中国大城市蔓延指数的开发

doi:10.11821/dlxb202012013

地理学报 ›› 2020, Vol. 75 ›› Issue (12): 2730-2743.doi: 10.11821/dlxb202012013

中国大城市蔓延指数的开发

岳文泽¹^,²(), 吴桐¹, 刘学¹, 张琳琳³(), 吴次芳¹^,², 叶艳妹¹^,², 郑国轴⁴

1.浙江大学土地管理系,杭州 310058
2.自然资源部城乡建设用地节约集约利用实验室,北京 100812
3.浙江工商大学城乡规划系,杭州 310018
4.浙江大学计算机科学与技术学院,杭州 310007

收稿日期:2019-08-05 修回日期:2020-06-30 出版日期:2020-12-25 发布日期:2021-02-25
作者简介:岳文泽(1977-), 男, 安徽凤台人, 博士, 教授, 博士生导师, 研究方向为城镇化与土地利用。E-mail: wzyue@zju.edu.cn
基金资助:
国家自然科学基金项目(41871169);国家自然科学基金项目(41671533);浙江省自然科学基金项目(LQ20D010004)

Developing an urban sprawl index for China's mega-cities

YUE Wenze¹^,²(), WU Tong¹, LIU Xue¹, ZHANG Linlin³(), WU Cifang¹^,², YE Yanmei¹^,², ZHENG Guozhou⁴

1. Department of Land Management, Zhejiang University, Hangzhou, 310058, China
2. Laboratory for Saving and Intensive Utilization of Urban and Rural Construction Land by Ministry of Natural Resources, Beijing 100812, China
3. Department of Urban-rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
4. College of Computer Science and Technology, Zhejiang University, Hangzhou 310007, China

Received:2019-08-05 Revised:2020-06-30 Published:2020-12-25 Online:2021-02-25
Supported by:
National Natural Science Foundation of China(41871169);National Natural Science Foundation of China(41671533);Zhejiang Provincial Natural Science Foundation(LQ20D010004)

摘要/Abstract

摘要：

城市蔓延已成为具有普遍意义的现象,然而,城市蔓延内涵的争议性和模糊性问题一直没有得到很好的解决。本文将城市蔓延定义为一种低效、低密度、无序的城市空间开发模式,这种开发模式与中国城市高质量发展的目标和要求是相违背的。为实现对城市蔓延的宏观管理和精准调控,有效遏制城市蔓延带来的负面影响,本文开发了一套多维度、可比较的,并且与城镇化质量紧密关联的城市蔓延指数。基于卫星影像与人口、经济统计数据,选取代表城市蔓延核心特征的多个指标,采用主成分分析法计算了全国主要大城市2014年城市蔓延指数。结果发现,经济效率维主成分对综合蔓延指数贡献最大（41.30%）,人口密度维主成分次之（20.49%）,空间形态维主成分贡献率排第三（12.35%）。值得注意的是,许多经济发展较落后的城市因为经济效率维度的短板效应显著而被列入最蔓延的行列。此外,不同维度城市蔓延指数空间分布差异明显,并且综合蔓延指数与城市规模呈一定的负相关关系。

关键词: 城市蔓延指数, 测度, 空间形态, 密度, 效率

Abstract:

