The impact of hazard indicator selection on urban heat risk assessment: evidence from two Sub-Saharan African cities

• 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.

Authors

Institutions

Publication Details

Journal
City and Environment Interactions
Published
2026-03-31
DOI
https://doi.org/10.1016/j.cacint.2026.100338
Citations
1
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
12.99

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The impact of hazard indicator selection on urban heat risk assessment: evidence from two Sub-Saharan African cities

Lazaro Eliyah Mngumi, Oluwafemi Benjamin, Olumuyiwa Bayode Adegun, Tobi Eniolu Morakinyo et al.
1 citations
City and Environment Interactions
Urban Heat Island Mitigation
12.99
article

The impact of hazard indicator selection on urban heat risk assessment: evidence from two Sub-Saharan African cities

Lazaro Eliyah Mngumi, Oluwafemi Benjamin, Olumuyiwa Bayode Adegun, Tobi Eniolu Morakinyo, Elinorata Mbuya, Ademola Akinbobola, Gerald Mills
article en
1 citations

Abstract

• 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.

City and Environment InteractionsVol. 30
University College Dublin (IE), Ardhi University (TZ), Federal University of Technology (NG), University of the Witwatersrand (ZA), Texas A&M University (US)
Science Foundation Ireland
Climate action
Openalex Percentile: Top 1%
Urban Heat Island Mitigation
12.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.