*See Google Scholar for a list of all publications. **HuMNet members are colored by green.
Mobility
Unraveling near real-time spatial dynamics of population using geographical ensemble learning. Song, Y., Wu, S., Chen, B., & Bell, M. L. (2024). International Journal of Applied Earth Observation and Geoinformation, 130, 103882. [DOI] [PDF]
Dynamic population mapping with AutoGluon. Song, Y., Xu, Y., Chen, B., He, Q., Tu, Y., Wang, F., & Cai, C. (2022). Urban Informatics, 1(1), 13. [DOI] [PDF]
Population mapping in China with Tencent social user and remote sensing data. Xu, Y., Song, Y., Cai, J., & Zhu, H. (2021). Applied Geography, 130, 102450. [DOI] [PDF]
An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Tian, H., Liu, Y., Li, Y., Wu, C., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., Wang, B., Yang, P., Cui, Y., Song, Y., Zheng, P., Wang, Q., Bjornstad, O. N., Yang, R., Grenfell, B. T., Pybus, O. G., & Dye, C. (2020). Science, 368(6491), 638–642. [DOI] [PDF]
Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2). Li, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., & Shaman, J. (2020). Science, 368(6490), 489–493. [DOI] [PDF]
Evaluating and characterizing urban vibrancy using spatial big data: Shanghai as a case study. Huang, B., Zhou, Y., Li, Z., Song, Y., Cai, J., & Tu, W. (2019). Environment and Planning B: Urban Analytics and City Science, 47(9), 1543–1559. [DOI] [PDF]
Environments
Shade watch: Mapping citywide shade dynamics through ray tracing and LiDAR data in Hong Kong’s complex 3-D built environment. Wu, S., Chen, B., Song, Y., An, J., Lin, C., & Gong, P. (2025). Sustainable Cities and Society, 118, 106011. [DOI] [PDF]
Spatiotemporally continuous estimates of daily 1-km PM2.5 concentrations and their long-term exposure in China from 2000 to 2020. He, Q., Ye, T., Wang, W., Luo, M., Song, Y., & Zhang, M. (2023). Journal of Environmental Management, 342, 118145. [DOI] [PDF]
Unraveling the nexus between urban expansion and cropland loss in China. Tu, Y., Chen, B., Yu, L., Song, Y., Wu, S., Li, M., Wei, H., Chen, T., Lang, W., Gong, P., & Xu, B. (2023). Landscape Ecology, 38(7), 1869–1884. [DOI] [PDF]
Understanding the long-term effects of public open space on older adults’ functional ability and mental health. Liu, Y., Guo, Y., Lu, S., Chan, O. F., Chui, C., Ho, H. C., Song, Y., Cheng, W., Chiu, R. L. H., Webster, C., & Lum, T. Y. (2023). Building and Environment, 234, 110126. [DOI] [PDF]
Neighborhood built environments and cognition in later life. Chan, O. F., Liu, Y., Guo, Y., Lu, S., Chui, H. K., Ho, H. C., Song, Y., Cheng, W., Chiu, L. H., & Webster, C. (2022). Ageing & Mental Health, 27(3), 466–474. [DOI] [PDF]
Spatiotemporal high-resolution imputation modeling of aerosol optical depth for investigating its full-coverage variation in China from 2003 to 2020. He, Q., Wang, W., Song, Y., Zhang, M., & Huang, B. (2023). Atmospheric Research, 281, 106481. [DOI] [PDF]
Spatial uncertainty and environment-health association: An empirical study of osteoporosis among “old residents” in public housing estates across a hilly environment. Ho, H. C., Cheng, W., Song, Y., Liu, Y., Guo, Y., Lu, S., Lum, T. Y., Chiu, R., & Webster, C. (2022). Social Science & Medicine, 306, 115155. [DOI] [PDF]
Urban greenery mitigates the negative effect of urban density on older adults’ life satisfaction: Evidence from Shanghai, China. He, D., Miao, J., Lu, Y., Song, Y., Chen, L., & Liu, Y. (2022). Cities, 124, 103607. [DOI] [PDF]
