Assessing the Impact of Green Infrastructure on Urban Heat Island Mitigation

Thesis Abstract

Urban heat island (UHI) effect presents a significant challenge to sustainable urban development, exacerbating heat-related health risks, increasing energy consumption, and deteriorating urban livability. Despite global recognition of green infrastructure (GI) as a mitigation strategy, empirical evidence quantifying its effectiveness in diverse urban contexts remains limited, especially within rapidly urbanizing regions. This study aims to assess the impact of green infrastructure on alleviating the urban heat island effect, focusing on spatial variability and the determinants of mitigation efficacy. The specific objectives include (1) evaluating the relationship between the extent and type of green infrastructure and temperature reduction across selected neighborhoods; (2) identifying key factors influencing the effectiveness of GI interventions; and (3) developing a predictive model for urban heat mitigation based on green infrastructure variables. The research employs a mixed-methods approach, integrating quantitative spatial analysis with qualitative stakeholder interviews to afford a comprehensive understanding of green infrastructure's role in UHI mitigation. A quantitative research design underpins the spatial analysis methodology. The study population comprises urban neighborhoods within the metropolitan area of a major city that have implemented varying green infrastructure interventions in the past five years. Using stratified random sampling, a total of 30 neighborhoods representing diverse socio-economic and environmental conditions are selected, with sample sizes of 120 temperature measurement points (four per neighborhood) established for detailed thermal profiling. Data collection involves remote sensing imagery, specifically Landsat 8 Thermal Infrared Sensor (TIRS) data, analyzed through GIS with emphasis on land surface temperature (LST) variations. Complementary field measurements are conducted using handheld infrared thermometers to validate satellite-derived data. Further, information on green infrastructure characteristics—such as vegetation cover percentage, tree canopy density, and type of GI implemented—is gathered through field surveys and municipal records. Stakeholder interviews with urban planners, landscape architects, and residents provide insights into the planning, implementation processes, and perceived benefits of green infrastructure—these qualitative data are analyzed through thematic analysis. Data analysis encompasses descriptive statistics to characterize green infrastructure and temperature patterns; correlation analysis to examine relationships between green variables and temperature reduction; and multiple regression analysis to develop a predictive model of UHI mitigation efficacy. Techniques such as analysis of variance (ANOVA) are used to assess spatial differences across neighborhoods. Model validation involves cross-validation with existing UHI datasets and sensitivity analysis to determine the influence of various GI factors. Expected findings suggest that higher percentages of tree canopy and native vegetation cover significantly correlate with temperature reductions of up to 3°C in targeted neighborhoods. Results are anticipated to reveal moderating effects of socio-economic variables and urban density on green infrastructure efficacy. The developed regression model aims to predict UHI mitigation potential based on measurable green infrastructure parameters, offering a practical tool for urban planners. This research contributes to the body of knowledge by empirically elucidating the quantitative relationship between green infrastructure and UHI mitigation in a contextualized urban setting, advancing theoretical understanding anchored in the Landscape Architecture Theory and Urban Climate Adaptation Frameworks. It provides policymakers and urban designers with evidence-based guidance on optimizing green infrastructure deployment for thermal regulation. The study concludes that strategic and context-sensitive green infrastructure implementation can effectively mitigate UHI effects, emphasizing the importance of integrating environmental and social dimensions in urban planning. Key recommendations include prioritizing native tree species, creating continuous green corridors, and involving local communities in planning processes to enhance the sustainability and effectiveness of green infrastructure interventions. Future research should explore longitudinal impacts of green infrastructure and examine innovative biophilic design strategies to further enhance urban thermal comfort.