Urban sprawl has become a global phenomenon. There is, however, no consensus on the connotation of urban sprawl, which still remains subjective to controversy and ambiguity. In this paper, urban sprawl was defined as an inefficient, low-density and disordered mode of urban space development. The definition includes three of the most recognized characteristics of urban sprawl summarized from previous studies. Characterized by the features mentioned above, urban sprawl has been recognized as an important challenge to the high-quality development of cities in China. Therefore, to build an urban sprawl index that can reflect the quality of urbanization is of significance to macro-micro regulation of urban sprawl. Multiple metrics representing the core characteristics of urban sprawl were selected as measuring indexes, based on satellite images and socio-economic statistical data. Furthermore, in order to make the results more objective and comparable, the method of principal component analysis was applied to calculate the comprehensive sprawl index. Finally, 106 of China's mega-cities were chosen as cases, and the degree of urban sprawl of each city was measured for the year 2014. As shown from the results, the first principal component mainly reflected the dimension of economic efficiency, contributing 41.30% to the comprehensive sprawl index. The second principal component mainly represented the dimension of population density, followed by the third principal component that described morphological dimension. It is noteworthy that, because the short board effect of economic efficiency dimension was significant, many less-developed cities were ranked to a high sprawling level. In addition, the spatial distribution of different dimensions of urban sprawl index were distinct. Population density and land use efficiency were generally consistent with each other, while the distributing law of city form showed distinguishing features. Last but not least, the comprehensive sprawl index had a certain negative correlation with city scale, which reminds us to pay more attention to urban sprawl in medium-sized cities in the future.

Key words: urban sprawl index, measurement, spatial morphology, density, efficiency

岳文泽, 吴桐, 刘学, 张琳琳, 吴次芳, 叶艳妹, 郑国轴. 中国大城市蔓延指数的开发[J]. 地理学报, 2020, 75(12): 2730-2743.

YUE Wenze, WU Tong, LIU Xue, ZHANG Linlin, WU Cifang, YE Yanmei, ZHENG Guozhou. Developing an urban sprawl index for China's mega-cities[J]. Acta Geographica Sinica, 2020, 75(12): 2730-2743.

图/表 12

表1

城市蔓延测度指标体系

一级指标	二级指标	二级指标方向	说明
空间紧凑度	景观形状指数(X₁)	正向	$LSI = ∑ i = 1 n p i 4 ∑ i = 1 n a i$ ,p_i和a_i分别为第i个建设用地斑块的周长和面积; n为建设用地斑块数(下同)。
	平均最近邻距离(X₂)	正向	$MNN = ∑ i = 1 n d i n$ ,d_i为第i个建设用地斑块与最近邻建设用地斑块间的欧氏距离。
	分离度(X₃)	正向	$SPLIT = A 2 ∑ i = 1 n a i 2$ ,a_i为第i个建设用地的面积;A为建设用地总面积。
人口聚集度	户籍人口密度(X₄)	负向	户籍人口/建设用地面积
	常住人口密度(X₅)	负向	常住人口/建设用地面积
	从业人口密度(X₆)	负向	从业人口/建设用地面积
建设用地效率	地均GDP(X₇)	负向	市辖区GDP/建设用地面积
	地均二三产值(X₈)	负向	市辖区二三产值/建设用地面积
	地均财政收入(X₉)	负向	市辖区财政收入/建设用地面积

