dr. M. Wang (Mingshu)

Interests

GIScience
Geodata Science
Urban Informatics
City and Regional Development

My research focuses on developing and applying methods of GIScience (i.e., geographical information systems, remote sensing, and spatial analysis) and big data analytics (e.g., machine learning, artificial intelligence, and econometrics) to understand urban systems. I have two interconnected research lines of cities from the perspective of people. At a macro-scale, I quantify urban structure and city performance via GIScience methods. At a micro-scale, I explore human mobility issues with crowdsourced geospatial data using machine learning and artificial intelligence methods.

Borsci, S. , Lehtola, V. V. , Nex, F. C. , Yang, M. Y. , Augustijn, P. W. M. , Bagheriye, L. , Brune, C., Kounadi, O. , Li, J. J. , Rebelo Moreira, J. L. , van der Nagel, J. E. L. , Veldkamp, B. P. , Le, D. V. , Wang, M. , Wijnhoven, F. , Wolterink, J. M. , & Zurita-Milla, R. (2022). Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle. AI & society. https://doi.org/10.1007/s00146-021-01383-x, https://doi.org/10.1007/s00146-021-01383-x

Wu, J., Lu, Y., Gao, H. , & Wang, M. (2022). Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning. Computers, environment and urban systems, 91, 1-12. [101716]. https://doi.org/10.1016/j.compenvurbsys.2021.101716

Wang, S. , Wang, M., & Liu, Y. (2021). Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches. Computers, environment and urban systems, 90, 1-13. [101713]. https://doi.org/10.1016/j.compenvurbsys.2021.101713

Wang, M., & Debbage, N. (2021). Urban morphology and traffic congestion: Longitudinal evidence from US cities. Computers, environment and urban systems, 89, 1-11. [101676]. https://doi.org/10.1016/j.compenvurbsys.2021.101676

Wu, C., Smith, D. , & Wang, M. (2021). Simulating the urban spatial structure with spatial interaction: A case study of urban polycentricity under different scenarios. Computers, environment and urban systems, 89, 1-13. [101677]. https://doi.org/10.1016/j.compenvurbsys.2021.101677

Li, B., Peng, Y., He, H. , Wang, M., & Feng, T. (2021). Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou. Sustainable Cities and Society, 66, 1-10. [102685]. https://doi.org/10.1016/j.scs.2020.102685

Derudder, B., Liu, X. , Wang, M., Zhang, W., Wu, K., & Caset, F. (2021). Measuring polycentric urban development: The importance of accurately determining the ‘balance’ between ‘centers’. Cities, 111, [103009]. https://doi.org/10.1016/j.cities.2020.103009

Wang, M. (2021). Polycentric urban development and urban amenities: Evidence from Chinese cities. Environment and Planning B: Urban Analytics and City Science, 48(3), 400-416. https://doi.org/10.1177/2399808320951205

Wang, M., & Vermeulen, F. (2020). Life between buildings from a street view image: What do big data analytics reveal about neighbourhood organisational vitality? Urban studies, 1-22. [004209802095719]. https://doi.org/10.1177/0042098020957198

Yuan, Y. , Wang, M., Zhu, Y., Huang, X., & Xiong, X. (2020). Urbanization's effects on the urban-rural income gap in China: A meta-regression analysis. Land use policy, 99, 1-9. [104995]. https://doi.org/10.1016/j.landusepol.2020.104995

Wei, X. , Wang, M. , & Kraak, M. J. (2020). Where we are in fighting against COVID-19. Environment and Planning A, 52(8), 1483-1486. https://doi.org/10.1177/0308518X20931515

Liu, X. , Wang, M., Qiang, W., Wu, K., & Wang, X. (2020). Urban form, shrinking cities, and residential carbon emissions: Evidence from Chinese city-regions. Applied energy, 261, 1-12. [114409]. https://doi.org/10.1016/j.apenergy.2019.114409

Wang, M., Chen, Z., Mu, L., & Zhang, X. (2020). Road network structure and ride-sharing accessibility: A network science perspective. Computers, environment and urban systems, 80(March), 1-9. [101430]. https://doi.org/10.1016/j.compenvurbsys.2019.101430

Bernardes, S., Madden, M., Astuti, I., Chuvieco, E., Cotten, D., Dennison, P. E., Dronova, Y., Gitas, I., Gong, P., Franch-Gras, B., Hancher, M., Hirano, A., Howard, A., Hu, X., Huete, A., Jordan, T., Justice, C., Lawrence, R. L., Lu, L., ... Zhang, Z. (2019). Image Processing and Analysis Methods. In Manual of Remote Sensing, 4th Edition (4 ed., pp. 631-868). American Society of Photogrammetry and Remote Sensing (ASPRS),. https://doi.org/10.14358/MRS/Chapter7

Zhou, X. , Wang, M., & Li, D. (2019). Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning. Journal of transport geography, 79, [102479]. https://doi.org/10.1016/j.jtrangeo.2019.102479

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Bachelor

Technology and Liberal Arts & Science (University College)

Master

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

201800301 - Integrated Geospatial Workflows

To date, as the PI and Co-PI, my research has been financially supported by the World Bank, Dutch Research Council (NWO), National Natural Science Foundation of China, Chinese Academy of Sciences, Microsoft Azure for Research, and Province of Overijssel (NL).