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Session
Presentation | GC33K: Remote Sensing for Sustainable Agriculture III Poster
Poster
GC33K-0922: Sub-Field Crop Yield Prediction Using Satellite-Based Machine Learning: A Multi-Year Analysis with USDA-ARS Ground-Truth Data
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Schedule
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Credits
Wed, Dec 17
Board 0922‚ Hall EFG (Poster Hall)
2:15pm - 5:45pm (Central)
NOLA CC
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Annelise Holguin
Texas State University
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Author(s):
Annelise Holguin
, Texas State University
(First Author, Presenting Author)
Eunsang Cho
, Texas State University
Jisung Chang
, USDA ARS
Feng Gao
, USDA-ARS Hydrology and Remote Sensing Laboratory
David Johnson
, USDA National Agricultural Statistics Service
Martha Anderson
, USDA ARS
Haoteng Zhao
, USDA-ARS Hydrology and Remote Sensing Laboratory
Richard Cirone
, Iowa State University
Martha Anderson
, USDA ARS
View Abstract
Scientific Discipline
Global Environmental Change
Suggested Itineraries
Biochemistry
Climate Change and Global Policy
Global Impacts‚ Solutions‚ & Policies
Machine Learning and AI
Open Science and Open Data
Neighborhood
Earth Covering
Type
Poster
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Main Session
Poster
GC33K: Remote Sensing for Sustainable Agriculture III Poster
2:15pm-5:45pm Dec 17 (Central)
Sheng Wang
Discussion