表1

图1

图2

表2

图3

图4

图5

图6

表3

表4

表5

图7

参考文献 38

[1]	Ewing R. Characteristics, causes, and effects of sprawl: A literature review. Environmental and Urban Issues, 1994,21(2):1-15.
[2]	Galster G, Hanson R, Ratcliffe M R, et al. Wrestling sprawl to the ground: Defining and measuring an elusive concept. Housing Policy Debate, 2001,12(4):681-717.
[3]	Frenkel A, Ashkenazi M. Measuring urban sprawl: How can we deal with it. Environment & Planning B Planning & Design, 2008,35(1):56-79.
[4]	Harvey R O, Clark W. The nature and economics of urban sprawl. Land Economics, 1965,41(1):1-9.
[5]	Burchell R, Shad N, Listokin D, et al. The Costs of Sprawl-Revisited. Report 39. Washington, DC: Transit Cooperative Research Program. Transportation Research Board, National Research Council, 1998.
[6]	Brueckner J K. Urban sprawl: Diagnosis and remedies. International Regional Science Review, 2000,23(2):160-171.
[7]	Schweitzer L, Zhou J. Neighborhood air quality, respiratory health, and vulnerable populations in compact and sprawled regions. Journal of the American Planning Association, 2010,76(3):363-371.
[8]	Stone B, Hess J J, Frumkin H. Urban form and extreme heat events: Are sprawling cities more vulnerable to climate change than compact cities. Environmental Health Perspectives, 2010,118(10):1425-1428. doi: 10.1289/ehp.0901879 pmid: 21114000
[9]	Ewing R, Hamidi S, Grace J B, et al. Does urban sprawl hold down upward mobility. Landscape & Urban Planning, 2016,148:80-88.
[10]	He J, Liu Y, Yu Y, et al. A counterfactual scenario simulation approach for assessing the impact of farmland preservation policies on urban sprawl and food security in a major grain-producing area of China. Applied Geography, 2013,37(1):127-138. doi: 10.1016/j.apgeog.2012.11.005
[11]	Saravanan P, Ilangovan P. Identification of urban sprawl pattern for Madurai region using GIS. International Journal of Geomatics & Geosciences, 2010(2):141-149.
[12]	Sperandelli D I, Dupas F A, Pons N A D. Dynamics of urban sprawl, vacant land, and green spaces on the metropolitan fringe of São Paulo, Brazil. Journal of Urban Planning & Development, 2013,139(4):274-279.
[13]	Ujoh F, Kwabe I D, Ifatimehin O O. Understanding urban sprawl in the federal capital city, Abuja: Towards sustainable urbanization in Nigeria. Environment & Planning A, 2010,3(5):106-113.
[14]	Hamidi S, Ewing R. A longitudinal study of changes in urban sprawl between 2000 and 2010 in the United States. Landscape & Urban Planning, 2014,128(3):72-82.
[15]	Lyu Tiangui, Wu Cifang, Li Hongyi, et al. The coordination and its optimizationabout population and land of urbanization: A case study of Nanchang City. Scientia Geographica Sinica, 2016,36(2):239-246.
	[ 吕添贵, 吴次芳, 李洪义, 等. 人口城镇化与土地城镇化协调性测度及优化: 以南昌市为例. 地理科学, 2016,36(2):239-246.]
[16]	Fulton W, Pendall R, Nguyen M, et al. Who Sprawls Most? How Growth Patterns Differ across the U.S. Washington, DC: Brookings Institution, Center on Urban and Metropolitan Policy, 2001.
[17]	Whyte W H. The Exploding Metropolis. New York: Doubleday, 1958: 133-156.
[18]	Gottmann J. Megalopolis: The Urbanized Northeastern Seaboard of the United States. New York: The Twentieth Century Fund, 1961: 13-25.
