References
- Ahas, R., et al. 2015. Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn. International Journal of Geographical Information Science, 29 (11), 2017–2039. doi:10.1080/13658816.2015.1063151
- Allen, J., et al., 2018. Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: the case of London. Transportation Research Part D: Transport and Environment, 61, 325–338. doi:10.1016/j.trd.2017.07.020
- Ballantyne, E.E., Lindholm, M., and Whiteing, A., 2013. A comparative study of urban freight transport planning: addressing stakeholder needs. Journal of Transport Geography, 32, 93–101. doi:10.1016/j.jtrangeo.2013.08.013
- Barbosa-Filho, H., et al., 2017. Human mobility: models and applications. arXiv preprint arXiv:1710.00004.
- Belyi, A., et al. 2017. Global multi-layer network of human mobility. International Journal of Geographical Information Science, 31 (7), 1381–1402. doi:10.1080/13658816.2017.1301455
- Boarnet, M.G., Hong, A., and Santiago-Bartolomei, R., 2017. Urban spatial structure, employment subcenters, and freight travel. Journal of Transport Geography, 60, 267–276. doi:10.1016/j.jtrangeo.2017.03.007
- Brockmann, D., Hufnagel, L., and Geisel, T., 2006. The scaling laws of human travel. Nature, 439 (7075), 462–465. doi:10.1038/nature04340
- Cetateanu, A., et al., 2016. A novel methodology for identifying environmental exposures using GPS data. International Journal of Geographical Information Science, 30 (10), 1944–1960.
- Cherrett, T., et al., 2012. Understanding urban freight activity–key issues for freight planning. Journal of Transport Geography, 24, 22–32. doi:10.1016/j.jtrangeo.2012.05.008
- Comendador, J., López-Lambas, M.E., and Monzón, A., 2012. A GPS analysis for urban freight distribution. Procedia-Social and Behavioral Sciences, 39, 521–533. doi:10.1016/j.sbspro.2012.03.127
- D’Este, G. 2007. Urban freight movement modeling. In Handbook of Transport Modelling. 2nd. Bingley, UK: Emerald Group Publishing Limited, 633–647.
- Flowerdew, R. and Lovett, A., 1988. Fitting constrained Poisson regression models to interurban migration flows. Geographical Analysis, 20 (4), 297–307. doi:10.1111/j.1538-4632.1988.tb00184.x
- Fu, Y. and Shi, X., 2013. Research on freight truck operation characteristics based on GPS data. Procedia-Social and Behavioral Sciences, 96, 2320–2331. doi:10.1016/j.sbspro.2013.08.261
- Gallotti, R., et al., 2016. A stochastic model of randomly accelerated walkers for human mobility. Nature Communications, 7, 12600. doi:10.1038/ncomms12600
- Gonzalez, M.C., Hidalgo, C.A., and Barabasi, A.L., 2008. Understanding individual human mobility patterns. Nature, 453 (7196), 779–782. doi:10.1038/nature06958
- Hardy, D., Frew, J., and Goodchild, M.F., 2012. Volunteered geographic information production as a spatial process. International Journal of Geographical Information Science, 26 (7), 1191–1212. doi:10.1080/13658816.2011.629618
- Hawelka, B., et al. 2014. Geo-located Twitter as proxy for global mobility patterns. Cartography and Geographic Information Science, 41 (3), 260–271. doi:10.1080/15230406.2014.890072
- Hesse, M. and Rodrigue, J.P., 2004. The transport geography of logistics and freight distribution. Journal of Transport Geography, 12 (3), 171–184. doi:10.1016/j.jtrangeo.2003.12.004
- Jiang, S., et al., 2017. Human mobility in space from three modes of public transportation. Physica A: Statistical Mechanics and Its Applications, 483, 227–238. doi:10.1016/j.physa.2017.04.182
- Kang, C., et al. 2012. Intra-urban human mobility patterns: an urban morphology perspective. Physica A: Statistical Mechanics and Its Applications, 391 (4), 1702–1717. doi:10.1016/j.physa.2011.11.005
- Kang, C., et al. 2015. A generalized radiation model for human mobility: spatial scale, searching direction and trip constraint. PloS one, 10 (11), e0143500. doi:10.1371/journal.pone.0143500
- Kim, K., et al. 2014. An analysis on movement patterns between zones using smart card data in subway networks. International Journal of Geographical Information Science, 28 (9), 1781–1801. doi:10.1080/13658816.2014.898768
- Kwan, M.P. and Neutens, T., 2014. Space-time research in GIScience. International Journal of Geographical Information Science, 28 (5), 851–854. doi:10.1080/13658816.2014.889300
- Lera, I., et al. 2017. Analysing human mobility patterns of hiking activities through complex network theory. PloS one, 12 (5), e0177712. doi:10.1371/journal.pone.0177712
- Levy, M., 2010. Scale-free human migration and the geography of social networks. Physica A: Statistical Mechanics and Its Applications, 389 (21), 4913–4917. doi:10.1016/j.physa.2010.07.008
- Liang, X., et al., 2013. Unraveling the origin of exponential law in intra-urban human mobility. Scientific Reports, 3, 2983. doi:10.1038/srep02983
- Liu, X. and Ban, Y., 2013. Uncovering spatio-temporal cluster patterns using massive floating car data. ISPRS International Journal of Geo-Information, 2 (2), 371–384. doi:10.3390/ijgi2020371
- Liu, Y., et al. 2012. Understanding intra-urban trip patterns from taxi trajectory data. Journal of Geographical Systems, 14 (4), 463–483. doi:10.1007/s10109-012-0166-z
- Liu, Y., et al. 2014. Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data. PloS one, 9 (1), e86026. doi:10.1371/journal.pone.0086026
- Masucci, A.P., et al. 2013. Gravity versus radiation models: on the importance of scale and heterogeneity in commuting flows. Physical Review E, 88 (2), 022812. doi:10.1103/PhysRevE.88.022812
- Mrazovic, P., et al., 2017. Understanding and predicting trends in urban freight transport. In 2017 IEEE 18th International Conference on Mobile Data Management (MDM), 124–133.
- Noulas, A., et al. 2012. A tale of many cities: universal patterns in human urban mobility. PloS one, 7 (5), e37027. doi:10.1371/journal.pone.0037027
- Ogden, K.W., 1978. The distribution of truck trips and commodity flow in urban areas: a gravity model analysis. Transportation Research, 12 (2), 131–137. doi:10.1016/0041-1647(78)90052-7
- Ogunsanya, A.A., 1982. Spatial pattern of urban freight transport in Lagos metropolis. Transportation Research Part A: General, 16 (4), 289–300. doi:10.1016/0191-2607(82)90056-5
- Okoko, E., 2008. The spatial pattern of urban goods movement in Akure, Nigeria. Pakistan Journal of Social Sciences, 5 (3), 226–234.
- Palchykov, V., et al., 2014. Inferring human mobility using communication patterns. Scientific Reports, 4, 6174. doi:10.1038/srep06174
- Pluvinet, P., Gonzalez-Feliu, J., and Ambrosini, C., 2012. GPS data analysis for understanding urban goods movement. Procedia-Social and Behavioral Sciences, 39, 450–462. doi:10.1016/j.sbspro.2012.03.121
- Ren, Y., et al., 2014. Predicting commuter flows in spatial networks using a radiation model based on temporal ranges. Nature Communications, 5, 5347. doi:10.1038/ncomms5972
- Roth, C., et al. 2011. Structure of urban movements: polycentric activity and entangled hierarchical flows. PloS one, 6 (1), e15923. doi:10.1371/journal.pone.0015923
- Siła-Nowicka, K., et al. 2016. Analysis of human mobility patterns from GPS trajectories and contextual information. International Journal of Geographical Information Science, 30 (5), 881–906. doi:10.1080/13658816.2015.1100731
- Simini, F., et al. 2012. A universal model for mobility and migration patterns. Nature, 484 (7392), 96–100. doi:10.1038/nature10856
- Song, C., et al. 2010. Modelling the scaling properties of human mobility. Nature Physics, 6 (10), 818–823. doi:10.1038/nphys1760
- Vegelius, J., Janson, S., and Johansson, F., 1986. Measures of similarity between distributions. Quality and Quantity, 20 (4), 437–441. doi:10.1007/BF00123091
- Vieira, J.G.V., Fransoo, J.C., and Carvalho, C.D., 2015. Freight distribution in megacities: perspectives of shippers, logistics service providers and carriers. Journal of Transport Geography, 46, 46–54. doi:10.1016/j.jtrangeo.2015.05.007
- Wang, W., et al., 2015. A comparative analysis of intra-city human mobility by taxi. Physica A: Statistical Mechanics and Its Applications, 420, 134–147. doi:10.1016/j.physa.2014.10.085
- Woudsma, C., 2001. Understanding the movement of goods, not people: issues, evidence and potential. Urban Studies, 38 (13), 2439–2455. doi:10.1080/00420980120094605
- Xu, Y., et al., 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.
- Yan, X.Y., et al., 2013. Diversity of individual mobility patterns and emergence of aggregated scaling laws. Scientific Reports, 3, 2678. doi:10.1038/srep02678
- Yan, X.Y., et al. 2014. Universal predictability of mobility patterns in cities. Journal of the Royal Society Interface, 11 (100), 20140834. doi:10.1098/rsif.2014.0834
- Yan, X.Y., et al. 2017. Universal model of individual and population mobility on diverse spatial scales. Nature Communications, 8 (1), 1639. doi:10.1038/s41467-017-01892-8
- Yin, J., et al. 2017. Depicting urban boundaries from a mobility network of spatial interactions: a case study of Great Britain with geo-located Twitter data. International Journal of Geographical Information Science, 31 (7), 1293–1313. doi:10.1080/13658816.2017.1282615
- Yuan, Y. and Medel, M., 2016. Characterizing international travel behavior from geotagged photos: a case study of flickr. PloS one, 11 (5), e0154885. doi:10.1371/journal.pone.0154885
- Yuan, Y. and Raubal, M., 2016. Analyzing the distribution of human activity space from mobile phone usage: an individual and urban-oriented study. International Journal of Geographical Information Science, 30 (8), 1594–1621. doi:10.1080/13658816.2016.1143555
- Zanjani, A., et al., 2015. Estimation of statewide origin-destination truck flows using large streams of GPS data: application for Florida statewide model. In Proceedings of the 94th Annual Transportation Research Board Conference.
- Zhao, K., et al., 2015a. Explaining the power-law distribution of human mobility through transportation modality decomposition. Scientific Reports, 5, 9136. doi:10.1038/srep09136
- Zhao, P., et al., 2015b. Statistical analysis on the evolution of OpenStreetMap road networks in Beijing. Physica A: Statistical Mechanics and Its Applications, 420, 59–72. doi:10.1016/j.physa.2014.10.076
- Zhao, P., et al., 2017b. A trajectory clustering approach based on decision graph and data field for detecting hotspots. International Journal of Geographical Information Science, 31 (6), 1101–1127.
- Zhao, P., Kwan, M.P., and Qin, K., 2017a. Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on individuals’ daily travel. Journal of Transport Geography, 62, 122–135. doi:10.1016/j.jtrangeo.2017.05.001
- Zhong, C., et al. 2014. Detecting the dynamics of urban structure through spatial network analysis. International Journal of Geographical Information Science, 28 (11), 2178–2199. doi:10.1080/13658816.2014.914521