基于空间插值的浙江省城市流时空演变特征研究

doi:10.12118/j.issn.1000-6060.2019.01.25

Abstract

Abstract: In order to explore the spatial and temporal characteristics of the interaction among the cities in developed province, this paper takes Zhejiang Province as the study sample, and from the perspective of city flow intensity makes an empirical analysis from 2005 to 2015 by using the inverse distance weighting method and the spatial interpolation method. The results show that: (1) the inter-city linkages are constantly strengthening. During the period, the strength of urban flow intensities has been enhanced as a whole over the time. From the initial "center point" to the "center area", the central city's radiation-led role has begun to play. (2) It shows a relatively stable distribution pattern with “North being high and South being low” from spatial structure perspective, and a multi-center city network that takes Hangzhou City as a leader, Ningbo City as a deputy core, and Wenzhou City, Shaoxing City and Zhoushan City as important nodes is initially formed. (3) The spatial differentiation of urban flow intensities is obvious, but the degree of differentiation has been slightly improved, which is reflected by the basic idea of the spatial transformation from the initial “single center” to the "center region" through the development and diffusion. In the end, the paper discusses how to strengthen the scale, regional coordination and sustainability of the “flow” among cites of Zhejiang Province.

Key words: regional structure, urban flow intensity, spatial interpolation, Zhejiang Province

Wei Guoen, Zhu Xiang, He Qingyun. Temporal-spatial characteristics of urban flow intensity in Zhejiang Province based on spatial interpolation[J].干旱区地理, 2019, 42(1): 215--222.

