First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry

Authors: PENG, Z. - Chinese Academy Of Sciences; ZHAO, T. - Institute Of Remote Sensing And Digital Earth, Chinese Academy Of Sciences; SHI, J. - Chinese Academy Of Sciences; HU, L. - Nanchang University; RODRIGUEZ-FERNANDEZ, N. - Center For The Study Of The Biosphère From Space(CESBIO); WIGNERON, J.-P. - University Of Bordeaux; Jackson, Thomas; WALKER, J. - Monash University; Cosh, Michael; YANG, K. - Tsinghua University; LU, H. - Tsinghua University; BAI, Y. - Chinese Academy Of Sciences; YAO, P. - Chinese Academy Of Sciences; ZHENG, J. - Hohai University; WEI, Z. - Tsinghua University

Submitted to: IEEE Transactions on Geoscience and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/18/2023
Publication Date: 12/26/2023
Citation: Peng, Z., Zhao, T., Shi, J.C., Hu, L., Rodriguez-Fernandez, N., Wigneron, J., Jackson, T.J., Walker, J., Cosh, M.H., Yang, K., Lu, H., Bai, Y., Yao, P., Zheng, J., Wei, Z. 2023. First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry. IEEE Transactions on Geoscience and Remote Sensing. 302. Article e113970. https://doi.org/10.1016/j.rse.2023.113970.
DOI: https://doi.org/10.1016/j.rse.2023.113970

Interpretive Summary: Microwave satellite remote sensing is capable of observing variations in soil moisture and vegetation water content. In order to compute both of these land surface variables, it is often necessary to have a significant amount of ancillary land surface information. A new methodology is being proposed which will dispense with this requirement and produce soil moisture and a vegetation optical depth (similar to water content) with only the observation data from the microwave satellite. This methodology is tested against in situ data resources around the world. There is reasonable agreement and the product is considered a worthy first step toward more robust remote sensing retrievals of these variables.

Technical Abstract: Retrieving soil moisture (SM) and vegetation optical depth (VOD) using passive microwave remote sensing at L-band (1.4 GHz) is significantly valuable for a better understanding of water exchanges at the land-atmosphere interface. Current retrieval algorithms generally ignore the polarization dependence of vegetation effects, while this study presents a new SM and polarization-dependent VOD product using the multi-channel collaborative algorithm (MCCA), based on the dual polarized L-band NASA Soil Moisture Active Passive (SMAP) observations at mono-angle (40°). The MCCA does not require any auxiliary data on vegetation or soil moisture to constrain the retrieval process but uses an information theory-based technology to obtain the surface roughness and effective scattering albedo pixel-wisely at a global scale. Intercomparison with other SM and VOD products (MT-DCA, and DCA, SCA-H, and SCA-V from SMAP Level-3 products version 7) shown an analogous spatial pattern. The MCCA derived SM has the lowest ubRMSD (about 0.058 m3/m3) followed by DCA (0.061 m3/m3), and an overall Pearson’s correlation coefficient of 0.702 (DCA performs best with R=0.746) when evaluated against in situ observations from 19 dense soil moisture networks. The MCCA generates VOD at both vertical (V-) and horizontal (H-) polarization, while magnitude of this polarized VODs is lower than other products. MCCA polarized VODs are found to have a good linearity with the live biomass and canopy height, but partial saturation exists in the relationship with live biomass at tropical forests but not canopy height. The polarization difference of VODs mainly located at densely vegetated and arid areas. It is worth to note that this new SM and polarized VODs may improve the understanding of the water-transport process in the soil-vegetation continuum.