Identifying subcenters with a nonparametric method and ubiquitous point-of-interest data: A case study of 284 Chinese cities. Long, Y., Song, Y., & Chen, L. (2022). Environment and Planning B: Urban Analytics and City Science, 49(1), 58–75. [DOI] [PDF]
Neighborhood built environment and late-life depression: A multilevel path analysis in a Chinese society. Lu, S., Liu, Y., Guo, Y., Ho, H. C., Song, Y., Cheng, W., Chui, C., Chan, O., Chiu, R. L. H., Webster, C., & Lum, T. Y. (2021). The Journals of Gerontology: Series B, 76(10), 2143–2154. [DOI] [PDF]
Satellite-derived 1-km estimates and long-term trends of PM2.5 concentrations in China from 2000 to 2018. He, Q., Gao, K., Zhang, L., Song, Y., & Zhang, M. (2021). Environment International, 156, 106726. [DOI] [PDF]
Mapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America. Chen, B., Tu, Y., Song, Y., Theobald, D., Zhang, T., Ren, Z., Li, X., Yang, J., Wang, J., Wang, X., Gong, P., Bai, Y., & Xu, B. (2021). ISPRS Journal of Photogrammetry and Remote Sensing, 178, 203–218. [DOI] [PDF]
Longitudinal associations between neighbourhood physical environments and depressive symptoms of older adults in Hong Kong: The moderating effects of terrain slope and declining functional abilities. Liu, Y., Lu, S., Guo, Y., Ho, H. C., Song, Y., Cheng, W., Hiu, C., Chui, K., Chan, O., Chiu, R. L. H., Webster, C., & Lum, T. Y. (2021). Health & Place, 70, 102585. [DOI] [PDF]
Neighbourhood physical environment, intrinsic capacity, and 4-year late-life functional ability trajectories of low-income Chinese older population: A longitudinal study with the parallel process of latent growth curve modelling. Lu, S., Liu, Y., Guo, Y., Ho, H. C., Song, Y., Cheng, W., Chui, C., Chan, O. F., Webster, C., Lai, R., Chiu, H., & Lum, T. Y. (2021). eClinicalMedicine, 36, 100927. [DOI] [PDF]
A novel method to extract urban human settlements by integrating remote sensing and mobile phone locations. Chen, B., Song, Y., Huang, B., & Xu, B. (2020). Science of Remote Sensing, 1, 100003. [DOI] [PDF]
Improved 1 km resolution PM2.5 estimates across China using enhanced space-time extremely randomized trees. Wei, J., Li, Z., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustina, A., Liu, L., Wu, H., & Song, Y. (2020). Atmospheric Chemistry and Physics, 20(6), 3273–3289. [DOI] [PDF]
Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018. Gong, P., Chen, B., Li, X., Liu, H., Song, Y., & Xu, B. (2020). Science Bulletin, 65(3), 182–187. [DOI] [PDF]
Natural outdoor environment, neighbourhood social cohesion and mental health: Using multilevel structural equation modelling, streetscape and remote-sensing metrics. Liu, Y., Wang, R., Lu, Y., Li, Z., Chen, H., Cao, M., Zhang, Y., & Song, Y. (2020). Urban Forestry & Urban Greening, 48, 126576. [DOI] [PDF]
Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery. Huang, B., Zhao, B., & Song, Y. (2018). Remote Sensing of Environment, 214, 73–86. [DOI] [PDF]
Using multi-source geospatial big data to identify the structure of polycentric cities. Cai, J., Huang, B., & Song, Y. (2017). Remote Sensing of Environment, 202, 210–221. [DOI] [PDF]
Exposure
Association between fine particulate matter (PM2.5) and severity of acute respiratory infections among young US children in the major cities in the United States: a claims-based cohort study.
