Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches
University of Illinois Urbana-Champaign · National Center for Supercomputing Applications · +9 more institutions
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Abstract
No abstract available for this paper.
Citation impact
568
total citations
- FWCI
- 41.28
- Percentile
- 100%
- References
- 122
Citations per year
Authors
11- YCYaping Cai
University of Illinois Urbana-Champaign, National Center for Supercomputing Applications
- KGKaiyu GuanCorresponding
Illinois Department of Natural Resources, University of Illinois Urbana-Champaign, National Center for Supercomputing Applications
- DBDavid B. Lobell
Stanford University
- APAndries Potgieter
The University of Queensland, Agriculture and Food
- SWShaowen Wang
University of Illinois Urbana-Champaign, National Center for Supercomputing Applications
Topics & keywords
Topics
Keywords
- Machine learning
- Crop yield
- Yield (engineering)
- Lasso (programming language)
- Satellite
- Empirical modelling
- Random forest
- Support vector machine
UN Sustainable Development Goals
- Climate action
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