Uncertainty in Urban Heat Risk: Thermal Exposure, Social Vulnerability and Adaptation in Tier II Indian cities

About the project

About the Project Background India’s urban heat crisis has reached a critical threshold with 2024 the warmest year on record. With recent evidence indicating that heatwave-related mortality in India is substantially larger than official statistics suggest, India’s disproportionate burden in seen in the fact that it has accounted for 20.7% of heatwave-associated excess deaths during 1990–2019. The critical challenge is no longer simply establishing that heat is increasing but determining where heat exposure is occurring, for whom, and how those patterns can be estimated at the spatial scale at which adaptation decisions are made. This challenge is acute in India’s rapidly expanding Tier-II cities where dense observational networks are limited, urbanisation is transforming land cover rapidly, and socio-economic vulnerability is poorly mapped. Heat risk is not directly observable from temperature alone with other underlying uncertainties needing to be addressed for a comprehensive representation of human exposure. PhD project We are at a point where we understand that heat risk is not directly observable from temperature alone. Two population groups experiencing similar thermal conditions may face very different consequences based not only on their own social vulnerabilities but also on their ability to access adaptation mechanisms that might be in place. Equally, with persistent extreme heatwaves, it is clear that the thresholds assumed by existing mitigation strategies are no longer sufficient introducing further uncertainties in the way we understand and address heat risk. This project will address these emerging limitations by treating uncertainty itself as an object of analysis rather than presenting heat-risk maps as deterministic representations of reality. In the first instance, it will use satellite-derived heat anomalies for selected Tier-II Indian cities, retaining prediction errors and spatial validation uncertainty to identify varying modes of thermal exposure and resolution. Secondly, the project will examine uncertainty in the translation from physical heat to human exposure and impact through household surveys across four cities where information will be collected on thermal experience, health and livelihood effects, housing conditions, adaptation practices and access to cooling resources. By combining the two through a hierarchical Baynesian framework, this project produces an uncertainty-quantified, neighbourhood-scale evidence base for urban heat risk in data-sparse Indian cities. The intention here is not another map of where cities are hot, but a demonstration of where heat-risk estimates are reliable, where they are uncertain, why that uncertainty arises, and how it affects conclusions about inequality and adaptation priorities. In parallel, through institutional process-tracing, the project will investigate how uncertainty in evidence interacts with implementation capacity and heat governance arrangements. Applicant Profile Students with a strong background in geography/remote sensing with an ability to combine mixed-methods investigations across physical and human sciences are encouraged to apply. A good understanding of geoAI modelling and an ability to conduct ethnographic fieldwork in Indian cities is ideal.

Research areas