山东沿海城市带空间格局及演变特征研究
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摘要
夜间灯光数据能够较好反映区域内城市发展状态,在对山东沿海城镇进行空间识别的基础上,通过构建网络化空间模型对山东沿海城市带空间结构及演变特征进行分析.研究发现山东沿海城市整体呈现"》"型空间结构,并通过两条带的交互作用促进了陆海统筹发展和区域一体化;发展态势上,碎化指数和均匀度指数不断提升,沿海城市带由单中心向多中心网络化演变;城市进入极化-扩散阶段,大都市区化特征明显;整体上沿海城市向海发展特征明显,沿海新生长空间不断涌现,同时县域次中心加快被识别,加速了城市空间格局重构.
The night light data can better reflect the development state of the city in the region. The article identifies the entry space of Shandong coastal cities and towns and then analyzes the spatial structure and evolution characteristics by constructing network spatial model. The study finds that the coastal cities show "》" spatial structure, and promotes the co-ordination development of land and sea and regional integration through the interaction of two bands. The fragmentation index and the uniformity index are increasing, and the coastal urban belt evolves from single center to multi center network. The urban has entered the stage of polarization and diffusion, and the characteristics of the metropolitan area are obvious. The coastal cities have obvious characteristics of developing towards the sea, and the new growth space of the coastal areas is constantly emerging. Meanwhile, the county sub centers are identified, which accelerate the reconstruction of the urban spatial pattern.
The night light data can better reflect the development state of the city in the region. The article identifies the entry space of Shandong coastal cities and towns and then analyzes the spatial structure and evolution characteristics by constructing network spatial model. The study finds that the coastal cities show "》" spatial structure, and promotes the co-ordination development of land and sea and regional integration through the interaction of two bands. The fragmentation index and the uniformity index are increasing, and the coastal urban belt evolves from single center to multi center network. The urban has entered the stage of polarization and diffusion, and the characteristics of the metropolitan area are obvious. The coastal cities have obvious characteristics of developing towards the sea, and the new growth space of the coastal areas is constantly emerging. Meanwhile, the county sub centers are identified, which accelerate the reconstruction of the urban spatial pattern.
引文
[1]马学广,窦鹏.基于客运交通流的山东沿海城市带多中心结构特征研究[J].现代城市研究,2017,(10):101-109.
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[4]王慧娟,兰宗敏,金浩,等.基于夜间灯光数据的长江中游城市群城镇体系空间演化研究[J].经济问题探索,2017,(3):107-114.
[5]邹进贵,陈艳华,丁鸽,等.利用DMSP/OLS灯光影像提取城镇建成区的聚类阈值法[J].武汉大学学报:信息科学版,2016,41(2):196-201.
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[12]吴健生,刘浩,彭建,等.中国城市体系等级结构及其空间格局-基于DMSP/OLS夜间灯光数据的实证[J].地理学报,2014,69(6):759-770.
[13]周婕,卢孟.基于MODIS影像和夜间灯光数据的长江中游城市群空间特征研究[J].现代城市研究,2017,(4):14-20.
[14]刘璐.基于夜间灯光数据的城市群蔓延指标[J].国土资源遥感,2018,30(2):208-213.
[15]沈丹,周亮,王培安.基于夜间灯光数据的六盘山连片特困区贫困空间分异特征分析[J].遥感信息,2018,33(4):42-48.
[16]Spiekermann K,Wegener M.Evaluating urban sustainability using land-use transport interaction models[J].European Journal of Transport&Infrastructure Research,2004,4(3):251-272.
[17]杨尚,王发曾.中原城市群城镇体系空间结构分形特征及优化启示[J].河南科学,2007,25(5):849-852.
[18]胡俭.环鄱阳湖城市群经济空间结构与优化研究[D].南昌:江西财经大学,2009.
[19]夏永久.基于分形理论的皖江城市带城镇体系结构演进[J].资源开发与市场,2009,25(1):37-39.
[20]曾鹏,黄图毅,阙菲菲.中国十大城市群空间结构特征比较研究[J].经济地理,2011,31(4):603-608.
