Abstract: Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia (2016 AGU Fall Meeting)

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

Seongkyun Kim¹, Hyunglok Kim², Minha Choi¹ and Kiyoung Kim³, (1)Sungkyunkwan University, Water Resources and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Suwon, Korea, Republic of (South), (2)Sungkyunkwan University, Water Resources and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Suwon, Gyeonggi-do, Korea, Republic of (South), (3)Sungkyunkwan University, Suwon, Gyeonggi-do, Korea, Republic of (South)
Scientific Team Name: Water Resource and Remote Sensing Lab, Sungkyunkwan university

Back to: Soil State Characteristics: From Observations to Data Assimilation and Modeling I Posters