TY - JOUR
T1 - Improved SMAP dual-channel algorithm for the retrieval of soil moisture
AU - Chaubell, Mario Julian
AU - Yueh, Simon H.
AU - Scott Dunbar, R.
AU - Colliander, Andreas
AU - Chen, Fan
AU - Chan, Steven K.
AU - Entekhabi, Dara
AU - Bindlish, Rajat
AU - O'Neill, Peggy E.
AU - Asanuma, Jun
AU - Berg, Aaron A.
AU - Bosch, David D.
AU - Caldwell, Todd
AU - Cosh, Michael H.
AU - Collins, Chandra Holifield
AU - Martinez-Fernandez, Jose
AU - Seyfried, Mark
AU - Starks, Patrick J.
AU - Su, Zhongbo
AU - Thibeault, Marc
AU - Walker, Jeffrey
PY - 2020/6
Y1 - 2020/6
N2 - The soil moisture active passive (SMAP) mission was designed to acquire L-band radiometer measurements for the estimation of soil moisture (SM) with an average ubRMSD of not more than 0.04 m3 m-3 volumetric accuracy in the top 5 cm for vegetation with a water content of less than 5 kg m2. Single-channel algorithm (SCA) and dual-channel algorithm (DCA) are implemented for the processing of SMAP radiometer data. The SCA using the vertically polarized brightness temperature (SCA-V) has been providing satisfactory SM retrievals. However, the DCA using prelaunch design and algorithm parameters for vertical and horizontal polarization data has a marginal performance. In this article, we show that with the updates of the roughness parameter $h$ and the polarization mixing parameters Q, a modified DCA (MDCA) can achieve improved accuracy over DCA; it also allows for the retrieval of vegetation optical depth (VOD or τ). The retrieval performance of MDCA is assessed and compared with SCA-V and DCA using four years (April 1, 2015 to March 31, 2019) of in situ data from core validation sites (CVSs) and sparse networks. The assessment shows that SCA-V still outperforms all the implemented algorithms.
AB - The soil moisture active passive (SMAP) mission was designed to acquire L-band radiometer measurements for the estimation of soil moisture (SM) with an average ubRMSD of not more than 0.04 m3 m-3 volumetric accuracy in the top 5 cm for vegetation with a water content of less than 5 kg m2. Single-channel algorithm (SCA) and dual-channel algorithm (DCA) are implemented for the processing of SMAP radiometer data. The SCA using the vertically polarized brightness temperature (SCA-V) has been providing satisfactory SM retrievals. However, the DCA using prelaunch design and algorithm parameters for vertical and horizontal polarization data has a marginal performance. In this article, we show that with the updates of the roughness parameter $h$ and the polarization mixing parameters Q, a modified DCA (MDCA) can achieve improved accuracy over DCA; it also allows for the retrieval of vegetation optical depth (VOD or τ). The retrieval performance of MDCA is assessed and compared with SCA-V and DCA using four years (April 1, 2015 to March 31, 2019) of in situ data from core validation sites (CVSs) and sparse networks. The assessment shows that SCA-V still outperforms all the implemented algorithms.
KW - Dual-channel algorithm (DCA)
KW - soil moisture (SM) retrieval
KW - soil moisture active passive (SMAP)
KW - vegetation optical depth (VOD) retrieval
UR - https://www.scopus.com/pages/publications/85084534988
U2 - 10.1109/TGRS.2019.2959239
DO - 10.1109/TGRS.2019.2959239
M3 - Article
AN - SCOPUS:85084534988
SN - 0196-2892
VL - 58
SP - 3894
EP - 3905
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 6
ER -