臺灣中型城市建築火災空間分析－以員林市為例

Among the all kinds of disasters, fire is a common disaster in urban areas. It is often discussed on the scale of heavy casualties and fire simulation in public places or on the scale of building type, structure, equipment, etc., and presented with spatial statistics and environmental description, that often studying with regression analysis. However, the spatial autocorrelation and spatial heterogeneity of fire have not been carefully studied in literature, which will lack of the explanatory power of urban fire theory due to spatial variability. This study we choose Yuanlin City, a medium-sized city in Taiwan, as a case study. And that uses average nearest neighbor to find out the spatial aggregation phenomenon in the building fire, and then uses the kernel density estimation and the index of the Local Indicators of Spatial Association (LISA) find out the building fire potential and the so called "hot zone". Our results show that the high potential area and the hot zone (HH) are concentrated in the urban area. That also indicates that the humanistic socio-economic characteristics and urban spatial patterns were selected through the urban buildings fire theory. We then construct different models including the ordinal regression analysis, spatial lag model and spatial error models for analysis. Two groups with different sample scale, including "statistical area" and "cell", were used to find out the relatively appropriate model. Our empirical findings concluded that the best model is the spatial error model, and confirmed the hypothesis of the spatial variability in building fire and regional spatial characteristics. The empirical results also show that the cell grid with 50 by 50 meters square which is the smaller space unit than the "statistical area" has higher model goodness-of-fit, namely the R-squared. And the spatial error model of the grid's building fire incidence rate was positively correlated to variables of population density, population ratio of low- and middle-income households, area ratio of commercial district, area ratio of residential district, area ratio of Industrial district and area ratio of religious district.