L-band-like Soil Moisture and Vegetation Optical Depth Can be Retrieved From C-band Soil Moisture data (A2S-RDCA, A2S-NNP)

This data contains L-band-like Soil Moisture (SM) and Vegetation Optical Depth (VOD) retrieved from Advanced SCATterometer (ASCAT). To retrieve L-band-like VOD and SM, (1) ASCAT SM has converted to SMAP SCA-V and SCA-H using an image-to-image translation algorithm (called ASCAT2SMAP; please refer to Lee et al., 2024) (2) Forward simulation of V- and H-polarized brightness temperature has been conducted based on SMAP SCA-V and SCA-H parameters (Chan et al., 2016). (3) SM and VOD are retrieved using the Regularized Dual Channel Algorithm (Chaubell et al., 2021) with two retrieval parameter configurations. (3-1) A2S-RDCA: Similar parameters of ⍵ and h used in original RDCA. (3-2) A2S-NNP: A newly developed ⍵ and h parameters by inversely tracing a deep-neural network-based SM estimates (Lee et al., 2024b) When retrieved L-band like VOD and SM from ASCAT are compared to the original data (and to in situ measurement for SM), they show good ability to track SM and ability to track temporal variability of VOD. References Lee, J., Jung, S., & Im, J. (2024). ASCAT2SMAP: image-to-image translation to obtain L-band-like soil moisture from C-band satellite data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Chan, S. K., Bindlish, R., O'Neill, P. E., Njoku, E., Jackson, T., Colliander, A., ... & Kerr, Y. (2016). Assessment of the SMAP passive soil moisture product. IEEE Transactions on Geoscience and Remote Sensing, 54(8), 4994-5007. Chaubell, J., Yueh, S., Dunbar, R. S., Colliander, A., Entekhabi, D., Chan, S. K., ... & Walker, J. P. (2021). Regularized dual-channel algorithm for the retrieval of soil moisture and vegetation optical depth from SMAP measurements. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 102-114. Lee, J., Im, J., Son, B., Cosio, E. G., & Salinas, N. (2024). Improved SMAP soil moisture retrieval using a deep neural network-based replacement of radiative transfer and roughness model. IEEE Transactions on Geoscience and Remote Sensing.