基于POI与NPP/VIIRS灯光数据的城市群边界定量识别
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摘要
科学识别城市群边界是城市群精明紧凑发展的关键,也是国家空间治理体系与空间治理能力的重要标志。论文以京津冀、长三角和珠三角3大城市群为研究区域,采用NPP/VIIRS(Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite)夜间灯光影像与POI(Point of Interest)数据,基于密度的曲线阈值法与分形网络演化算法,对3个城市群的实际物理边界和集聚空间范围进行精准识别与空间特征解析。研究结果表明:①基于POI密度的曲线阈值法与NPP/VIIRS分形网络演化算法识别出城市群边界均小于国家城市群规划的行政边界,识别范围约占规划范围的20.90%～24.40%,识别结果显示3大城市群中长三角城市群发育最好,识别的城市群面积是京津冀和珠三角城市群的2倍左右;②从POI与NPP/VIIRS灯光数据提取的城市群边界面积非常接近,其中POI数据提取的城市群面积偏大,更大程度上反映的是城市群整体边界轮廓而非内部细节;NPP/VIIRS影像提取的城市群更细碎,能更好地识别城市群聚集中心与关键核心区域,2种方法可以相互比较和验证;③POI与灯光数据识别的城市群边界叠置分析发现,3大城市群中除了关键核心地带(集聚区)以外,外围还有众多孤立的点状区域(中小城镇),外围的点状区域与城市群集聚中心区空间割裂,一定程度上很难快速有效地接受来自城市群核心区域的辐射带动(涓滴效应)。
Identification of urban agglomeration boundary is the key to the smart and compact development of urban agglomerations. It also contributes to the development of national spatial governance system and the ability of spatial governance. Taking the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations as an example and by combining the Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite(NPP/VIIRS) night light images and points of interest(POI) data, this study aimed to accurately identify the actual physical boundaries of the three urban agglomerations and to analyze the spatial features of the agglomeration space by density-based curve threshold method and object-oriented fractal network evolution algorithm. The results show that: 1) The curve threshold method based on POI density and the NPP/VIIRS fractal network evolution algorithm both recognize that the boundaries of urban agglomeration are smaller than the administrative boundaries of the national urban agglomeration planning, and the identified ranges are 20.90%-24.40% of the planned ranges. 2) The areas of urban agglomeration extracted by POI and night light data are very close and can be compared and verified with each other. The areas of urban agglomerations extracted by POI data are larger, which to a great extent reflect the overall boundary of urban agglomeration instead of internal details. The urban agglomeration areas extracted by NPP/VIIRS images are more fragmented, which can identify the core areas of urban agglomerations. 3) Overlay of urban agglomerations extracted from the POI and the light data shows that in addition to the core zones, there are many isolated point areas in the three urban agglomerations, indicating that the three major urban agglomerations in China are still at a rapid development stage. The intensity of inter-city contact needs to be further strengthened.
Identification of urban agglomeration boundary is the key to the smart and compact development of urban agglomerations. It also contributes to the development of national spatial governance system and the ability of spatial governance. Taking the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations as an example and by combining the Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite(NPP/VIIRS) night light images and points of interest(POI) data, this study aimed to accurately identify the actual physical boundaries of the three urban agglomerations and to analyze the spatial features of the agglomeration space by density-based curve threshold method and object-oriented fractal network evolution algorithm. The results show that: 1) The curve threshold method based on POI density and the NPP/VIIRS fractal network evolution algorithm both recognize that the boundaries of urban agglomeration are smaller than the administrative boundaries of the national urban agglomeration planning, and the identified ranges are 20.90%-24.40% of the planned ranges. 2) The areas of urban agglomeration extracted by POI and night light data are very close and can be compared and verified with each other. The areas of urban agglomerations extracted by POI data are larger, which to a great extent reflect the overall boundary of urban agglomeration instead of internal details. The urban agglomeration areas extracted by NPP/VIIRS images are more fragmented, which can identify the core areas of urban agglomerations. 3) Overlay of urban agglomerations extracted from the POI and the light data shows that in addition to the core zones, there are many isolated point areas in the three urban agglomerations, indicating that the three major urban agglomerations in China are still at a rapid development stage. The intensity of inter-city contact needs to be further strengthened.
引文
陈守强,黄金川.2015.城市群空间发育范围识别方法综述[J].地理科学进展,34(3):313-320.[Chen S Q,Huang JC.2015.Review of range recognition research on urban agglomerations.Progress in Geography,34(3):313-320.]
邓羽,刘盛和,蔡建明.2013.中国中部地区城市影响范围划分方法的比较[J].地理研究,32(7):1220-1230.[Deng Y,Liu S H,Cai J M.2013.Comparative study of identification methods to delineate urban spheres of influence in central China.Geographical Research,32(7):1220-1230.]
