About Me
Interests
- GIScience
- Geodata Science
- Urban Informatics
- City and Regional Development
Research
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.
Publications
Recent
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
UT Research Information System
Google Scholar Link
Affiliated Study Programmes
Bachelor
Master
Courses Academic Year 2021/2022
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.
Courses Academic Year 2020/2021
Projects
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).
Current Projects
Tweets
Contact Details
Visiting Address
University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands
Mailing Address
University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands