基于“流空间”视角的铁路客运空间组织分析——以长三角城市群为例

doi:10.11821/dlyj020190573

摘要/Abstract

摘要：

当前,以“流空间”视角阐释现代交通运输方式在实现区域一体化中发挥的作用,通过关联性描述其网络空间组织过程,能为交通与城市体系互动发展提供科学支撑。基于此,以2000年以来铁路客运班次数据为依托,应用社区发现算法分析长三角城市群铁路客运网络及空间变化特征,结论如下：① 城市群发育出京沪社区、浙江社区、皖江社区和苏中北社区等子群,各社区内部为铁路客运联系的主要范围和方向,且表现出差异性空间联系格局变化;② 高内部联系社区具有较高外部社区间联系强度,枢纽城市间多发生跨社区高联系,形成不依赖于铁路可达性的“核心-边缘”式结构;③ 按空间特征将各社区分为单核心社区、双核心社区、多核心社区和无核心社区,从社区内联系模式看,核心城市数量不断减少、较高联系通道不断发育,但两者间存在不匹配;④ 从社区间联系模式看,高速铁路在增强跨社区交流过程中扮演重要角色,核心城市间联系增强,客运网络由通道指向转变为枢纽指向。

关键词: 流空间, 铁路客运, 社区发现, 长三角城市群

Abstract:

Explaining the role of modern transport in realizing regional integration from the perspective of "space of flow" can provide scientific support for the interactive development of transport and urban system. Based on this, this paper uses the railway passenger data since 2000, and applies community detection algorithm to analyze the spatial organization of railway passenger transportation of the Yangtze River Delta urban agglomeration, in order to provide a new perspective for regional studies represented by transportation, and a guarantee for the study of regional integration through the rational use of railway passenger service. The conclusions can be drawn as follows: (1) We use combo community detection algorithm to divide the railway links of the Yangtze River Delta urban agglomeration into sub-groups, such as the Jinghu Community, the Zhejiang Community, the Wanjiang Community, and the Suzhongbei Community. These communities present different spatial linkage patterns and the main scope and direction of urban passenger rail links are concentrated within the community. (2) In general, the inter-community linkage is lower than the internal linkage of the community. The high internal contact community has a high degree of connection between the external communities. There is a high cross-community relationship between the railway hub cities, which forms a "core-edge" structure that does not depend on the accessibility of the railway. (3) According to the spatial characteristics, communities are divided into the single-core community, dual-core community, multi-core community, and non-core community. Different types of associations may be derived from the same type of community. During the study period, the core continued to decrease, while the higher communication channels continued to develop, connecting the main cities in each community and expanding continuously, but the channels did not match the core cities, and the transfer of core cities may occur. (4) There is a high connection between the cross-community hub cities, and the contact network is transformed from a channel point to a hub point. High-speed rails play an important role in enhancing cross-community communication and its spatial pattern changes from channel orientation to hub orientation. In the future study, it is necessary to analyze the role of different types of trains and trains in different operations. And we should combine the time cost with the number of trains, so as to more truly reflect the spatial process of urban agglomeration railway passenger transport organization.

Key words: space of flow, railway passenger transportation, community detection, Yangtze River Delta urban agglomeration

陈维肖, 刘玮辰, 段学军. 基于“流空间”视角的铁路客运空间组织分析——以长三角城市群为例[J]. 地理研究, 2020, 39(10): 2330-2344.

CHEN Weixiao, LIU Weichen, DUAN Xuejun. Spatial organization evolution of railway passenger transportation in the perspective of "space of flow": A case study of the Yangtze River Delta urban agglomeration[J]. GEOGRAPHICAL RESEARCH, 2020, 39(10): 2330-2344.

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年份	京沪社区	浙江社区	皖江社区	苏中北社区
2000	南京、苏州、无锡、常州、镇江、滁州	上海、杭州、宁波、嘉兴、金华、绍兴	合肥、芜湖、马鞍山、铜陵、宣城、湖州、安庆	-
2008	南京、苏州、无锡、常州、镇江、滁州、上海	杭州、宁波、嘉兴、金华、绍兴	合肥、芜湖、马鞍山、铜陵、宣城、湖州、安庆	扬州、泰州、南通、盐城
2018	南京、苏州、无锡、常州、镇江、滁州、上海	杭州、宁波、嘉兴、金华、绍兴、湖州、台州	合肥、芜湖、马鞍山、铜陵、宣城、安庆、池州	扬州、泰州、南通、盐城

统计类型		2000年				2008年					2018年
统计类型		京沪	浙江	皖江		京沪	浙江	皖江	苏中北		京沪	浙江	皖江	苏中北
直达城市对	全部直达城市对(个)	15	15	12		21	10	15	6		21	20	20	6
	动车组列车直达城市对(个)	-	-	-		20	3	0	0		21	20	13	3
	直达城市对占所有城市对比例(%)	100.00	100.00	57.14		100.00	100.00	71.43	100.00		100.00	95.24	95.24	100.00
	动车组列车直达城市对比例(%)	-	-	-		95.24	30.00	0.00	0.00		100.00	100.00	65.00	50.00
开行列车	全部开行列车数(班)	130	114	47		215	174	94	30		652	613	211	63
	动车组列车数(班)	-	-	-	80		11	0	0	500		472	107	26
	开行列车数占所有列车数比例(%)	53.72	47.11	19.42	46.74		37.83	20.43	6.52	46.70		43.91	15.11	4.51
	动车组列车比例(%)	-	-	-	37.21		6.32	0.00	0.00	76.69		77.00	50.71	41.27

统计类型		2000年				2008年							2018年
统计类型		京沪- 浙江	浙江- 皖江	浙江- 皖江		京沪- 浙江	京沪- 皖江	京沪- 苏中北	浙江- 皖江	浙江- 苏中北	皖江- 苏中北		京沪- 浙江	京沪- 皖江	京沪- 苏中北	浙江- 皖江	浙江- 苏中北	皖江- 苏中北
直达城市对	全部直达城市对(个)	36	37	18		33	41	18	20	2	13		45	46	7	38	0	19
	其中动车组列车直达城市对(个)	-	-	-		10	6	0	0	0	0		45	36	3	22	0	3
	直达城市对占所有城市对比例(%)	100.00	88.10	42.86		94.29	83.67	64.29	57.14	10.00	46.43		91.84	93.88	25.00	77.55	0.00	67.86
	其中动车组列车直达城市对比例(%)	-	-	-		30.30	14.63	0.00	0.00	0.00	0.00		100.00	78.26	42.86	57.89	0.00	15.79
开行列车	全部开行列车数(班)	114	38	20		150	63	16	36	2	10		548	262	39	110	0	13
	其中动车组列车数(班)	-	-	-	24		10	0	0	0	0	435		222	24	61	0	6
	开行列车数占所有列车数比例(%)	47.11	15.7	8.26	32.61		13.7	3.48	7.83	0.43	2.17	39.26		18.77	2.79	7.88	0.00	0.93
	其中动车组列车比例(%)	-	-	-	16.00		15.87	0.00	0.00	0.00	0.00	79.38		84.73	61.54	55.45	0.00	46.15