| 融合多源时空数据的城市火灾危险性评估 |
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| 引用本文： | 赵晓旭.融合多源时空数据的城市火灾危险性评估[J].测绘通报,2020,0(5):101-106. |
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| 作者姓名： | 赵晓旭 |
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| 作者单位： | 福州市规划设计研究院, 福建 福州 350100 |
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| 摘 要： | 城市层面的火灾风险评估主要包括火灾危险性、危害性及救援能力等方面。本文选取火灾危险性评估进行针对性研究，在大数据思维的指导下，以相关关系代替因果关系，采用多源数据对评估指标权重、分值进行率定，得出福州市城区火灾危险性时空分布图。首先利用高德地图API对消防历史出警记录进行地址解析，将近万条火灾出警地址空间落点，获得福州市历史火灾空间分布；然后综合城市用地性质现状、用地开发性质、人口分布热力图等多源异构数据，探索其与历史火灾空间分布的相关性；最后以福州城区为例，初步实现具有充分数理支撑的火灾危险性评估方法，形成火灾危险性动态评估成果，为城市消防规划等提供支撑和依据。
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| 关 键 词： | 大数据 多源时空数据 多元线性回归 火灾危险性评估 福州 |
| 收稿时间： | 2019-12-10 |
Urban fire hazard assessment based on multi-source spatiotemporal data |
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| ZHAO Xiaoxu.Urban fire hazard assessment based on multi-source spatiotemporal data[J].Bulletin of Surveying and Mapping,2020,0(5):101-106. |
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| Authors: | ZHAO Xiaoxu |
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| Institution: | Fuzhou Planning Design & Research Institute, Fuzhou 350100, China |
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| Abstract: | The fire risk assessment at the city level mainly includes fire hazard, fire harmfulness, and fire emergency response capability. This article selects fire hazard assessment for targeted research. In the era of big data, causal relationships could be replaced with correlation. Thus, multi-source data is used for weighing and scoring the evaluation indicators in order to obtain a spatiotemporal distribution of fire danger in the urban area of Fuzhou. First, address analysis of the fire alarm records in the past few years is performed using the AMap API tool, and nearly 10 000 fire alarm locations are spatially assigned mapping the spatial distribution of historical fires in Fuzhou. Furthermore, multi-source and heterogeneous data, such as the structure of urban land use, property of land use development, and thermal map of population distribution, is further integrated to explore its correlation with the spatial distribution of historical fires. Finally, taking Fuzhou as an example, the results of dynamic fire risk assessment are formed, and the fire risk assessment method with sufficient mathematical support is developed, which provides strong support for urban fire control planning. |
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| Keywords: | big data multi-source spatiotemporal data multiple linear regression fire hazard assessment Fuzhou |
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