摘要
为解决海量人口和建筑物数据导致的地图渲染时间长、页面卡顿无响应等技术问题,本文提出了一种多尺度人口空间大数据聚合模型,通过研究海量数据逐级嵌套的树型逻辑架构和可视域内的空间关系,实现了超大城市多尺度行政区域的人口空间数据统计分析与可视化,并在多源异构属性融合方面得到了较好的应用,更好地满足了超大城市精细化管理需求。
In order to solve the technical problems such as long rendering time of maps and unresponsive pages caused by massive population and building data,a multi-scale population spatial big data aggregation model is proposed in this paper.By studying the hierarchical nested tree logical structure of massive data and spatial relationship within the viewable area,the statistical analysis and visualization of population spatial data in the multi-scale administrative areas of megacities are realized.It has been well applied in multi-source heterogeneous attribute fusion,which better meets the needs of fine management of megacities.
作者
李亚云
忻静
丛婧
LI Yayun;XIN Jing;CONG Jing(Shanghai Municipal Institute of Surveying and Mapping,Shanghai 200063,China;Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities,MNR,Shanghai 200063,China)
出处
《测绘通报》
CSCD
北大核心
2024年第3期145-150,共6页
Bulletin of Surveying and Mapping
基金
上海市2021年度“科技创新行动计划”社会发展科技攻关项目(21DZ1204100)。
关键词
人口普查
海量数据
地理信息系统
多尺度空间
population census
mass data
geographic information system
multi-scale space
作者简介
李亚云(1990—),女,硕士,工程师,主要研究方向为地理信息研发。E-mail:lyy1072286390@163.com。
