Integrating Satellite‐Based and Participatory Spatial Analyses for Local, Contextualised, and Nuanced Extreme Heat Hotspot Mapping in Overheated Urban Southeast Asia

ABSTRACT Rapid urbanisation in Southeast Asia intensifies extreme‐heat exposure, especially where high population density, extensive impervious surfaces, and limited green cover coincide. This study combines multi‐decadal satellite‐derived land surface temperature (LST) mapping with spatial regression and community participatory mapping to locate community‐level heat clusters of extreme heat in Metro Manila and the Bangkok Metropolitan Area. Using a 1 km grid and a suite of built‐environment, infrastructural, natural feature, and socioeconomic covariates (including two policy‐oriented efficiency ratios), we find that: (1) LST clusters exhibit significant positive spatial autocorrelation, and (2) a statistically significant quadratic relationship links a building‐efficiency ratio to local temperatures in both cities—implying an optimal level of compactness beyond which further densification reduces surface heat (consistent with increased shading and compact‐form benefits). In addition, higher population density, dense road networks, and proximity to extensive heat‐retaining infrastructure (notably airports) are consistently associated with elevated temperatures, whereas greater greenspace accessibility is associated with cooling. Crucially, participatory mapping supplied fine‐scale, lived‐experience data that (a) identified microhotspots that LST products missed, (b) revealed exposure pathways linked to travel distances and service access, and (c) highlighted social vulnerabilities and coping practises that inform equitable intervention priorities. Together, the integrated approach yields place‐sensitive insights—translating statistical relationships into implementable targets (e.g., green space per capita, building‐to‐economic activity benchmarks) for targeted greening, shading, and accessibility improvements. We discuss limitations—namely, the 1 km LST resolution and the small participatory sample—and argue that scaling this framework will better guide locally appropriate, equity‐centred heat adaptation in megacities.