Adaptive estimation of visual smoke detection parameters based on spatial data and fire risk index
Computer Vision and Image Understanding
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Forest fire is a usual disaster in real life, causing huge live, property and ecology losses. A risk assessment model to identify, classify and map forest fire risk areas is presented in this paper. This model considers three parts, i.e. hazards identification, vulnerability analysis, and emergency response capacity analysis. The first part concentrates on several influence factors in forest fires, including the land use, topography and meteorology where the forest situate. The second part is made up of population density and value of forest resources. The forest fire response capacity including forest fire-brigade, watch-tower and helicopter water source is the third part. Through GIS spatial analytical procedure, the forest fire risk ranging from high to low is derived, according to its sensitivity to fire or fire-inducing capability. Spatial analyst is used to combine some single influence factors in risk maps to display the total fire risk map. The weight to each factor is determined by Grey Relativity Analysis (GRA). This model is illustrated with a case study of forest fire risk of area in China. It is suggested that risk mapping is helpful for the forest fire management to minimize forest fire hazard.