Peer-Reviewed Journal Articles:
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. https://doi.org/10.1016/j.cities.2025.106245
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. https://doi.org/10.1016/j.jtrangeo.2025.104189
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. https://doi.org/10.1016/j.healthplace.2025.103419
Liu, D., Wang, J., Song, J., Kwan, M.P., Fang, D., Ariga, T., Chen, Y. and Stinckwich, S., 2025. Exploring the inequality in fine-grained primary healthcare accessibility in Macau based on high-resolution geospatial data under the 15-minute city framework. Applied Geography, 174, p.103473. https://doi.org/10.1016/j.apgeog.2024.103473
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. https://doi.org/10.1016/j.apgeog.2024.103451
Liu, D., Kan, Z., Kwan, M.P. and Tang, L., 2024. Space-time analysis of refueling patterns of alternative fuel vehicles (AFVs) using GPS trajectory data and machine learning. Transactions in GIS, 28(8), pp. 2639-2651. https://doi.org/10.1111/tgis.13258
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. https://doi.org/10.1016/j.ufug.2024.128335
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. https://doi.org/10.1111/tesg.12613
Liu, D., Kwan, M.P. and Wang, J., 2024. Developing the 15-minute city: A comprehensive assessment of the status in Hong Kong. Travel Behaviour and Society, 34, p.100666. https://doi.org/10.1016/j.tbs.2023.100666
Liu, D., Lee, J., Zhong, S. and Gilliland, J., 2024. Echoes of home: Mapping vulnerable places for Cantonese-speaking immigrants seeking family doctors in the Greater Toronto Area. Health & Social Care in the Community, p. 1980874. https://doi.org/10.1155/2024/1980874
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, 329, p.116040. https://doi.org/10.1016/j.socscimed.2023.116040
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), pp. 689–702. https://doi.org/10.1007/s12061-022-09495-7
Liu, D., Kwan, M.P., Kan, Z., Song, Y. and Li, X., 2023. Racial/ethnic inequality in transit-based accessibility to COVID-19 vaccination sites. Journal of Racial and Ethnic Health Disparities, 10, pp.1533–1541. https://doi.org/10.1007/s40615-022-01339-x
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. https://doi.org/10.3390/su142416914
Liu, D. and Kwan, M.P., 2022. Integrated analysis of doubly disadvantaged neighborhoods by considering both green space and blue space accessibility and COVID-19 infection risk. PLOS One, 17(11), p.e0273125. https://doi.org/10.1371/journal.pone.0273125
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. https://doi.org/10.1111/area.12796
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, pp.57-64. https://doi.org/10.1016/j.tbs.2021.11.005
Liu, D., Kwan, M.P. and Kan, Z., 2021. Analyzing disparities in transit-based healthcare accessibility in the Chicago Metropolitan Area. The Canadian Geographer//Le Géographe canadien, 66(2), pp.248–262. https://doi.org/10.1111/cag.12708
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, p.127029. https://doi.org/10.1016/j.ufug.2021.127029
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
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, pp.1-27. https://doi.org/10.1080/17535069.2021.1923795
Liu, D. and Kwan, M.P., 2020. Measuring spatial mismatch and job access inequity based on transit-based job accessibility for poor job seekers. Travel Behaviour and Society, 19, pp.184-193. https://doi.org/10.1016/j.tbs.2020.01.005
Liu, D. and Kwan, M.P., 2020. Measuring job accessibility through integrating travel time, transit fare and income: a study of the Chicago Metropolitan Area. Tijdschrift voor Economische en Sociale Geografie, 111(4), pp. 671–685. https://doi.org/10.1111/tesg.12415
Wang, L., Zhou, S., Kwan, M.P., Liu, D., Zhang, L. and Song, J., 2026. Space-based planning implications for age-friendly cities: Insights from spatial non-stationarity in multiple environment-health relationships. Cities, 169, p.106495. https://doi.org/10.1016/j.cities.2025.106495
Fang, D., Liu, D. and Kwan, M.P., 2025. Evaluating spatial variation of accessibility to urban green spaces and its inequity in Chicago: Perspectives from multi-types of travel modes and travel time. Urban Forestry & Urban Greening, 104, p. 128593. https://doi.org/10.1016/j.ufug.2024.128593
Wang, J., Kwan, M.P., Liu, D., Liu, Y. and Wang, Y., 2025. 15-minute city beyond the urban core: Lessons from the urban-suburban disparity in PCR accessibility within the X-minute framework. Transportation Research Part A: Policy and Practice, 198, p. 104546. https://doi.org/10.1016/j.tra.2025.104546
Fang, D., Kwan, M.P. and Liu, D., 2025. Evaluating the mismatch between urban greenery and cycling. Transportation Research Part D: Transport and Environment, 147, p. 104935. https://doi.org/10.1016/j.trd.2025.104935
Song, J., Zhou, S., Kwan, M.P., Liao, Y., Liu, D. and Zhang, X., 2025. Association between real-time noise exposure in broader activity contexts and job satisfaction: Evidence from Guangzhou, China. Cities, 161, p. 105912. https://doi.org/10.1016/j.cities.2025.105912
Ahmed, N., Jui, J., Liu, D., Kim, K., Kim, J. and Lee, J., 2025. Understanding inequalities in geographic accessibility to emergency cyclone shelters in Bangladesh under climate change. Journal of Transport Geography, 123, p. 104134. https://doi.org/10.1016/j.jtrangeo.2025.104134
