贾斐雪,闫金凤,王甜

• 1:山东科技大学测绘与空间信息学院

摘要(Abstract)：

针对如何解决各类兴趣点(POI)的用地面积差异并精确地识别功能区等问题,该文构建了一种新的功能区识别模型。使用网上调查的各类POI的面积数据等,对各类POI的面积大小所处的区间进行赋值,整理出各类POI的面积评分表,并通过对各类POI进行核密度分析得到每个兴趣点的核密度值。通过构建面积评分与核密度值二级赋分评价模型,增加了POI数据的可用性,实现快速获取城市空间结构。经过精度检验,Kappa系数为0.76,功能区识别精度较高。研究结果可用于区位熵指数、土地利用混合度、平均最邻近距离与标准差椭圆等分析,有利于规划人员掌握城市空间结构与进行科学决策。

关键词(KeyWords)： 青岛市;兴趣点;城市功能区;核密度分析

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金重大项目(41890854);; 山东省重大科技创新工程项目(2019JZZY020103)

作者(Author): 贾斐雪,闫金凤,王甜

DOI: 10.16251/j.cnki.1009-2307.2021.08.024

参考文献(References)：

• [1] 周干峙.城市及其区域：一个典型的开放的复杂巨系统[J].城市轨道交通研究，2009,12(12):1-3.(ZHOU Ganzhi.City and its region:a typical open complex huge system[J].Urban Mass Transit,2009,12(12):1-3.)
• [2] 渠涛，张理茜，武占云.不同历史时期特殊事件影响下的城市空间结构演变研究：以天津市为例[J].地理科学，2014,34(6):656-663.(QU Tao,ZHANG Liqian,WU Zhanyun.City spatial structure evolution affected by special events in different historical periods:a case study of Tianjin[J].Scientia Geographica Sinica,2014,34(6):656-663.)
• [3] 李新运.城市空间数据挖掘方法与应用研究[D].青岛：山东科技大学，2004.(LI Xinyun.Research on methods and application for urban spatial data mining[D].Qingdao:Shandong University of Science and Technology,2004.)
• [4] 吴文恒，徐泽伟，杨新军.功能分区视角下的西安市发展空间分异[J].地理研究，2012,31(12):2173-2184.(WU Wenheng,XU Zewei,YANG Xinjun.Quantitative research of spatial development differentiation in Xi’an from the perspective of urban functional zoning[J].Geographical Research,2012,31(12):2173-2184.)
• [5] 辜寄蓉，陈先伟，杨海龙.城市功能区划分空间聚类算法研究[J].测绘科学，2011,36(5):65-67.(GU Jirong,CHEN Xianwei,YANG Hailong.Spatial clustering algorithm on urban function oriented zone[J].Science of Surveying and Mapping,2011,36(5):65-67.)
• [6] 陈世莉，陶海燕，李旭亮，等.基于潜在语义信息的城市功能区识别：广州市浮动车GPS时空数据挖掘[J].地理学报，2016,71(3):471-483.(CHEN Shili,TAO Haiyan,LI Xuliang,et al.Discovering urban functional regions using latent semantic information:spatiotemporal data mining of floating cars GPS data of Guangzhou[J].Acta Geographica Sinica,2016,71(3):471-483.)
• [7] 于翔.基于城市公交刷卡数据和兴趣点的城市功能区识别研究：以北京市为例[D].杭州：浙江大学，2014.(YU Xiang.Discovering zones of different functions using bus smart card data and points of interest:a case study of Beijing[D].Hangzhou:Zhejiang University,2014.)
• [8] WANG Y D,WANG T,TSOU M H,et al.Mapping dynamic urban land use patterns with crowdsourced geo-tagged social media(Sina-Weibo) and commercial points of interest collections in Beijing,China[J].Sustainability,2016,8(11):1202.
• [9] 钮心毅，丁亮，宋小冬.基于手机数据识别上海中心城的城市空间结构[J].城市规划学刊，2014(6):61-67.(NIU Xinyi,DING Liang,SONG Xiaodong.Understanding urban spatial structure of Shanghai central city based on mobile phone data[J].Urban Planning Forum,2014(6):61-67.)
• [10] 李强，郑新奇，晁怡.大数据支持的武汉市功能识别与分布特征研究[J].测绘科学，2020,45(5):119-125.(LI Qiang,ZHENG Xinqi,CHAO Yi.Research on function identification and distribution characteristics of Wuhan supported by big data[J].Science of Surveying and Mapping,2020,45(5):119-125.)
• [11] 黄亮东.基于多源POI数据的天津市城市功能区识别与分析[D].徐州：中国矿业大学，2019.(HUANG Liangdong.Identification and analysis of urban functional areas in Tianjin using multi-source POI data[D].Xuzhou:China University of Mining and Technology,2019.)
• [12] 徐海洋，于丙辰，陈刚，等.基于OpenStreetMap数据的城市街区提取与精度评价[J].地理空间信息，2019,17(3):71-74.(XU Haiyang,YU Bingchen,CHEN Gang,et al.Accuracy evaluation and extraction of urban block based on OpenStreetMap data[J].Geospatial Information,2019,17(3):71-74.)
• [13] 中华人民共和国国家质量监督检验检疫总局，中国国家标准化管理委员会.零售业态分类：GB/T 18106—2004[S].北京：中国标准出版社，2004.(General Administration of Quality Supervision,Inspection and Quarantine of the People’s Republic of China,Standardization Administration of the People’s Republic of China.Classification of retail formats:GB/T 18106-2004[S].Beijing:China Standards Press,2004.)
• [14] SILVERMAN B W.Density estimation for statistics and data analysis[M]//Monographs on Statistics and Applied Probability.London:Chapman and Hall,1986.
• [15] 黄怡敏，邵世维，雷英哲，等.运用网络核密度估计与克里格插值识别城市功能区[J].测绘地理信息，2019,44(4):14-18.(HUANG Yimin,SHAO Shiwei,LEI Yingzhe,et al.Identification of urban functional zones using network kernel density estimation and Kriging interpolation[J].Journal of Geomatics,2019,44(4):14-18.)
• [16] ZHANG X Y,DU S H,WANG Q.Hierarchical semantic cognition for urban functional zones with VHR satellite images and POI data[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,132:170-184.
• [17] SONG Y,KNAAP G J.Measuring the effects of mixed land uses on housing values[J].Regional Science and Urban Economics,2004,34(6):663-680.
• [18] LIU X J,LONG Y.Automated identification and characterization of parcels with OpenStreetMap and points of interest[J].Environment and Planning B:Planning and Design,2016,43(2):341-360.
• [19] 田光进，沙默泉.基于点状数据与GIS的广州大都市区产业空间格局[J].地理科学进展，2010,29(4):387-395.(TIAN Guangjin,SHA Moquan.The spatial pattern of Guangzhou metropolitan area industry based on point data and GIS[J].Progress in Geography,2010,29(4):387-395.)
• [20] 赵宏波，余涤非，苗长虹，等.基于POI数据的郑州市文化设施的区位布局特征与影响因素研究[J].地理科学，2018,38(9):1525-1534.(ZHAO Hongbo,YU Difei,MIAO Changhong,et al.The location distribution characteristics and influencing factors of cultural facilities in Zhengzhou based on POI data[J].Scientia Geographica Sinica,2018,38(9):1525-1534.)