Minxuan Lan
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Assistant Professor
Director of Spatial Social Science Research Lab, School of Exercise and Rehabilitation Sciences , Health and Human Services
Contact Info
Overview
overview
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Dr. Lan is a human geographer with backgrounds in GIS, spatial statistics, crime science, public health, and big data mining. He is particularly intrigued by the possibility of using interdisciplinary theories and methods to solve real-world problems. He believes that researchers shall actively adopt new data sources and new data-driven methods, while the research shall be guided and closely tied to established theories.
Dr. Lan is the director of the Spatial Social Science Research Lab at UToledo. His publications are mainly focusing on applications of spatial analysis on spatial-temporal crime patterns, advancements in criminology theories, and the substance abuse epidemic. His current research interests are:
- Spatial-temporal analysis and its applications to crime, public health, and human sustainability
- Data mining, natural language processing (NLP), and their applications on social media big data
- Substance abuse epidemic and drug problem
- Google Scholar: https://scholar.google.com/citations?user=I6XAgVEAAAAJ&hl
- ORCID: https://orcid.org/0000-0002-4528-9544
- ResearchGate: https://www.researchgate.net/profile/Minxuan_Lan
- Web of Science: https://www.webofscience.com/wos/author/record/1957117
Publications
selected publications
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Article (Faculty180)
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2023A Multiscale Assessment of the Impact of Perceived Safety from Street View Imagery on Street Crime. Annals of the American Association of Geographers. 0:1-22.
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2023Assessing Potable Water Access and Its Implications for Households’ Livelihoods: The Case of Sibi in the Nkwanta North District, Ghana. ISPRS International Journal of Geo-Information. 12.
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2023Understanding crime and place: A methods handbook. REGIONAL SCIENCE POLICY AND PRACTICE. 15:709-710.
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2022Agglomerative effects of crime attractors and generators on street robbery? An assessment by Luojia 1-01 satellite nightlight. Annals of the American Association of Geographers. 112:350.
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2022Are Crime and Collective Emotion Interrelated? A "Broken Emotion" Conjecture from Community Twitter Posts. Social Science Computer Review. 08944393221113210.
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2022Assessing the intraday variation of the spillover effect of tweets-derived ambient population on crime. Social Science Computer Review. 40:512.
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2022Different Ways Ambient and Immobile Population Distributions Influence Urban Crime Patterns. ISPRS International Journal of Geo-Information. 11:581.
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2022Interpretable machine learning models for crime prediction. Computers, Environment and Urban Systems. 94:101789.
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2022The impact of civil registration-based demographic heterogeneity on community thefts. Habitat International. 129:102673.
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2021Assessing Impacts of New Subway Stations on Urban Thefts in the Surrounding Areas. ISPRS International Journal of Geo-Information. 10:632.
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2021Burglaries and entry controls in gated communities. Urban Studies. 58:2920.
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2021Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records. Hydrology and Earth System Sciences. 25:1643.
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2021Using Google Street View imagery to capture micro built environment characteristics in drug places, compared with street robbery. Computers, Environment and Urban Systems. 88:101631.
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2020A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery. International Journal of Geographical Information Science. 34:1740.
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2020Assessing the effects of bus stop relocation on street robbery. Computers, Environment and Urban Systems. 80:101455.
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2020Crime prediction with historical crime and movement data of potential offenders using a spatio-temporal cokriging method. ISPRS International Journal of Geo-Information. 9:732.
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2020Linking Luojia 1-01 nightlight imagery to urban crime. Applied geography. 125:102267.
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2020The Effects of Police CCTV Camera on Crime Displacement and Diffusion of Benefits: A Case Study from Gusu District in Suzhou, China. Scientia Geographica Sinica. 40:1601-1609.
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2019
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2019Crime geographical displacement: Testing its potential contribution to crime prediction. ISPRS International Journal of Geo-Information. 8:383.
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2019
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2019How is the confidentiality of crime locations affected by parameters in kernel density estimation?. ISPRS International Journal of Geo-Information. 8:544.
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2019The spillover effect of geotagged tweets as a measure of ambient population for theft crime. Sustainability. 11:6748.
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Other Scholarly Work (Faculty180)
Contact
full name
- Minxuan Lan
visualizations
Cumulative publications in Scholars@UToledo