Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches-Reference-Cited by-同舟云学术

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Published:2019-08 Issue: Volume:274 Page:144-159
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Cai Yaping^ORCID,Guan Kaiyu,Lobell David^ORCID,Potgieter Andries B.,Wang Shaowen,Peng Jian,Xu Tianfang^ORCID,Asseng Senthold,Zhang Yongguang,You Liangzhi^ORCID,Peng Bin^ORCID

Funder

Blue Waters Professorship and NASA New Investigator Award

University of Illinois ACES Future Interdisciplinary Research Explorations

Illinois Distinguished Graduate Fellowship

National Science Foundation

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference114 articles.

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5. An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with U.S. drought monitor classifications;Anderson;J. Hydrometeorol.,2013

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