基于路网分割的京津冀城乡空间识别及特征分析

doi:10.13249/j.cnki.sgs.2017.08.005

摘要/Abstract

摘要：

提出一种基于路网分割应用于区域尺度快速识别城乡边界的方法。该方法利用路网与城市空间格局的强耦合联系,通过城乡斑块地理分割与精度计算确定城市斑块的最优解,识别区域城乡空间。以京津冀为例开展方法验证,分析了区域城乡空间格局、路网特征及城市用地经济效率。结果表明,该方法识别精度较高,可用于低成本、快速、高效的区域城乡空间识别;京津冀城市空间格局呈现“大京津、小河北”的差异性,路网密度特征呈现京、津、石3个显著的高密度区域,二者存在高耦合性;2015年该区域城市用地经济效益总体良好,石家庄、保定、和承德3市综合效率值欠佳,需进一步提高土地利用效率。

关键词: 城乡边界, 区域尺度, 道路网络, 空间分析, 京津冀

Abstract:

In recent years, urban expansion is grim with rapid urbanization in China. Border recognition for urban and rural space is the technical prerequisite of urban sprawl control. Existing urban-rural boundary identification methods could accurately extract the city boundaries in theory, but also has some difficulties including data acquisition, poor real-time and heavy workload. Therefore, we proposed an approach based road networks segmentation applied to quickly identify urban border in regional scale. The method was based on strong coupling link between road network and urban spatial structure. Rural patches and urban patches were generated with a geographic division of the road network. By calculating optimal solution of the evaluation accuracy with land use map, rural patches and urban patches were used to identify urban and rural space. Taking Jing-Jin-Ji as an example, the space of urban and rural area was extracted and the related accuracy was verified. Then this article analyzed the spatial pattern of urban and rural, characteristics of road network and economic efficiency of urban land. Results indicated that: 1) The extraction accuracy by this method is high, and it can be used for low-cost, fast and efficient identification for urban-rural space on regional scale; 2) Urban spatial distribution of Jing-Jin-Ji presented a significant differences of “bigger Beijing and Tianjin, smaller Hebei”, and characteristics of road network density presented three remarkable high-density region in Beijing, Tianjin and Shijiazhuang, exhibiting high coupling with urban spatial distribution; 3) The economic efficiency of urban land in Jing-Jin-Ji was generally good in 2015 and overall efficiency value in Shijiazhuang, Baoding and Chengde was poor and needed to further improve the efficiency of land use. In total, spatial identification for urban and rural based on road network data have an advantage from real-time data and relatively high computational efficiency, furtherly enriching the existing urban-rural boundary extraction methods.

Key words: urban-rural area, regional scale, road network, spatial analysis, Beijing-Tianjin-Hebei

中图分类号:

F291

赵国梁, 郑新奇, 刘飞, 刘东亚. 基于路网分割的京津冀城乡空间识别及特征分析[J]. 地理科学, 2017, 37(8): 1159-1169.

Guoliang Zhao, Xinqi Zheng, Fei Liu, Dongya Liu. Urban and Rural Spatial Recognition and Analysis Based on Road Networks Segmentation: A Case Study of Beijing-Tianjin-Hebei[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(8): 1159-1169.