Foo, D., Regan, A. K., Heo, S., Schneider, E. B., Canner, J., Song, Y., & Bell, M. L. (2025, October).
In Open Forum Infectious Diseases, Vol. 12, No. 10, p. ofaf442. [DOI] [PDF]
Delineating urbanicity and rurality: impact on environmental exposure assessment.
Song, Y., Deziel, N. C., & Bell, M. L. (2024). Environmental Science & Technology, 58(43), 19178–19188. [DOI] [PDF]
A systematic review of animal feeding operations including concentrated animal feeding operations (CAFOs) for exposure, health outcomes, and environmental justice.
Son, J. Y., Heo, S., Byun, G., Foo, D., Song, Y., Lewis, B. M., & Bell, M. L. (2024). Environmental Research, 259, 119550. [DOI] [PDF]
Wildfire smoke exposure during pregnancy and adverse perinatal, obstetric, and early childhood health outcomes: a systematic review and meta-analysis.
Foo, D., Heo, S., Dhamrait, G., Stewart, R., Choi, H. M., Song, Y., & Bell, M. L. (2023). Environmental Research, 226, 115318. [DOI] [PDF]
Beyond green environments: multi-scale difference in human exposure to greenspace in China.
Chen, B., Tu, Y., Wu, S., Song, Y., Jin, Y., Webster, C., Xu, B., & Gong, P. (2022). Environment International, 166, 107348. [DOI] [PDF]
Associations between metabolic syndrome and anthropogenic heat emissions in northeastern China.
Cong, J., Wang, L. B., Liu, F. J., Qian, Z., McMillin, S. E., Vaughn, M. G., Song, Y., Wang, S., Chen, S., Xiong, S., Shen, X., Sun, X., Zhou, Y., Ho, H. C., & Dong, G. H. (2022). Environmental Research, 204, 111974. [DOI] [PDF]
Early-life exposure to submicron particulate air pollution in relation to asthma development in Chinese preschool children.
Zhang, Y., Wei, J., Shi, Y., Quan, C., Ho, H. C., Song, Y., & Zhang, L. (2021). Journal of Allergy and Clinical Immunology, 148(3), 771–782. [DOI] [PDF]
Perceived influence of street-level visible greenness exposure in the work and residential environment on life satisfaction: Evidence from Beijing, China.
Wu, W., Yao, Y., Song, Y., He, D., & Wang, Y. (2021). Urban Forestry & Urban Greening, 62, 127161. [DOI] [PDF]
Spatiotemporal assessment of PM2.5 concentrations and exposure in China from 2013 to 2017 using satellite-derived data.
He, Q., Zhang, M., Song, Y., & Huang, B. (2021). Journal of Cleaner Production, 286, 124965. [DOI] [PDF]
How does urban expansion impact people’s exposure to green environments? A comparative study of 290 Chinese cities.
Song, Y., Chen, B., & Kwan, M. P. (2020). Journal of Cleaner Production, 246, 119018. [DOI] [PDF]
Dynamic assessment of PM2.5 exposure and health risk using remote sensing and geo-spatial big data.
Song, Y., Huang, B., He, Q., Chen, B., Wei, J., & Mahmood, R. (2019). Environmental Pollution, 253, 288–296. [DOI] [PDF]
Dynamic assessments of population exposure to urban greenspace using multi-source big data.
Song, Y., Huang, B., Cai, J., & Chen, B. (2018). Science of the Total Environment, 634, 1315–1325. [DOI] [PDF]
How do people in different places experience different levels of air pollution? Using worldwide Chinese as a lens.
Chen, B., Song, Y., Kwan, M. P., Huang, B., & Xu, B. (2018). Environmental Pollution, 238, 874–883. [DOI] [PDF]
Real-time estimation of population exposure to PM2.5 using mobile- and station-based big data.
