Information diffusion-based spatio-temporal risk analysis of grassland fire disaster in northern China

  • Authors:

  • Xingpeng Liu;Jiquan Zhang;Weiying Cai;Zhijun Tong

  • Affiliations:

  • College of Urban and Environmental Sciences, Natural Disaster Research Institute, Northeast Normal University, Changchun 130024, China and Key Laboratory for Vegetation Ecology of Ministry of Educ ...;College of Urban and Environmental Sciences, Natural Disaster Research Institute, Northeast Normal University, Changchun 130024, China and Key Laboratory for Vegetation Ecology of Ministry of Educ ...;College of Boda, Jilin Normal University, Siping 136000, China;College of Urban and Environmental Sciences, Natural Disaster Research Institute, Northeast Normal University, Changchun 130024, China and Key Laboratory for Vegetation Ecology of Ministry of Educ ...

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2010

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Abstract

This study presents a Geographical Information Systems (GIS) and information diffusion-based methodology for spatio-temporal risk analysis of grassland fire disaster to livestock production in the grassland area of the northern China. We employed information matrix to analyze and to quantify fuzzy relationship between the number of annual severe grassland fire disasters and annual burned area. We also evaluated the consequences of grassland fire disaster between 1991 and 2006 based on historical data from 12 northern China provinces. The results show that the probabilities of annual grassland fire disasters and annual damage rates on different levels increase gradually from southwest to northeast across the northern China. The annual burned area can be predicted effectively using the number of annual severe grassland fire disasters. The result shows reliability as tested by two-tailed Pearson correlation coefficient. This study contributes a reference in decision making for prevention of grassland fire disaster and for stockbreeding sustainable development planning. The fuzzy relationship could provide information to make compensation plan for the disaster affected area.