图/表 12

图1

图2

图3

表1

图4

表2

图5

图6

图7

表3

图8

表4

参考文献 33

[1]	C D Storie, J Storie, G Salinas de Salmuni. Urban boundary extraction using 2-component polarimetric SAR decomposition[C]//2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany, IEEE,2012:5741-5744.
[2]	国务院发展研究中心课题组. 城乡空间边界划分的国际经验及启示[J]. 中国发展观察, 2010,(7):54-57.
	[Development and Research center of State Department.The international experience and Enlightenment of the division of the urban and rural space boundary. China Development Observation, 2010,(7):54-57.]
[3]	王迎. 城乡边界划分标准与技术研究[D]. 北京:北京大学, 2010.
	[Wang Ying.Research on the standards and techniques of urban and rural boundary demarcation. Beijing: Peking University, 2010.]
[4]	Ahmadi S,Zoej M J V, Ebadi H et al. Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours[J]. International Journal of Applied Earth Observation & Geoinformation, 2010, 12(3):150-157. doi: 10.1016/j.jag.2010.02.001
[5]	刘沁萍, 杨永春, 付冬暇,等 . 基于DMSP_OLS灯光数据的1992~2010年中国城市空间扩张研究[J]. 地理科学, 2014, 34(2): 129-136.
	[Liu Qinping, Yang Yongchun, Fu Dongxia et al. Urban Spatial Expansion Based on DMSP_OLS Nighttime Light Data in China in 1992-2010. Scientia Geographica Sinica, 2014, 34(2): 129-136.]
[6]	吴小语, 张鹏林. 融合DMSP-OLS和Landsat影像的城区边界提取[J]. 应用科学学报, 2016, 34(1):67-74. doi: 10.3969/j.issn.0255-8297.2016.01.008
	[Wu Xiaoyu, Zhang Penglin.Urban Boundary Extraction by Fusing of DMSP-OLS and Landsat Images.Journal of Applied Sciences,2016, 34(1): 67-74.] doi: 10.3969/j.issn.0255-8297.2016.01.008
[7]	Tannier C, Thomas I, Vuidel Get al. A Fractal Approach to Identifying Urban Boundaries[J]. Geographical Analysis, 2011, 43(2):211-227. doi: 10.1111/j.1538-4632.2011.00814.x
[8]	姚君兰, 王红, 胡斌斌. 基于矢量数据的城市建成区范围提取方法[J]. 测绘通报, 2016, (5): 84-87.
	[Yao Junlan, Wang Hong, Hu Binbin.Urban Built-up Area Extraction Based on Vector Data. Bulletin of Surveying and Mapping, 2016, (5): 84-87.]
[9]	李海江, 刘耀林, 谭荣辉,等. 一种新的基于高分辨率全色影像的城市建成区边界提取算法[J]. 测绘通报, 2015, (7):36-41. doi: 10.13474/j.cnki.11-2246.2015.0206
	[Li Haijiang, Liu Yaolin, Tan Ronghui et al. A New Algorithm of Urban Built-up Area Boundary Extraction Based on High-resolution Panchromatic Image. Bulletin of Surveying and Mapping,2015, (7): 36-41.] doi: 10.13474/j.cnki.11-2246.2015.0206
[10]	谭兴业, 陈彦光. 基于邻域扩展量化法的城市边界识别[J]. 地理科学进展, 2015,34(10):1259-1265.
	[Tan Xingye,Chen Yanguang.Urban boundary identification based on neighborhood dilation. Progress in Geography, 2015, 34(10): 1259-1265.]
[11]	黄祥. 基于综合景观指数的城乡结合部边界划分[J]. 地理空间信息, 2015, 13(4):7-9.
	[Huang Xiang.Urban-rural Fringe Division Based on the Landscape Pattern Index.Geospatial Information, 2015, 13(4):7-9.]
[12]	杨振, 王晓霞, 刘会敏. 洱海流域城镇用地扩展边界划分研究[J]. 经济地理, 2015, 35(2):163-168. doi: 10.15957/j.cnki.jjdl.2015.02.023
	[Yang Zhen, Wang Xiaoxia, Liu Huimin.Defining the Boundary of the Urban Land Expansion in Erhai Lake Basin.Economic Geography, 2015, 35(2):163-168.] doi: 10.15957/j.cnki.jjdl.2015.02.023
[13]	高晓路, 许泽宁, 牛方曲. 基于“点-轴系统”理论的城市群边界识别[J]. 地理科学进展, 2015, 34(3):280-289.
	[Cao Xiaolu,Xu Zening,Niu Fangqu.Delineating the scope of urban agglomerations based upon the Pole-Axis theory. Progress in Geography, 2015, 34(3): 280-289.]
[14]	Barringtonleigh C, Millardball A.A century of sprawl in the United States[J]. Proceedings of the National Academy of Sciences, 2015, 112(5):244-8249. doi: 10.1073/pnas.1419038112 pmid: 25535390
[15]	范科红, 李阳兵, 冯永丽. 基于GIS的重庆市道路密度的空间分异[J]. 地理科学, 2011,31(3):365-371.
	[Fan Kehong, Li Yangbing, Feng Yongli.Spatial distribution of road density in Chongqing based on GIS. Scientia Geographica Sinica, 2011, 31(3): 365-371.]
[16]	赵国梁,郑新奇,原智远,等.道网密度与城镇扩张时空变化特征及关联性分析[J].农业工程学报,2015,31(12):220-229. doi: 10.11975/j.issn.1002-6819.2015.12.030
	[Zhao Guoliang,Zheng Xinqi,Yuan Zhiyuan et al.Spatial and temporal characteristics and correlation analysis of road networks and urban sprawl.Transactions of the Chinese Society of Agricultural Engineering (Transactions ofthe CSAE),2015,31(12):220-229.] doi: 10.11975/j.issn.1002-6819.2015.12.030
[17]	魏伟, 石培基, 脱敏雍,等. 基于GIS的甘肃省道路网密度分布特征及空间依赖度分析[J]. 地理科学, 2012, 32(11):1297-1303.