Chen, B., Song, Y., Jiang, T., Chen, Z., Huang, B., & Xu, B. (2018). International Journal of Environmental Research and Public Health, 15(4), 573. [DOI] [PDF]
Inequity
Evaluating Algorithmic Approaches to Uncover Racial, Ethnic, and Gender Disparities in Scientific Authorship.
Song, Y., Dasgupta, N., & Bell, M. L. (2025).
American Journal of Public Health, (0), e1–e8. [DOI] [PDF]
Human Health Impacts of Energy Transitions across the United States among Sociodemographic Subpopulations for the Year 2050.
Stewart, R. K., Kim, H., Choi, H. M., Song, Y., Zhang, Y., Gillingham, K. T., & Bell, M. L. (2025).
Environmental Science & Technology. [DOI] [PDF]
Neighbourhood green space and loneliness in middle-aged and older adults: Evidence from WHO Study on Global Ageing and Adult Health in China.
Wang, R., Song, Y., Yang, L., & Browning, M. H. (2024).
Urban Forestry & Urban Greening, 95, 128324. [DOI] [PDF]
Racial/Ethnic Inequity in Transit-Based Spatial Accessibility to COVID-19 Vaccination Sites.
Liu, D., Kwan, M. P., Kan, Z., Song, Y., & Li, X. (2022).
Journal of Racial and Ethnic Health Disparities, 10, 1533–1541. [DOI] [PDF]
How do forms and characteristics of Asian public housing neighbourhoods affect dementia risk among senior population? A cross-sectional study in Hong Kong.
Ho, H. C., Song, Y., Cheng, W., Liu, Y., Guo, Y., Lu, S., Lum, T., Chiu, R. L. H., & Webster, C. (2023).
Public Health, 219, 44–52. [DOI] [PDF]
Contrasting inequality in human exposure to greenspace between cities of Global North and Global South.
Chen, B., Wu, S., Song, Y., Webster, C., Xu, B., & Gong, P. (2022).
Nature Communications, 13, 4636. [DOI] [PDF]
Inter- and intra-racial/ethnic disparities in walking accessibility to grocery stores.
Liu, D., Kwan, M. P., Kan, Z., Song, Y., & Li, X. (2022).
Area, 54(4), 627–637. [DOI] [PDF]
Analyzing income-based inequality in transit nodal accessibility.
Liu, D., Kwan, M. P., Huang, J., Kan, Z., Song, Y., & Li, X. (2022).
Travel Behaviour and Society, 27, 57–64. [DOI] [PDF]
Observed inequality in urban greenspace exposure in China.
Song, Y., Chen, B., Ho, C. H., Kwan, M. P., Liu, D., Wang, J., Cai, J., Li, X., Xu, Y., He, Q., Wang, H., Xu, Q., & Song, Y. (2021).
Environment International, 156, 106778. [DOI] [PDF]
Do socioeconomic factors modify the effects of PM1 and SO2 on lung cancer incidence in China?
Guo, H., Wei, J., Li, X., Ho, H. C., Song, Y., Wu, J., & Li, W. (2021).
Science of the Total Environment, 756, 143998. [DOI] [PDF]
An integrated analysis of housing and transit affordability in the Chicago metropolitan area.
Liu, D., Kwan, M. P., Kan, Z., & Song, Y. (2021).
The Geographical Journal, 187(2), 110–126. [DOI] [PDF]
Spatial and temporal variations of spatial population accessibility to public hospitals: A case study of rural-urban comparison.
Song, Y., Tan, Y., Song, Y., Wu, P., Cheng, J. C., Kim, M. J., & Wang, X. (2018).
