GCOM-W AMSR2 soil moisture product validation using core validation sites

Authors: BINDLISH, R. - Goddard Space Flight Center; Cosh, Michael; Jackson, Thomas; KOIKE, T. - University Of Tokyo; FUIJI, X. - Tokyo University Of Agriculture & Technology; DE JEU,, R.A.M. - Research Institute For Knowledge Systems (RIKS BV); CHAN, S. - Jet Propulsion Laboratory; ASANUMA, J. - University Of Tsukuba; BERG, A. - University Of Guelph; Bosch, David; CALDWELL, T. - University Of Texas At Austin; Holifield Collins, Chandra; MCNAIRN, H. - Agriculture And Agri-Food Canada; MARTINEZ-FERNANDEZ, J - University Of Salamanca; Prueger, John; ROWLANDSON, TRACY - University Of Guelph; Seyfried, Mark; Starks, Patrick; SU, Z. - University Of Twente; THIBEAULT, M. - Universidad Nacional Del Sur (UNS); VAN DER VELDE, R. - University Of Twente; WALKER, J. - Monash University; COOPERSMITH, E. - Collaborator

Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/1/2017
Publication Date: 1/1/2018
Citation: Bindlish, R., Cosh, M.H., Jackson, T.J., Koike, T., Fuiji, X., De Jeu,, R., Chan, S., Asanuma, J., Berg, A., Bosch, D.D., Caldwell, T., Holifield Collins, C.D., McNairn, H., Martinez-Fernandez, J., Prueger, J.H., Rowlandson, T., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., van der Velde, R., Walker, J., Coopersmith, E. 2018. GCOM-W AMSR2 soil moisture product validation using core validation sites. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(1):209-219. https://doi.org/10.1109/JSTARS.2017.2754293.
DOI: https://doi.org/10.1109/JSTARS.2017.2754293

Interpretive Summary: Core validation sites were used to assess three widely used soil moisture products derived from the Advanced Microwave Scanning Radiometer 2 (AMSR2) on the Global Change Observation Mission-Water satellite. This instrument extends the time series of twelve years established by its predecessor. Although there have been a number of validation studies involving soil moisture products derived from AMSR2, the results are often not robust enough to reliably assess performance for specific site conditions. The approach used in this investigation addresses this shortcoming by using sites that include replicate spatial in situ sampling and scaling, thus providing a more reliable estimate of the soil moisture that is used to assess the satellite products. Results indicate that two of the products had similar performance and could meet the established requirements. Establishing the performance of the soil moisture retrieval approach and linking the new instrument measurements to the preceding mission is important to its implementation in algorithms as well as long term trend assessments.This study will influence the addition of the AMSR2 data product to all future soil moisture data records, impacting hydrologic modeling, weather forecasting, and a variety of agricultural applications.

Technical Abstract: The Advanced Microwave Scanning Radiometer 2 (AMSR2) is part of the Global Change Observation Mission-Water (GCOM-W). AMSR2 has filled the gap in passive microwave observations left by the loss of the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) after almost 10 years of observations. Both missions provide brightness temperature observations that are used to retrieve soil moisture estimates at the near surface. A merged AMSR-E and AMSR2 data product will help build a consistent long-term dataset; however, before this can be done, it is necessary to conduct a thorough validation and assessment of the AMSR2 soil moisture products. This study focuses on the validation of the AMSR2 soil moisture products by comparison with in situ reference data from a set of core validation sites around the world. A total of three soil moisture products that rely on different algorithms were evaluated; the Japan Aerospace Exploration Agency (JAXA) soil moisture algorithm, the Land Parameter Retrieval Model (LPRM), and the Single Channel Algorithm (SCA). JAXA, SCA and LPRM soil moisture estimates capture the overall climatological features. The spatial features of the three products have similar overall spatial structure. The JAXA soil moisture product shows a lower dynamic range in the retrieved soil moisture with a satisfactory performance matrix when compared to in situ observations. The SCA performs well over low and moderately vegetated areas. The LPRM product has a large dynamic range compared to in situ observations with a wet. Some of the error is due to the difference in observation depth between the in situ sensors (5 cm) and satellite estimates (1 cm). Results indicate that overall the JAXA and SCA have the best performance based upon the metrics considered.