ASCAT2SMAP-V2: Deriving L-band-like Soil Moisture and Vegetation Optical Depth from C-band Satellite Observations

This dataset contains L-band-like soil moisture (SM) and vegetation optical depth (VOD) derived from Advanced Scatterometer (ASCAT) observations. The L-band-like SM and VOD products were generated through the following procedure: ASCAT SM was translated into SMAP-like SCA-V and SCA-H SM using the ASCAT2SMAP (A2S) image-to-image translation framework (Lee et al., 2024a). V- and H-polarized L-band-like brightness temperatures were forward-simulated from the translated SCA-V and SCA-H SM using the corresponding SMAP Single-Channel Algorithm parameterizations. SM and VOD were jointly retrieved from the simulated dual-polarized brightness temperatures using the regularized Dual-Channel Algorithm (DCA; Chaubell et al., 2022) under two parameter configurations: A2S-DCA uses the scattering albedo (ω) and surface roughness (h) parameters adopted from the operational SMAP DCA product. A2S-NNP uses updated ω and h parameters derived from SMAP-NN, a deep-neural-network-based SM retrieval framework (Lee et al., 2024b). Comparisons with the corresponding SMAP products—and, for SM, with in situ measurements—demonstrate that the resulting products effectively capture SM variability and the temporal dynamics of L-band-like VOD. Nevertheless, the reconstructed VOD should be interpreted as a SMAP-like vegetation signal rather than as an independently validated long-term VOD record. References Lee, J., Jung, S., & Im, J. (2024a). 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. Chaubell, J., Yueh, S., Dunbar, R. S., Colliander, A., Entekhabi, D., Chan, S. K., et al. (2022). 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. (2024b). 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.