• 首页关于本刊投稿须知期刊订阅编委会期刊合作English
引用本文:
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 2311次   下载 2818 本文二维码信息
码上扫一扫!
分享到: 微信 更多
基于多源数据的云南人口空间分布模拟研究
曹彦波, 李永强, 李敏, 李兆隆, 吴艳梅, 李智蓉
云南省地震局,昆明市北市区北辰大道650224
摘要:
人口数据精度是提高地震灾情速判准确度的关键之一。本文基于多源数据融合思路,以云南第6 次人口普查数据为基础,把居民地作为人口分布指示因子,利用GIS 软件工具,分析了人口分布与地貌形态、坡度、地形起伏度以及土地利用之间的关系,构建了人口影响因子的权重系数,并采用城乡人口-面积统一模型对人口统计数据进行了网格化空间模拟及精度检验。以2013 年3 月3 日云南洱源5. 5 级地震为例,通过多种估算方法对灾区人口进行了计算及对比分析,结果表明,多源数据融合法生成的千米网格人口与实际人口的相关性均在0. 89 以上,人口数据精度符合实际,可为灾情速判提供可靠的数据基础。
关键词:  地震  人口数据  空间化  居民地  公里网格
DOI:
分类号:
基金项目:地震行业科研专项———西南地震应急对策新模式与关键技术研究( 201108013) 与中国地震局地震应急青年基金项目——云南人口公里网格修正方法研究( CEA_EDEM-201205) 联合资助
Simulation of spatial distribution of the population of Yunnan based on the integration of multi-resource data
Cao Yanbo, Li Yongqiang, Li Min, Li Zhaolong, Wu Yanmei, Li Zhirong
Earthquake Administration of Yunnan Province,Kunming 650224,China
Abstract:
According to the theory of integration of multi-resource data, we refer to the demographic data of Yunnan Province released in 2011 after the Sixth National Population Census,to set the residential area as an indicator of population distribution in Yunnan. Then by using GIS to analyze the relation between the population distribution and the factors such as landform,topographic slope,amplitude of landform relief,and land-use,we get the weighing coefficient of the impact factor of population. Finally,we use the unified model of population and area to estimate the earthquake-affected population by way of kilometer-grid transformation and check the precision of the result. To test the practicability of our estimation,we calculate with various methods the population of the disaster area of the Eryuan,Yunnan,M5. 5 earthquake on March 3,2013. By comparing the results from these methods,we find that the estimated population through the kilometer-grid transformation is highly-related with the real population; the correlation coefficient is over 0. 89. So, the estimated population is reliable for the quick judgment of the disaster condition.
Key words:  Earthquake  Demographic data  Space-based transformation  Residential area  Kilometer grid