1. Liu, D., Kan, Z., Wang, J., Kwan, M.P., Song, J. and Wei, J., 2025. Using spatially explicit high-granularity 3D geospatial data for quantifying public transport walking accessibility inequality and vulnerability in the x-minute city. Cities, 166, p.106245.
2. Liu, D., Wei, J. and Kan, Z*., 2025. Integrated transit service status assessment using smart transit card big data under the x-minute city framework. Journal of Transport Geography, 125, p.104189.
3. Liu, D., Kan, Z., Kwan, M.P., Cai, J. and Liu, Y., 2025. Assessing the impact of socioeconomic and environmental factors on mental health during the COVID-19 pandemic based on GPS-enabled mobile sensing and survey data. Health & Place, 92, p.103419.
4. Su, L., Kan, Z*. and Kwan, M.P., 2025. Exploring the factors behind the discrepancy between two-dimensional and three-dimensional indicators of greenspace exposure. Ecological Indicators, 175, p.113584.
5. Wei, J., Kan, Z., Liu, Z., Wang, Z. and Chen, Y., 2025. Exploring spatio-temporal variations in nonlinear correlations between the built environment and metro-bike travel: evidence from Beijing. Transportmetrica B: Transport Dynamics, 13(1), p.2541282.
6. Zhao, Z., Kan, Z., Kwan, M.P. and Tang, L., 2025. Identifying urban spatial clusters via flow dynamics: a coupled tensor-based method. International Journal of Digital Earth, 18(1), p.2525382.
7. Guo, X., Fang, M., Tang, L., Kan, Z., Yang, X., Pei, T., Li, Q. and Li, C., 2025. An adaptive OD flow clustering method to identify heterogeneous urban mobility trends. Journal of Transport Geography, 123, p.104080.
8. Kan, Z*., Liu, D., Yang, X. and Lee, J., 2024. Measuring exposure and contribution of different types of activity travels to traffic congestion using GPS trajectory data. Journal of Transport Geography, 117, p.103896.
9. Liu, D., Kan, Z., Kwan, M.-P. and Tang, L. 2024, Space–time analysis of refueling patterns of alternative fuel vehicles using GPS trajectory data and machine learning. Transactions in GIS. https://doi.org/10.1111/tgis.13258.
10. Wei, J., Kan, Z*., Kwan, M.P., Liu, D., Su, L. and Chen, Y., 2024. Uncovering travel communities among older and younger adults using smart card data. Applied Geography, 173, p.103453.
11. Shi, H., Zhao, Z., Tang, L., Kan, Z. and Du, Y., 2024. Advancing human mobility modeling: a novel path flow approach to mining traffic congestion dynamics. International Journal of Geographical Information Science, p.1-28.
12. Zhao, Z., Tang, L., Ren, C., Yang, X., Kan, Z. and Li, Q., 2024. Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory. GIScience & Remote Sensing, 61(1), p.2290347.c
13. Liu, D., Kan, Z. and Lee, J., 2024. The proposal of a 15-minute city composite index through integrating GPS trajectory data-inferred urban function attraction based on the Bayesian framework. Applied Geography, 173, p.103451.
14. Huang, J., Kwan, M.P., Kan, Z., Kieu, M., Lee, J., Schwanen, T. and Yamada, I., 2024. Inter-relationships among individual views of COVID-19 control measures across multi-cultural contexts. Social Science & Medicine, 358, p.117247.
15. Liu, D., Kwan, M.P., Yang, Z. and Kan, Z., 2024. Comparing subjective and objective greenspace accessibility: Implications for real greenspace usage among adults. Urban Forestry & Urban Greening, 96, p.128335.
16. Zheng, L., Kwan, M.P., Liu, Y., Liu, D., Huang, J. and Kan, Z., 2024. How mobility pattern shapes the association between static green space and dynamic green space exposure. Environmental Research, 258, p.119499.
17. Liu, D., Kwan, M.P., Wang, L., Kan, Z., Wang, J. and Huang, J., 2024. Development of a Chrono‐Urbanism Status Composite Index under the 5/10/15‐Minute City Concept Using Social Media Big Data. Tijdschrift voor economische en sociale geografie. 115: 554-570.
18. Kwan, M.P., Huang, J. and Kan, Z., 2023. People’s political views, perceived social norms, and individualism shape their privacy concerns for and acceptance of pandemic control measures that use individual-level georeferenced data. International Journal of Health Geographics, 22(1), p.35.
19. Kan, Z., Kwan, M.P., Huang, J., Cai, J. and Liu, D., 2023. A Spatial Network-Based Assessment of Individual Exposure to COVID-19. Annals of the American Association of Geographers, p.1-11.
20. Ahmed, N., Lee, J., Liu, D., Kan, Z. and Wang, J., 2023. Identifying urban green space deserts by considering different walking distance thresholds for healthy and socially equitable city planning in the Global South. Urban Forestry & Urban Greening, 89, p.128123.
21. Kan, Z., Kwan, M.P., Cai, J., Liu, Y. and Liu, D., 2023. Nonstationary relationships among individuals’ concurrent exposures to noise, air pollution and greenspace: A mobility-based study using GPS and mobile sensing data. Health & Place, 83, p.103115.
22. Cai, J., Kwan, M.P., Kan, Z. and Huang, J., 2023. Perceiving noise in daily life: How real-time sound characteristics affect personal momentary noise annoyance in various activity microenvironments and times of day. Health & Place, 83, p.103053.
23. Liu, D., Kwan, M.P., Kan, Z., Song, Y. and Li, X., 2023. Racial/ethnic inequity in transit-based spatial accessibility to COVID-19 vaccination sites. Journal of Racial and Ethnic Health Disparities, 10(4), p.1533-1541.
24. Liu, D., Kwan, M.P., Kan, Z. and Liu, Y., 2023. Examining individual-level tri-exposure to greenspace and air/noise pollution using individual-level GPS-based real-time sensing data. Social Science & Medicine, p.116040.
25. Liu, D., Kwan, M.P. and Kan, Z., 2023. Assessment of doubly disadvantaged neighborhoods by healthy living environment exposure. Applied Spatial Analysis and Policy, 16(2), p.689-702.
26. Liu, Y., Kwan, M.P. and Kan, Z., 2023. Inconsistent association between perceived air quality and self-reported respiratory symptoms: a pilot study and implications for environmental health studies. International Journal of Environmental Research and Public Health, 20(2), p.1491.
27. Kan, Z., Kwan, M.P. and Tang, L., 2022. Ripley’s K‐function for network‐constrained flow data. Geographical Analysis, 54(4), p.769-788.
28. Kan, Z., Kwan, M.P., Liu, D., Tang, L., Chen, Y. and Fang M., 2022. Assessing individual activity-related exposures to traffic congestion using GPS trajectory data. Journal of Transport Geography, 98, 103240.
29. Liu, D., Kwan, M.P., Kan, Z., Song, Y. and Li, X., 2022. Inter‐and intra‐racial/ethnic disparities in walking accessibility to grocery stores. Area, 54(4), pp.627-637.
30. Zhao, Z., Fang, M., Tang, L., Yang, X., Kan, Z. and Li, Q., 2022. The Impact of Community Shuttle Services on Traffic and Traffic-Related Air Pollution. International Journal of Environmental Research and Public Health, 19(22), p.15128.
31. Tang, L., Zhao, Z., Yang, X., Kan, Z., et al., Road crowd-sensing with high spatio-temporal resolution in big data era. Acta Geodaetica et Cartographica Sinica, 2022, 51(6): 1070-1090.
