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Abstract Architecture
Black and White Architecture

Publications

120 

papers have been published since the establishment of the USI in December 2022
2024

68 papers published from 1 January 2024 to 1 September 2024

  • Chan, V.K.Y. et al. (2024) ‘Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a 9-year population-based study’, BMC Medicine, 22(1). Available at: https://doi.org/10.1186/s12916-024-03386-z.

  • Chen, B., Tu, Y., et al. (2024) ‘Quantification of losses in agriculture production in eastern Ukraine due to the Russia-Ukraine war’, Communications Earth and Environment, 5(1). Available at: https://doi.org/10.1038/s43247-024-01488-3.

  • Chen, B., Wu, S., et al. (2024) ‘Wildfire risk for global wildland–urban interface areas’, Nature Sustainability, 7(4), pp. 474–484. Available at: https://doi.org/10.1038/s41893-024-01291-0.

  • Connolly, C. (2024) ‘COVID-19 and the density debate’, Nature Cities, 1(1), pp. 18–19. Available at: https://doi.org/10.1038/s44284-023-00012-6.

  • Dai, M. and He, S. (2024) ‘Social mix and subjective wellbeing in Chinese urban neighborhoods: Exploring the domino effects of social capital through multilevel serial mediation analysis’, Habitat International, 143, p. 102968. Available at: https://doi.org/10.1016/j.habitatint.2023.102968.

  • Ding, F., Chen, S. and Zhao, Z. (2024) ‘Incorporating walking into ride-hailing: The potential benefits of flexible pick-up and drop-off’, Transportation Research Part D: Transport and Environment, 127. Available at: https://doi.org/10.1016/j.trd.2024.104064.

  • Doan, Q.C. et al. (2024) ‘How urban air quality affects land values: Exploring non-linear and threshold mechanism using explainable artificial intelligence’, Journal of Cleaner Production, 434, p. 140340. Available at: https://doi.org/10.1016/j.jclepro.2023.140340.

  • Fan, X. et al. (2024) ‘Post-traumatic stress, depression, and anxiety during the 2021 Myanmar conflict: a nationwide population-based survey’, The Lancet Regional Health - Southeast Asia, 26. Available at: https://doi.org/10.1016/j.lansea.2024.100396.

  • Fang, Z. et al. (2024) ‘UrbanClassifier: A deep learning-based model for automated typology and temporal analysis of urban fabric across multiple spatial scales and viewpoints’, Computers, Environment and Urban Systems, 111. Available at: https://doi.org/10.1016/j.compenvurbsys.2024.102132.

  • Gao, X. et al. (2024) ‘Spatial spillover effects of skilled migration on innovation in China’, Heliyon, 10(11). Available at: https://doi.org/10.1016/j.heliyon.2024.e30849.

  • Gerlofs, B.A. (2024) ‘Land fictions: The commodification of land in city and country’, Planning Theory, p. 14730952241257704. Available at: https://doi.org/10.1177/14730952241257704.

  • Gerlofs, B.A. et al. (2024) ‘Tank to Table: Hong Kong’s Wet Markets and the Geographies of Lively Commodification Beyond Companionship’, Annals of the American Association of Geographers, 114(4), pp. 844–862. Available at: https://doi.org/10.1080/24694452.2024.2304200.

  • He, Q. and Colic-Peisker, V. (2024) ‘Homeownership Habitus and Residential Practice of Highly-Skilled Chinese Migrants in the Netherlands’, Housing, Theory and Society [Preprint]. Available at: https://doi.org/10.1080/14036096.2024.2353052.

  • He, Q. and He, S. (2024) ‘Disentangling the intersectional field of education and housing in China: Genesis, strategies and discontents’, Environment and Planning A: Economy and Space, p. 0308518X241228453. Available at: https://doi.org/10.1177/0308518X241228453.

  • He, S., Shan, L. and Zhu, J. (2024) ‘How planning intervention changes the “price tags” of property rights? Towards a dynamic understanding of China’s small property right housing’, Cities, 150. Available at: https://doi.org/10.1016/j.cities.2024.105091.

