Urban Heat Islands (UHI) pose a significant environmental threat as well as public health challenges, particularly in cities which are highly industrial. Understanding the distribution of these heat islands is crucial for climate resilience and sustainable urban planning. This study will investigate the effect of UHI in Ulsan, South Korea, by analysing Land Surface Temperature (LST) and its relationship with various land cover types. By using satellite imagery from Landsat 8-9, spatial mapping was conducted in ArcGIS Pro to visualise variations in temperature across the city. Furthermore, spatial data processing and machine learning models (Random Forest and Linear Regression) were used within R to identify the main drivers of heat accumulation, specifically the lack of vegetation density. Results indicated that surface temperatures in Ulsan’s southeastern industrial zones were approximately 20 to 25 °C higher than the surrounding forested areas. Through using geospatial data and tools, this report shows a scalable workflow in monitoring urban microclimates, providing insights which can support future environmental mitigation strategies within South Korea and the rest of the globe.
Alexander Copping (Mon,) studied this question.
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