Assessing Urban Heat Island Effects in Informal Settlements through Mobile Monitoring

Thesis Abstract

Urban heat island (UHI) effects in informal settlements pose heightened health risks and energy burdens, particularly under rapidly urbanizing conditions in low- and middle-income countries. This study addresses how mobile monitoring can quantify spatial and temporal UHI dynamics within informal settlements and elucidate the socio-physical drivers underlying observed thermal patterns. The aim is to develop a high-resolution, mobility-based assessment framework that links microclimate indicators to environmental and built-form variables to inform heat-mitigation strategies. Specific objectives are to (i) map fine-scale surface and air temperatures across multiple informal settlements using a standardized mobile transect protocol, (ii) identify spatiotemporal hot spots and their association with land cover, albedo, vegetation, material properties, and street canyons, (iii) examine the influence of socio-economic factors (household density, dwelling construction, roof materials) on thermal exposure, and (iv) evaluate the potential of mobile-derived thermal data to support community-led heat-adaptation planning. The study employs a mixed-methods, explanatory sequential design anchored in the urban climate and place-based geographies of informal settlements. The population comprises residents and built-form elements within three representative informal settlements in a rapidly urbanizing city. A stratified random sampling approach targets 120 households for supplementary qualitative interviews and surveys, while 20 mobile transect routes are conducted across different times of day (dawn, midday, late afternoon) over a four-month period to capture diurnal and synoptic variability. Instrumentation includes handheld infrared radiometers for surface temperature, compact air-temperature sensors, GPS-enabled data loggers, and high-resolution handheld cameras for contextual imagery. Land-use and surface characteristics are derived from high-resolution satellite imagery and drone-based orthophotos, complemented by crowd-sourced socio-economic data. Data collection instruments are validated through calibration against fixed meteorological stations and standardized protocols for radiometric readings. Spatial data are integrated within a geographic information system (GIS), while statistical analyses are conducted in R and Python. Analytical techniques encompass descriptive statistics to characterize thermal distributions, hotspot analysis using Getis-Ord Gi* statistics, and multivariate regression models to quantify relationships between temperatures and control variables (surface albedo, thermal inertia, vegetation indices such as NDVI, occupancy density, roofing materials). A mixed-effects model accounts for repeated measures across time and space, while a generalized additive model (GAM) explores nonlinear temperature–environment relationships. The theoretical framework draws on the Urban Ecology and Political Ecology of Urban Heat, incorporating the 3D urban form approach and the Thermal Comfort theory to interpret exposure implications. The study also utilizes a participatory lens to interpret findings against community-perceived heat stress indicators gathered from interviews, ensuring alignment with local knowledge. Expected findings indicate that mobile monitoring will reveal pronounced micro-urban heat islands within informal settlements, with peak surface temperatures exceeding ambient air temperatures by 5–12°C in open courtyards and rooftop-exposed areas. HVAC-relevant exposure disparities are anticipated to correlate strongly with roofing materials (tin, corrugated metal) and low-vegetation districts, while streets with narrow canyons exhibit amplified heating due to limited airflow. Vegetation cover and water features are expected to mitigate local temperatures, albeit unevenly due to maintenance and size constraints. Regression and GAM results are anticipated to show statistically significant associations (p < 0.05) between thermal indices and variables such as thermal inertia, albedo, and NDVI, with socio-economic factors moderating these effects. Qualitative analyses will illuminate community adaptive practices and perceived constraints. The study contributes to knowledge by (i) producing high-resolution, mobile-derived thermal datasets for informal settlements, (ii) linking physical infrastructure and socio-economic determinants to observed UHI patterns, and (iii) providing a replicable methodological framework for mobile climate monitoring in resource-constrained urban environments. The main conclusion posits that mobile monitoring is a cost-effective, scalable method to diagnose microclimate disparities and support targeted, community-informed adaptation interventions. Recommendations include prioritizing reflective roofing, perimeter shade, and small-greenery interventions integrated into informal settlement upgrading plans, alongside policy guidance for equitable heat resilience that foregrounds vulnerable residents and participatory governance.