2024
How does extreme point sampling affect non-extreme simulation in geographical random forest? (Journal article)
Wang, H., Chen, M., Wang, Z., Huang, L., Caudill, C. C., Qu, S., & Que, X. (2024). How does extreme point sampling affect non-extreme simulation in geographical random forest?. Earth Science Informatics, 17(3), 1983-1991. doi:10.1007/s12145-024-01268-9DOI: 10.1007/s12145-024-01268-9
Huang, X., Wang, S., Yang, D., Hu, T., Chen, M., Zhang, M., . . . Hohl, A. (2024). Crowdsourcing Geospatial Data for Earth and Human Observations: A Review. Journal of Remote Sensing, 4. doi:10.34133/remotesensing.0105DOI: 10.34133/remotesensing.0105
Vivid London: Assessing the Resilience of Urban Vibrancy During the Covid-19 Pandemic Using Social Media Data (Preprint)
DOI: 10.2139/ssrn.4799144
2023
Chen, M., Singleton, A., & Robinson, C. (2023). Exploring Energy Deprivation Across Small Areas in England and Wales. In Leibniz International Proceedings in Informatics, LIPIcs Vol. 277. doi:10.4230/LIPIcs.GIScience.2023.20DOI: 10.4230/LIPIcs.GIScience.2023.20
Liu, Y., Chen, M., Wang, M., Huang, J., Thomas, F., Rahimi, K., & Mamouei, M. (2023). An interpretable machine learning framework for measuring urban perceptions from panoramic street view images. ISCIENCE, 26(3). doi:10.1016/j.isci.2023.106132DOI: 10.1016/j.isci.2023.106132
2022
An image library: The potential of imagery in (quantitative) social sciences (Chapter)
An image library: The potential of imagery in (quantitative) social sciences (2022). In Handbook of Spatial Analysis in the Social Sciences (pp. 528-543). Edward Elgar Publishing. doi:10.4337/9781789903942.00042DOI: 10.4337/9781789903942.00042
Assessing the value of user-generated images of urban surroundings for house price estimation (Journal article)
Chen, M., Liu, Y., Arribas-Bel, D., & Singleton, A. (2022). Assessing the value of user-generated images of urban surroundings for house price estimation. Landscape and Urban Planning, 226, 104486. doi:10.1016/j.landurbplan.2022.104486DOI: 10.1016/j.landurbplan.2022.104486
2021
Chen, M. (2021, November 10). A New Picture of the City: Volunteered Geographic Image Information and the Cities. (University of Liverpool).
Chen, M., Chi, B., Van Dijk, J., & Longley, P. (n.d.). The use of Linked Consumer Registers to understand social and residential mobility. In 29th Annual GIS Research UK Conference (GISRUK). Cardiff, UK. doi:10.5281/zenodo.4665856DOI: 10.5281/zenodo.4665856
Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City (Journal article)
Liu, Y., Singleton, A., Arribas-bel, D., & Chen, M. (2021). Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 86. doi:10.1016/j.compenvurbsys.2020.101592DOI: 10.1016/j.compenvurbsys.2020.101592
2020
Chen, M., Arribas-Bel, D., & Singleton, A. (2020). Quantifying the Characteristics of the Local Urban Environment through Geotagged Flickr Photographs and Image Recognition. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 9(4). doi:10.3390/ijgi9040264DOI: 10.3390/ijgi9040264
Chen, M., Fahrner, D., Arribas-Bel, D., & Rowe, F. (n.d.). A reproducible notebook to acquire, process and analyse satellite imagery. REGION, 7(2), R15-R46. doi:10.18335/region.v7i2.295DOI: 10.18335/region.v7i2.295
2019
Chen, M., Arribas-Bel, D., & Singleton, A. (2019). Understanding the dynamics of urban areas of interest through volunteered geographic information. JOURNAL OF GEOGRAPHICAL SYSTEMS, 21(1), 89-109. doi:10.1007/s10109-018-0284-3DOI: 10.1007/s10109-018-0284-3