32. Kan, Z., Kwan, M.P., Ng, M. K., Tieben, H., 2022. The Impacts of Housing Characteristics and Built-Environment Features on Mental Health. International Journal of Environmental Research and Public Health, 19(9): 5143. https://doi.org/10.3390/ijerph19095143
33. Liu, D., Kwan, M.P., Kan, Z., Song, Y. and Li, X., 2022. Racial/Ethnic Inequity in Transit-Based Spatial Accessibility to COVID-19 Vaccination Sites. Journal of Racial and Ethnic Health Disparities, 1-9.
34. Liu, D., Kwan, M.P., Huang, J., Kan, Z., Song Y. and Li, X., 2022. Analyzing income-based inequality in transit nodal accessibility. Travel Behaviour and Society. 27, 57-64. https://doi.org/10.1016/j.tbs.2021.11.005
35. Huang, J., Kwan, M.P., Cai, J., Song, W., Yu, C., Kan, Z. and Yim, S.H.L., 2022. Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research. Sensors, 22(6), 2381. https://doi.org/10.3390/s22062381
36. Liu, D., Kwan, M.P., Kan, Z. and Wang, J., 2022. Toward a healthy urban living environment: Assessing 15-minute green-blue space accessibility. Sustainability, 14(24), p.16914.
37. Kan, Z., Kwan, M.P., Huang, J., Wong, M.S. and Liu, D., 2021. Comparing the space-time patterns of high-risk areas in different waves of COVID-19 in Hong Kong. Transaction in GIS. 00, 1– 20. https://doi.org/10.1111/tgis.12800
38. Kan, Z., Kwan, M.P., Wong, M.S., Huang, J. and Liu, D., 2021. Identifying the space-time patterns of COVID-19 risk and their associations with different built environment features in Hong Kong. Science of the Total Environment, 772, 145379. https://doi.org/10.1016/j.scitotenv.2021.145379
39. Huang, J., Kwan, M.P. and Kan, Z., 2021. The superspreading places of COVID-19 and the associated built-environment and socio-demographic features: A study using a spatial network framework and individual-level activity data. Health & Place, 102694. https://doi.org/10.1016/j.healthplace.2021.102694
40. Ren, C., Tang, L., Long, J., Kan, Z. and Yang, X., 2021. Modelling place visit probability sequences during trajectory data gaps based on movement history. ISPRS International Journal of Geo-Information, 10(7), 456. https://doi.org/10.3390/ijgi10070456
41. Kwok, C.Y.T., Wong, M.S., Chan, K.L., Kwan, M.P., Nichol, J.E., Liu, C.H., Wong, J.Y.H., Wai, A.K.C., Chan, L.W.C., Xu, Y., Li, H., Huang, J. and Kan, Z., 2021. Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong. Science of the Total Environment, 764, 144455. https://doi.org/10.1016/j.scitotenv.2020.144455
42. Liu, D., Kwan, M.P., Kan, Z., 2021. Analyzing disparities in transit-based healthcare accessibility in the Chicago Metropolitan Area. Canadian Geographer/Le Géographe canadien. 1-15. https://doi.org/10.1111/cag.12708
43. Liu, D., Kwan, M.P., Kan, Z. and Song, Y., 2021. An integrated analysis of housing and transit affordability in the Chicago Metropolitan Area. The Geographical Journal, 187, 110–126. https://doi.org/10.1111/geoj.12377
44. Liu, D., Kwan, M.P. and Kan, Z., 2021. Analysis of urban green space accessibility and distribution inequity in the City of Chicago. Urban Forestry & Urban Greening, 59,127029. https://doi.org/10.1016/j.ufug.2021.127029
45. Liu, D., Kwan, M.P. and Kan, Z., 2021. Assessing job-access inequity for transit-based workers across space and race with the Palma ratio. Urban Research & Practice, 1-27 https://doi.org/10.1080/17535069.2021.1923795
