1,489
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data

, , , , , & show all
Pages 499-516 | Received 24 Aug 2022, Accepted 23 Jul 2023, Published online: 30 Jul 2023

References

  • Barbosa, H., M. Barthelemy, G. Ghoshal, C. R. James, M. Lenormand, T. Louail, R. Menezes, J. J. Ramasco, F. Simini, and M. Tomasini. 2018. “Human Mobility: Models and Applications.” Physics Reports 734:1–74. https://doi.org/10.1016/j.physrep.2018.01.001.
  • Batty, M. 2009. Cities as Complex Systems: Scaling, Interaction, Networks, Dynamics and Urban Morphologies.
  • Batty, M. 2013. The New Science of Cities. MIT press. https://doi.org/10.7551/mitpress/9399.001.0001.
  • Beel, J., B. Gipp, S. Langer, and C. Breitinger. 2016. “Research-Paper Recommender Systems: A Literature Survey.” International Journal on Digital Libraries 17 (4): 305–338. https://doi.org/10.1007/s00799-015-0156-0.
  • Bengio, Y., A. Courville, and P. Vincent. 2013. “Representation Learning: A Review and New Perspectives.” IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (8): 1798–1828. https://doi.org/10.1109/TPAMI.2013.50.
  • Boeing, G. 2017. “OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks.” Computers, Environment and Urban Systems 65:126–139. https://doi.org/10.1016/j.compenvurbsys.2017.05.004.
  • Brauer, A., V. Mäkinen, and J. Oksanen. 2021. “Characterizing Cycling Traffic Fluency Using Big Mobile Activity Tracking Data.” Computers, Environment and Urban Systems 85:101553. https://doi.org/10.1016/j.compenvurbsys.2020.101553.
  • Brown, L. A., and J. Holmes. 1971. “The Delimitation of Functional Regions, Nodal Regions, and Hierarchies by Functional Distance approaches.” Ekistics 32 (192): 387–391. JSTOR.
  • Brown, B. B., I. Yamada, K. R. Smith, C. D. Zick, L. Kowaleski-Jones, and J. X. Fan. 2009. “Mixed Land Use and Walkability: Variations in Land Use Measures and Relationships with BMI, Overweight, and Obesity.” Health & Place 15 (4): 1130–1141. https://doi.org/10.1016/j.healthplace.2009.06.008.
  • Burger, M. J., B. van der Knaap, and R. S. Wall. 2014. “Polycentricity and the Multiplexity of Urban Networks.” European Planning Studies 22 (4): 816–840. https://doi.org/10.1080/09654313.2013.771619.
  • Burghardt, K., J. Uhl, K. Lerman, and S. Leyk. 2021. Road Network Evolution in the Urban and Rural United States Since 1900. ArXiv:2108.13407 [Nlin, Physics:Physics]. http://arxiv.org/abs/2108.13407.
  • Cai, M. 2021. “Natural Language Processing for Urban Research: A Systematic Review.” Heliyon 7 (3): e06322. https://doi.org/10.1016/j.heliyon.2021.e06322.
  • Chen, T., E. C. M. Hui, J. Wu, W. Lang, and X. Li. 2019. “Identifying Urban Spatial Structure and Urban Vibrancy in Highly Dense Cities Using Georeferenced Social Media Data.” Habitat International 89:102005. https://doi.org/10.1016/j.habitatint.2019.102005.
  • Chen, Y., J. Xu, and M. Xu. 2015. “Finding Community Structure in Spatially Constrained Complex Networks.” International Journal of Geographical Information Science 29 (6): 889–911. https://doi.org/10.1080/13658816.2014.999244.
  • Crivellari, A., and A. Ristea. 2021. “CrimeVec—Exploring Spatial-Temporal Based Vector Representations of Urban Crime Types and Crime-Related Urban Regions.” ISPRS International Journal of Geo-Information 10 (4): 210. Article 4. https://doi.org/10.3390/ijgi10040210.
  • Cui, J., F. Liu, D. Janssens, S. An, G. Wets, and M. Cools. 2016. “Detecting Urban Road Network Accessibility Problems Using Taxi GPS Data.” Journal of Transport Geography 51:147–157. https://doi.org/10.1016/j.jtrangeo.2015.12.007.