  • Hu, L. and He, S. (2024) ‘Are gated communities “safe havens”? Examining housing price dynamics of Chinese gated and non-gated communities during COVID-19 pandemic’, Housing Studies [Preprint]. Available at: https://doi.org/10.1080/02673037.2024.2313606.

  • Hu, L., He, S. and Su, S. (2024) ‘Accessibility of Healthcare Resources to Public Housing in Shenzhen, China: Indirect Map Service and Optimized Two-Step Floating Catchment Area Method’, Tropical Geography, 44(2), pp. 226–235. Available at: https://doi.org/10.13284/j.cnki.rddl.003824.

  • Hu, Y., Chen, L. and Zhao, Z. (2024) ‘How does street environment affect pedestrian crash risks? A link-level analysis using street view image-based pedestrian exposure measurement’, Accident Analysis and Prevention, 205. Available at: https://doi.org/10.1016/j.aap.2024.107682.

  • Huang, G., Zhao, Z. and Yeh, A.G.O. (2024) ‘How shareable is your trip? A path-based analysis of ridesplitting trip shareability’, Computers, Environment and Urban Systems, 110. Available at: https://doi.org/10.1016/j.compenvurbsys.2024.102120.

  • Jiang, F., Ma, J., Webster, C.J., Wang, W., et al. (2024) ‘Automated site planning using CAIN-GAN model’, Automation in Construction, 159. Available at: https://doi.org/10.1016/j.autcon.2024.105286.

  • Jiang, F., Ma, J., Webster, C.J., Chen, W., et al. (2024) ‘Estimating and explaining regional land value distribution using attention-enhanced deep generative models’, Computers in Industry, 159–160. Available at: https://doi.org/10.1016/j.compind.2024.104103.

  • Jiang, X. et al. (2024) ‘Built environment and airbnb spatial distribution in Hong Kong: A case study considering the spatial heterogeneity and multiscale effects’, Applied Geography, 166. Available at: https://doi.org/10.1016/j.apgeog.2024.103262.

  • Jiang, X., Huang, B. and Zhao, Y. (2024) ‘Spatiotemporal Image Fusion With Spectrally Preserved Pre-Prediction: Tackling Complex Land-Cover Changes’, IEEE Transactions on Geoscience and Remote Sensing, 62, pp. 1–14. Available at: https://doi.org/10.1109/TGRS.2024.3412154.

  • Lai, K.Y. et al. (2024) ‘Association between Residential Greenness and Allostatic Load: A Cohort Study’, Environmental Science and Technology, 58(11), pp. 4884–4893. Available at: https://doi.org/10.1021/acs.est.3c04792.

  • Lai, Ka Yan et al. (2024) ‘Nexus between residential air pollution and physiological stress is moderated by greenness’, Nature Cities, 1(3), pp. 225–237. Available at: https://doi.org/10.1038/s44284-024-00036-6.

  • Li, C. and He, S. (2024) ‘Too Privileged to Move? Neighbourhood Perception and Relocation Intention in China’s Gated Communities’, Tijdschrift voor Economische en Sociale Geografie [Preprint]. Available at: https://doi.org/10.1111/tesg.12616.

  • Li, X. et al. (2024) ‘Enhancing Urban Climate-Energy Modeling in the Community Earth System Model (CESM) Through Explicit Representation of Urban Air-Conditioning Adoption’, Journal of Advances in Modeling Earth Systems, 16(4). Available at: https://doi.org/10.1029/2023MS004107.

  • Li, Z., Ma, J., et al. (2024) ‘Assessing the impacts of urban morphological factors on urban building energy modeling based on spatial proximity analysis and explainable machine learning’, Journal of Building Engineering, 85. Available at: https://doi.org/10.1016/j.jobe.2024.108675.

  • Li, Z., Chen, B., et al. (2024) ‘Deep learning for urban land use category classification: A review and experimental assessment’, Remote Sensing of Environment, 311. Available at: https://doi.org/10.1016/j.rse.2024.114290.

