I am Koichi Ito and am a PhD researcher at Urban Analytics Lab at the National University of Singapore. I am currently working on causal inference and computer vision for active mobility research 🚴.
- 🔭 I'm currently working on my PhD projects, ranging from developing a Python package for street view imagery analysis to causal inference + computer vision
- 👯 I’m looking to collaborate on cool research projects on mobility and machine learning 🔬
- 💬 Ask me about active mobility research and street view imagery analysis
- 📫 How to reach me: [email protected]
- ℹ️ More information: https://koichiito.com/
- ✅ Check out my Python package for street view imagery analysis: ZenSVI
📝 Under Review:
- Ito, K., et al. (2024). ZenSVI: An Open-Source Software for Integrated Acquisition, Processing and Analysis of Street View Imagery.
🔬 Published:
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Ito, K., Bansal, P., & Biljecki, F. (2024). Examining the causal impacts of the built environment on active transportation using time-series street view imagery. Transportation Research Part A: Policy and Practice. https://doi.org/10.1016/j.tra.2024.104286
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Ito, K., Quintana, M., Han, X., Zimmermann, R., & Biljecki, F. (2024). Translating street view imagery to correct perspectives to enhance bikeability and walkability studies. International Journal of Geographical Information Science. https://doi.org/10.1080/13658816.2024.2391969
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Ito, K., Kang, Y., Zhang, Y., Zhang F., & Biljecki, F. (2024). Understanding Urban Perception with Visual Data: A Systematic Review. Cities, 152, 105169. https://doi.org/10.1016/j.cities.2024.105169
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Fujiwara, K., Ito, K., Ignatius, M., & Biljecki, F. (2024). A panorama-based technique to estimate sky view factor and solar irradiance considering transmittance of tree canopies. Building and Environment, 266, 112071. https://doi.org/10.1016/j.buildenv.2024.112071
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Hou, Y., et al. (Ito, K.) (2024). Global Streetscapes – A comprehensive dataset of millions of street-level images over 700 cities for urban science and analytics. ISPRS Journal of Photogrammetry and Remote Sensing, 215. https://doi.org/10.1016/j.isprsjprs.2024.06.023
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Wang, S., et al. (Ito, K.) (2024). Mapping the landscape and roadmap of geospatial artificial intelligence (GeoAI) in quantitative human geography: An extensive systematic review. International Journal of Applied Earth Observations and Geoinformation, 128, 103734. https://doi.org/10.1016/j.jag.2024.103734
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Wang, Z., Ito, K., & Biljecki, F. (2023). Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery. Cities, 145, 104704. https://doi.org/10.1016/j.cities.2023.104704
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Ito, K., & Biljecki, F. (2021). Assessing bikeability with street view imagery and computer vision. Transportation Research Part C: Emerging Technologies, 132, 103371. https://doi.org/10.1016/j.trc.2021.103371
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Biljecki, F., & Ito, K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning, 215, 104217. https://doi.org/10.1016/j.landurbplan.2021.104217