基于灯光数据的中国县域城市规模时空格局分析
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摘要
为掌握城市规模时空格局演化规律,促进区域协调发展,以平均灯光强度表征城市规模,采取探索性时空数据分析(exploratory time-space data analysis,ESTDA)的研究框架对我国1992～2015年的县域城市规模时空格局进行分析。结果发现:(1)中国县域城市规模的核心-边缘结构与局部空间关联格局较为稳定但趋向动荡,城市规模变化呈现出"稳步增长"、"逐级递增"的特点,城市局部关联较弱,缺乏共同向上跃迁的动力;(2)京汕断裂带、110°E与100°E三条LL断裂带将城市规模空间格局割裂,阻碍了区域协调发展,但城市规模空间格局有可能突破胡焕庸线;(3) 2003年后城市规模的局部空间动态性、增长波动性与局部依赖性增强。东部的局部空间动态性趋于稳定,中西部局部空间动态性开始增强,城市规模增长波动性与局部依赖性重心向南方与东北方向转移;(4)自然因素、交通状况、城市行政级别、政策导向、经济发展水平、人口规模与空间临近效应是影响县域城市规模时空格局的主要因素。研究表明利用灯光数据进行城市规模研究具有科学性与可行性,未来应该着力构筑东中西部互联互动的网络通道,实现区域协调发展。
It is necessary to research the city scale,especially the change of spatial-temporal pattern and the dynamic evolution of which is the key to promote regional coordinated development. Based on the night-time light data,this paper calculated the city scale at county level in China during the 1992-2015 by average night light index,then analyzed it by ESTDA framework. The result shows: First,the core-periphery structure and the local spatial pattern of city scale is stable,but was becoming fluctuating. The city scale was growing slowly,but the city local correction is weak,and lacks the force of common motivation to jump upward. Second,the spatial pattern of city scale was separated by Jing-Shan economic trough belt,110°E belt,and 100°E belt,however the Hu Line may be broken in the future. Third,the local spatial dynamics,growth volatility and local dependence of the city scale after 2003 was increased,and the local dynamics of city scale becomed stable in east,but unstable in west. Meanwhile the center of growth volatility and local dependence shifted to the south and northeast; Forth,the main factors affecting the spatial-temporal pattern and dynamic evolution of city scale at county level were the natural factors,traffic conditions,urban administrative levels,spatial effects,policy orientation and economic development level,and so on. Finally,this research has proved that it is scientific to use the night-time light data to calculate the city scale,and it is important to establish a network for different regions to achieve coordinated development.
It is necessary to research the city scale,especially the change of spatial-temporal pattern and the dynamic evolution of which is the key to promote regional coordinated development. Based on the night-time light data,this paper calculated the city scale at county level in China during the 1992-2015 by average night light index,then analyzed it by ESTDA framework. The result shows: First,the core-periphery structure and the local spatial pattern of city scale is stable,but was becoming fluctuating. The city scale was growing slowly,but the city local correction is weak,and lacks the force of common motivation to jump upward. Second,the spatial pattern of city scale was separated by Jing-Shan economic trough belt,110°E belt,and 100°E belt,however the Hu Line may be broken in the future. Third,the local spatial dynamics,growth volatility and local dependence of the city scale after 2003 was increased,and the local dynamics of city scale becomed stable in east,but unstable in west. Meanwhile the center of growth volatility and local dependence shifted to the south and northeast; Forth,the main factors affecting the spatial-temporal pattern and dynamic evolution of city scale at county level were the natural factors,traffic conditions,urban administrative levels,spatial effects,policy orientation and economic development level,and so on. Finally,this research has proved that it is scientific to use the night-time light data to calculate the city scale,and it is important to establish a network for different regions to achieve coordinated development.
引文
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[2]蒋涛,沈正平.聚集经济与最优城市规模探讨[J].人文地理,2007,22(6):68-71.JIANG T,SHEN Z P. A tentative study on the agglomeration economy and the optimal city size[J]. Human Geography,2007,22(6):68-71.
[3] ZIPF G K. 1949. Human behavior and the principle of least effort[M]. Cambridge,MA:Addison-Wesley Press.
[4] JEFFERSON M. The law of the Primate city[J]. Geographical Review,1939,29(2):226-232.
[5]沃尔特·克里斯塔勒.德国南部中心地原理[M].北京:商务印书馆,2010.CHRISTALLER W. The principle of central location in southern Germany[M]. Beijing:The Commercial Press,2010.
[6] MANDELBROT B. Fractal Geometry of Nature[M]. W. H.Freeman,1982.
[7]叶浩,庄大昌.城市体系规模分布与空间分布的关系研究[J].世界地理研究,2015(3):75-82.YE H,ZHUANG D C. The relationship between Size distribution and spatial distribution of urban systems[J]. World Regional Studies,2015(3):75-82.
