The scientific community has just released a comprehensive, high‑resolution map that quantifies how many people worldwide are exposed to heat‑wave conditions amplified by the urban heat‑island (UHI) effect. By pairing a global 1‑km daily land‑surface temperature (LST) product with the latest gridded population estimates, researchers can now pinpoint where cities turn already‑warm days into dangerous heat‑waves that strain health systems, and infrastructure.
In the first months of 2024, an international team led by Yu W. And colleagues uploaded the “Global UHE (Urban Heat‑wave Exposure) dataset” to Figshare Global UHE dataset. The dataset builds on the seamless 1‑km LST record covering 2003‑2020 Zhang et al., 2022 and the LandScan Global 30‑arc‑second population grids Lebakula et al., 2025. Together they enable a year‑by‑year accounting of how many city dwellers experience temperatures that exceed the wet‑bulb globe temperature (WBGT) thresholds used by the World Health Organization to define “dangerous heat”.
The release follows a series of studies that warned of rising heat‑related mortality. Zhao et al. Showed that from 2000‑2019, non‑optimal ambient temperatures contributed to over 4 million premature deaths globally Lancet Planetary Health, 2021. More recently, Lüthi et al. Documented a “rapid increase” in heat‑related mortality risk, especially in densely built environments Nature Communications, 2023. The new UHE dataset quantifies the exposure side of that equation, offering a tool for policymakers, city planners, and health officials.
How the dataset was assembled
Creating a global picture of UHI‑enhanced heat‑waves required three core layers:
- Surface temperature. The 1‑km LST product merges MODIS, VIIRS and Landsat observations, applying bias‑correction algorithms to ensure consistency across sensors Zhang et al., 2022.
- Urban extent. Urban boundaries were derived from the GAIA (Global Artificial Impervious Area) dataset, which maps built‑up surfaces using a combination of Sentinel‑2 and nighttime lights Li et al., 2020. This delineates the spatial footprint of the UHI effect.
- Population distribution. The LandScan Global 30‑arc‑second grids provide yearly estimates of where people live at a 1‑km resolution, accounting for daytime versus nighttime population shifts Lebakula et al., 2025.
Researchers then overlaid the temperature data with the urban mask and counted the number of residents whose daily maximum WBGT exceeded 30 °C—a threshold linked to increased risk of heat‑stroke and cardiovascular events Ebi et al., 2021. The result is a series of raster files that can be summed to produce national, regional, or city‑level exposure totals for any year between 2003 and 2020.
What the numbers reveal
Preliminary analysis shows that UHI‑boosted heat‑wave exposure is far from uniform. In 2020, more than 1.2 billion people—roughly 15 % of the world’s total population—lived in urban areas where at least one day exceeded the 30 °C WBGT threshold. The burden is concentrated in prompt‑growing megacities:
| City | Population (2020, millions) | Heat‑wave days | People exposed |
|---|---|---|---|
| Delhi, India | 31.0 | 12 | ≈ 28 M |
| Lagos, Nigeria | 14.8 | 9 | ≈ 13 M |
| São Paulo, Brazil | 22.0 | 8 | ≈ 19 M |
| Mexico City, Mexico | 21.7 | 7 | ≈ 15 M |
| Cairo, Egypt | 20.0 | 10 | ≈ 18 M |
These figures echo earlier findings that “over half of the global urban population experienced at least one extreme heat event between 2000 and 2019” Tuholske et al., 2021, but the new dataset refines the estimate by isolating the contribution of the UHI effect. In regions where green space is scarce and building density is high, the temperature excess can add 2–5 °C to ambient values, turning a marginally uncomfortable day into a public‑health emergency.
Health and policy implications
Heat‑related mortality risk rises sharply once WBGT passes 30 °C. Gasparrini et al. Estimated that each additional hot day could account for up to 0.5 % of total deaths in vulnerable populations The Lancet, 2015. When the UHI effect pushes city temperatures above that line, the health burden compounds existing climate‑change stressors identified in the IPCC’s AR6 report IPCC WGII, 2022. Cities can use the UHE dataset to target cooling interventions—such as expanding urban trees, installing reflective roofing, or redesigning street canyons—to the neighborhoods where the exposure gap is widest.
Beyond health, the exposure map informs climate‑risk financing. Insurance firms are already integrating WBGT‑based metrics into flood and drought models; the UHE data adds a layer that captures the “urban amplification” of heat risk, which could affect premium calculations for commercial property and infrastructure.
Where to access the data and next steps
The full suite of raster files, metadata, and code notebooks is publicly available on Figshare Global UHE dataset. Users can download the data directly or query it via the Earth Data Cloud platform, where the LST product is already hosted. The authors plan to extend the time series to 2024 in an upcoming release, incorporating the latest MODIS‑Terra observations and the 2023 population update from LandScan.
City officials and public‑health agencies are encouraged to incorporate the exposure layers into their heat‑action plans and to share local validation results with the research team. As the dataset matures, it will serve as a baseline for tracking the effectiveness of mitigation measures such as cool roofs, urban greening, and heat‑alert systems.
Disclaimer: The information in this article is for general informational purposes only and does not constitute medical advice. Individuals experiencing heat‑related symptoms should seek professional medical care.
We welcome feedback from researchers, planners, and community groups. Share your thoughts in the comments below and help spread awareness of this new tool for protecting urban residents from dangerous heat.
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