articleTop 1% cited
Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches
Agricultural and Forest Meteorology · 2019 · Vol. 274 · pp. 144–159
Yaping Cai(University of Illinois Urbana-Champaign)Kaiyu Guan✉(Illinois Department of Natural Resources)David B. Lobell(Stanford University)Andries Potgieter(The University of Queensland)Shaowen Wang(University of Illinois Urbana-Champaign)Jian Peng(University of Illinois Urbana-Champaign)Tianfang Xu(Utah State University)Senthold Asseng(University of Florida)Yongguang Zhang(Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)Liangzhi You(International Food Policy Research Institute)Bin Peng(Illinois Department of Natural Resources)
Remote Sensing in AgricultureClimate change impacts on agriculturePlant Water Relations and Carbon DynamicsMachine learningCrop yieldYield (engineering)Lasso (programming language)SatelliteEmpirical modellingRandom forestSupport vector machinePredictive modellingEnvironmental science
Funding
- National Science Foundation
- National Aeronautics and Space Administration
- European Organization for the Exploitation of Meteorological Satellites
- University of Illinois at Urbana-Champaign
Citations
560
FWCI
40.97
field-weighted impact
References
122
Percentile
100%
vs. same field & year
Citations per year
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