摘要
以兴趣点(Points of Interest,POI)为主要代表的地理空间大数据对于人地关系研究具有重要革新意义。研发大数据多维语义关联模型、语义关联元数据索引及组织技术以及大数据可视化算法等关键技术体系,同时以基于电子地图POI、网络文本大数据的城市商住空间格局及关联关系计算,运用空间核密度估计等GIS技术分析城市人地系统要素的空间聚集形态及相关性特征,并揭示要素之间的关联机理建立数据计算平台。本平台为利用大数据进行人-地关系研究提供计算环境,为创新人地关系的大数据分析方法与理论体系,促进科学知识发现(人地关系)与决策应用服务(政策调控)提供实验基地。
A big-data-based platform for human-land relations analysis and application in urban areas was recognized by the Geographical Society of China(GSC) as the GSC Best Practice Data Computing Environment 2018. The system was developed by calculating the spatial patterns of urban businesses and residences and relevant correlations based on electronic map POIs and web text data. GIS tools, such as the spatial kernel density estimation, were used to analyze the spatial aggregation patterns and correlations between human-land system elements. Based on these correlations, we established a data-computing platform. This platform provides a computing environment for the study of human-land relationships using big data. It also provides an experimental basis for innovating big data analysis methods and theoretical systems in the study of human-land relationships, and thus facilitates scientific discovery(human-land relationship) and decision-making.
作者
薛冰
李京忠
肖骁
谢潇
庞敏
姜璐
逯承鹏
任婉侠
Xue B.;Li J.Z.;Xiao X.;Xie X.;Pang M.;Jiang L.;Lu C.P.;Ren W.X.(Key Lab of Pollution Ecology and Environmental Engineering,Institute of Applied Ecology,Chinese Academy of Sciences,Shenyang 110016,China;Key Lab for Environmental Computation and Sustainability of Liaoning Province,Shenyang 110016,China;College of Urban Planning and Architecture,Xuchang University,Xuchang 461000,China;College of Geography and Environment Science,Northwest Normal University,Lanzhou 730070,China;College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China)
出处
《全球变化数据学报（中英文）》
2018年第3期290-294,179-183,共10页
Journal of Global Change Data & Discovery
基金
国家自然科学基金(41471116,41701142,41701466)
沈阳市科技局重点科技研发计划(17-117-6-00)及双百工程(Z17-7-030)
中国科学院青年创新促进会(会员号:2016181)
关键词
人地关系
空间格局
POI
空间分析
沈阳市
human-land relationship
computing environment
big data
urban area
point of interest
作者简介
通讯作者:薛冰,D-1830-2009,中国科学院沈阳应用生态研究所,xuebing@iae.ac.cn;李京忠,S-3218-2018;肖骁,S-3189-2018;谢潇,S-3278-2018;庞敏,S-3205-2018;姜璐,S-9924-2018;逯承鹏,S-3201-2018;任婉侠,S-3252-2018