  • Liang, Y., Liu, Y., et al. (2024) ‘Exploring large language models for human mobility prediction under public events’, Computers, Environment and Urban Systems, 112. Available at: https://doi.org/10.1016/j.compenvurbsys.2024.102153.

  • Liang, Y., Zhao, Z., et al. (2024) ‘Time-dependent trip generation for bike sharing planning: A multi-task memory-augmented graph neural network’, Information Fusion, 106. Available at: https://doi.org/10.1016/j.inffus.2024.102294.

  • Liao, Q. et al. (2024) ‘Motivators and Demotivators for COVID-19 Vaccination Based on Co-Occurrence Networks of Verbal Reasons for Vaccination Acceptance and Resistance: Repetitive Cross-Sectional Surveys and Network Analysis’, JMIR Public Health and Surveillance, 10. Available at: https://doi.org/10.2196/50958.

  • Ling, C. et al. (2024) ‘Unravelling heterogeneity and dynamics of commuting efficiency: Industry-level insights into evolving efficiency gaps based on a disaggregated excess-commuting framework’, Journal of Transport Geography, 115. Available at: https://doi.org/10.1016/j.jtrangeo.2024.103820.

  • Liu, Y. and He, S. (2024) ‘The promise and reality of middle-class homeownership in China: housing assetisation, speculative urban (re)development and residential inequalities’, Urban Geography, pp. 1–23. Available at: https://doi.org/10.1080/02723638.2024.2397255.

  • Lu, H. et al. (2024) ‘A dose of nature to reduce sexual crimes in public outdoor spaces: Proposing the Landscape-Sexual Crime Model’, Landscape and Urban Planning, 250. Available at: https://doi.org/10.1016/j.landurbplan.2024.105143.

  • Ni, Y. et al. (2024) ‘Understanding paediatric COVID-19 vaccination during the pandemic: a prospective cohort and a population-based registry study’, The Lancet Regional Health - Western Pacific, 43, p. 100976. Available at: https://doi.org/10.1016/j.lanwpc.2023.100976.

  • Ou, Y., Song, W. and Nam, K.-M. (2024) ‘Metro-line expansions and local air quality in Shenzhen: Focusing on network effects’, Transportation Research Part D: Transport and Environment, 126, p. 103991. Available at: https://doi.org/10.1016/j.trd.2023.103991.

  • Qiao, R. et al. (2024) ‘The nonlinear influence of land conveyance on urban carbon emissions: An interpretable ensemble learning-based approach’, Land Use Policy, 140. Available at: https://doi.org/10.1016/j.landusepol.2024.107117.

  • Shan, L., Fan, Z. and He, S. (2024) ‘Towards a better understanding of capitalization of urban greening: Examining the interactive relationship between public and club green space accessibility’, Urban Forestry and Urban Greening, 96. Available at: https://doi.org/10.1016/j.ufug.2024.128359.

  • Tian, L. et al. (2024) ‘Examining the non-linear relationship between urban form and air temperature at street level: A case of Hong Kong’, Building and Environment, 264. Available at: https://doi.org/10.1016/j.buildenv.2024.111884.

  • Tian, T. et al. (2024) ‘Mapping the Time-Series of Essential Urban Land Use Categories in China: A Multi-Source Data Integration Approach’, Remote Sensing, 16(17), p. 3125.

  • Tu, Y. et al. (2024) ‘A 30 m annual cropland dataset of China from 1986 to 2021’, Earth System Science Data, 16(5), pp. 2297–2316. Available at: https://doi.org/10.5194/essd-16-2297-2024.

  • Wang, X. et al. (2024) ‘Municipal and Urban Renewal Development Index System: A Data-Driven Digital Analysis Framework’, Remote Sensing, 16(3). Available at: https://doi.org/10.3390/rs16030456.

  • Webster, Chris (2024) ‘Coupling planning models with models of spontaneous order’, Environment and Planning B: Urban Analytics and City Science, 51(5), pp. 1051–1054. Available at: https://doi.org/10.1177/23998083241246594.

  • Webster, C. (2024) ‘Tiebout, Coase and urban scaling’, Annals of Regional Science [Preprint]. Available at: https://doi.org/10.1007/s00168-024-01272-3.

