• Hazard indicator choice (LST vs. Humidex) shapes urban heat risk assessment in African cities. • LCZ-disaggregated CHRZ maps reveal hotspots concentrated in LCZ 3, 6, and 7. • Statistical analysis confirms moderate-to-strong spatial agreement between LST- and Humidex-based CHRZs. • Monte Carlo simulations quantify uncertainty from LCZ misclassification on CHRZ distribution. • Framework provides a replicable approach for planning and adaptation in data-scarce tropical cities. Urban heat exposure poses significant health and socio-economic risks in rapidly growing Sub-Saharan African cities. Accurate mapping of heat risk is critical for targeted adaptation, yet the choice of hazard indicator can influence risk assessment outcomes. This study evaluates the impact of hazard indicator selection on urban heat risk by comparing Critical Heat Risk Zones (CHRZs) derived from Land Surface Temperature (LST) and Humidex (HI) in Dar es Salaam, Tanzania, and Lagos, Nigeria. Using high-resolution geospatial data, WRF derived climate data, and Local Climate Zone (LCZ) disaggregation, we quantified the spatial agreement between LST- and HI-based CHRZs through Cohen’s Kappa and Bivariate Moran’s I. Results show moderate-to-strong spatial correspondence in both cities (Dar es Salaam: Kappa = 0.584, Moran’s I = 0.706; Lagos: Kappa = 0.336, Moran’s I = 0.521), with heat risk concentrated in LCZ 3, 6, and 7. Monte Carlo simulations highlight the robustness of LCZ-based CHRZ disaggregation under realistic classification uncertainty. Findings emphasize that merging multiple hazard indicators can guide urban planning, early-warning systems, and neighbourhood-level interventions. The framework is transferable to other data-scarce African cities, supporting context-sensitive heat mitigation strategies and climate-resilient urban development.
Morakinyo et al. (Sun,) studied this question.