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Building probabilistic models of fire occurrence and fire risk zoning using logistic regression in Shanxi Province, China

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  • Jinghu Pan

    (Northwest Normal University)

  • Weiguo Wang

    (Northwest Normal University)

  • Junfeng Li

    (Northwest Normal University)

Abstract

Fires are a recurrent environmental and economic emergency throughout the world. Fire risk analysis and forest fire risk zoning are important aspects of forest fire management. MODIS remote sensing datasets for Shanxi Province from 2002 to 2012 were used to build a spatial logistic forest fire risk model, based on the spatial distribution of forest fires and forest fire-influencing factors, using geographic information system technology. A forest fire risk zoning study was conducted at a large temporal scale and a provincial spatial scale. The resulting logistic model of forest fire risk, built with spatial sampling, showed a good fit (p

Suggested Citation

  • Jinghu Pan & Weiguo Wang & Junfeng Li, 2016. "Building probabilistic models of fire occurrence and fire risk zoning using logistic regression in Shanxi Province, China," 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. 81(3), pages 1879-1899, April.
    • Handle: RePEc:spr:nathaz:v:81:y:2016:i:3:d:10.1007_s11069-016-2160-0
    DOI: 10.1007/s11069-016-2160-0
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    References listed on IDEAS

    as
    1. Litao Wang & Yi Zhou & Weiqi Zhou & Shixing Wang, 2013. "Fire danger assessment with remote sensing: a case study in Northern China," 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. 65(1), pages 819-834, January.
    2. Stephen Matthews & Tse-Chuan Yang, 2012. "Mapping the results of local statistics," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 26(6), pages 151-166.
    3. Jaehoon Jung & Changjae Kim & Shanmuganathan Jayakumar & Seongsam Kim & Soohee Han & Dong Kim & Joon Heo, 2013. "Forest fire risk mapping of Kolli Hills, India, considering subjectivity and inconsistency issues," 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. 65(3), pages 2129-2146, February.
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    Cited by:

    1. Chaoxue Tan & Zhongke Feng, 2023. "Mapping Forest Fire Risk Zones Using Machine Learning Algorithms in Hunan Province, China," Sustainability, MDPI, vol. 15(7), pages 1-17, April.
    2. Liu, Shilei & Xu, Jintao, 2022. "Wildfire, protected areas and forest ownership: The case of China," Land Use Policy, Elsevier, vol. 122(C).
    3. Xu Jia & Yong Gao & Baocheng Wei & Shan Wang & Guodong Tang & Zhonghua Zhao, 2019. "Risk Assessment and Regionalization of Fire Disaster Based on Analytic Hierarchy Process and MODIS Data: A Case Study of Inner Mongolia, China," Sustainability, MDPI, vol. 11(22), pages 1-17, November.

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