Yang, Z., Kwan, M.P., Liu, D. and Huang, J., 2025. How objective and subjective greenspace, combined with air and noise pollution, impacts mental health through the mediation of physical activity. Urban Forestry & Urban Greening, 105, p.128683. https://doi.org/10.1016/j.ufug.2025.128683
Zheng, L., Kwan, M.P., Huang J. and Liu, D., 2025. Exploring the interaction between perceived risk and travel flexibility in daily mobility change: Evidence from Hong Kong’s COVID-19 pandemic. Travel Behaviour and Society, 40, p.101015. https://doi.org/10.1016/j.tbs.2025.101015
Li, Y., Zhang, Y., Kam, K.W., Chan, P., Liu, D., Zaabaar, E., Zhang, X.J., Ho, M., Ng, M.P.H., Ip, P., Young, A., Pang, C.P., Tham, C.C., Kwan, M.P., Chen, L.J. and Yam, J.C., 2025. Associations of long-term joint exposure to multiple ambient air pollutants with the incidence of age-related eye diseases. Ecotoxicology and Environmental Safety, 294, p. 118052. https://doi.org/10.1016/j.ecoenv.2025.118052
Zaabaar, E., Zhang, Y., Kam, K.W., Li, Y., Zhang, X.J., Ho, M., Liu, D., Ng, M.P.H., Ip, P., Young, A., Pang, C.P., Tham, C.C., Kwan, M.P., Chen, L.J. and Yam, J.C., 2025. Association of residential air pollution with visual impairment in adults: the UK Biobank study. Asia-Pacific Journal of Ophthalmology, p.100209. https://doi.org/10.1016/j.apjo.2025.100209
Yue, Y., Yan, G., Lan, T., Cao, R., Gao, Q., Gao, W., Huang, B., Huang, G., Huang, Z., Kan, Z., Li, X., Liu, D., Liu, X., Ma, D., Wang, L., Xia, J., Yang, X., Zhou, M., Yeh, A., Guo, R. and Claramunt, C., 2025. Shaping future sustainable cities with AI-powered urban informatics: Toward human-AI symbiosis. Computational Urban Science, 5(31). https://doi.org/10.1007/s43762-025-00190-0
Song, L., Liu, D., Kwan, M.P., Liu, Y. and Zhang, Y., 2024. Machine-based understanding of noise perception in urban environments using mobility-based sensing data. Computers, Environment and Urban Systems, 114, p.102204. https://doi.org/10.1016/j.compenvurbsys.2024.102204
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. https://doi.org/10.1016/j.apgeog.2024.103453
Wang, L., Kwan, M.P., Zhou, S. and Liu, D., 2024. Assessing the affective quality of soundscape for individuals: Using third-party assessment combined with an artificial intelligence (TPA-AI) model. Science of The Total Environment, 953, p. 176083. https://doi.org/10.1016/j.scitotenv.2024.176083
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. https://doi.org/10.1016/j.envres.2024.119499
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, pp.103896. https://doi.org/10.1016/j.jtrangeo.2024.103896
Du, M., Li, X., Wang, H., Yang, J., Liu, D. and Kwan, M.P., 2024. Investigating the influential factors of ride-hailing usage frequency in the post-pandemic era. Applied Sciences, 14(22), p.10722. https://doi.org/10.3390/app142210722
Du, M., Li, Z., Li, X., Xu, J., Liu, D. and Kwan, M.P., 2024. Understanding the spatial variation of integrated use of ride-hailing services with the metro. Journal of Advanced Transportation. https://doi.org/10.1155/atr/9210901
Du, M., Li, Z., Li, X., Xu, J., Liu, D. and Kwan, M.P., 2024. Understanding the spatial variation of integrated use of ride-hailing services with the metro. Journal of Advanced Transportation, 2024(1). https://doi.org/10.1155/atr/9210901
Yang, Z., Huang, J., Kwan, M.P. and Liu, D., 2024. The interplay among individuals’ distress, daily activities, and perceptions of COVID-19 and neighborhood cohesion: A study using network analysis. PLOS One, 19(1), p.e0293157. https://doi.org/10.1371/journal.pone.0293157
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, pp.1-11. https://doi.org/10.1080/24694452.2023.2266021
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. https://doi.org/10.1016/j.healthplace.2023.103115
Li, X., Xu, J., Du, M., Liu, D. and Kwan, M.P., 2023. Understanding the spatiotemporal variation of ride-hailing orders under different travel distances. Travel Behaviour and Society, 32, p.100581. https://doi.org/10.1016/j.tbs.2023.100581
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, 128123. https://doi.org/10.1016/j.ufug.2023.128123
Wang, J., Kwan, M.P., Liu, D. and Peng, X., 2023. Assessing the spatial distribution of and inequality in 15-minute PCR test site accessibility in Beijing and Guangzhou, China. Applied Geography, 154, p.102925. https://doi.org/10.1016/j.apgeog.2023.102925
Cai, J., Kwan, M.P., Hou, C., Liu, D. and Yam, Y., 2023.Curriculum design of artificial intelligence and sustainability in secondary school. I-GUIDE Forum 2023: Harnessing the Geospatial Data Revolution for Sustainability Solutions, Columbia University. https://doi.org/10.5703/1288284317666
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, pp.103240. https://doi.org/10.1016/j.jtrangeo.2021.103240
Song, Y., Chen B., Ho, H.C., Kwan, M.P., Liu, D., Wang, F., Wang, J., Cai, J., Li X., Xu Y., He, Q., Wang H., Xu, Q., Song, Y., 2021. Observed inequality in urban greenspace exposure in China. Environment International, 156, p.106778. https://doi.org/10.1016/j.envint.2021.106778
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. Transactions in GIS, 25, pp.2982-3001. https://doi.org/10.1111/tgis.12800
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, p.145379. https://doi.org/10.1016/j.scitotenv.2021.145379
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, pp.229-243. https://doi.org/10.1016/j.compenvurbsys.2018.11.007
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, pp.340-352. https://doi.org/10.1016/j.jclepro.2018.08.222