董青,李玉江,刘海珍.2008.中国城市群划分与空间分布研究[J].城市发展研究,15(6):70-75.[Dong Q,Li Y J,Liu H Z.2008.Research on the spatial distribution and division of urban agglomerations in China.Urban Studies,15(6):70-75.]
董树军.2016.城市群府际博弈的整体性治理研究[D].长沙:湖南大学.[Dong S J.2016.The holistic governance of city cluster intergovernmental game.Changsha,China:Hunan University.]
方创琳.2009.城市群空间范围识别标准的研究进展与基本判断[J].城市规划学刊,(4):1-6.[Fang C L.2009.Research progress and general definition about identification standards of urban agglomeration space.Urban Planning Forum,(4):1-6.]
方创琳.2011.中国城市群形成发育的新格局及新趋向[J].地理科学,31(9):1025-1033.[Fang C L.2011.New structure and new trend of formation and development of urban agglomerations in China.Scientia Geographica Sinica,31(9):1025-1033.]
高晓路,许泽宁,牛方曲.2015.基于“点-轴系统”理论的城市群边界识别[J].地理科学进展,34(3):280-289.[Gao X L,Xu Z N,Niu F Q.2015.Delineating the scope of urban agglomerations based upon the Pole-Axis theory.Progress in Geography,34(3):280-289.]
顾朝林,庞海峰.2008.基于重力模型的中国城市体系空间联系与层域划分[J].地理研究,27(1):1-12.[Gu C L,Pang H.2008.Study on spatial relations of Chinese urban system:Gravity model approach.Geographical Research,27(1):1-12.]
黄建毅,张平宇.2009.辽中城市群范围界定与规模结构分形研究[J].地理科学,29(2):181-187.[Huang J Y,Zhang P Y.2009.Delimitation and fractal research on structure of central liaoning urban agglomeration.Scientia Geographica Sinica,29(2):181-187.]
黄金川.2016.基于辐射扩散测度的中国城市群发育格局识别[J].经济地理,36(11):199-206.[Huang J C.2016.Identification of urban agglomeration in China based on radiation diffusion measurement.Economic Geography,36(11):199-206.]
姜晓丽,张平宇.2013.基于Huff模型的辽宁沿海港口腹地演变分析[J].地理科学,33(3):282-290.[Jiang X L,Zhang P Y.2013.The hinterland evolution of Liaoning coastal ports based on the Huff model.Scientia Geographica Sinica,33(3):282-290.]
柯善咨.2009.中国城市与区域经济增长的扩散回流与市场区效应[J].经济研究,(8):85-98.[Ke S Z.2009.Spreadbackwash and market area effects of urban and regional growth in China.Economic Research,(8):85-98.]
陆大道,陈明星.2015.关于“国家新型城镇化规划(2014-2020)”编制大背景的几点认识[J].地理学报,70(2):179-185.[Lu D D,Chen M X.2015.Several viewpoints on the background of compiling the"National New Urbanization Planning(2014-2020)".Acta Geographica Sinica,70(2):179-185.]
刘卫东.2014.经济地理学与空间治理[J].地理学报,69(8):1109-1116.[Liu W D.2014.Economic geography for spatial governance.Acta Geographica Sinica,69(8):1109-1116.]
牛方曲,刘卫东,宋涛.2015.城市群多层次空间结构分析算法及其应用:以京津冀城市群为例[J].地理研究,34(8):1447-1460.[Niu F Q,Liu W D,Song T.2015.Amulti-level spatial structure analysis algorithm for urban agglomeration study in China.Geographical Research,34(8):1447-1460.]
潘竟虎,戴维丽.2017.基于网络分析的城市影响区和城市群空间范围识别[J].地理科学进展,36(6):667-676.[Pan J H,Dai W L.2017.Identification of urban hinterlands and urban agglomerations in China based on network analysis.Progress in Geography,36(6):667-676.]
王成新,郝兆印,姚士谋,等.2012.城市群时代中心城市的影响腹地界定研究:以济南市为例[J].人文地理,(4):78-82.[Wang C X,Hao Z Y,Yao S M,et al.2012.Study on the hinterland area of center cities in urban agglomerations era:A case study of Jinan.Human Geography,(4):78-82.]
王丽,邓羽,牛文元.2013.城市群的界定与识别研究[J].地理学报,68(8):1059-1070.[Wang L,Deng Y,Niu W Y.2013.The definition and identification of urban agglomerations.Acta Geographica Sinica,68(8):1059-1070.]
