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Spatially enabled emergency event analysis using a multi-level association rule mining method

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  • Bo Fan
  • Jifeng Luo

Abstract

Spatial attributes are important factors affecting the entire process of emergency management. Despite the importance of spatial attributes in emergency rescue, this subject has not been subjected to thorough examination in previous literature. This paper presents a new method that incorporates spatial predicates describing the spatial relationships between emergency locations and surrounding objects into emergency event analysis. More specifically, we developed three mechanisms to achieve spatially enabled emergency analysis. First, a novel fact constellation schemas that integrate the spatial predicates and non-spatial data of emergency events is created for multi-level analysis. Second, a filtering algorithm is designed to remove redundant predicates from the huge amount of spatial predicates for data association rule mining. Third, by incorporating the filtering method, a multi-level spatial data association algorithm was proposed to realize the analytical function for emergency events. Experiments were conducted, and the results validate the effectiveness of our method. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Bo Fan & Jifeng Luo, 2013. "Spatially enabled emergency event analysis using a multi-level association rule mining method," 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. 67(2), pages 239-260, June.
  • Handle: RePEc:spr:nathaz:v:67:y:2013:i:2:p:239-260
    DOI: 10.1007/s11069-013-0556-7
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    References listed on IDEAS

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    1. Chang, Mei-Shiang & Tseng, Ya-Ling & Chen, Jing-Wen, 2007. "A scenario planning approach for the flood emergency logistics preparation problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 737-754, November.
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    1. Bo Fan, 2014. "Hybrid spatial data mining methods for site selection of emergency response centers," 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. 70(1), pages 643-656, January.

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