[8]蒲英霞,马荣华,马晓冬,等.长江三角洲地区城市规模分布的时空演变特征[J].地理研究,2009,28(1):161-172.PU Y X,MA R H,MA X D. et al. Spatio-temporal dynamics of city-size distribution in Yangtze River delta[J]. Geographical Research,2009,28(1):161-172.
[9]孙在宏,袁源,王亚华,等.基于分形理论的江苏省城市规模分布与异速生长特征[J].地理研究,2011,30(12):2163-2172.SUN Z H,YUAN Y,WANG Y H,et al. Research on city-size distribution and allometric growth in Jiangsu Province based on fractal theory[J]. Geographical Research,2011,30(12):2163-2172.
[10] PEZ A,SCOTT D M. Spatial statistics for urban analysis:A review of techniques with examples[J]. Geojournal,2004,61(1):53-67.
[11] HENDERSON J V. Economic theory and the cities[M]//Economic theory and the cities. Academic Press,1985.
[12]王海军,王惠霞,邓羽,等.武汉城市圈城镇用地扩展的时空格局与规模等级模式分异研究[J].长江流域资源与环境,2018,27(2):272-285.
[13]程开明,庄燕杰.城市体系位序-规模特征的空间计量分析——以中部地区地级以上城市为例[J].地理科学,2012,32(8):905-912.CHEN K M,ZHUANG Y J. Spatial econometric analysis of the rank-size rule for urban system:A case of prefectural-level cities in China’ s middle area[J]. Scientia Geographica Sinica,2012,32(8):905-912.
[14]戚伟,刘盛和.中国城市流动人口位序规模分布研究[J].地理研究,2015,34(10):1981-1993.QI W,LIU S H. Research on the rank-size distribution rule of China’s urban floating population[J]. Geographical Research,2015,34(10):1981-1993.
[15]谈明洪,吕昌河.以建成区面积表征的中国城市规模分布[J].地理学报,2003,58(2):285-293.TAN M H,LU C H. Distribution of China city size expressed by urban built-up area[J]. Acta Geographica Sinica,2003,58(2):285-293.
[16]吕薇,刁承泰.中国城市规模分布演变特征研究[J].西南大学学报(自然科学版),2013,35(6):136-141.LU WEI,DIAO C T. Characteristics of evolution in city-size distribution in china[J]. Journal of Southwest University(Natural Science Edition),2013,35(6):136-141.
[17] 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.
[18]周一星,张莉.改革开放条件下的中国城市经济区[J].地理学报,2003,58(2):271-284.ZHOU Y X,ZHANG L. China’s urban economic region in the open context[J]. Acta Geographica Sinica,2003,58(2):271-284.
[19]潘竟虎,戴维丽.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,2017,36(6):667-676.PAN J H,DAI W L. Identification of urban hinterlands and urban agglomerations in China based on network analysis[J].Progress in Geography,2017,36(6):667-676.
[20]郭源园,胡守庚,金贵.基于改进城市引力模型的湖南省经济区空间格局演变研究[J].经济地理,2012,32(12):67-72.GUO Y Y,HU S G,JIN G. Evolution of spatial pattern on Hunan province’s economic zones based on improved Gravitational models of cities[J]. Economic Geography,2012,32(12):67-72.
[21]王茂军,曹广忠,赵群毅,等.基于距离与规模的中国城市体系规模结构[J].地理研究,2010,29(7):1257-1268.WANG M J,CAO G Z,ZHAO Q Y,et al. Study on structure of urban system in China from the angles of distance between cities and city population size[J]. Geographical Research,2010,29(7):1257-1268.
[22]钟业喜,陆玉麒.基于铁路网络的中国城市等级体系与分布格局[J].地理研究,2011,30(5):785-794.ZHONG Y X,LU Y Q. Hierarchical structure and distribution pattern of Chinese urban system based on railway network[J].Geographical Research,2011,30(5):785-794.
[23]孙在宏,袁源,王亚华,等.基于分形理论的江苏省城市规模分布与异速生长特征[J].地理研究,2011,30(12):2163-2172.SUN Z H,YUAN Y,WANG Y H,et al. Research on city-size distribution and allometric growth in Jiangsu Province based on fractal theory[J]. Geographical Research,2011,30(12):2163-2172.
[24]刘涛,曹广忠.城市规模的空间聚散与中心城市影响力—基于中国637个城市空间自相关的实证[J].地理研究,2012,31(7):1317-1327.LIU T,CAO G Z. Agglomeration and dispersion of city sizes and the influence of central cities:Based on the multi-scale spatial autocorrelation and the case of China.[J]. Geographical Research,2012,31(7):1317-1327.
[25]张子昂,黄震方,曹芳东,等.浙江省县域入境旅游时空跃迁特征及驱动机制[J].地理研究,2016,35(6):1177-1192.ZHANG Z A,HUANG Z F,CAO F D,et al. The space-time transition characteristics and its driving mechanism of countyscale inbound tourism in Zhejiang province[J]. Geographical Research,2016,35(6):1177-1192.
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