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Featured Peer-reviewed Research Articles

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2024

[33] Kim, J*, Kim, D., David-John, B. (2024). The role of privacy concerns, perceived benefits, and trust in citizens' acceptance of street-view image collection by local planning agencies. Cities. https://doi.org/10.1016/j.cities.2024.105339

[32] Kim, J. Lee, J., Thornhill T. [...] Gonsalves, G. (2024). Accessibility of Opioid Treatment Programs Based on Conventional vs Perceived Travel Time Measures. JAMA Network Open. https://doi.org/10.1001/jamanetworkopen.2024.0209 

[31] Kim, J.*, Park, J., Lee., J., & Jang. K. (2024). Examining the socio-spatial patterns of bus shelters with deep learning analysis of street-view images: A case study of 20 cities in the U.S. Cities. https://doi.org/10.1016/j.cities.2024.104852 

[30] Kim, J.*, Lee, J., Jang, K., & Lourentzou, I. (2024). Exploring the limitations in how ChatGPT introduces environmental justice issues in the United States: A case study of 3,108 counties. Telematics and Informatics. 102085. https://doi.org/10.1016/j.tele.2023.102085

[29] Kim, J.*, Rapuri, S., Wang, K., Guan, W., & Laituri, M. (2024). A scoping review of COVID-19 research adopting quantitative geographical methods in geography, urban studies, and planning: a text mining approach. Annals of GIS. https://doi.org/10.1080/19475683.2024.2304205 (Undergraduate Students: Rapuri; Wang)

[28] Atkins, C., Girgente, G., Shirzaei, M., & Kim, J.* (2024). Generative AI tools can enhance climate literacy but must be checked for biases and inaccuracies. Communications Earth & Environment. https://doi.org/10.1038/s43247-024-01392-w (Graduate student: Atkins; Undergraduate Student: Girgente)

[27] Gyanwali, S., Karki, S., Jang, K., Crawford, T., Zhang, M., & Kim, J.* (2024). Implications for spatial non-stationarity and the neighborhood effect averaging problem (NEAP) in green inequality research: evidence from three states in the USA. Journal of Geographical Systems. https://doi.org/10.1007/s10109-024-00448-x (Graduate student: Gyanwali; Karki)

[26] Jang, K., Chen, J., Kang, Y., Kim, J., Lee, J., Duare, F., & Ratti, C. Place identity: a generative AI’s perspective. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-024-03645-7

[25] Ahmed, N., Lee, J., Liu, L., Kim, J., Jang, K., & Wang, J. (2024). The cost of climate change: A generalized cost function approach for incorporating extreme weather exposure into public transit accessibility. Computers Environment and Urban Systems. https://doi.org/10.1016/j.compenvurbsys.2024.102145

2023

[24] Kim, J. & Jang, K. (2023). An examination of the spatial coverage and temporal variability of Google Street View (GSV) images in small- and medium-sized cities: A people-based approach. Computers, Environment and Urban Systems. 102. https://doi.org/10.1016/j.compenvurbsys.2023.101956

[23] Kim, J.* & Lee, J. (2023). How does ChatGPT introduce transport problems and solutions in North America? Findings, March. https://doi.org/10.32866/001c.72634

[22] Kim, J. & Lee, B. (2023). Campus commute mode choice in a college town: An application of the integrated choice and latent variable (ICLV) model. Travel Behaviour and Society, 30. https://doi.org/10.1016/j.tbs.2022.10.002  

[21] Kim, J.*, Rapuri, S., Chuluunbaatar, E., Sumiyasuren, E., Lkhagvasuren, B., Budhathoki, N., & Laituri, M. (2023). Developing and examining the transit-based accessibility to hospitals of Ulaanbaatar, Mongolia, Habitat International, 131. https://doi.org/10.1016/j.habitatint.2022.102729 

[20] Lee, J., & Kim, J. (2023). Social equity analysis of public transit accessibility to healthcare might be erroneous when travel time uncertainty impacts are overlooked, Travel Behaviour and Society, 32. https://doi.org/10.1016/j.tbs.2023.100588  

[19] Javanmard, R., Lee, J., Kim, J., Lu, L., & Diab, E. (2023). The impacts of the modifiable spatial unit problem (MSUP) on social equity analysis of public transit reliability. Journal of Transport Geography, 106, 103500.  https://doi.org/10.1016/j.jtrangeo.2022.103500 

[18] Jin, C., Park, S., Ha, H. J., Lee, J., Kim, J., Hutchenreuther, J., & Nara, A. (2023). Predicting households’ residential mobility trajectories with geographically localized interpretable model-agnostic explanation (GLIME). International Journal of Geographical Information Science, 1-23. https://doi.org/10.1080/13658816.2023.2264921 

