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Improving regional wheat drought risk assessment for insurance application by integrating scenario-driven crop model, machine learning, and satellite data

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  • Li, Ziyue
  • Zhang, Zhao
  • Zhang, Lingyan

Abstract

Accurate estimation of yield losses from natural disasters on a regional scale can guide agronomic management and agricultural insurance, transfer disaster risk, and ensure food security. Conventional yield losses, however, mainly depend on historical events, for which detailed records of locations and losses are unavailable.

Suggested Citation

  • Li, Ziyue & Zhang, Zhao & Zhang, Lingyan, 2021. "Improving regional wheat drought risk assessment for insurance application by integrating scenario-driven crop model, machine learning, and satellite data," Agricultural Systems, Elsevier, vol. 191(C).
    • Handle: RePEc:eee:agisys:v:191:y:2021:i:c:s0308521x21000949
    DOI: 10.1016/j.agsy.2021.103141
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    References listed on IDEAS

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    Cited by:

    1. Beatrice Monteleone & Iolanda Borzí & Brunella Bonaccorso & Mario Martina, 2023. "Quantifying crop vulnerability to weather-related extreme events and climate change through vulnerability curves," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 2761-2796, April.
    2. Riao, Dao & Guga, Suri & Bao, Yongbin & Liu, Xingping & Tong, Zhijun & Zhang, Jiquan, 2023. "Non-overlap of suitable areas of agro-climatic resources and main planting areas is the main reason for potato drought disaster in Inner Mongolia, China," Agricultural Water Management, Elsevier, vol. 275(C).
    3. Liu, Cong & Li, Kaiwei & Zhang, Jiquan & Guga, Suri & Wang, Rui & Liu, Xingpeng & Tong, Zhijun, 2023. "Dynamic risk assessment of waterlogging disaster to spring peanut (Arachis hypogaea L.) in Henan Province, China," Agricultural Water Management, Elsevier, vol. 277(C).
    4. Monteleone, Beatrice & Borzí, Iolanda & Arosio, Marcello & Cesarini, Luigi & Bonaccorso, Brunella & Martina, Mario, 2023. "Modelling the response of wheat yield to stage-specific water stress in the Po Plain," Agricultural Water Management, Elsevier, vol. 287(C).
    5. Yining Ma & Suri Guga & Jie Xu & Jiquan Zhang & Zhijun Tong & Xingpeng Liu, 2021. "Comprehensive Risk Assessment of High Temperature Disaster to Kiwifruit in Shaanxi Province, China," IJERPH, MDPI, vol. 18(19), pages 1-22, October.
    6. Luo, Li & Sun, Shikun & Xue, Jing & Gao, Zihan & Zhao, Jinfeng & Yin, Yali & Gao, Fei & Luan, Xiaobo, 2023. "Crop yield estimation based on assimilation of crop models and remote sensing data: A systematic evaluation," Agricultural Systems, Elsevier, vol. 210(C).

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