  • Cui, H., L. Wu, and Z. He. 2022. “Optimization Framework for Spatiotemporal Analysis Units Based on Floating Car Data.” Remote Sensing 14 (10): 2376. Article 10. https://doi.org/10.3390/rs14102376.
  • de Andrade, S. C., J. Porto de Albuquerque, C. Restrepo-Estrada, R. Westerholt, C. A. M. Rodriguez, E. M. Mendiondo, and A. C. B. Delbem. 2021. “The Effect of Intra-Urban Mobility Flows on the Spatial Heterogeneity of Social Media Activity: Investigating the Response to Rainfall Events.” International Journal of Geographical Information Science 36 (6): 1140–1165. https://doi.org/10.1080/13658816.2021.1957898.
  • De Montis, A., S. Caschili, and A. Chessa. 2013. “Commuter Networks and Community Detection: A Method for Planning Sub Regional Areas.” The European Physical Journal Special Topics 215 (1): 75–91. https://doi.org/10.1140/epjst/e2013-01716-4.
  • Dokuz, A. S. 2022. “Weighted Spatio-Temporal Taxi Trajectory Big Data Mining for Regional Traffic Estimation.” Physica A: Statistical Mechanics and Its Applications 589:126645. https://doi.org/10.1016/j.physa.2021.126645.
  • Edler, D., L. Bohlin, and M. Rosvall. 2017. “Mapping Higher-Order Network Flows in Memory and Multilayer Networks with Infomap.” Algorithms 10 (4): 112. https://doi.org/10.3390/a10040112.
  • Estrada, E. 2012. The Structure of Complex Networks: Theory and Applications. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199591756.001.0001.
  • Foley, D. L. 1964. ”An Approach to Metropolitan Spatial Structure”. Explorations into Urban Structure. edited by. Melvin M. Webber 21–78 , Philadelphia: University of Pennsylvania Press. https://doi.org/10.9783/9781512808063-004.
  • Fortunato, S., and D. Hric. 2016. “Community Detection in Networks: A User Guide.” Physics Reports 659:1–44. https://doi.org/10.1016/j.physrep.2016.09.002.
  • Gao, S. 2017. Extracting Computational Representations of Place with Social Sensing [UC Santa Barbara Extracting Computational Representations of Place with Social Sensing]. https://escholarship.org/uc/item/9303m2hj.
  • Gao, S., K. Janowicz, and H. Couclelis. 2017. “Extracting Urban Functional Regions from Points of Interest and Human Activities on Location-Based Social Networks.” Transactions in GIS 21 (3): 446–467. https://doi.org/10.1111/tgis.12289.
  • Gao, S., Y. Liu, Y. Wang, and X. Ma. 2013. “Discovering Spatial Interaction Communities from Mobile Phone Data.” Transactions in GIS 17 (3): 463–481. https://doi.org/10.1111/tgis.12042.
  • Gotelli, N. J., and R. K. Colwell. 2011. “Estimating Species Richness.” Biological Diversity: Frontiers in Measurement and Assessment 12 (39–54): 35.
  • Guo, S., T. Pei, S. Xie, C. Song, J. Chen, Y. Liu, H. Shu, X. Wang, and L. Yin. 2021. “Fractal Dimension of Job-Housing Flows: A Comparison Between Beijing and Shenzhen.” Cities 112:103120. https://doi.org/10.1016/j.cities.2021.103120.
  • He, Z., M. Deng, J. Cai, Z. Xie, Q. Guan, and C. Yang. 2020. “Mining Spatiotemporal Association Patterns from Complex Geographic Phenomena.” International Journal of Geographical Information Science 34 (6): 1162–1187. https://doi.org/10.1080/13658816.2019.1566549.
  • Hong, Y., and Y. Yao. 2019. “Hierarchical Community Detection and Functional Area Identification with OSM Roads and Complex Graph Theory.” International Journal of Geographical Information Science 33 (8): 1569–1587. https://doi.org/10.1080/13658816.2019.1584806.
  • Hric, D., R. K. Darst, and S. Fortunato. 2014. “Community Detection in Networks: Structural Communities versus Ground Truth.” Physical Review E 90 (6): 062805. https://doi.org/10.1103/PhysRevE.90.062805.
  • Huang, W., L. Cui, M. Chen, D. Zhang, and Y. Yao. 2022. “Estimating Urban Functional Distributions with Semantics Preserved POI Embedding.” International Journal of Geographical Information Science: 36(10):1–26. https://doi.org/10.1080/13658816.2022.2040510.