	[Wei Wei, Shi Peiji, Tuo Minyong et al . The road network density and its spatial dependence in Gansu Province based on GIS. Scientia Geographica Sinica, 2012, 32(11): 1297-1303.]
[18]	Bin Jiang, Xintao Liu.Scaling of geographic space from the perspective of city and field blocks and using volunteered geographic information[J]. International Journal of Geographical Information Science, 2013, 26(2):215-229. doi: 10.1080/13658816.2011.575074
[19]	李京涛,周生路, 吴绍华.道路交通网络与城市土地利用时空耦合关系——以南京市为例[J]. 长江流域资源与环境, 2014, 23(1): 18-25. doi: 10.11870/cjlyzyyhj201401003
	[Li Jingtao, Zhou Shenglu, Wu Shaohua.Relationship between traffic network and urban landuse in Nanjing with landsat TM/ETM+images. Resources and environment in the Yangtze basin, 2014, 23(1): 18-25.] doi: 10.11870/cjlyzyyhj201401003
[20]	李阳兵, 邵景安, 赵岩洁,等 . “二环八射”道路格局对重庆地区建设用地扩展演变特征的驱动[J]. 地理科学, 2014, 34(3): 288-294.
	[Li Yangbing, Shao Jing’an, Zhao Yanjie et al. Influence of Road Pattern of “Two Rings and Eight Radial Highway” on the Evolving of Construction Land in Chongqing Area. Scientia Geographica Sinica, 2014, 34(3): 288-294.]
[21]	刘承良, 余瑞林, 段德忠 . 基于空间句法的武汉城市圈城乡道路网通达性演化分析[J]. 地理科学, 2015, 35(6): 698-707. doi: 10.1016/j.dendro.2011.01.009
	[Liu Chengliang, Yu Ruilin, Duan Dezhong.The evolution of spatial accessibility of urban-rural road network based on the space syntax in Wuhan Metropolitan Area. Scientia Geographica Sinica, 2015, 35(6): 698-707. doi: 10.1016/j.dendro.2011.01.009
[22]	Rozenfeld H D, Rybski D, Gabaix X et al. The area and population of cities: New insights from a different perspective on cities[J]. The American Economic Review, 2011, 101(5): 2205-2225. doi: 10.1257/aer.101.5.2205
[23]	Lämmer S, Gehlsen B, Helbing D.Scaling laws in the spatial structure of urban road networks[J]. Physica A Statistical Mechanics & Its Applications, 2006, 363(1):89-95. doi: 10.1016/j.physa.2006.01.051
[24]	彭代彦, 彭旭辉. 中国城市地价波动的幂律特性[J]. 中国土地科学, 2016, 30(1):61-67.
	[Peng Daiyan, Peng Xuhui.Power Laws Features of Land Price Fluctuation in Chinese Cities. China Land Science, 2016, 30(1):61-67]
[25]	魏权龄. 数据包络分析(DEA)[J]. 科学通报, 2000, 45(17):1793-1808.
	[Wei Quanling.Data envelopment analysis (DEA). Chinese Science Bulletin, 2000, 45(17): 1793-1808.]
[26]	郑新奇, 王筱明. 城镇土地利用结构效率的数据包络分析[J]. 中国土地科学, 2004, 18(2):34-39. doi: 10.3969/j.issn.1001-8158.2004.02.006
	[Zheng Xinqi, Wang Xiaoming.DEA Analysis for the Efficiency of land use structure in Cities and towns. China Land Science,2004,18(2):34-39.] doi: 10.3969/j.issn.1001-8158.2004.02.006
[27]	陈雪婷, 宋涛, 蔡建明,等 . 基于DEA和Malmquist的中国城市代谢效率研究[J]. 地理科学, 2015, 35(4): 419-426.
	[Chen Xueting, Song Tao, Cai Jianming et al. The Chinese Urban Metabolic Efficiencies Based on the DEA and Malmquist. Scientia Geographica Sinica, 2015, 35(4): 419-426.]
[28]	Street Map contributors. Copyright and License[J/OL]..
[29]	国家统计局.中国城市统计年鉴(2015)[M].北京:中国统计出版社,2015.
	[National Bureau of Statistics of China. National Bureau of Statistics of China city statistical yearbook (2015).Beijing: China Statistics Press, 2015.]
[30]	北京市统计局,国家统计局北京调查总队.北京统计年鉴(2015)[M] .北京:中国统计出版社,2015.
	[Beijing Municipal Bureau of Statistics,NBS Survey Office in Beijing.Beijing Statistical Yearbook (2015).Beijing: China Statistics Press, 2015.]
[31]	王丽, 邓羽, 牛文元. 城市群的界定与识别研究[J]. 地理学报, 2013, 68(8):1059-1070.
	[Wang Li, DengYu, Niu Wenyuan. The definition and identification of urban agglomerations. Acta Geographica Sinica, 2013, 68(8): 1059-1070.]
[32]	文魁, 祝尔娟, 叶堂林,等. 京津冀发展报告(2016)[M]. 北京:社会科学文献出版社, 2016.
	[Wen Kui, Zhu Erjuan, Ye Tanglin et al. Annual Report on Beijing-Tianjin-Hebei Metropolitan Region Development(2016).Beijing:Social Sciences Academic Press(China),2016.]
[33]	杨建军,汤燕,连城. 交通引导下的城市群空间组织研究——以浙中城市群为例[J]. 浙江大学学报(理学版), 2005, 32(5):584-587. doi: 10.3321/j.issn:1008-9497.2005.05.024
	[Yang Jianjun, Tang Yan, Lian Cheng.Research on urban agglomerations’spatial organization oriented by transportation: The case of mid-Zhejiang urban agglomeration. Journal of Zhejiang University (Science Edition), 2005, 32(5): 584-587.] doi: 10.3321/j.issn:1008-9497.2005.05.024