GIScience & Remote Sensing, 55(5), 718–744. [DOI] [PDF]
Health
Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019. Ferrari, A. J., Santomauro, D. F., Aali, A., Song, Y., Vos, T., & Murray, C. J. L. (2025).Nature Communications, 2025, 16(1), 4235. [DOI] [PDF]
A scoping review on the impact of ambient temperature on human infertility. Heo, S., Byun, G., Choi, Y., Song, Y., Bravo, M., Ma, T., & Bell, M. L. (2025). Environmental Research, 123641. [DOI] [PDF]
Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Ferrari, A. J., Santomauro, D. F., Aali, A., Song, Y., Vos, T., & Murray, C. J. L. (2024). The Lancet, 403(10440), 2133–2161. [DOI] [PDF]
Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Naghavi, M., Ong, K. L., Aali, A., Song, Y., Wool, E. E., & Murray, C. J. L. (2024). The Lancet, 403(10440), 1989–2056. [DOI] [PDF]
Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Bhattacharjee, N. V., Schumacher, A. E., Aali, A., Abate, Y. H., Abbasgholizadeh, R., Abbasian, M., & Bahri, R. A. (2024). The Lancet, 403(10440), 2057–2099. [DOI] [PDF]
Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Schumacher, A. E., Kyu, H. H., Aali, A., Abbafati, C., Abbas, J., Abbasgholizadeh, R., & Amzat, J. (2024). The Lancet, 403(10440), 1989–2056. [DOI] [PDF]
Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Steinmetz, J. D., Seeher, K. M., Schiess, N., Song, Y., Ong, K. L., Feigin, V. L., Vos, T., & Dua, T. (2024). The Lancet Neurology, 23(4), 344–381. [DOI] [PDF]
The temporal trend of disease burden attributable to metabolic risk factors in China, 1990–2019: An analysis of the Global Burden of Disease study. Jin, Y., So, H., Cerin, E., Song, Y., Tam, L., & Wu, D. (2023). Frontiers in Nutrition, 9, 1035439. [DOI] [PDF]
Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Ikuta, K. S., Swetschinski, L. R., Aguilar, G. R., Song, Y., Murray, C. J. L., & Mohsen, N. (2022). The Lancet, 400(10369), 2221–2248. [DOI] [PDF]
Age–sex differences in the global burden of lower respiratory infections and risk factors, 1990–2019: results from the Global Burden of Disease Study 2019. Kyu, H. H., Vongpradith, A., Sirota, S. B., Song, Y., & Murray, C. J. L. (2022). The Lancet Infectious Diseases, 22(11), 1626–1647. [DOI] [PDF]
The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019. Tran, K. B., Lang, J. J., Compton, K., Song, Y., Force, L. M., & Murray, C. J. L. (2022). The Lancet, 400(10352), 563–591. [DOI] [PDF]
Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020. Bryazka, D., Reitsma, M. B., Griswold, M. G., Song, Y., & Gakidou, E. (2022). The Lancet, 400(10347), 185–235. [DOI] [PDF]
Ambient particulate matter (PM1, PM2.5, PM10) and childhood pneumonia: The smaller particle, the greater short-term impact? Wang, X., Xu, Z., Su, H., Ho, H. C., Song, Y., Zheng, H., Hossain, M. Z., Khan, M. F., Bogale, F., Wei, J., & Cheng, J. (2021). Science of the Total Environment, 772, 145509. [DOI] [PDF]
Intraday effects of ambient PM1 on emergency department visits in Guangzhou, China: a case-crossover study. Liu, L., Song, F., Fang, J., Wei, J., Ho, H. C., Song, Y., Zhang, Y., Wang, L., Hu, C., & Zhang, Y. (2021). Science of the Total Environment, 750, 142347. [DOI] [PDF]
Global COVID-19 pandemic demands joint interventions for the suppression of future waves. Li, R., Chen, B., Zhang, T., Ren, Z., Song, Y., Xiao, Y., Hou, L., Cai, J., Xu, B., Chan, K. K. Y., Tu, Y., Yang, J., Liu, Z., Shen, C., Wang, C., Xu, L., Liu, Q., Bao, S., Zhang, J., Bai, Y., Deng, K., Zhang, W., Huang, W., Whittington, J. D., Stenseth, N. C., Guan, D., Gong, P., & Xu, B. (2020). Proceedings of the National Academy of Sciences, 117(42), 26151–26157. [DOI] [PDF]