  • Wei, H., Chen, Y., et al. (2024) ‘Built environments, communities, and housing price: A data-model integration approach’, Applied Geography, 166. Available at: https://doi.org/10.1016/j.apgeog.2024.103270.

  • Wei, H., Chen, B., et al. (2024) ‘Moderating AC Usage Can Reduce Thermal Disparity between Indoor and Outdoor Environments’, Environmental Science and Technology, 58(24), pp. 10524–10535. Available at: https://doi.org/10.1021/acs.est.4c00424.

  • Wong, I.O.L. et al. (2024) ‘Assessment of the impact of the vaccine pass policy on COVID-19 vaccine hesitancy and uptake among Chinese adults in Hong Kong’, Vaccine, 42(14), pp. 3346–3354. Available at: https://doi.org/10.1016/j.vaccine.2024.04.035.

  • Wu, S., Song, Y., et al. (2024) ‘High-resolution greenspace dynamic data cube from Sentinel-2 satellites over 1028 global major cities’, Scientific Data, 11(1). Available at: https://doi.org/10.1038/s41597-024-03746-7.

  • Wu, S., Lin, X., et al. (2024) ‘Satellite observations reveal a decreasing albedo trend of global cities over the past 35 years’, Remote Sensing of Environment, 303. Available at: https://doi.org/10.1016/j.rse.2024.114003.

  • Wu, Shengbiao et al. (2024) ‘The interplay of cloud cover and 3D urban structures reduces human access to sunlight’, Nature Cities, pp. 1–9. Available at: https://doi.org/10.1038/s44284-024-00120-x.

  • Xia, H. et al. (2024) ‘Enhancing phenology modeling through the integration of artificial light at night effects’, Remote Sensing of Environment, 303. Available at: https://doi.org/10.1016/j.rse.2024.113997.

  • Xu, W. et al. (2024) ‘Greener view, safer drive: Using repeated field experiments and deep transfer learning technique to investigate impacts of urban road landscapes on driving performance’, Landscape and Urban Planning, 251. Available at: https://doi.org/10.1016/j.landurbplan.2024.105156.

  • Xu, Wenyan et al. (2024) ‘Racial disparities in environmental exposures and SARS-CoV-2 infection rates: A detailed population-weighted analysis’, Sustainable Cities and Society, 101, p. 105135. Available at: https://doi.org/10.1016/j.scs.2023.105135.

  • Xu, W., He, J. and Jiang, B. (2024) ‘Not just More, but more diverse: Green landscapes along urban roads may significantly reduce drivers’ psychophysiological fatigue’, Transportation Research Part F: Traffic Psychology and Behaviour, 103, pp. 273–289. Available at: https://doi.org/10.1016/j.trf.2024.04.009.

  • Xue, H. et al. (2024) ‘Integrating visual factors in crash rate analysis at Intersections: An AutoML and SHAP approach towards cycling safety’, Accident Analysis and Prevention, 200. Available at: https://doi.org/10.1016/j.aap.2024.107544.

  • Yan, X. et al. (2024) ‘Governing cross-border healthcare in mainland China: a scoping review of national policies from 2002 to 2022’, The Lancet Regional Health - Western Pacific, 45. Available at: https://doi.org/10.1016/j.lanwpc.2024.101046.

  • Yan, X. and He, S. (2024) ‘Demystifying hospital size distribution: A geographical approach’, Applied Geography, 163, p. 103185. Available at: https://doi.org/10.1016/j.apgeog.2023.103185.

  • Yu, X. et al. (2024) ‘Can we trust our eyes? Interpreting the misperception of road safety from street view images and deep learning’, Accident Analysis and Prevention, 197. Available at: https://doi.org/10.1016/j.aap.2023.107455.

  • Yuan, J. et al. (2024) ‘Dynamic predictors of COVID-19 vaccination uptake and their interconnections over two years in Hong Kong’, Nature Communications, 15(1). Available at: https://doi.org/10.1038/s41467-023-44650-9.

