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Abstract: Assessing Performance of Remote-Sensing Based Machine Learning Approaches for Soil Moisture Retrieval Across Agricultural Landscapes Using ISMN (AGU25)

Assessing Performance of Remote-Sensing Based Machine Learning Approaches for Soil Moisture Retrieval Across Agricultural Landscapes Using ISMN

Veda Sunkara, Stanford University, Stanford, CA, United States, Siddharth Sachdeva, Stanford University, Stanford, United States, David B Lobell, Stanford University, Department of Earth System Science & Center on Food Security and the Environment, Stanford, United States and Alexandra G Konings, Stanford University, Earth System Science, Stanford, United States
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