[17] Xu, T., Wang, S., Liu, Q., Kim, J., Zhang, J., Ren, Y., ... & Wu, J. (2023). Vegetation color exposure differences at the community and individual levels: An explanatory framework based on the neighborhood effect averaging problem. Urban Forestry & Urban Greening, 86, 128001. https://doi.org/10.1016/j.ufug.2023.128001

2022

[16] Kim, J.*, Hagen, E., Muindi, Z., Mbonglou, G., & Laituri, M. (2022). An examination of water, sanitation, and hygiene (WASH) accessibility and opportunity in urban informal settlements during the COVID-19 pandemic: Evidence from Nairobi, Kenya. Science of the Total Environment, 823, 153398. https://doi.org/10.1016/j.scitotenv.2022.153398 

[15] Wang, J., Kim, J., & Kwan, M-P. (2022). An exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data. Cartography and Geographic Information Science, 49(5), 385-406. https://doi.org/10.1080/15230406.2022.2056510 

[14] Kim, Y., Kim, J., Ha, H., Nakajima, N, & Lee, J. (2022). Job accessibility as a lens for understanding the urban structure of colonial cities: A digital humanities study of the colonial Seoul in the 1930s using GIS. ISPRS International Journal of Geo-Information, 11(12), 614, 1-16. https://doi.org/10.3390/ijgi11120614 

[13] Singh, S., Javanmard, R., Lee, J., Kim, J., & Diab, E. (2022). Evaluating the accessibility benefits of the new BRT system during the COVID-19 pandemic in Winnipeg, Canada. Journal of Urban Mobility, 2, 100016. https://doi.org/10.1016/j.urbmob.2022.100016 

[12] Ha, H. J., Lee, J., Kim, J., & Kim, Y. (2022). Uncovering Inequalities in Food Accessibility between Koreans and Japanese in 1930s Colonial Seoul Using GIS and Open-Source Transport Analytics Tools. Sustainability, 14(19), 11852. https://doi.org/10.3390/su141911852 

[11] Laituri, M., Richardson, R., Kim, J., Cline, L., Viscuso, S., & Schwartz, L. Examining second-order impacts of COVID-19 in urban areas. (2022). Annals of GIS, 28(4), 479-490. https://doi.org/10.1080/19475683.2021.1954087   

2021

[10] Kim, J., & Kwan, M.-P. (2021). How neighborhood effect averaging might affect assessment of individual exposures to air pollution: A study of ozone exposures in Los Angeles. Annals of the American Association of Geographers, 111(1), 121-140. https://doi.org/10.1080/24694452.2020.1756208

[9] Kim, J., & Kwan, M-P. (2021). Assessment of sociodemographic disparities in environmental exposure might be erroneous due to neighborhood effect averaging: Implications for environmental inequality research. Environmental Research, 195, 110519. https://doi.org/10.1016/j.envres.2020.110519

[8] Kim, J., & Kwan, M-P. (2021). The impact of the COVID-19 pandemic on people’s mobility: A longitudinal study of the U.S. from March to September of 2020, Journal of Transport Geography, 93, 103039. https://doi.org/10.1016/j.jtrangeo.2021.103039

[7] Kim, J., Kwan, M.-P., Levenstein, M. C., & Richardson, D. B. (2021). How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection. Cartography and Geographic Information Science, 48(1), 2-20. https://doi.org/10.1080/15230406.2020.1794976

[6] Kim, J., & Kwan, M-P. (2021). An examination of people’s privacy concerns, perceptions of social benefits, and acceptance for COVID-19 mitigation measures that harness location information: A comparative study of the U.S. and South Korea. ISPRS International Journal of Geo-Information, 10(1), 25, 1-23. https://doi.org/10.3390/ijgi10010025

[5] Kim, J., & Kwan, M-P. (2021). Travel time errors caused by geomasking might be different between transportation modes and types of urban area. Transactions in GIS, 25(4), 1910-26. https://doi.org/10.1111/tgis.12751  

[4] Kim, Y., Lee, J., Kim, J., & Nakajima, N. The disparity in transit travel time between Koreans and Japanese in 1930s Colonial Seoul. (2021). Findings, July. https://doi.org/10.32866/001c.25226

[3] Huang, J., Kwan, M.-P., & Kim, J. (2021). How culture and sociopolitical tensions might influence people’s acceptance of COVID-19 control measures that use individual-level georeferenced data. ISPRS International Journal of Geo-Information, 10(7), 490, 1-19. https://doi.org/10.3390/ijgi10070490

2019

[2] Kim, J., & Lee, B. (2019). More than travel time: New job accessibility index capturing the connectivity of transit services. Journal of Transport Geography, 78, 8-18. https://doi.org/10.1016/j.jtrangeo.2019.05.008

[1] Kim, J., & Kwan, M.-P. (2019). Beyond commuting: Ignoring individuals’ activity-travel patterns may lead to inaccurate assessments of their exposure to traffic congestion. International Journal of Environmental Research and Public Health, 16(1), 1-20. https://doi.org/10.3390/ijerph16010089

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