Biophysical Modelling of Surface Temperatures in Different Urban Landscape Characters: A Multi-scale Perspective

M-GEO
M-SE
PLUS
WCC
M-SE Core knowledge areas
Spatial Information Science (SIS)
Spatial Planning for Governance (SPG)
Additional Remarks

Skillset Required: 

Essential skills include proficiency in geo-computing platforms like Python, R, QGIS, and other data visualization tools like Tableau or Power BI. 

Other Info: 

This study adheres to the FAIR principles, promoting transparency and reproducibility in the scientific process. Students should be prepared to work with a diverse range of data sources and analytical techniques. 

 

Topic description

Urban land surface temperature (ULST) dynamics are influenced by a myriad of factors related to urban landscape character. Despite extensive research, there remain significant gaps in understanding the interactions between these factors and ULST. For instance, recent studies highlight inconsistencies in how different urban landscape elements—such as green spaces, water bodies, and built-up areas or their arrangement (configuration)—affect ULST. These discrepancies arise from variations in study methodologies, scales of analysis, and geographic contexts. For example, research in temperate cities like Berlin shows green spaces significantly mitigate ULST, while studies in tropical cities like Jakarta present less pronounced effects. Additionally, the role of small-scale landscape features in influencing ULST remains underexplored. This project aims to address these gaps by systematically analysing major urban landscape character types and their impact on ULST. The study will explore how landscape heterogeneity, including variations in vegetation cover, built infrastructure, and water bodies, contributes to the spatial variability of ULST. Furthermore, the project will investigate how these relationships differ in the Global North and South, acknowledging the divergent urban development trajectories of their landscapes. This approach will provide a fine-grained understanding of ULST dynamics, essential for developing effective urban planning strategies to mitigate urban heat islands and enhance urban liveability. 

Topic objectives and methodology

The study's primary objective is to elucidate the dynamics of surface temperature across different urban landscape types, employing a multi-scale analysis. Satellite data from the Copernicus data hub and/or NASA repositories will be utilized. The project involves identifying at least two major urban landscape character types in both the Global North and South, followed by computing and analysing ULSTs using robust landscape metrics and multi-scale assessments.  

References for further reading

Lausch, A., Blaschke, T., Haase, D., Herzog, F., Syrbe, R. U., Tischendorf, L., & Walz, U. (2015). Understanding and quantifying landscape structure - A review on relevant process characteristics, data models and landscape metrics. Ecological Modelling, 295(January), 31–41. https://doi.org/10.1016/j.ecolmodel.2014.08.018 

Liu, Y., Peng, J., & Wang, Y. (2018). Efficiency of landscape metrics characterizing urban land surface temperature. Landscape and Urban Planning, 180, 36–53. https://doi.org/10.1016/j.landurbplan.2018.08.006 

Natural England. (2014). An Approach to Landscape Character Assessment. In Natural England (Issue October). https://www.gov.uk/government/publications/landscape-character-assessments-identify-and-describe-landscape-types