  • Zhang, L. et al. (2024) ‘A Prolonged Artificial Nighttime-light Dataset of China (1984-2020)’, Scientific Data, 11(1). Available at: https://doi.org/10.1038/s41597-024-03223-1.

  • Zhang, P. et al. (2024) ‘Accessible Jobs and Secured Jobs by Mode of Travel and Isochrone: An Exploratory Study of Shanghai, China’, Transportation Research Record [Preprint]. Available at: https://doi.org/10.1177/03611981241246774.

  • Zhao, L., Shen, S. and Zhao, Z. (2024) ‘Planning decentralized battery-swapping recharging facilities for e-bike sharing systems’, Sustainable Cities and Society, 101, p. 105118. Available at: https://doi.org/10.1016/j.scs.2023.105118.

  • Zhou, M. and Zhou, J. (2024) ‘Multiscalar trip resilience and metro station-area characteristics: A case study of Hong Kong amid the pandemic’, Journal of Transport Geography, 116. Available at: https://doi.org/10.1016/j.jtrangeo.2024.103851.

  • Zhou, Y. et al. (2024) ‘Impacts of social deprivation on mortality and protective effects of greenness exposure in Hong Kong, 1999–2018: A spatiotemporal perspective’, Health and Place, 87. Available at: https://doi.org/10.1016/j.healthplace.2024.103241.

  • Zhou, Yang et al. (2024) ‘Residence-Workplace Identification and Validation Based on Mobile Phone Data: A Case Study in a Large-Scale Urban Agglomeration in China’, Transportation Research Record: Journal of the Transportation Research Board, p. 03611981241270163. Available at: https://doi.org/10.1177/03611981241270163.

  • Zhu, J. et al. (2024) ‘COVID-19 and aggravated housing precarity for international students: an Australian case study’, International Journal of Housing Policy, 24(2), pp. 344–371. Available at: https://doi.org/10.1080/19491247.2024.2339441.

  • Zu, J. et al. (2024) ‘Carsharing in China: Impact of system and urban factors on usage and efficiency’, Journal of Transport Geography, 117. Available at: https://doi.org/10.1016/j.jtrangeo.2024.103897.

​​

2023

41 papers published in 2023

  • Cantwell, G.T., Kirkley, A. and Radicchi, F. (2023) ‘Heterogeneous message passing for heterogeneous networks’, Physical Review E, 108(3), p. 034310. Available at: https://doi.org/10.1103/PhysRevE.108.034310.

  • Chen, B. (2023) ‘Coincided disparity between housing price and health outcome’, The Lancet Regional Health - Europe, 27, p. 100593. Available at: https://doi.org/10.1016/j.lanepe.2023.100593.

  • Chen, R., Zhang, M. and Zhou, J. (2023) ‘Jobs-housing relationships before and amid COVID-19: An excess-commuting approach’, Journal of Transport Geography, 106, p. 103507. Available at: https://doi.org/10.1016/j.jtrangeo.2022.103507.

  • Feng, L. et al. (2023) ‘Reconstruction of long-term high-resolution lake variability: Algorithm improvement and applications in China’, Remote Sensing of Environment, 297, p. 113775. Available at: https://doi.org/10.1016/j.rse.2023.113775.

  • Guo, M., Ni, M.Y., et al. (2023) ‘Automated simulation for household road traffic noise exposure: Application and field evaluation in a high-density city’, Computers, Environment and Urban Systems, 104, p. 102000. Available at: https://doi.org/10.1016/j.compenvurbsys.2023.102000.

  • Guo, M., Lin, Y., et al. (2023) ‘Characterizing environmental pollution with civil complaints and social media data: A case of the Greater Taipei Area’, Journal of Environmental Management, 348, p. 119310. Available at: https://doi.org/10.1016/j.jenvman.2023.119310.

  • Hao, T. et al. (2023) ‘Heat and park attendance: Evidence from “small data” and “big data” in Hong Kong’, Building and Environment, 234, p. 110123. Available at: https://doi.org/10.1016/j.buildenv.2023.110123.

