基于多源大数据的城市贫困地理研究进展  

Progress in urban poverty geography research based on multi-source big data

作　　者：袁媛 陈曦 李珊 刘慧雯 吴庆瑜 YUAN Yuan;CHEN Xi;LI Shan;LIU Huiwen;WU Qingyu(School of Geography and Planning Institute,Sun Yat-Sen University/Guangdong Key Laboratory for Urbanization and Geo-simulation,Guangzhou 510275,China;College of Architecture and Urban Planning,Guangzhou University,Guangzhou 510006,China;Guangdong Architectural Design and Research Institute Co.,LTD,Guangzhou 510010,China)

机构地区：[1]中山大学地理科学与规划学院广东省城市化与地理环境空间模拟重点实验室,广州510275 [2]广州大学建筑与城市规划学院,广州510006 [3]广东省建筑设计研究院有限公司,广州510010

出　　处：《地理研究》2024年第4期1036-1050,共15页Geographical Research

基　　金：国家自然科学基金项目(41871161、52278085、42301182);广东省自然科学基金(2023A1515010704);广东省基础与应用基础研究基金(2022A1515110331)。

摘　　要：消除贫困是联合国可持续发展目标之首。2020年,中国脱贫攻坚战取得了全面胜利,城市相对贫困成为消除绝对贫困后的重要议题之一。随着技术进步,依托于大数据及其分析方法,城市内部难以测度的相对贫困问题可用多种形式被发掘,推动了城市贫困地理研究的“大数据转向”。城市贫困地理研究经历了“观测与可视化-内容对象发掘-多源多维分析”三大发展阶段,并形成了“城市贫困的重点群体”“城市贫困群体的多维表征”和“城市贫困空间的测度数据与技术方法”三大热点议题。空间建成环境和个体社会经济大数据及其对应的新方法,正在带领城市贫困地理研究突破传统研究数据和方法的局限,为挖掘潜在贫困地区、贫困人群、贫困表征等关键要素提供科学支撑。未来,研究需依托大数据及其方法,构建“中国化”的城市贫困地理研究理论框架,并将其转向实践应用,在中国解决农村绝对贫困问题后为缓解城市相对贫困奠定基础。Poverty eradication is the primary goal of the United Nations(UN)Sustainable Development Goals(SDGs).In 2020,China's battle against poverty has achieved a comprehensive victory,and urban relative poverty has become one of the most critical issues in the new phase after the elimination of absolute poverty.With the advancement of technology,relying on big data analysis can reveal the hard-to-observe relative poverty phenomenon in cities in various forms.Big data analytical methods have greatly promoted the“big data turn”in urban poverty geography research.This paper analyzes the knowledge map of 1572 urban poverty geography literatures involving multi-source big data in the Scopus database from 2000 to 2022,systematically sorts out the trends and hotspots of related research,and summarizes the research framework and dimensions.It is found that based on multi-source big data,from 2000 to 2022,urban poverty geography research has gone through three key stages:“observation and visualization”,“content and object discovery”,and“multi-source and multidimensional analysis”.Moreover,three hot topics have been developed:“key groups of urban poverty”,“multidimensional representation of urban poverty”,and“spatial measurement data and methods of urban poverty”.As the key to the research turn,spatial built environment and individual socioeconomic big data analysis platforms have differentiated research applicability and good synergy,which greatly expands the depth and breadth of urban geography research,allowing for an in-depth exploration of urban poverty in the dimensions of economic development,physical and mental health,housing environment,and social welfare.Currently,new technologies such as big data are leading urban poverty geography research to break through the limitations of traditional data and methods,providing critical scientific support for exploring key element such as potential poverty areas,poverty groups,and poverty representations.In the future,a Chinese theoretical framework for u

关 键 词：城市贫困 贫困地理 大数据 贫困测度 多维贫困 

分 类 号：F126[经济管理—世界经济] K901[历史地理—人文地理学]