[21]甄峰,王波,陈映雪.基于网络社会空间的中国城市网络特征:以新浪微博数据为例[J].地理学报,2012,67(8):1031-1043.
[22]唐子来,李涛.长三角地区和长江中游地区的城市体系比较研究:基于企业关联网络的分析方法[J].城市规划学刊,2014,(2):24-31.
[23]罗震东.分权与碎化-中国都市区域发展的阶段与趋势[J].城市规划,2007,31(11):64-70.
[2]马学广,贾朝祥,张瑞敏.城市群体区域空间联系格局的多尺度研究-以山东沿海城市带为例[J].青岛科技大学学报:社会科学版,2015,(4):1-6.
[3]杨洋,黄聪,何春阳,黄庆旭.山东半岛城市群新型城镇化综合水平的时空变化[J].经济地理,2017,(8):77-85.
[4]王慧娟,兰宗敏,金浩,等.基于夜间灯光数据的长江中游城市群城镇体系空间演化研究[J].经济问题探索,2017,(3):107-114.
[5]邹进贵,陈艳华,丁鸽,等.利用DMSP/OLS灯光影像提取城镇建成区的聚类阈值法[J].武汉大学学报:信息科学版,2016,41(2):196-201.
[6]Henderson J V,Storeygard A,Weil D.Measuring economic growth from outer space[J].The American Economic Review,2012,102(2):994-1028.
[7]徐康宁,陈丰龙,刘修岩.中国经济增长的真实性:基于全球夜间灯光数据的检验[J].经济研究,2015,(9):17-29.
[8]程砾瑜.基于DMSP/OLS夜间灯光数据的中国人口分布时空变化研究[D].北京:中国科学院遥感应用研究所,2008.
[9]Ma T,Zhou C,Tao P,et al.Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data:A comparative case study from China's cities[J].Remote sensing of environment,2012,(124):99-107.
[10]李爱民,刘杉,吕安民.基于卫星遥感影像的郑州市建成区扩展变化研究[J].郑州大学学报:工学版,2011,32(2):125-128.
[11]Small C,Elvidge C D,Balk D,et al.Spatial scaling of stable night lights[J].Remote Sensing of Environment,2011,115(2):269-280.
[12]吴健生,刘浩,彭建,等.中国城市体系等级结构及其空间格局-基于DMSP/OLS夜间灯光数据的实证[J].地理学报,2014,69(6):759-770.
[13]周婕,卢孟.基于MODIS影像和夜间灯光数据的长江中游城市群空间特征研究[J].现代城市研究,2017,(4):14-20.
[14]刘璐.基于夜间灯光数据的城市群蔓延指标[J].国土资源遥感,2018,30(2):208-213.
[15]沈丹,周亮,王培安.基于夜间灯光数据的六盘山连片特困区贫困空间分异特征分析[J].遥感信息,2018,33(4):42-48.
[16]Spiekermann K,Wegener M.Evaluating urban sustainability using land-use transport interaction models[J].European Journal of Transport&Infrastructure Research,2004,4(3):251-272.
[17]杨尚,王发曾.中原城市群城镇体系空间结构分形特征及优化启示[J].河南科学,2007,25(5):849-852.
[18]胡俭.环鄱阳湖城市群经济空间结构与优化研究[D].南昌:江西财经大学,2009.
[19]夏永久.基于分形理论的皖江城市带城镇体系结构演进[J].资源开发与市场,2009,25(1):37-39.
[20]曾鹏,黄图毅,阙菲菲.中国十大城市群空间结构特征比较研究[J].经济地理,2011,31(4):603-608.
[21]甄峰,王波,陈映雪.基于网络社会空间的中国城市网络特征:以新浪微博数据为例[J].地理学报,2012,67(8):1031-1043.
[22]唐子来,李涛.长三角地区和长江中游地区的城市体系比较研究:基于企业关联网络的分析方法[J].城市规划学刊,2014,(2):24-31.
[23]罗震东.分权与碎化-中国都市区域发展的阶段与趋势[J].城市规划,2007,31(11):64-70.