Comparative Analysis of Urban Heat Islands in Coastal Cities and Inland Counterparts

Thesis Abstract

Urban heat island (UHI) effects pose divergent climatic and health risks across coastal and inland urban environments, driven by differential land-use, moisture regimes, and anthropogenic heat emissions. This study investigates the extent, drivers, and consequences of UHIs in coastal cities versus inland counterparts, addressing a gap in comparative evidence that informs climate resilience and urban planning. The aim is to quantify and compare UHI intensity, investigate contributing factors, and assess potential adaptive strategies across heterogeneous urban morphologies. Specific objectives are to (i) estimate UHI intensity using surface temperature data from Landsat 8 and Sentinel-2 imagery for a paired sample of five coastal and five inland metropolitan areas over the warm season (May–September) between 2019 and 2023; (ii) examine the relationships between UHI intensity and land surface temperature, albedo, vegetation cover (NDVI), impervious surface fraction (IF), and urban morphology metrics; (iii) evaluate diurnal and seasonal variation in UHI magnitude and its correlation with meteorological conditions (wind speed, humidity, solar radiation); (iv) assess health and energy demand implications through cross-sectional proxies (hospital admissions for heat-related illnesses, electricity demand indices) and (v) test the applicability of two theoretical perspectives—the Biophilic Urbanism framework and the Urban Climate Comfort Paradigm—in explaining observed patterns and informing adaptation options. The methodology adopts a comparative cross-sectional research design anchored in urban climatology and geography. The population comprises metropolitan areas with distinct coastal and inland characteristics, sampled to ensure climatic and socio-economic comparability. A total of 10 cities (5 coastal, 5 inland) with uniform data availability is selected. The study employs a mixed-methods approach quantitative analysis uses satellite-derived land surface temperatures to compute UHI indices, supported by high-resolution land-use data (CORINE/Global Land Cover), NDVI, and IF layers, alongside meteorological records from national weather stations. Instrumentation includes remote sensing processing workflows (radiometric and atmospheric correction, surface temperature retrieval via split-window and emissivity corrections) and GIS-based morphometric calculations. Data analysis proceeds in four stages. First, descriptive statistics summarize UHI measures across sites. Second, regression analyses—including multiple linear regression and generalized additive models—evaluate the relationships between UHI intensity and explanatory variables (NDVI, albedo, IF, building height, and sky-view factor). Third, a multilevel hierarchical model tests cross-site differences and diurnal/seasonal patterns, while controlling for city-specific fixed effects. Fourth, a health-energy nexus is explored through regression linking UHI proxies with heat-related health indicators and electricity demand indices, where available. Model specification adheres to theory-driven expectations from the Biophilic Urbanism framework (nature integration and microclimate regulation) and the Urban Climate Comfort Paradigm (thermal comfort as a function of ambient conditions and urban form). The study also employs sensitivity analyses to assess the robustness of remote-sensing-derived UHI estimates against atmospheric variability and land-cover misclassification. Expected findings indicate that coastal cities exhibit moderated nighttime UHI intensities relative to inland cities due to higher humidity and persistent evapotranspiration, yet may experience elevated daytime heat in concrete-dominated districts with low vegetation. It is anticipated that UHI strength correlates positively with impervious surface fraction and building density, while inversely with NDVI and surface moisture. Diurnal analysis is expected to reveal larger nocturnal cooling differences in inland cities. The health-energy analysis may show stronger correlations between UHI metrics and heat-related health admissions in inland areas, whereas coastal cities show greater sensitivity of electricity demand to peak solar loads. The contribution to knowledge includes a refined comparative understanding of how urban form and climatic context shape UHI dynamics, providing evidence-based guidance for targeted adaptation measures such as green infrastructure investments, reflective surfaces, and microclimate design, aligned with the Biophilic Urbanism and Climate Comfort frameworks. The conclusion will emphasize that coastal–inland disparities in UHI are mediated by a combination of vegetation, moisture, and urban morphology, necessitating location-specific mitigation strategies. Policy recommendations advocate prioritizing greenspace expansion and high-albedo materials in inland urban cores, while promoting coastal wetland preservation and wind-assisted ventilation in coastal zones. Limitations relate to the use of proxy health indicators and potential inconsistencies across satellite-derived temperatures; future research should integrate in-situ observations and longitudinal health and energy data to validate and extend the findings.