  • He, S. and Qian, J. (2023) ‘Police and Politics in Aesthetics‐Based Urban Governance: Redevelopment and Grassroots Struggles in Enninglu, Guangzhou, China’, Antipode, 55(3), pp. 853–876. Available at: https://doi.org/10.1111/anti.12919.

  • He, W. et al. (2023) ‘Global urban fractional changes at a 1 km resolution throughout 2100 under eight scenarios of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs)’, Earth System Science Data, 15(8), pp. 3623–3639. Available at: https://doi.org/10.5194/essd-15-3623-2023.

  • Hu, J. et al. (2023) ‘Multi-city assessments of human exposure to extreme heat during heat waves in the United States’, Remote Sensing of Environment, 295, p. 113700. Available at: https://doi.org/10.1016/j.rse.2023.113700.

  • Huang, G. et al. (2023) ‘To share or not to share? Revealing determinants of individuals’ willingness to share rides through a big data approach’, Transportation Research Part C: Emerging Technologies, 157, p. 104372. Available at: https://doi.org/10.1016/j.trc.2023.104372.

  • Huang, G., Liang, Y. and Zhao, Z. (2023) ‘Understanding market competition between transportation network companies using big data’, Transportation Research Part A: Policy and Practice, 178, p. 103861. Available at: https://doi.org/10.1016/j.tra.2023.103861.

  • Kirkley, A. et al. (2023) ‘Compressing network populations with modal networks reveal structural diversity’, Communications Physics, 6(1), p. 148. Available at: https://doi.org/10.1038/s42005-023-01270-5.

  • Lai, K.Y. et al. (2023) ‘Associations of Urban Built Environment with Cardiovascular Risks and Mortality: a Systematic Review’, Journal of Urban Health, 100(4), pp. 745–787. Available at: https://doi.org/10.1007/s11524-023-00764-5.

  • Li, C. and He, S. (2023) ‘“Carrot and stick” approach to housing demolition and relocation under flexible authoritarianism in urban China’, Humanities and Social Sciences Communications, 10(1), p. 296. Available at: https://doi.org/10.1057/s41599-023-01807-7.

  • Li, C., Zhu, J. and He, S. (2023) ‘Panacea or Pandora’s Box? An institutional analysis of the contested long-term rental apartments development in China’, Habitat International, 131. Available at: https://doi.org/10.1016/j.habitatint.2022.102715.

  • Liang, Y. et al. (2023) ‘Deep trip generation with graph neural networks for bike sharing system expansion’, Transportation Research Part C: Emerging Technologies, 154, p. 104241. Available at: https://doi.org/10.1016/j.trc.2023.104241.

  • Lun, P. et al. (2023) ‘COVID-19 Vaccination Willingness and Reasons for Vaccine Refusal’, JAMA Network Open, 6(10), p. e2337909. Available at: https://doi.org/10.1001/jamanetworkopen.2023.37909.

  • Luo, W., Zhou, Y., et al. (2023) ‘Cross-regional analysis of the association between human mobility and COVID-19 infection in Southeast Asia during the transitional period of “living with COVID-19”’, Health & Place, 81, p. 103000. Available at: https://doi.org/10.1016/j.healthplace.2023.103000.

  • Luo, W., Liu, Q., et al. (2023) ‘Spatiotemporal variations of “triple-demic” outbreaks of respiratory infections in the United States in the post-COVID-19 era’, BMC Public Health, 23(1), p. 2452. Available at: https://doi.org/10.1186/s12889-023-17406-9.

  • Peixoto, T.P. and Kirkley, A. (2023) ‘Implicit models, latent compression, intrinsic biases, and cheap lunches in community detection’, Physical Review E, 108(2), p. 024309. Available at: https://doi.org/10.1103/PhysRevE.108.024309.

  • Poudyal, B., Ghoshal, G. and Kirkley, A. (2023) ‘Characterizing network circuity among heterogeneous urban amenities’, Journal of The Royal Society Interface, 20(208), p. 20230296. Available at: https://doi.org/10.1098/rsif.2023.0296.