熊丽芳.2014.长三角城市群居民活动时空间特征及范围划界研究:基于微博签到数据[D].南京:南京大学.[Xiong L F.2014.Study on spatio-temporal figure of residents,activity and delimitating the spatial boundary based on sina Micro-blog check-in data:A case study in the Yangtze River Delta.Nanjing,China:Nanjing University.]
姚士谋,陈振光,朱英明,等.中国城市群[M].合肥:中国科学技术大学出版社,2006:5-7.[Yao S M,Chen Z G,Zhu Y M,et al.China's urban agglomeration.Hefei,China:University of Science and Technology of China Press,2006:5-7.]
余斌,刘明华,朱丽霞,等.2012.城市群的边界效应与边界地区发展[J].地理科学,32(6):666-672.[Yu B,Liu H M,Zhu,L X.2012.The border effect and the development of border region between conurbations.Scientia Geographica Sinica,32(6):666-672.]
Bailey T C,Gatrell A C.1995.Interactive spatial data analysis[M].London,UK:Routledge.
Benz U C,Hofmann P,Willhauck G,et al.2004.Multi-resolution,object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J].ISPRS Journal of Photogrammetry and Remote Sensing,58(3/4):239-258.
Duranton G,Puga D.2003.Micro-foundations of urban agglomeration economies[M]//Henderson J V,Thisse J-F.Handbook of Regional and Urban Economics,Volume 4.North-Holland,Netherlands:2063-2117.
Fragkias M,Seto K C.2009.Evolving rank-size distributions of intra-metropolitan urban clusters in South China[J].Computers Environment&Urban Systems,33(3):189-199.
Gottmann J.1957.Megalopolis or the urbanization of the northeastern seaboard[J].Economic Geography,33(7):189-200.
Heidenreich N B,Schindler A,Sperlich S.2013.Bandwidth selection for kernel density estimation:A review of fully automatic selectors[J].Advances in Statistical Analysis,97(4):403-433.
Ma T,Zhou C,Pei T,et al.2014.Responses of Suomi-NPP VI-IRS-derived nighttime lights to socioeconomic activity in China's cities[J].Remote Sensing Letters,5(2):165-174.
Yin J,Soliman A,Yin D.2017.Depicting urban boundaries from a mobility network of spatial interactions:A case study of Great Britain with geo-located Twitter data[J].International Journal of Geographical Information Systems,31(7):1293-1313.
邓羽,刘盛和,蔡建明.2013.中国中部地区城市影响范围划分方法的比较[J].地理研究,32(7):1220-1230.[Deng Y,Liu S H,Cai J M.2013.Comparative study of identification methods to delineate urban spheres of influence in central China.Geographical Research,32(7):1220-1230.]
董青,李玉江,刘海珍.2008.中国城市群划分与空间分布研究[J].城市发展研究,15(6):70-75.[Dong Q,Li Y J,Liu H Z.2008.Research on the spatial distribution and division of urban agglomerations in China.Urban Studies,15(6):70-75.]
董树军.2016.城市群府际博弈的整体性治理研究[D].长沙:湖南大学.[Dong S J.2016.The holistic governance of city cluster intergovernmental game.Changsha,China:Hunan University.]
方创琳.2009.城市群空间范围识别标准的研究进展与基本判断[J].城市规划学刊,(4):1-6.[Fang C L.2009.Research progress and general definition about identification standards of urban agglomeration space.Urban Planning Forum,(4):1-6.]
方创琳.2011.中国城市群形成发育的新格局及新趋向[J].地理科学,31(9):1025-1033.[Fang C L.2011.New structure and new trend of formation and development of urban agglomerations in China.Scientia Geographica Sinica,31(9):1025-1033.]
高晓路,许泽宁,牛方曲.2015.基于“点-轴系统”理论的城市群边界识别[J].地理科学进展,34(3):280-289.[Gao X L,Xu Z N,Niu F Q.2015.Delineating the scope of urban agglomerations based upon the Pole-Axis theory.Progress in Geography,34(3):280-289.]
顾朝林,庞海峰.2008.基于重力模型的中国城市体系空间联系与层域划分[J].地理研究,27(1):1-12.[Gu C L,Pang H.2008.Study on spatial relations of Chinese urban system:Gravity model approach.Geographical Research,27(1):1-12.]
黄建毅,张平宇.2009.辽中城市群范围界定与规模结构分形研究[J].地理科学,29(2):181-187.[Huang J Y,Zhang P Y.2009.Delimitation and fractal research on structure of central liaoning urban agglomeration.Scientia Geographica Sinica,29(2):181-187.]
黄金川.2016.基于辐射扩散测度的中国城市群发育格局识别[J].经济地理,36(11):199-206.[Huang J C.2016.Identification of urban agglomeration in China based on radiation diffusion measurement.Economic Geography,36(11):199-206.]
