人口数据是地震灾害人员伤亡评估的基础,准确的人口空间分布信息对提高应急灾情评估的准确度和开展高效的应急决策具有重要意义。本文结合建筑物空间分布、POI(兴趣点)、路网与人口统计等数据,基于Spearman相关分析以及多元线性回归分析方法,构建人口空间化模型,实现了人口统计数据基于规则格网的更为精确的可视化表达。结果表明:①建筑物空间分布能较好地反映人口的宏观分布特征,但是对于人口分布细节特征的刻画,则是以POI数据来反映人口的微观分布特征效果更为理想; ②受区域经济发展影响,人口分布具有明显的空间差异,由城镇向乡村区域递减的趋势明显,中心城区、周边城镇、偏远乡镇之间的人口密度差异巨大。基于建筑物与POI数据的人口模拟值与实际值的偏差较小,数据精度符合实际情况,可为灾情研判提供可靠的基础数据。

Population data is the basis of earthquake disaster assessment. Accurate population spatial distribution information is of great significance to conduct emergency disaster assessment and to carry out efficient emergency decision-making. In this paper,based on the Spearman correlation analysis and multiple linear regression analysis,a population spatial model is constructed by combining building spatial distribution,POI(points of interest),road network and population statistics data,in order to achieve a relatively high accurate visual expression of population data based on regular grids. The results show that:① The spatial distribution of buildings can well reflect the macro distribution characteristics of the population,but for the description of the detailed characteristics of the population distribution,POI data is better. ② Affected by the regional economic development,the population distribution is of obvious spatial differences with the trend of decreasing from urban to rural areas. The population density between the central urban area,surrounding towns and faraway towns is tremendously different. The deviation between the actual real value and the population simulation value based on the building and POI data is small,and the data accuracy is close to the reality,which can provide a reliable data basis for the rapid hazard assessment of disaster.

P315

新疆维吾尔自治区自然科学基金面上项目(2023D01A103)、新疆地震科学基金项目(202109)共同资助