  • Huffman, D. A. 1952. “A Method for the Construction of Minimum-Redundancy Codes.” Proceedings of the IRE 40 (9): 1098–1101. https://doi.org/10.1109/JRPROC.1952.273898.
  • Hu, S., S. Gao, L. Wu, Y. Xu, Z. Zhang, H. Cui, and X. Gong. 2021. “Urban Function Classification at Road Segment Level Using Taxi Trajectory Data: A Graph Convolutional Neural Network Approach.” Computers, Environment and Urban Systems 87:101619. https://doi.org/10.1016/j.compenvurbsys.2021.101619.
  • Hunter, P. R., and M. A. Gaston. 1988. “Numerical Index of the Discriminatory Ability of Typing Systems: An Application of Simpson’s Index of Diversity.” Journal of Clinical Microbiology 26 (11): 2465–2466. https://doi.org/10.1128/jcm.26.11.2465-2466.1988.
  • Hu, S., Y. Xu, L. Wu, X. Wu, R. Wang, Z. Zhang, R. Lu, and W. Mao. 2021. “A Framework to Detect and Understand Thematic Places of a City Using Geospatial Data.” Cities 109:103012. https://doi.org/10.1016/j.cities.2020.103012.
  • Jusup, M., P. Holme, K. Kanazawa, M. Takayasu, I. Romić, Z. Wang, S. Geček, et al. 2022. “Social Physics.” Physics Reports 948:1–148. https://doi.org/10.1016/j.physrep.2021.10.005.
  • Lee, J.-G., and M. Kang. 2015. “Geospatial Big Data: Challenges and Opportunities.” Big Data Research 2 (2): 74–81. https://doi.org/10.1016/j.bdr.2015.01.003.
  • Levy, O., and Y. Goldberg 2014. “Dependency-Based Word Embeddings”. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Baltimore, Maryland, 302–308.
  • Liang, X., and Y. Kang. 2021. “A Review of Spatial Network Insights and Methods in the Context of Planning: Applications, Challenges, and Opportunities.” In Urban Informatics and Future Cities, edited by S. C. M. Geertman, C. Pettit, R. Goodspeed, and A. Staffans, 71–91. Springer International Publishing. https://doi.org/10.1007/978-3-030-76059-5_5.
  • Li, Y., T. Fei, and F. Zhang. 2019. “A Regionalization Method for Clustering and Partitioning Based on Trajectories from NLP Perspective.” International Journal of Geographical Information Science 33 (12): 2385–2405. https://doi.org/10.1080/13658816.2019.1643025.
  • Liu, K., S. Gao, and F. Lu. 2019. “Identifying Spatial Interaction Patterns of Vehicle Movements on Urban Road Networks by Topic Modelling.” Computers, Environment and Urban Systems 74:50–61. https://doi.org/10.1016/j.compenvurbsys.2018.12.001.
  • Liu, K., S. Gao, P. Qiu, X. Liu, B. Yan, F. Lu, K. Liu, et al. 2017. “Road2Vec: Measuring Traffic Interactions in Urban Road System from Massive Travel Routes.” ISPRS International Journal of Geo-Information 6 (11): 321. https://doi.org/10.3390/ijgi6110321.
  • Liu, X., L. Gong, Y. Gong, and Y. Liu. 2015. “Revealing Travel Patterns and City Structure with Taxi Trip Data.” Journal of Transport Geography 43:78–90. https://doi.org/10.1016/j.jtrangeo.2015.01.016.
  • Liu, Y., C. Kang, S. Gao, Y. Xiao, and Y. Tian. 2012. “Understanding Intra-Urban Trip Patterns from Taxi Trajectory Data.” Journal of Geographical Systems 14 (4): 463–483. https://doi.org/10.1007/s10109-012-0166-z.
  • Liu, X., C. Kang, L. Gong, and Y. Liu. 2016. “Incorporating Spatial Interaction Patterns in Classifying and Understanding Urban Land Use.” International Journal of Geographical Information Science 30 (2): 334–350. https://doi.org/10.1080/13658816.2015.1086923.