[19]	Anderson W P, Kanaroglou P S, Miller E J. Urban form, energy and the environment: A review of issues, evidence and policy. Urban Studies, 1996,33(1):7-36. doi: 10.1080/00420989650012095
[20]	Dutton J A. New American Urbanism: Reforming the Suburban Metropolis. London: Distributed Elsewhere by Thames & Hudson, 2000: 15-27.
[21]	Soule D C. Urban Sprawl: A Comprehensive Reference Guide. Westport, CT: Greenwood Press, 2006: 3-11.
[22]	Batty M, Longley P. Fractal Cities a Geometry ofForm and Function. San Diego, CA: Academic Press Professional, Inc, 1994: 30-55.
[23]	Fulton W. The New Urbanism. Cambridge, MA: Lincoln Institute of Land Policy, 1996: 1-7.
[24]	Burton E. The compact city: Just or just compact? A preliminary analysis. Urban Studies, 2000,37(11):1969-2006.
[25]	Ewing R, Pendall R, Chen D D T. Measuring sprawl and its impact. Smart Growth America, 2002,57(2):320-326.
[26]	Zeng Chen. Multi Level-Dimension Measurement and Multi Scale-Strategy Spatial Regression Modeling for Urban Sprawl. Beijing: Science Press, 2016: 45-57.
	[ 曾晨. 城市蔓延的多层次多维度测度和多尺度多策略空间回归建模. 北京: 科学出版社, 2016: 45-57.]
[27]	Zhang Linlin. Research on the urban sprawl in transitional China: Multi-scale measurement, mechanism, and remedies[D]. Hangzhou: Zhejiang University, 2018.
	[ 张琳琳. 转型期中国城市蔓延的多尺度测度, 内在机理与管控研究[D]. 杭州: 浙江大学, 2018.]
[28]	Lopez R, Hynes H P. Sprawl in the 1990s measurement, distribution, and trends. Urban Affairs Review, 2003,38(3):325-355. doi: 10.1177/1078087402238805 pmid: 16990927
[29]	Gao B, Huang Q, He C, et al. How does sprawl differ across cities in China? A multi-scale investigation using nighttime light and census data. Landscape & Urban Planning, 2016,148(41):89-98.
[30]	Wang Jiating, Zhang Juntao. Measurement on the urban spreading in China: Empirical study based on the panel data of 35 large and middle cities. Economist, 2010(10):56-63.
	[ 王家庭, 张俊韬. 我国城市蔓延测度: 基于35个大中城市面板数据的实证研究. 经济学家, 2010(10):56-63.]
[31]	Yue W, Liu Y, Fan P. Measuring urban sprawl and its drivers in large Chinese cities: The case of Hangzhou. Land Use Policy, 2013,31(31):358-370.
[32]	Jiang Fang, Liu Shenghe, Yuan Hong. Measuring urban sprawl in Beijing with geo-spatial indices. Acta Geographica Sinica, 2007,62(6):649-658.
	[ 蒋芳, 刘盛和, 袁弘. 北京城市蔓延的测度与分析. 地理学报, 2007,62(6):649-658.]
[33]	Xu C, Liu M, Zhang C, et al. The spatiotemporal dynamics of rapid urban growth in the Nanjing metropolitan region of China. Landscape Ecology, 2007,22(6):925-937.
[34]	Zhang Linlin, Yue Wenze, Fan Beilei. Measuring urban sprawl in large Chinese cities: A case study of Hangzhou. Scientia Geographica Sinica, 2014,34(4):394-400.
	[ 张琳琳, 岳文泽, 范蓓蕾. 中国大城市蔓延的测度研究: 以杭州市为例. 地理科学, 2014,34(4):394-400.]
[35]	Yang Yu. Analysis of weighting methods in multi-index comprehensive evaluation. Statistics & Decision, 2006(13):17-19.
	[ 杨宇. 多指标综合评价中赋权方法评析. 统计与决策, 2006(13):17-19.]
[36]	Zhang Yaoting. Lecture Notes of Multiple Statistical Analysis. Beijing: China Statitics Press, 2003.
	[ 张尧庭. 多元统计分析选讲. 北京: 中国统计出版社, 2003.]
[37]	Gao Huixuan. Application of Multivariate Statistical Analysis. Beijing: Peking University Press, 2005.
	[ 高惠璇. 应用多元统计分析. 北京: 北京大学出版社, 2005.]
[38]	Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective. Acta Geographica Sinica, 2017,72(1):116-134.
	[ 王劲峰, 徐成东. 地理探测器: 原理与展望. 地理学报, 2017,72(1):116-134.]

