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Data Details

Dataset of China's Intercity Network from the Railway Perspective (2007-2024)


REN Hongyan1WANG Qi2XU Nankang1,3
1 Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China2 School of Geographic Sciences，East China Normal University，Shanghai 200241，China3 China Telecom Corporation Limited Shanghai Branch，Shanghai 200120，China

DOI:10.3974/geodb.2026.07.10.V1

Published:July 2026

Visitors：25       Data Files Downloaded：0      
Data Downloaded： 无      Citations：

Key Words：

Spatiotemporal distance index,urban relationship network,railway,2007-2024

Abstract：

The dataset was developed based on intercity train schedules in China from 2007 to 2024. By comprehensively considering train travel time and frequency and referring to the concept of spatiotemporal proximity, the average travel time between cities is represented by the average running time of direct trains between cities, while the total intercity flow is represented by train service frequency. The spatiotemporal distance index is then constructed by taking the reciprocal of these measures and normalizing them. Based on this approach, a dataset of China's intercity network from the railway perspective (2007–2024) was developed, with cities as nodes and the spatiotemporal distance index as edges. The dataset includes: (1) spatiotemporal distance index directed network, spatiotemporal distance index undirected network, spatiotemporal distance index binary network, and spatiotemporal distance index network features. The dataset is archived in .xlsx and .shp data formats, and consists of 12 data files with data size of 1.68 GB (compressed into one file with 737 MB).

Foundation Item：

Ministry of Science and Technology of P. R. China (2023YFC2307502)

Data Citation：

REN Hongyan, WANG Qi, XU Nankang. Dataset of China's Intercity Network from the Railway Perspective (2007-2024)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2026. https://doi.org/10.3974/geodb.2026.07.10.V1.
.

References：


     [1] Shen, W. C., Li, P. Q., Yao, W. W., et al. Spatial structure characteristics and organizational patterns of China's urban network from the perspective of multiple flow spaces [J]. Geographical Research, 2023, 42(2): 514-533.
     [2] Sun, B. D., Zhang, J. Critical reflections on urban network research in China [J]. Urban Planning Forum, 2023, (2): 26-32.
     [3] Chen, W., Xiu, C. L. Rethinking the theoretical connotation of urban agglomerations in the new era [J]. Progress in Geography, 2021, 40(5): 848-857.
     [4] Wang, X. M. Spatial evolution and influencing factors of China's urban network from the perspective of aviation and high-speed rail [D]. Shanghai: East China Normal University, 2022.
     [5] Huang, Y., Hong, T., Ma, T. Urban network externalities, agglomeration economies and urban economic growth [J]. Cities, 2020, 107: 102882.
     [6] Zhou, H. H., Gu, G. F. Urban network evolution and its environmental effects in China from the perspective of externalities [J]. Geographical Research, 2022, 41(1): 268-285.
     [7] Chen, W., Liu, W., Ke, W., et al. Understanding spatial structures and organizational patterns of city networks in China: A highway passenger flow perspective [J]. Journal of Geographical Sciences, 2018, 28(4): 477-494.
     [8] Zheng, W., Kuang, A., Wang, X., et al. Measuring network configuration of the Yangtze River Middle Reaches urban agglomeration: Based on modified radiation model [J]. Chinese Geographical Science, 2020, 30(4): 677-694.
     [9] Shaw, S.-L., Fang, Z., Lu, S., et al. Impacts of high speed rail on railroad network accessibility in China [J]. Journal of Transport Geography, 2014, 40: 112-122.
     [10] Zhong, Y. X., Lu, Y. Q. Urban hierarchy and distribution pattern in China based on railway network [J]. Geographical Research, 2011, 30(5): 785-794.
     [11] Li, X. W., Cao, C. X., Chang, C. Y. The first law of geography and the proposition of spatiotemporal proximity [J]. Chinese Journal of Nature, 2007, (2): 69-71.
     [12] Newman, M. E. J. The structure and function of complex networks [J]. SIAM Review, 2003, 45(2): 167-256.

Data Product:

ID Data Name Data Size Operation
1 TrainNetwork2007-2024.rar 755495.89KB
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