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Abstract: Sub-Field Crop Yield Prediction Using Satellite-Based Machine Learning: A Multi-Year Analysis with USDA-ARS Ground-Truth Data (AGU25)

Sub-Field Crop Yield Prediction Using Satellite-Based Machine Learning: A Multi-Year Analysis with USDA-ARS Ground-Truth Data

Annelise Holguin1, Dr. Eunsang Cho, Ph.D.2, Simon Kraatz3, Dr. Jisung Chang3, Martha Anderson3, Feng Gao4, David Johnson5, Haoteng Zhao4 and Richard Cirone6, (1)Texas State University, Geography and Environmental Studies, San Marcos, United States, (2)Texas State University, Department of Civil Engineering, San Marcos, United States, (3)USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, United States, (4)USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, United States, (5)USDA National Agricultural Statistics Service, Washington, DC, United States, (6)Iowa State University, Ames, IA, United States
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