학술논문
Regularized Dual-Channel Algorithm for the Retrieval of Soil Moisture and Vegetation Optical Depth From SMAP Measurements
Document Type
Periodical
Author
Chaubell, J.; Yueh, S.; Dunbar, R.S.; Colliander, A.; Entekhabi, D.; Chan, S.K.; Chen, F.; Xu, X.; Bindlish, R.; O'Neill, P.; Asanuma, J.; Berg, A.A.; Bosch, D.D.; Caldwell, T.; Cosh, M.H.; Collins, C.H.; Jensen, K.H.; Martinez-Fernandez, J.; Seyfried, M.; Starks, P.J.; Su, Z.; Thibeault, M.; Walker, J.P.
Source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 15:102-114 2022
Subject
Language
ISSN
1939-1404
2151-1535
2151-1535
Abstract
In August 2020, soil moisture active passive (SMAP) released a new version of its soil moisture and vegetation optical depth (VOD) retrieval products. In this article, we review the methodology followed by the SMAP regularized dual-channel retrieval algorithm. We show that the new implementation generates SM retrievals that not only satisfy the SMAP accuracy requirements, but also show a performance comparable to the single-channel algorithm that uses the V polarized brightness temperature. Due to a lack of in situ measurements we cannot evaluate the accuracy of the VOD. In this article, we show analyses with the intention of providing an understanding of the VOD product. We compare the VOD results with those from SMOS. We also study the relation of the SMAP VOD with two vegetation parameters: tree height and biomass.