Ganmin Yin

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Ganmin Yin

Ph.D. Candidate,
Institute of Remote Sensing & GIS,
Peking University,
No. 5 Yiheyuan Road,
Beijing, China
E-mail: yinganmin6837@163.com

About Me

I am Ganmin Yin, currently a Ph.D. candidate (2020-2025, expected) majoring in GIScience at Peking University. I am also a research assistant in the Geocomputation Group of the Spatio-Temporal Social Sensing Lab (S3-Lab), supervised by Prof. Zhou Huang and Prof. Yu Liu. Before that, I received my B.S. Degree on GIScience at Peking University in 2020.

My research interests focus on urban analytics with geospatial big data and advanced models, including sustainability issues like transportation and urbanization. My research goal is to introduce state-of-the-art theories and models to better understand the human-environment relationship.

Besides, I am also very interested in Hiking, Traveling, and Reading :）.

Note: I am looking for a postdoc position starting in 2025, fall. Feel free to contact me!

News

Education

Ph.D. Candidate, Cartography and GIScience, Peking University, 2020 - Present

B.S., GIScience, Peking University, 2016 - 2020

Selected Publications

*Corresponding author, #Equal contribution

  1. Yin, G., Fu, C., Ren, S., Yan, X., Qi, J., Bao, Y., & Huang, Z.* (2025). Traffic prediction and road space optimization for the integration of dockless bike-sharing and subway. Sustainable Cities and Society, 121, 106162. (IF = 10.5, 3/91)

  2. Yin, G., Huang, Z.*, Yang, L., Ben-Elia, E., Xu, L., Scheuer, B., & Liu, Y. (2023). How to quantify the travel ratio of urban public transport at a high spatial resolution? A novel computational framework with geospatial big data. International Journal of Applied Earth Observation and Geoinformation, 118, 103245. (IF = 7.6, 6/62)

  3. Yin, G., Huang, Z.*, Fu, C., Ren, S., Bao, Y., & Ma, X. (2024). Examining active travel behavior through explainable machine learning: Insights from Beijing, China. Transportation Research Part D: Transport and Environment, 127, 104038. (IF = 7.4, 5/57) [ESI Highly Cited Paper]

  4. Yin, G., Huang, Z.*, Bao, Y., Wang, H., Li, L., Ma, X., & Zhang, Y. (2023). ConvGCN-RF: A hybrid learning model for commuting flow prediction considering geographical semantics and neighborhood effects. GeoInformatica, 27(2), 137-157. (IF = 2.2, 31/65) [Top 1 Most Cited Paper in 2023]

  5. Huang, Z., Yin, G., Peng, X.*, Zhou, X., & Dong, Q. (2023). Quantifying the environmental characteristics influencing the attractiveness of commercial agglomerations with big geo-data. Environment and Planning B: Urban Analytics and City Science, 50(9), 2470-2490. (IF = 2.6, 36/171) [ESI Highly Cited Paper]

  6. Yin, G., Feng, Y., Jiang, Y., & Bao, Y.* (2024). A Scene-Object-Economy framework for identifying and validating urban-rural fringe using multisource geospatial big data. Applied Sciences, 14(22), 10191. (IF = 2.5, 44/179)

Full list of publications in Google Scholar.

Presentations

  1. Yin, G. "Analysis and application of urban sustainable transportation based on geographic big data". The 9th "Zhizhuo" Doctoral Student Forum (Wuhan, China, 2024). (Oral)

  2. Yin, G. "Evaluating the efficiency-emission impacts of travel mode shift on sustainable transportation: A multi-objective optimization". The 2024 International Graduate Workshop on GeoInformatics (IGWG 2024) (Beijing, China, 2024). (Oral)

  3. Yin, G. "Exploring the influencing factors of urban commercial agglomeration attractiveness based on mobile signaling big data". The 18th China Annual Conference on GIS Theory and Method (Guilin, China, 2023). (Oral)

  4. Yin, G. "Understanding public transport supply and demand from the perspective of public transport travel ratio in a fine spatial scale". The 29th International Conference on Geoinformatics (CPGIS 2021) (Nanchang, China, 2021). (Oral)

Honors and Awards

Peer Review Services

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