46. Yu, X., Wong, M.S., Kwan, M.P., Nichol, J.E., Zhu, R., Heo, J., Chan, P.W., Chin, D.C., Kwok, C.Y.T. and Kan, Z., 2021. Covid-19 infection and mortality: Association with PM2.5 concentration and population density—An exploratory study. ISPRS International Journal of Geo-Information, 10(3),123. https://doi.org/10.3390/ijgi10030123
47. Kan, Z., Wong, M. S., Zhu, R., 2020. Understanding space-time patterns of vehicular emission flows in urban areas using geospatial technique. Computers, Environment and Urban Systems, 79, 101399. https://doi.org/10.1016/j.compenvurbsys.2019.101399
48. Chen, Y., Tang, L., Kan, Z., Bilal, M. and Li, Q., 2020. A novel water body extraction neural network (WBE-NN) for optical high-resolution multispectral imagery. Journal of Hydrology, 588, 125092. https://doi.org/10.1016/j.jhydrol.2020.125092
49. Cheng, L., Yang, X., Tang, L., Duan, Q., Kan, Z., Zhang, X. and Ye, X., 2020. Spatiotemporal analysis of taxi-driver shifts using big trace data. ISPRS International Journal of Geo-Information, 9(4), 281. https://doi.org/10.3390/ijgi9040281
50. Chen, Y., Tang, L., Kan, Z., Latif, A., Yang, X., Bilal, M. and Li, Q., 2020. Cloud and cloud shadow detection based on multiscale 3D-CNN for high resolution multispectral imagery. IEEE Access, 8, 16505-16516. https://doi.org/10.1109/ACCESS.2020.2967590
51. Huang, J., Kwan, M. P., Kan, Z. et al. 2020. Investigating the relationship between the built environment and relative risk of COVID-19 in Hong Kong. ISPRS International Journal of Geo-Information, 9(11): 624. https://doi.org/10.3390/ijgi9110624
52. Kwok, C.Y.T., Wong, M.S., Li, H., Hui, K.K.W., Ko, F.W.Y., Shiu, H.Y.K. and Kan, Z., 2020. Detection of structural tree defects using thermal infrared imaging. In 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019. http://www.scopus.com/inward/record.url?scp=85085665273&partnerID=8YFLogxK
53. Kan, Z., Tang, L., Kwan, M.P., Ren, C., Liu, D. and Li, Q., 2019. Traffic congestion analysis at the turn level using taxis’ GPS trajectory data. Computers, Environment and Urban Systems, 74, 229-243. https://doi.org/10.1016/j.compenvurbsys.2018.11.007
54. Tang, L., Gao, J., Ren, C., Zhang, X., Yang, X. and Kan, Z., 2019. Detecting and evaluating urban clusters with spatiotemporal big data. Sensors, 19(3), p.461. https://doi.org/10.3390/s19030461
55. Tang L., Kan Z., Ren C. et al., 2019. Fine-grained analysis of traffic congestions at the turning level using GPS traces. Acta Geodaetica et Cartographica Sinica, 48(1), 75-85. https://doi.org/10.11947/j.AGCS.2019.20170448
56. Kan, Z., Tang, L., Kwan, M. P. and Zhang, X., 2018. Estimating vehicle fuel consumption and emissions using GPS big data. International Journal of Environmental Research and Public Health, 15(4), 566. https://doi.org/10.3390/ijerph15040566
57. Kan, Z., Tang, L., Kwan, M.P., Ren, C., Liu, D., Pei, T., Liu, Y., Deng, M. and Li, Q., 2018. Fine-grained analysis on fuel-consumption and emission from vehicles trace. Journal of cleaner production, 203, 340-352. https://doi.org/10.1016/j.jclepro.2018.08.222
58. Tang, L., Sun, F., Kan, Z., Ren, C. and Cheng, L., 2017. Uncovering distribution patterns of high performance taxis from big trace data. ISPRS International Journal of Geo-Information, 6(5), 134. https://doi.org/10.3390/ijgi6050134
59. Tang, L., Kan, Z.*, Duan, Q. et al., 2017. A space-time path supported estimation approach for vehicles’ fuel-consumption and emissions. Acta Geodaetica et Cartographica Sinica, 46(12), 2024-2031. (Corresponding author). https://doi.org/10.11947/j.AGCS.2017.20160439
60. Tang, L., Kan, Z.*, Liu, H., et al., 2017. A kernel density estimation method for linear features in network space. Acta Geodaetica et Cartographica Sinica, 46(1), 107-113. (Corresponding author). https://doi.org/10.11947/j.AGCS.2017.20150158
61. Tang L., Duan Q., Kan, Z. et al., 2017. Study on identification and space-time distribution analysis of taxi shift behavior. ISPRS Journal of Geo-Information Science, 19(2), 167-175. https://doi.org/10.3724/SP.J.1047.2017.00167
62. Tang L., Jin C., Yang X., Kan. Z. et al., 2017. Road network topology automatic change detection based on GPS spatio-temporal trajectories. Geomatics and Information Science of Wuhan University, 42(10), 1381-1386. https://doi.org/10.13203/j.whugis20150662
63. Tang, L., Kan, Z.*, Zhang, X., et al., 2016. A network kernel density estimation for linear features in space–time analysis of big trace data. International Journal of Geographical Information Science, 30(9), 1717-1737. (Corresponding author). https://doi.org/10.1080/13658816.2015.1119279
64. Tang, L., Kan, Z.*, Huang, F., et al., 2016. Travel time detection at intersection from taxis’ trace data. Geomatics and Information Science of Wuhan University, 41(1), 136-142. (Corresponding author). https://doi.org/10.13203/j.whugis20130822
65. Liu, H., Kan, Z.*, Sun, F., et al., 2016. Taxis’ short-term out-of-service behaviors detection using big trace data. Geomatics and Information Science of Wuhan University, 41(9), 1192-1198. (Corresponding author). https://doi.org/10.13203/j.whugis20150569
66. Liu, H., Kan, Z., Wu, H. et al., 2016. Vehicles’ refueling activity modeling and space-time distribution analysis. Bulletin of Surveying and Mapping, 9, 29-34. https://doi.org/10.13474/j.cnki.11-2246.2016.0286
67. Tang, L., Yang, X., Kan, Z. et al., 2016. Traffic lane numbers detection based on the naive Bayesian classification. China Journal of Highway and Transport, 29(3), 116-123. https://doi.org/10.3969/j.issn.1001-7372.2016.03.015
68. Tang L., Liu Z., Yang X., Kan Z. et al., 2016. A method of spatio-temporal trajectory fusion and road network generation based on cognitive law. Acta Geodaetica et Cartographica Sinica, 44(11), p.1271. https://doi.org/10.11947/j.AGCS.2015.20140591
69. Tang, L., Kan, Z.*, Zhang, X., et al., 2016. Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data. Cartography and Geographic Information Science, 43(5), 417-426. (Corresponding author). https://doi.org/10.1080/15230406.2015.1130649
70. Tang, L., Yang, X., Kan, Z. et al., 2015. Lane-level road information mining from vehicle GPS trajectories based on naïve Bayesian classification. ISPRS International Journal of Geo-Information, 4(4), 2660-2680. https://doi.org/10.3390/ijgi4042660
71. Huang L., Kan, Z. and Li D., 2015. Design and realization of 3d electronic map based on time and space base state correction. Geospatial Information, 34(1), 311-315. https://doi.org/10.3969/j.issn.1672-4623.2015.01.055
72. Tang, L., Zhang, X., Kan, Z., Yang, B. and Li, Q., 2014. Spatial data Internet progressive transmission control based on the geometric shapes similarity. International Journal of Control, Automation and Systems, 12(5), 1110-1117. (Corresponding author). https://doi.org/10.1007/s12555-012-0484-4