  • Liu, Y., X. Liu, S. Gao, L. Gong, C. Kang, Y. Zhi, G. Chi, and L. Shi. 2015. “Social Sensing: A New Approach to Understanding Our Socioeconomic Environments.” Annals of the Association of American Geographers 105 (3): 512–530. https://doi.org/10.1080/00045608.2015.1018773.
  • Liu, K., P. Qiu, S. Gao, F. Lu, J. Jiang, and L. Yin. 2020. “Investigating Urban Metro Stations as Cognitive Places in Cities Using Points of Interest.” Cities 97:102561. https://doi.org/10.1016/j.cities.2019.102561.
  • Liu, Y., F. Wang, Y. Xiao, and S. Gao. 2012. “Urban Land Uses and Traffic ‘Source-Sink areas’: Evidence from GPS-Enabled Taxi Data in Shanghai.” Landscape and Urban Planning 106 (1): 73–87. https://doi.org/10.1016/j.landurbplan.2012.02.012.
  • Luo, W., P. Gao, and S. Cassels. 2018. “A Large-Scale Location-Based Social Network to Understanding the Impact of Human Geo-Social Interaction Patterns on Vaccination Strategies in an Urbanized Area.” Computers, Environment and Urban Systems 72:78–87. https://doi.org/10.1016/j.compenvurbsys.2018.06.008.
  • Luo, W., and A. M. MacEachren. 2014. “Geo-Social Visual Analytics.” Journal of Spatial Information Science 2014 (8): 27–66. https://doi.org/10.5311/JOSIS.2014.8.139.
  • Luo, W., Y. Wang, X. Liu, and S. Gao. 2019. “Cities as Spatial and Social Networks: Towards a Spatio-Socio-Semantic Analysis Framework.” In Cities as Spatial and Social Networks, 21–37. Springer International Publishing. https://doi.org/10.1007/978-3-319-95351-9_3.
  • Mai, G., K. Janowicz, Y. Hu, S. Gao, B. Yan, R. Zhu, L. Cai, and N. Lao. 2022. “A Review of Location Encoding for GeoAi: Methods and Applications.” International Journal of Geographical Information Science : 1–35. https://doi.org/10.1080/13658816.2021.2004602.
  • Martin, M. E., and N. Schuurman. 2020. “Social Media Big Data Acquisition and Analysis for Qualitative GIScience: Challenges and Opportunities.” Annals of the American Association of Geographers 110 (5): 1335–1352. https://doi.org/10.1080/24694452.2019.1696664.
  • Mikolov, T., I. Sutskever, K. Chen, G. Corrado, and J. Dean 2013. “Distributed Representations of Words and Phrases and Their Compositionality”. Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 2, Red Hook, NY, USA, 3111–3119.
  • Niu, H., and E. A. Silva. 2021. “Delineating Urban Functional Use from Points of Interest Data with Neural Network Embedding: A Case Study in Greater London.” Computers, Environment and Urban Systems 88:101651. https://doi.org/10.1016/j.compenvurbsys.2021.101651.
  • Noronha, V. T., and M. F. Goodchild. 1992. “Modeling Interregional Interaction: Implications for Defining Functional Regions.” Annals of the Association of American Geographers 82 (1): 86–102. JSTOR. https://doi.org/10.1111/j.1467-8306.1992.tb01899.x.
  • Ratti, C., S. Sobolevsky, F. Calabrese, C. Andris, J. Reades, M. Martino, R. Claxton, S. H. Strogatz, and O. Sporns. 2010. “Redrawing the Map of Great Britain from a Network of Human Interactions.” PloS One 5 (12): e14248. https://doi.org/10.1371/journal.pone.0014248.
  • Rehurek, R., and P. Sojka 2010. “Software Framework for Topic Modelling with Large Corpora”. In Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, Valletta, Malta.
  • Rodrigue, J.-P., C. Comtois, and B. Slack. 2016. The Geography of Transport Systems. Routledge.
  • Rosvall, M., and C. T. Bergstrom. 2008. “Maps of Random Walks on Complex Networks Reveal Community Structure.” Proceedings of the National Academy of Sciences 105 (4): 1118–1123. https://doi.org/10.1073/pnas.0706851105.
  • Schläpfer, M., L. Dong, K. O’Keeffe, P. Santi, M. Szell, H. Salat, S. Anklesaria, M. Vazifeh, C. Ratti, and G. B. West. 2021. “The Universal Visitation Law of Human Mobility.” Nature 593 (7860): 522–527. https://doi.org/10.1038/s41586-021-03480-9.
