PRELIMINARY STUDY OF GEO-INFORMATIC TUPU METHOD FOR URBAN COMMUNITY QUALITY OF LIFE SPACE BASED ON BIG DATA: A CASE STUDY OF XI'AN
ZHANG Su1, CHANG Fang2, LI Jiu-quan2, CHEN Zheng-jiang1, XIE Yuan-li1
1. College of Urban and Environment, Northwest University, Xi'an 710127, China;
2. College of Tourism and Human Geography Institute, Xi'an International University, Xi'an 710128, China
Abstract：Researches on problems of quality of living space for urban communities have always been the focus of the (new) urban social geography. Urban social geography, from the prospective of space justice with humanistic methodology, discusses the "quality view of the urban (social) living space" formed in the field of the urban living space quality, and this "quality view" is the theoretic cornerstone to carry out researches on the quality of community living space. This paper, based on the mega-data concept, seeks out related information of urban communities, community resources system and residen's spatial accessibility distance from data of urban commerce, service and leisure resources venues. Taking the "quality view of the urban (social) living space" as theoretic support, the authors use mega-data, GIS spatial analysis methodology and expressions of geo-info Tupu, and put forward the atlas expression concept of the quality of urban community living space. Having improved the calculation method of community resources accessibility/availability index (CRAI) and analyzed spatial patterns of the accessibility/availability of urban community resources, the authors put forward urban community living space expressions of geo-info Tupu of the quality urban community living space, and hopes to provide references for further researches on spatial deprivation law of community resources and for its overall planning.
张苏, 常芳, 李九全, 陈正江, 谢元礼. 大数据支持下城市社区生活空间质量的可获性图谱法初探——以西安为例[J]. 人文地理, 2016, 31(3): 52-59.
ZHANG Su, CHANG Fang, LI Jiu-quan, CHEN Zheng-jiang, XIE Yuan-li. PRELIMINARY STUDY OF GEO-INFORMATIC TUPU METHOD FOR URBAN COMMUNITY QUALITY OF LIFE SPACE BASED ON BIG DATA: A CASE STUDY OF XI'AN. HUMAN GEOGRAPHY, 2016, 31(3): 52-59.
