Jul 23, 2023 · Accurate global soil moisture (SM) data are crucial for modeling land surface hydrological cycles and monitoring climate change.
Accurate global soil moisture (SM) data are crucial for modeling land surface hydrological cycles and monitoring climate change.
Accurate global soil moisture (SM) data are crucial for modeling land surface hydrological cycles and monitoring climate change.
Read a pre-publication review of Using Robust Regression to Retrieve Soil Moisture from CyGNSS Data on Publons.
Oct 15, 2023 · After removing open water, a multiple linear regression model is created to retrieve SM by combining the SST and vegetation optical depth (VOD) ...
The flowchart for roughness LUT estimation, (dB). Using Robust Regression to Retrieve Soil Moisture from CyGNSS Data. Article. Full-text available. Jul 2023.
The soil moisture retrieval algorithm is an update of the previous version developed by UCAR-CU using a linear regression of CYGNSS angle-normalized effective ...
Missing: Robust | Show results with:Robust
9 hours ago · Soil moisture is a crucial component of the global terrestrial ecosystem water vapor cycle, and higher spatial-temporal soil moisture.
Apr 19, 2022 · In this study, a new scheme is proposed for retrieving soil moisture from the Cyclone GNSS (CyGNSS) data. The variation of CyGNSS-derived Δ Γ is ...
Jan 1, 2024 · In this study, the SSM is retrieved from different Cyclone GNSS (CYGNSS) SSM retrieval models formed with different SSM reference data products.
Missing: Robust | Show results with:Robust