Urban remote sensing

Remotely sensed images and the corresponding analytical techniques offer a comprehensive approach to observing and monitoring urban environments in real-time through high spatial-temporal-spectral-resolution data.

One of the main challenges of urban remote sensing is that the sensors were not originally designed to collect the information from urban areas. In this research project, we will address this challenge by creatively using multisource remotely sensed images (LIDAR, RADAR, optical, etc.) to understand the complex urban environment, establish digital twins, and answer urban-related social, economic, and environmental questions.

Aims and objectives

The project has the following aims and objectives:

• Use high-resolution satellite images to identify vacant/derelict land in Glasgow and provide solutions for these sites
• Understand how to better design urban green/blue infrastructure to alleviate urban heat island effects and improve living conditions in cities
• Design a new 3D city model with buildings and trees by using high resolution LiDAR data with Glasgow City Council

Researchers

Lead: Dr Qunshan Zhao

Team: Dr Qiaosi Li

Latest Outputs

• Li, Q., & Zhao, Q. (2023). Weakly-Supervised Semantic Segmentation of Airborne LiDAR Point Clouds in Hong Kong Urban Areas. 2023 Joint Urban Remote Sensing Event (JURSE), 1–4. https://doi.org/10.1109/JURSE57346.2023.10144215
• Park, Y., Zhao, Q., Guldmann, J.-M., & Wentz, E. A. (2023). Quantifying the cumulative cooling effects of 3D building and tree shade with high resolution thermal imagery in a hot arid urban climate. Landscape and Urban Planning, 240, 104874. https://doi.org/10.1016/j.landurbplan.2023.104874
• Wang, C., Turner, V. K., Wentz, E. A., Zhao, Q., & Myint, S. W. (2021). Optimization of residential green space for environmental sustainability and property appreciation in metropolitan Phoenix, Arizona. Science of The Total Environment, 763, 144605. https://doi.org/10.1016/j.scitotenv.2020.144605
• Paper: Yang, J., Shi, Q., Menenti, M., Wong, M. S., Wu, Z., Zhao, Q., Abbas, S., & Xu, Y. (2021). Observing the impact of urban morphology and building geometry on thermal environment by high spatial resolution thermal images. Urban Climate, 39, 100937.
• Paper: Zhao, Q., & Wentz, E. A. (2020). Editorial for the Special Issue: “Remote Sensing of Urban Ecology and Sustainability”. Remote Sensing, 12(3), 443.
• Paper: Wang, Z., Fan, C., Zhao, Q., & Myint, S. W. (2020). A geographically weighted regression approach to understanding urbanisation impacts on urban warming and cooling: A case study of Las Vegas. Remote Sensing, 12(2), 222.
• Paper: Wang, C., Li, Y., Myint, S. W., Zhao, Q., & Wentz, E. A. (2019). Impacts of spatial clustering of urban land cover on land surface temperature across Köppen climate zones in the contiguous United States. Landscape and Urban Planning, 192, 103668.
• Paper: Zhao, Q., Reynolds, R., Wang, C., & Wentz, E. A. (2019). A multidimensional urban land cover change analysis in Tempe, AZ. 2019 Joint Urban Remote Sensing Event (JURSE), 1–4.