  • Siła-Nowicka, K., J. Vandrol, T. Oshan, J. A. Long, U. Demšar, and A. S. Fotheringham. 2016. “Analysis of Human Mobility Patterns from GPS Trajectories and Contextual Information.” International Journal of Geographical Information Science 30 (5): 881–906. https://doi.org/10.1080/13658816.2015.1100731.
  • Simpson, E. H. 1949. “Measurement of Diversity.” Nature 163 (4148): 688–688. https://doi.org/10.1038/163688a0.
  • State Information Center. 2017. Map POI (Point of Interest) Data, V2 ed. Peking University Open Research Data Platform. https://doi.org/10.18170/DVN/WSXCNM.
  • Sun, Z., H. Jiao, H. Wu, Z. Peng, and L. Liu. 2021. “Block2vec: An Approach for Identifying Urban Functional Regions by Integrating Sentence Embedding Model and Points of Interest.” ISPRS International Journal of Geo-Information 10 (5): 339. Article 5. https://doi.org/10.3390/ijgi10050339.
  • Tobler, W. R. 1970. “A Computer Movie Simulating Urban Growth in the Detroit Region.” Economic Geography 46:234–240. https://doi.org/10.2307/143141.
  • van Meeteren, M., A. Poorthuis, B. Derudder, and F. Witlox. 2016. “Pacifying Babel’s Tower: A Scientometric Analysis of Polycentricity in Urban Research.” Urban Studies 53 (6): 1278–1298. https://doi.org/10.1177/0042098015573455.
  • Wuhan. (2021). In Wikipedia. https://en.wikipedia.org/w/index.php?title=Wuhan&oldid=1035568696.
  • Wu, C., D. Smith, and M. Wang. 2021. “Simulating the Urban Spatial Structure with Spatial Interaction: A Case Study of Urban Polycentricity Under Different Scenarios.” Computers, Environment and Urban Systems 89:101677. https://doi.org/10.1016/j.compenvurbsys.2021.101677.
  • Wu, N., X. W. Zhao, J. Wang, and D. Pan 2020. “Learning Effective Road Network Representation with Hierarchical Graph Neural Networks”. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 6–14. https://doi.org/10.1145/3394486.3403043.
  • Xie, J., S. Kelley, and B. K. Szymanski. 2013. “Overlapping Community Detection in Networks: The State-Of-The-Art and Comparative Study.” ACM Computing Surveys (CSUR) 45 (4): 1–35. https://doi.org/10.1145/2501654.2501657.
  • Xu, Y., S.-L. Shaw, Z. Zhao, L. Yin, F. Lu, J. Chen, Z. Fang, and Q. Li. 2016. “Another Tale of Two Cities: Understanding Human Activity Space Using Actively Tracked Cellphone Location Data.” Annals of the American Association of Geographers 106 (2): 489–502. https://doi.org/10.1080/00045608.2015.1120147.
  • Xu, D., C. Wei, P. Peng, Q. Xuan, and H. Guo. 2020. “GE-GAN: A Novel Deep Learning Framework for Road Traffic State Estimation.” Transportation Research Part C: Emerging Technologies 117:102635. https://doi.org/10.1016/j.trc.2020.102635.
  • Xu, Y., Z. Xie, Z. Chen, and M. Xie. 2021. “Measuring the Similarity Between Multipolygons Using Convex Hulls and Position Graphs.” International Journal of Geographical Information Science 35 (5): 847–868. https://doi.org/10.1080/13658816.2020.1800016.
  • Xu, Y., Z. Xie, L. Wu, and Z. Chen. 2019. “Multilane Roads Extracted from the OpenStreetmap Urban Road Network Using Random Forests.” Transactions in GIS 23 (2): 224–240. https://doi.org/10.1111/tgis.12514.
  • Yang, C., and G. Gidófalvi. 2018. “Fast Map Matching, an Algorithm Integrating Hidden Markov Model with Precomputation.” International Journal of Geographical Information Science 32 (3): 547–570. https://doi.org/10.1080/13658816.2017.1400548.
  • Yao, Y., X. Li, X. Liu, P. Liu, Z. Liang, J. Zhang, and K. Mai. 2017. “Sensing Spatial Distribution of Urban Land Use by Integrating Points-Of-Interest and Google Word2Vec Model.” International Journal of Geographical Information Science 31 (4): 825–848. https://doi.org/10.1080/13658816.2016.1244608.
  • Yao, Y., J. Wang, Y. Hong, C. Qian, Q. Guan, X. Liang, L. Dai, and J. Zhang. 2021. “Discovering the Homogeneous Geographic Domain of Human Perceptions from Street View Images.” Landscape and Urban Planning 212:104125. https://doi.org/10.1016/j.landurbplan.2021.104125.
  • Yu, W. 2018. “Discovering Frequent Movement Paths from Taxi Trajectory Data Using Spatially Embedded Networks and Association Rules.” IEEE Transactions on Intelligent Transportation Systems 20 (3): 855–866. https://doi.org/10.1109/TITS.2018.2834573.
  • Yue, Y., T. Lan, A. G. Yeh, and Q.-Q. Li. 2014. “Zooming into Individuals to Understand the Collective: A Review of Trajectory-Based Travel Behaviour Studies.” Travel Behaviour and Society 1 (2): 69–78. https://doi.org/10.1016/j.tbs.2013.12.002.
  • Yue, Y., Y. Zhuang, A. G. O. Yeh, J.-Y. Xie, C.-L. Ma, and Q.-Q. Li. 2017. “Measurements of POI-Based Mixed Use and Their Relationships with Neighbourhood Vibrancy.” International Journal of Geographical Information Science 31 (4): 658–675. https://doi.org/10.1080/13658816.2016.1220561.
  • Zhang, J., X. Li, Y. Yao, Y. Hong, J. He, Z. Jiang, and J. Sun. 2020. “The Traj2Vec Model to Quantify residents’ Spatial Trajectories and Estimate the Proportions of Urban Land-Use Types.” International Journal of Geographical Information Science. 35(1):193211. (1):193211. https://doi.org/10.1080/13658816.2020.1726923.
  • Zhang, D., L. Sun, B. Li, C. Chen, G. Pan, S. Li, and Z. Wu. 2014. “Understanding Taxi Service Strategies from Taxi GPS Traces.” IEEE Transactions on Intelligent Transportation Systems 16 (1): 123–135. https://doi.org/10.1109/TITS.2014.2328231.
  • Zhang, S., J. Tang, H. Wang, Y. Wang, and S. An. 2017. “Revealing Intra-Urban Travel Patterns and Service Ranges from Taxi Trajectories.” Journal of Transport Geography 61:72–86. https://doi.org/10.1016/j.jtrangeo.2017.04.009.
  • Zhang, X., Y. Xu, W. Tu, and C. Ratti. 2018. “Do Different Datasets Tell the Same Story About Urban Mobility—A Comparative Study of Public Transit and Taxi Usage.” Journal of Transport Geography 70:78–90. https://doi.org/10.1016/j.jtrangeo.2018.05.002.
  • Zheng, Y., L. Capra, O. Wolfson, and H. Yang. 2014. “Urban Computing: Concepts, Methodologies, and Applications.” ACM Trans Intell Syst Technol 5 (3): 55. 38:1-38. https://doi.org/10.1145/2629592.
  • Zheng, Y., Y. Liu, J. Yuan, and X. Xie 2011, September. “Urban Computing with Taxicabs”. Proceedings of the 13th ACM International Conference on Ubiquitous Computing. https://www.microsoft.com/en-us/research/publication/urban-computing-with-taxicabs/.
  • Zhong, C., S. M. Arisona, X. Huang, M. Batty, and G. Schmitt. 2014. “Detecting the Dynamics of Urban Structure Through Spatial Network Analysis.” International Journal of Geographical Information Science 28 (11): 2178–2199. https://doi.org/10.1080/13658816.2014.914521.
  • Zhu, D., Z. Huang, L. Shi, L. Wu, and Y. Liu. 2018. “Inferring Spatial Interaction Patterns from Sequential Snapshots of Spatial Distributions.” International Journal of Geographical Information Science 32 (4): 783–805. https://doi.org/10.1080/13658816.2017.1413192.
  • Zhu, D., N. Wang, L. Wu, and Y. Liu. 2017. “Street as a Big Geo-Data Assembly and Analysis Unit in Urban Studies: A Case Study Using Beijing Taxi Data.” Applied Geography 86:152–164. https://doi.org/10.1016/j.apgeog.2017.07.001.