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Fine scale population density data and its application in risk assessment

机译:精细人口密度数据及其在风险评估中的应用

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ABSTRACT Population density is one of the key parameters for assessing the magnitude of population exposed to risk, and the better quality data we have, the better the assessment of risk. The aim of this study is to elaborate a high-resolution spatially distributed population density grid, which estimates population at the commune scale with a reliability of over 90%. The novelty of the approach is population density estimation in a regular European grid, based on buildings vector data collected in the national topographic database. Using abductive reasoning in combination with statistics and spatial analysis, the authors extract approximate information about a population from the large-scale topographic data. Moreover, linking the obtained population data with the cadastral data ?¢???? by unique building identifier ?¢???? allows for regular, quick and census survey-independent updates of the population surface. A shortcoming of the approach is the issue of the possible existence of two houses per family, which leads to an overestimation of population. However, in the study area it affected only two of the total 14 communes by 7%?¢????9%.
机译:摘要人口密度是评估面临风险的人口规模的关键参数之一,而我们拥有的质量越好数据,对风险的评估就越好。这项研究的目的是建立一个高分辨率的空间分布的人口密度网格,该网格以公社规模估算人口,其可靠性超过90%。这种方法的新颖之处在于,可以根据国家地形数据库中收集的建筑物矢量数据,在规则的欧洲网格中估算人口密度。作者将归纳推理与统计和空间分析相结合,从大规模地形数据中提取有关种群的近似信息。此外,将获得的人口数据与地籍数据链接起来。通过唯一的建筑物标识符?¢ ????允许定期,快速且与普查无关的人口表面更新。该方法的一个缺点是每个家庭可能存在两所房屋的问题,这导致人口过高估计。但是,在研究区中,它仅影响了14个公社中的两个公社,占7%– 9%。

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