  • Shan, L. and He, S. (2023) ‘Intensified discrimination against tenants and its health effects during the COVID-19 pandemic in large Chinese cities’, Scientific Reports, 13(1), p. 22316. Available at: https://doi.org/10.1038/s41598-023-48935-3.

  • Shan, L., He, S. and Wan, C. (2023) ‘Unraveling the dynamic Airbnb-gentrification interrelation before and after the COVID-19 Pandemic: Evidence from Beijing, China’, Cities, 137, p. 104270. Available at: https://doi.org/10.1016/j.cities.2023.104270.

  • Shi, J. et al. (2023) ‘Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study’, Environmental Pollution, 338, p. 122641. Available at: https://doi.org/10.1016/j.envpol.2023.122641.

  • Stenseth, N.Chr. et al. (2023) ‘How to avoid a local epidemic becoming a global pandemic’, Proceedings of the National Academy of Sciences, 120(10), p. e2220080120. Available at: https://doi.org/10.1073/pnas.2220080120.

  • Tu, Y., Wu, S., et al. (2023) ‘A 30 m annual cropland dataset of China from 1986 to 2021’. ESSD – Land/Land Cover and Land Use. Available at: https://doi.org/10.5194/essd-2023-190.

  • Tu, Y., Chen, B., Yang, J., et al. (2023) ‘Olympic effects on reshaping urban greenspace of host cities’, Landscape and Urban Planning, 230, p. 104615. Available at: https://doi.org/10.1016/j.landurbplan.2022.104615.

  • Tu, Y., Chen, B., Yu, L., et al. (2023) ‘Raveling the nexus between urban expansion and cropland loss in China’, Landscape Ecology, 38(7), pp. 1869–1884. Available at: https://doi.org/10.1007/s10980-023-01653-7.

  • Wei, H. et al. (2023) ‘Impact of early heat anomalies on urban tree cooling efficiency: Evidence from spring heatwave events in India’, International Journal of Applied Earth Observation and Geoinformation, 120, p. 103334. Available at: https://doi.org/10.1016/j.jag.2023.103334.

  • Wu, S., Chen, B., et al. (2023) ‘Improved human greenspace exposure equality during 21st century urbanization’, Nature Communications, 14(1), p. 6460. Available at: https://doi.org/10.1038/s41467-023-41620-z.

  • Wu, S., Yu, W., et al. (2023) ‘Remote sensing of urban greenspace exposure and equality: Scaling effects from greenspace and population mapping’, Urban Forestry & Urban Greening, 90, p. 128136. Available at: https://doi.org/10.1016/j.ufug.2023.128136.

  • Wu, S., Yu, W. and Chen, B. (2023) ‘Observed inequality in thermal comfort exposure and its multifaceted associations with greenspace in United States cities’, Landscape and Urban Planning, 233, p. 104701. Available at: https://doi.org/10.1016/j.landurbplan.2023.104701.

  • Xu, G. et al. (2023) ‘Settlement scaling law reveals population-land tensions in 7000+ African urban agglomerations’, Habitat International, 142, p. 102954. Available at: https://doi.org/10.1016/j.habitatint.2023.102954.

  • Xu, W. et al. (2023) ‘Racial disparities, environmental exposures, and SARS-CoV-2 infection rates: A racial map study in the USA’. Epidemiology. Available at: https://doi.org/10.1101/2023.04.17.23288622.

  • Yan, X. and He, S. (2023) ‘Healthcare in cumulatively caused migration: Hong Kong residents’ perceived Mainland healthcare quality and migration intentions in the Greater Bay Area, China’, Habitat International, 136. Available at: https://doi.org/10.1016/j.habitatint.2023.102828.

  • Yang, Y. and Jiang, B. (2023) ‘Green spaces in highly urbanized tracts tied to lower prevalence of chronic respiratory diseases: A nationwide study across levels of urbanicity’, Urban Forestry & Urban Greening, 90, p. 128149. Available at: https://doi.org/10.1016/j.ufug.2023.128149.