指标	第一主成分	第二主成分	第三主成分
X₁	0.489	-0.574	-0.143
X₂	-0.328	0.218	0.596
X₃	-0.053	0.506	0.651
X₄	0.113	0.838	-0.422
X₅	0.603	0.682	-0.216
X₆	0.772	0.126	0.026
X₇	0.923	-0.043	0.174
X₈	0.924	-0.069	0.170
X₉	0.830	-0.144	0.169
特征值	3.717	1.844	1.111
方差贡献率(%)	41.296	20.489	12.348
累计贡献率(%)	41.296	61.785	74.133

地理分区	城市数量(个)	城市名称
东北地区	20	鞍山、本溪、长春、大连、大庆、丹东、抚顺、阜新、哈尔滨、鹤岗、鸡西、吉林、佳木斯、锦州、辽阳、牡丹江、盘锦、齐齐哈尔、沈阳、伊春
华北地区	12	包头、保定、北京、大同、邯郸、呼和浩特、秦皇岛、石家庄、太原、唐山、天津、张家口
华东地区	34	常州、德州、东营、福州、杭州、合肥、淮北、淮南、济南、嘉兴、临沂、马鞍山、南昌、南京、南通、宁波、青岛、厦门、上海、绍兴、苏州、台州、泰安、泰州、威海、潍坊、温州、无锡、徐州、烟台、扬州、枣庄、镇江、淄博
华南地区	14	东莞、佛山、广州、桂林、海口、惠州、江门、柳州、南宁、汕头、深圳、湛江、中山、珠海
华中地区	16	安阳、新乡、焦作、平顶山、荆州、南阳、开封、洛阳、襄阳、武汉、黄石、衡阳、株洲、长沙、郑州、湘潭
西北地区	5	兰州、乌鲁木齐、西安、西宁、银川
西南地区	5	成都、重庆、贵阳、昆明、拉萨

地理区位		东北	华北	华东	华南	华中	西北	西南	总体
第一主成分效率维	最大值	2.357	2.342	2.650	2.067	2.237	2.309	2.496	2.650
	最小值	1.775	1.210	1.389	0.814	1.297	1.778	1.249	0.814
	平均值	2.087	1.908	1.865	1.641	1.883	2.015	1.897	1.893
	标准差	0.188	0.332	0.275	0.404	0.238	0.203	0.515	0.314
第二主成分密度维	最大值	1.389	1.146	1.291	1.295	1.072	1.115	1.379	1.389
	最小值	0.735	0.443	0.491	0.614	0.537	0.768	0.453	0.443
	平均值	0.970	0.871	0.984	0.933	0.796	0.915	0.909	0.927
	标准差	0.173	0.219	0.189	0.217	0.138	0.148	0.329	0.199
第三主成分形态维	最大值	1.428	0.628	0.854	1.346	0.737	0.538	0.647	1.428
	最小值	0.287	0.278	0.205	0.000	0.246	0.347	0.350	0.000
	平均值	0.577	0.443	0.451	0.579	0.540	0.450	0.439	0.504
	标准差	0.253	0.120	0.148	0.338	0.123	0.078	0.120	0.202
综合蔓延指数	最大值	1.352	1.237	1.372	1.223	1.169	1.225	1.356	1.372
	最小值	0.968	0.733	0.758	0.523	0.747	0.958	0.661	0.523
	平均值	1.132	1.021	1.027	0.940	1.007	1.075	1.024	1.034
	标准差	0.112	0.163	0.136	0.201	0.114	0.104	0.267	0.155

城市规模		超大城市 (1000万以上)	特大城市 (500万~1000万)	大城市Ⅰ型（300万~500万)	大城市Ⅱ型 (100万~300万)	中等城市 (50万~100万)	总体
第一主成分效率维	最大值	1.584	2.062	2.181	2.650	2.496	2.650
	最小值	0.814	1.249	1.434	1.114	1.297	0.814
	平均值	1.206	1.734	1.893	1.935	2.086	1.893
	标准差	0.317	0.248	0.221	0.263	0.300	0.314
第二主成分密度维	最大值	1.023	1.295	1.172	1.389	1.379	1.389
	最小值	0.443	0.453	0.719	0.491	0.625	0.443
	平均值	0.773	0.887	0.952	0.932	0.958	0.927
	标准差	0.238	0.237	0.133	0.208	0.190	0.199
第三主成分形态维	最大值	0.378	1.346	0.544	1.029	1.428	1.428
	最小值	0.000	0.219	0.246	0.277	0.350	0.000
	平均值	0.221	0.504	0.390	0.543	0.593	0.504
	标准差	0.139	0.303	0.087	0.157	0.242	0.202
综合蔓延指数	最大值	0.858	1.223	1.165	1.372	1.356	1.372
	最小值	0.523	0.661	0.800	0.758	0.747	0.523
	平均值	0.684	0.960	1.025	1.057	1.131	1.034
	标准差	0.139	0.145	0.095	0.126	0.154	0.155

中国大城市蔓延指数的开发

Developing an urban sprawl index for China's mega-cities

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