姜晓丽,张平宇.2013.基于Huff模型的辽宁沿海港口腹地演变分析[J].地理科学,33(3):282-290.[Jiang X L,Zhang P Y.2013.The hinterland evolution of Liaoning coastal ports based on the Huff model.Scientia Geographica Sinica,33(3):282-290.]
柯善咨.2009.中国城市与区域经济增长的扩散回流与市场区效应[J].经济研究,(8):85-98.[Ke S Z.2009.Spreadbackwash and market area effects of urban and regional growth in China.Economic Research,(8):85-98.]
陆大道,陈明星.2015.关于“国家新型城镇化规划(2014-2020)”编制大背景的几点认识[J].地理学报,70(2):179-185.[Lu D D,Chen M X.2015.Several viewpoints on the background of compiling the"National New Urbanization Planning(2014-2020)".Acta Geographica Sinica,70(2):179-185.]
刘卫东.2014.经济地理学与空间治理[J].地理学报,69(8):1109-1116.[Liu W D.2014.Economic geography for spatial governance.Acta Geographica Sinica,69(8):1109-1116.]
牛方曲,刘卫东,宋涛.2015.城市群多层次空间结构分析算法及其应用:以京津冀城市群为例[J].地理研究,34(8):1447-1460.[Niu F Q,Liu W D,Song T.2015.Amulti-level spatial structure analysis algorithm for urban agglomeration study in China.Geographical Research,34(8):1447-1460.]
潘竟虎,戴维丽.2017.基于网络分析的城市影响区和城市群空间范围识别[J].地理科学进展,36(6):667-676.[Pan J H,Dai W L.2017.Identification of urban hinterlands and urban agglomerations in China based on network analysis.Progress in Geography,36(6):667-676.]
王成新,郝兆印,姚士谋,等.2012.城市群时代中心城市的影响腹地界定研究:以济南市为例[J].人文地理,(4):78-82.[Wang C X,Hao Z Y,Yao S M,et al.2012.Study on the hinterland area of center cities in urban agglomerations era:A case study of Jinan.Human Geography,(4):78-82.]
王丽,邓羽,牛文元.2013.城市群的界定与识别研究[J].地理学报,68(8):1059-1070.[Wang L,Deng Y,Niu W Y.2013.The definition and identification of urban agglomerations.Acta Geographica Sinica,68(8):1059-1070.]
熊丽芳.2014.长三角城市群居民活动时空间特征及范围划界研究:基于微博签到数据[D].南京:南京大学.[Xiong L F.2014.Study on spatio-temporal figure of residents,activity and delimitating the spatial boundary based on sina Micro-blog check-in data:A case study in the Yangtze River Delta.Nanjing,China:Nanjing University.]
姚士谋,陈振光,朱英明,等.中国城市群[M].合肥:中国科学技术大学出版社,2006:5-7.[Yao S M,Chen Z G,Zhu Y M,et al.China's urban agglomeration.Hefei,China:University of Science and Technology of China Press,2006:5-7.]
余斌,刘明华,朱丽霞,等.2012.城市群的边界效应与边界地区发展[J].地理科学,32(6):666-672.[Yu B,Liu H M,Zhu,L X.2012.The border effect and the development of border region between conurbations.Scientia Geographica Sinica,32(6):666-672.]
Bailey T C,Gatrell A C.1995.Interactive spatial data analysis[M].London,UK:Routledge.
Benz U C,Hofmann P,Willhauck G,et al.2004.Multi-resolution,object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J].ISPRS Journal of Photogrammetry and Remote Sensing,58(3/4):239-258.
Duranton G,Puga D.2003.Micro-foundations of urban agglomeration economies[M]//Henderson J V,Thisse J-F.Handbook of Regional and Urban Economics,Volume 4.North-Holland,Netherlands:2063-2117.
Fragkias M,Seto K C.2009.Evolving rank-size distributions of intra-metropolitan urban clusters in South China[J].Computers Environment&Urban Systems,33(3):189-199.
Gottmann J.1957.Megalopolis or the urbanization of the northeastern seaboard[J].Economic Geography,33(7):189-200.
Heidenreich N B,Schindler A,Sperlich S.2013.Bandwidth selection for kernel density estimation:A review of fully automatic selectors[J].Advances in Statistical Analysis,97(4):403-433.
Ma T,Zhou C,Pei T,et al.2014.Responses of Suomi-NPP VI-IRS-derived nighttime lights to socioeconomic activity in China's cities[J].Remote Sensing Letters,5(2):165-174.
Yin J,Soliman A,Yin D.2017.Depicting urban boundaries from a mobility network of spatial interactions:A case study of Great Britain with geo-located Twitter data[J].International Journal of Geographical Information Systems,31(7):1293-1313.
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