Urban Heat Island Calculator
Temperature differential from land cover and albedo.
About this calculator
Urban heat islands exist because cities replace vegetated, reflective land with dark, heat-retaining pavement and buildings, then add waste heat from engines and machinery on top. This calculator builds up that effect piece by piece rather than treating it as one fudge factor. It starts from T.R. Oke's foundational 1973 paper "City size and the urban heat island" (Atmospheric Environment), which established that bigger cities run hotter in a roughly logarithmic way — this calculator's population term (0.73 × ln(population/1000)) follows that same logarithmic shape, though with coefficients recalibrated for this tool rather than reproducing Oke's original regression exactly. It then adds a heating term scaled to impervious surface coverage, subtracts a cooling term scaled to tree canopy and greenspace (evapotranspiration moves heat into evaporating water instead of the air), adds a term for the albedo gap between urban and rural surfaces multiplied by solar radiation, and adds a small term for anthropogenic waste heat.
Wind speed then divides the whole total down through a dispersal factor, since a stiff breeze mixes the urban air with cooler surrounding air and calm conditions let heat pool in place. The result is annual-average UHI intensity in °C, with nighttime and summer-peak figures scaled up from it (1.7x and 1.8x) to reflect how heat stored in concrete and asphalt during the day is released after dark, and how the effect intensifies in summer. A rough cooling-energy-demand penalty and a cool-roof mitigation estimate (recomputed at albedo 0.35) round out the picture. Treat every coefficient here as an order-of-magnitude approximation drawn from published UHI literature, not a site-specific measurement — real UHI intensity depends heavily on local geometry, building height-to-width ratios, and microclimate factors this model doesn't capture. It's best used to compare scenarios (more trees vs. cool roofs vs. denser development) rather than to predict an exact temperature for a specific city block.
Inputs
Results
UHI intensity (°C)
4.2
Figures current as of 1973. Source: Oke, T.R. "City size and the urban heat island." Atmospheric Environment, 1973;7(8):769-779.
How to Use This Calculator
- Enter city population, impervious surface (%), and tree canopy/green space (%).
- Set urban and rural albedo values, solar radiation (W/m²), wind speed (m/s), and anthropogenic heat (W/m²).
- Review UHI Intensity (°C), Nighttime UHI (°C), and cooling potential from interventions.
- Each 10% increase in green space typically reduces UHI intensity by 0.3–0.5°C.
How the result changes with Wind speed (m/s)
| Wind speed (m/s) | UHI intensity (°C) |
|---|---|
| 1.5 | 4.97 |
| 2.25 | 4.55 |
| 4.5 | 3.63 |
| 7.5 | 2.86 |
What each input means
- City population
- City population — larger cities have stronger UHI effect (Oke 1973).
- Impervious surface (%)
- Percentage of land covered by pavement, buildings, and other impervious surfaces.
- Tree canopy / green space (%)
- Percentage of land with tree canopy or vegetated green space.
- Urban albedo (0-1)
- Surface reflectivity: dark asphalt ~0.10, concrete ~0.20, cool roofs ~0.35.
- Rural albedo (0-1)
- Surrounding rural albedo: grassland ~0.25, forest ~0.15, desert ~0.35.
- Solar radiation (W/m²)
- Mean daily incoming solar radiation. ~150 temperate, ~250 tropical.
- Wind speed (m/s)
- Average wind speed — higher winds disperse the heat island.
- Anthropogenic heat (W/m²)
- Waste heat from buildings, vehicles, industry. Typical: 10-50 W/m².
What each result means
- UHI intensity (°C)
- Average urban-rural temperature differential.
- Nighttime UHI (°C)
- Nighttime UHI is typically 1.5-2× daytime due to thermal mass release.
- Summer peak UHI (°C)
- Peak summer UHI intensity.
- Cooling energy increase (%)
- Estimated increase in cooling energy demand from UHI.
- Albedo heating (°C)
- Temperature contribution from urban-rural albedo difference.
- Greenspace cooling (°C)
- Cooling provided by vegetation and evapotranspiration.
- Wind dispersal factor
- Wind speed reduction factor on UHI (1.0 = calm, lower = more dispersal).
- Cool roof mitigation (°C)
- Potential UHI reduction if urban albedo increased to 0.35 (cool roofs).
How this is calculated
Worked example, using the default values
- Identify Input Parameters4 parametersCity population = 500000, Impervious surface (%) = 60, Tree canopy / green space (%) = 15, Urban albedo (0-1) = 0.15 = 8 input(s) provided
- Calculate UHI intensityUHI intensity4.2 = 4.2
- Calculate Nighttime UHINighttime UHI = uhiIntensity * 1.77.14 = 7.14
- Calculate Summer peak UHISummer peak UHI = uhiIntensity * 1.87.56 = 7.56
Figures and sources
- City-size / urban heat island logarithmic scaling relationship (1973) — Oke, T.R. "City size and the urban heat island." Atmospheric Environment, 1973;7(8):769-779.
Engine last updated . Checked against 2 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.
Frequently Asked Questions
Why does population affect UHI logarithmically instead of linearly?
The calculator follows the logarithmic city-size relationship established by T.R. Oke's 1973 paper "City size and the urban heat island" (Atmospheric Environment 7(8):769-779) — a term shaped as 0.73 × ln(population / 1000), which means going from 10,000 to 100,000 people adds roughly the same UHI as going from 100,000 to 1,000,000 — each tenfold increase in size adds a fixed amount of heat rather than a fixed rate per resident. This matches observed data: doubling a small town's population barely moves the needle, but a city crossing into the millions shows a measurably stronger heat island than a mid-sized one.
What does the wind dispersal factor actually do to my result?
After all the heating and cooling components are summed, the total is multiplied by 1 / (1 + 0.15 × windSpeed), so it scales the entire UHI estimate down rather than subtracting a fixed amount. At calm conditions (around 1 m/s) that factor is close to 0.87, while at a brisk 10 m/s it drops to about 0.4 — reflecting that wind mixes urban air with the cooler surrounding air and disperses heat that would otherwise pool near the surface.
Why does the cool-roof mitigation figure always assume albedo 0.35 instead of my input?
The 'Cool Roof Mitigation' output re-runs the full calculation with urban albedo replaced by 0.35 (a typical reflective/cool-roof value) while holding every other input the same, then reports the difference from your actual UHI intensity. It's meant to answer 'how much would switching to cool roofs help this specific city,' not to reflect a real intervention you've already made — if your urban albedo input is already above 0.35, the reported mitigation will be small or zero.
Why is nighttime UHI reported as higher than the daytime average?
The calculator multiplies the base UHI intensity by 1.7 for nighttime and 1.8 for summer peak, reflecting that pavement and buildings absorb solar heat during the day and release it slowly after dark, when rural areas cool off much faster without that stored thermal mass. These are fixed multipliers applied to whatever UHI intensity your inputs produce, not independently modeled — they scale proportionally with your base result rather than being calculated from separate physics.
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