目标层	要素层	指标	单位	指标代码
投入	资本	单位土地固定资本额	万元/km²	a11
	资本	单位土地财政支出额	万元/km²	a12
	劳动	单位土地第二产业从业人数	人/km²	b11
	劳动	单位土地第三从业人数	人	b12
	土地	建成区面积	km²	c11
产出	经济	单位土地第二产业产值	万元/km²	d11
		单位土地第三产业产值	万元/km²	d12
		单位土地财政收入	万元/km²	d13
	生态环境	建成区绿化覆盖率	％	e11

区域	地块总数	最小面积（km²）	最大面积（km²）	总面积（km²）	平均面积（km²）	标准差
北京	53285	1.08E-06	751.949	16377.932	0.307	7.070
天津	19281	1.01E-06	285.244	11611.688	0.602	5.353
河北	26567	1.02E-06	2964.834	187276.661	7.049	70.119
总计	98753	1.02E-06	2964.834	215266.384	2.180	36.933

城市	城市斑块	城乡斑块比	地区面积（km²）	市辖区面积（km²）	市辖区比例（%）	建成区面积（km²）	市辖区人口（万人）	人口密度（万人/km²）	GDP（当年价格）（亿元）
承德	941	1.9	39414	659	1.7	115	59	0.52	280
张家口	2208	10.7	36636	602	1.6	105	91	0.87	450
北京	50909	21.2	16376	12177	74.4	1386	2072	1.50	21019
秦皇岛	2305	29.6	7748	396	5.1	103	90	0.87	731
唐山	3158	8.3	13018	3309	25.4	296	330	1.11	3173
廊坊	2498	7.5	6410	979	15.3	101	84	0.83	656
天津	18324	18.7	11613	7118	61.3	738	1278	1.73	14291
保定	2308	6.4	22283	2550	11.4	146	281	1.92	553
沧州	1750	5.8	14104	165	1.2	68	54	0.80	641
石家庄	3993	12.0	14045	2170	15.4	264	408	1.55	2735
衡水	871	4.5	8817	592	6.7	48	54	1.13	260
邢台	1389	7.4	12474	162	1.0	90	88	0.97	274
邯郸	2220	7.4	12035	466	3.9	124	174	1.40	794

城市	综合效率	纯技术效率	规模效率	规模收益
北京市	1	1	1	-
天津市	1	1	1	-
石家庄市	0.855	0.874	0.978	irs
唐山市	1	1	1	-
秦皇岛市	1	1	1	-
邯郸市	1	1	1	-
邢台市	1	1	1	-
保定市	0.996	1	0.996	irs
张家口市	1	1	1	-
承德市	0.913	0.997	0.916	irs
沧州市	1	1	1	-
廊坊市	1	1	1	-
衡水市	1	1	1	-
平均数	0.982	0.990	0.991