References

[1] DILKESFRAYNE E. Drugs at the campsite: Socio-spatial relations and drug use at music festivals.[J]. International Journal of Drug Policy, 2016, 33:27-35.
[2] KRISZTIN T, FISCHER M M. The Gravity Model for International Trade: Specification and Estimation Issues[J]. Spatial Economic Analysis, 2015, 10(4):451-470.
[3] POPRAWE M. On the relationship between corruption and migration: empirical evidence from a gravity model of migration[J]. Public Choice, 2015, 163(3-4):337-354.
[4] KAUKIN, ANDREI, DRISOV, et al. The gravity model of foreign trade in Russia: the case of a large area of the country with the longest border[J]. Economic Policy, 2015.
[5] SHUJIRO U, MISA O. The Impacts of Free Trade Agreements on Trade Flows: An Application of the Gravity Model Approach[M]// Free Trade Agreements In The Asia Pacific. 2016:195-239.
[6] RASOULINEZHAD E, KANG G S. A panel data analysis of south Korea's trade with OPEC member countries: The gravity model approach[J]. 2016, 20(2):203-224.
[7] SHEN J. Modeling Interregional Migration in China in 2005–2010:The roles of regional attributes and spatial interaction effects in modeling error[J]. Population Space & Place, 2016, 23(3):n/a-n/a.
[8] 周晓艳, 华敏, 秦雅雯,等. 长江中游城市群空间联系研究[J]. 长江流域资源与环境, 2016, 25(10): 1492-1500. [ZHOU Xiaoyan,HUA Min, QIN Yawen, et al. Urban agglomeration spatial contacts research in the middle reachs of Yangtze River [J]. Resources and Environment in the Yangtze Basin, 2016, 25(10): 1492-1500. ]
[9] 赵正, 王佳昊, 冯骥. 京津冀城市群核心城市的空间联系及影响测度[J]. 经济地理, 2017, 37(6): 60-66. [ZHAO Zheng, WANG Jiahao, FENG Ji. Research on the spatial correlation of central cities in Beijing-Tianjin-Hebei urban agglomeration[J]. Economic Geography, 2017, 37(6): 60-66. ]
[10] 谢波, 颜亚如. 昆明对周边城市外联经济量与地缘经济关系匹配研究[J]. 人文地理, 2016, 31(02): 106-112. [XIE Bo, YAN Yaru. Research of the match between the inter-city economic contact and geo-economic relationship: a case study of Kunming[J]. Human Geography, 2016, 31(02): 106-112.
[11] PATUELLI R, ARBIA G. Spatial Econometric Interaction Modelling: Where Spatial Econometrics and Spatial Interaction Modelling Meet[J]. 2016.
[12] LIU X, KANG C, GONG L, et al. Incorporating spatial interaction patterns in classifying and understanding urban land use[J]. International Journal of Geographical Information Science, 2016, 30(2):334-350.
[13] HE, J H, SHI X. Modeling the Spatial Expansion of Urban Agglomeration Considering Their Spatial Interaction: A Case Study of Wuhan Metropolitan Area[C]. Geomatics & Information Science of Wuhan University, 2016.
[14] 王彬燕,王士君,田俊峰. 基于城市流强度的哈长与辽中南城市群比较研究[J]. 经济地理,2015,(11):94-100+116. [WANG Binyan, WANG Shijun, TIAN Junfeng. Comparative research about Ha-Chang and mid-southern Liaoning urban agglomerations based on the intensity of urban flow[J]. Economic Geography, 2015, 35(11):94-100+116. ]
[15] 白永亮, 石磊, 党彦龙. 长江中游城市群空间集聚与扩散——基于31个城市18个行业的劳动力要素流动检验[J]. 经济地理, 2016, 36(11): 38-46. [BAI Yongliang, SHI Lei, DANG Yanlong. Spatial agglomeration and diffusion of urban agglomerations in middle reaches of Yangtze River: a flow test based on labor factors of 18 industries in 31 cities[J]. Economic Geography, 2016, 36(11): 38-46. ]
[16] 肖汝琴, 陈东景. 山东半岛蓝色经济区城市群空间联系定量研究[J]. 经济地理,2014,(08):75-80. [XIAO Ruqin, CHEN Dongjing. The spatial contacts among cities of the Shandong Peninsula Blue Economic Zone[J]. Economic Geography, 2014, (08):75-80. ]
[17] 孙平军, 修春亮, 丁四保, 等. 东北地区域发展的非均衡性与空间极化研究[J]. 地理科学进展, 2013, 30(6): 715-723. [SUN Pingjun, XIU Chunliang, DING Sibao, et al. Regional spatial polarization in the three provinces of Northeast China based on the ability of urban agglomeration[J]. Progress in Geography, 2013, 30(6): 715-723. ]
[18] 姜博, 修春亮, 陈才. 辽中南城市群城市流分析与模型阐释[J]. 经济地理, 2008,28(5):853-856. [ZHANG Bo, XIU Chunliang, CHEN Cai. Analysis of urban flow and model explanation on the urban group in middle-south part of Liaoning Province[J]. Economic Geography, 2016, 25(10): 1475-1483. ]
[19] 刘玮辰, 陆玉麒, 文玉钊. 长江经济带城市对外服务能力时空演变分析[J]. 长江流域资源与环境, 2016, 25(10): 1475-1483. [LIU Weichen, LU Yuqi, WEN Yuzhao. Spatio-temporal evolution analysis of external service capabilities of the Yangtze River Economic Belt cities[J]. Resources and Environment in the Yangtze Basin, 2016, 25(10): 1475-1483. ]
[20] 王圣云, 翟晨阳, 顾筱和. 长江中游城市群空间联系网络结构及其动态演化[J]. 长江流域资源与环境, 2016, 25(3): 353-364. [WANG Shengyun, ZHAI Chenyang, GU Xiaohe. Analysis on spatial network structure’s dynamic evolution of urban agglomerations in the middle Yangtze River Basin[J]. Resources and Environment in the Yangtze Basin, 2016, 25(3): 353-364. ]
[21] 孙平军, 修春亮, 王颖. “流”视角的长春市蔓延特征与作用机理分析[J]. 城市发展研究, 2012, 19(3): 15-19. [SUN Pingjun, XIU Chunliang, WANG Ying. The characteristic and mechanism of urban sprawl of Changchun based on the “flow” perspective[J]. Urban Development Studies, 2012, 19(3): 15-19. ]
[22] 申立敬, 程广斌. 丝绸之路经济带城市群空间联系特征比较研究——以我国西北地区城市群为例[J]. 人文地理, 2016(5):126-132. [SHEN Lijing, CHENG Guangbin. Comparative study on spatial connection of groups along the Silk Road Economic Belt: a case of city groups in Northwest China[J]. Human Geography, 2016(5):126-132. ]
[23] CASTELLS M. Grassrooting the space of flows[J]. Urban Geography, 1999, 20(4): 294-302.
[24] 曼纽尔·卡斯特著, 夏铸九等译. 网络社会的崛起[M]. 北京: 社会科学文献出版社, 2006. [MANUEL C O, XIA Z J. The rise of network society[M]. Beijing: Social Science Literature Publishing House, 2006. ]
[25] 修春亮, 孙平军, 王绮. 沈阳市居住就业结构的地理空间和流空间分析[J]. 地理学报. 2013, 68(08): 1110-1118. [XIU Chunliang, SUN Pingjun, WANG Qi. Residence-employment structure analysis on spaces of geography and flows in Shenyang City[J]. Acta Geographica Sinica. 2013, 68(08): 1110-1118. ]
[26] 沈丽珍, 甄峰, 席广亮. 解析信息社会流动空间的概念、属性与特征[J]. 人文地理, 2012, 27(4): 14-18. [SHEN Lizhen, ZHENG Feng, XI Guangliang. Analyzing the concept, attributes and characteristics of the attributes of space of flow in the information society[J]. Human Geography, 2012, 27(4): 14-18. ]
[27] 路紫, 刘岩. 信息通信技术 ICTs: 区域发展的催化剂[J]. 地域研究与开发, 1996, 15(4): 23-25. [LU Zi, LIU Yan. Information and Communication Technologies: the catalyst for regional development [J]. Areal Research and Development, 1996, 15(4): 23-25. ]
[28] 孙中伟, 路紫. 流空间基本性质的地理学透视[J]. 地理与地理信息科学,2005, 21(1): 109-112. [SUN Zhongwei, LU Zi. A geographical perspective to the elementary nature of space of flows[J]. Geography and Geo-Information Science, 2005, 21(1): 109-112. ]

Temporal-spatial characteristics of urban flow intensity in Zhejiang Province based on spatial interpolation

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 4

Metrics

Comments

Recommended 0

[1]	ZHUO Jing, ZHU Yan-nian. Spatial interpolation methods of annual average precipitation on Qinling Mountains [J]. , 2017, 40(3): 555-563.
[2]	ZHAO Yan-nan, YANG Degang, ZHANG Xin-huan, XIONG Chuan-he. Spatial distribution characteristics and hot zone patterns of lodging industry in Urumqi [J]. , 2016, 39(5): 1143-1152.
[3]	XIE Xian-jian, ZHANG Bin. Evaluation and spatial-temporal evolvement of the city competitiveness of Sichuan province [J]. , 2016, 39(4): 877-885.
[4]	CHEN Pengxiang,MAO Weiyi. GISbased spatial interpolation of air temperature in Xinjiang [J]. , 2012, 35(03): 438-445.