  • Zhang, R. et al. (2023) ‘Association of climatic variables with risk of transmission of influenza in Guangzhou, China, 2005–2021’, International Journal of Hygiene and Environmental Health, 252, p. 114217. Available at: https://doi.org/10.1016/j.ijheh.2023.114217.

  • Zhou, M., Zhou, Jiali, et al. (2023) ‘Introducing social contacts into the node-place model: A case study of Hong Kong’, Journal of Transport Geography, 107, p. 103532. Available at: https://doi.org/10.1016/j.jtrangeo.2023.103532.

  • Zhou, M., Ma, H., et al. (2023) ‘Metro travel and perceived COVID-19 infection risks: A case study of Hong Kong’, Cities, 137, p. 104307. Available at: https://doi.org/10.1016/j.cities.2023.104307.

  • Zhou, M. and Zhou, J. (2023) ‘Structural change and spatial pattern of intentional travel groups: A case study of metro riders in Hong Kong’, Applied Geography, 152, p. 102885. Available at: https://doi.org/10.1016/j.apgeog.2023.102885.

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2022

11 papers published in 2022 (after the establishment of USI in December 2022)

  • Chen, B. et al. (2022) ‘Contrasting inequality in human exposure to greenspace between cities of Global North and Global South’, Nature Communications, 13(1), p. 4636. Available at: https://doi.org/10.1038/s41467-022-32258-4.

  • Chen, B. and Webster, C. (2022) ‘Eight Reflections on Quantitative Studies of Urban Green Space: A Mapping-Monitoring-Modeling-Management (4M) Perspective’, Landscape Architecture Frontiers, 10(3), p. 66. Available at: https://doi.org/10.15302/J-LAF-1-030035.

  • He, S. and Zhang, Y. (2022) ‘Reconceptualising the rural through planetary thinking: A field experiment of sustainable approaches to rural revitalisation in China’, Journal of Rural Studies, 96, pp. 42–52. Available at: https://doi.org/10.1016/j.jrurstud.2022.10.008.

  • Huang, J., Jones, P. and He, X. (2022) ‘Masks, ventilation and exposure time: A web-based calculator of indoor COVID-19 infection risk’, Frontiers in Built Environment, 8, p. 986923. Available at: https://doi.org/10.3389/fbuil.2022.986923.

  • Jiang, B. et al. (2022) ‘Green spaces, especially nearby forest, may reduce the SARS-CoV-2 infection rate: A nationwide study in the United States’, Landscape and Urban Planning, 228, p. 104583. Available at: https://doi.org/10.1016/j.landurbplan.2022.104583.

  • Kirkley, A. (2022) ‘Spatial regionalization based on optimal information compression’, Communications Physics, 5(1), p. 249. Available at: https://doi.org/10.1038/s42005-022-01029-4.

  • Lin, X. et al. (2022) ‘Estimating 10-m land surface albedo from Sentinel-2 satellite observations using a direct estimation approach with Google Earth Engine’, ISPRS Journal of Photogrammetry and Remote Sensing, 194, pp. 1–20. Available at: https://doi.org/10.1016/j.isprsjprs.2022.09.016.

  • Mimar, S. et al. (2022) ‘Connecting intercity mobility with urban welfare’, PNAS Nexus. Edited by T. Jaworski, 1(4), p. pgac178. Available at: https://doi.org/10.1093/pnasnexus/pgac178.

  • Pi, X. et al. (2022) ‘Mapping global lake dynamics reveals the emerging roles of small lakes’, Nature Communications, 13(1), p. 5777. Available at: https://doi.org/10.1038/s41467-022-33239-3.

  • Wang, X. et al. (2022) ‘Grid-Based Essential Urban Land Use Classification: A Data and Model Driven Mapping Framework in Xiamen City’, Remote Sensing, 14(23), p. 6143. Available at: https://doi.org/10.3390/rs14236143.

  • Zhou, Y. et al. (2022) ‘Satellite mapping of urban built-up heights reveals extreme infrastructure gaps and inequalities in the Global South’, Proceedings of the National Academy of Sciences, 119(46), p. e2214813119. Available at: https://doi.org/10.1073/pnas.2214813119.

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