Insights into heat islands at the regional scale using a data-driven approach

Urban heat island (UHI) phenomenon is crucial in the context of climate change. However, while substantial attention has been given to studying UHIs within cities, our understanding at the regional level still needs to be improved. This study delves into the intricate dynamics of the regional heat island (RHI) by examining its relationship with land use/land cover (LULC), vegetation, and elevation. The objective is to enhance our knowledge of RHI to inform effective mitigation strategies. The research employs a data-driven approach, leveraging satellite data and spatial modeling, examining surface and canopy-layer regional heat islands, and considering daytime and nighttime variations. To assess the impact of LULC, the study evaluates three main categories: anthropized (urbanized), agricultural, and wooded/semi-natural environments. Furthermore, it delves into the influence of vegetation on RHI and incorporates elevation data to understand its role in RHI intensity. The findings reveal meaningful variations in heat islands across different LULCs, providing essential insights. Although urbanized areas exhibit the highest RHI intensity, agricultural regions contribute notably to RHI due to land use changes and reduced vegetation cover. This emphasizes the significant impact of human activities. In contrast, wooded and semi-natural environments demonstrate potential for mitigating RHI, owing to their dense vegetation and shading effects. Elevation, while generally associated with reduced heat island, shows variations based on local conditions. Ultimately, this research underscores the complexity of the RHI phenomenon and the importance of considering factors such as different temperatures and their daily variation, landscape heterogeneity, and elevation. Additionally, the study emphasizes the significance of sustainable spatial planning and land management. Targeted efforts to increase vegetation in high daytime land surface temperature areas can reduce heat storage and mitigate RHI. Similarly, planning for agroforestry and green infrastructure in agricultural areas can significantly increase resilience to climate.