文化古城鎮建築物火災潛勢空間辨認──以鹿港鎮為例

Identifying the Spatial Potential Fire Disaster Area in the Historical Township--The Case Study of Lukang Township

有關城鎮災害的風險管控，長期以來一直是城鎮規劃與城鎮治理的重要議題。而城鎮災害中，以火災最為常見的災害類型，且常有重大人員及財物損失。相關文獻中，常見以單一建築物或建築群進行案場模擬；或進而以建築物之使用類型、結構設備等等特徵尺度進行研析。然而，面對城鎮土地之複合使用與相容性考量，城鎮空間存在區域間非同質的差異，也因而造成城鎮火災的災害損失差異。如何從既有的空間資訊辨識城鎮火災的潛勢地區，並給予及早因應，則是防治災害的重要議題。本研究以彰化縣鹿港鎮之文化古城鎮為例，進行區域屬性相關之火災理論研析。透過平均最近鄰分析，初步觀察得知建築物火災呈現空間群聚現象，再依核密度推估法及Getis-Ord’s Gi*統計量分析找出建築物火災潛勢區及熱點。研究成果發現，最高潛勢區及熱點皆集中於城鎮空間結集地區。進而本研究透過城鎮建築火災理論，選取人為社經特徵及城鎮空間特徵等變項，以最小統計區為樣本，經多元線性迴歸、空間落遲模型與空間誤差模型，及地理加權迴歸模型進行分析。實證以地理加權迴歸模型解釋力最佳，並檢定驗證建築物火災與地區空間存有空間變異現象。結果分析中，以人口密度、老年人口數、混合使用住宅區面積比於顯著區域呈正相關。因此藉由實證成果，本研究可提供更詳細建築物火災發生率空間分析，亦供城鎮治理及火災預防之規劃參考。

Urban fires are the most common type of urban disaster, and often result in significant loss of life and heavy property losses. In literature, it is common to use a single building or group of buildings as a case study or analyze the building in terms of its type of use, structural features, and other characteristic scales. While urban land use with complex and compatibility, would come with spatial autocorrelation and spatial heterogeneity, that result in difference of damage and losses. This study we choose Lukang town, a tourist town in Changhua County, 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 Getis-Ord’s Gi* spatial statistics find out the building fire potential and the so called“hot spots”. Our results show that the high potential area and the hot spots are concentrated in the urban area. That also indicates that the humanistic socio-economic characteristics and urban spatial characteristics were selected through the urban buildings fire theory. Taking the smallest statistical area as a sample, it is analyzed through multiple linear regression, spatial lag model and spatial error model, and geographically weighted regression. Our empirical findings concluded that the best model is the geographically weighted regression and confirmed the hypothesis of the spatial variability in building fire and regional spatial characteristics. The empirical results show that building fire incidence rate was positively correlated to variables of population density, Elderly population, and area ratio of mixed-use residential district. Therefore, this study can provide a more detailed spatial analysis of structure fire potential and serve as a reference for urban governance and fire prevention planning.