Spatio-temporal population modelling as improved exposure information for risk assessments tested in the Autonomous Province of Bolzano
Spatio-temporal population modelling as improved exposure information for risk assessments tested in the Autonomous Province of Bolzano
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DOI：
10.1016/j.ijdrr.2017.11.011
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发表时间：
2018-03
影响因子：
5
通讯作者：
K. Renner;S. Schneiderbauer;Fabio Pruß;Christian Kofler;David J. Martin;S. Cockings
中科院分区：
文献类型：
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作者：
K. Renner;S. Schneiderbauer;Fabio Pruß;Christian Kofler;David J. Martin;S. Cockings
行政单位的人口数据通常是指最近一次人口普查的年份。信息的这种聚合程度和静态性质给灾害管理或空间规划等应用的空间分析造成了特别困难，因为这些应用需要对时间敏感得多的人口分布。在这项研究中，一个灵活的模型，以创建动态网格人口数据的空间分辨率为100米的山区，灾害易发和高度旅游地区的博尔扎诺自治省，在一个明确的时空建模框架内的多个数据源的集成的基础上实施。有人认为，动态网格人口信息提供了一个改进现有的区域数据集。我们的研究表明，将每日和季节变化与人口分布相结合，可以改善风险评估的暴露信息，特别是在旅游密集地区。
Population data is commonly available for administrative units referring to the year of the last census. That level of aggregation and the static character of the information pose particular difficulties for spatial analysis in applications such as disaster management or spatial planning, for which much more time-sensitive population distributions are required. In this study, a flexible model to create dynamic gridded population data with a spatial resolution of 100 m is implemented for the mountainous, hazard-prone and highly touristic region of the Autonomous Province of Bolzano, based on the integration of multiple data sources within an explicit spatio-temporal modelling framework. It is argued that dynamic gridded population information provides an improvement to the existing regional datasets. Our study shows that integrating daily and seasonal changes to the distribution of population improves exposure information for risk assessments especially in highly touristic areas.