downscaling method, analysis was performed using PALS data from the Soil Moisture Experiments in 2002 (SMEX02). For this study, 4 km L-band observations were downscaled to 800 m. The root mean square errors (RMSE) between the downscaled TBL at 800m with the observed TBL at 800m are 2.63 K and 1.60 K for H and V polarizations respectively. The results also showed that it was possible to use these disaggregated TB to estimate soil moisture to meet the mission requirement of 0.04 m3/m3. These results showed that we can obtain higher resolution soil moisture from L band passive TB with a high accuracy (<0.04 m3/m3) by using S-band information.