Universal Thermal Comfort Index

The universal thermal climate index (UTCI) is an equivalent temperature (°C), it is a measure of the human physiological response to the thermal environment. The universal thermal climate index (UTCI) describes the synergistic heat exchanges between the thermal environment and the human body, namely its energy budget, physiology and clothing. UTCI takes into consideration the clothing adaptation of the population in response to actual environmental temperature. There are four variables required to calculate the UTCI: 2m air temperature, 2m dew point temperature (or relative humidity), wind speed at 10m above ground level and mean radiant temperature (MRT).

Cooling impact

The universal thermal climate index (UTCI) is an equivalent temperature (°C), it is a measure of the human physiological response to the thermal environment. The universal thermal climate index (UTCI) describes the synergistic heat exchanges between the thermal environment and the human body, namely its energy budget, physiology and clothing. UTCI takes into consideration the clothing adaptation of the population in response to actual environmental temperature. There are four variables required to calculate the UTCI: 2m air temperature, 2m dew point temperature (or relative humidity), wind speed at 10m above ground level and mean radiant temperature (MRT).

Shadow

This layer shows areas shaded by buildings and trees over the course of a day. Shade is modeled using the open-source SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry) model, which simulates shadows based on the three-dimensional structure of buildings and trees, ground elevation, and the position of the sun. The model estimates how shade moves and changes throughout the day across the study area. Caution: 1m resolution shade is based on open-source building and tree data, which can contain errors in feature placement and height.

Albedo

This layer shows albedo, a metric describing the reflectivity of surfaces. Albedo is a unitless value between 0 and 1 that expresses what percent of incoming sunlight a surface reflects. Light-colored surfaces, like snow, have higher albedos, while dark surfaces, like asphalt, have lower albedos.    Albedo is measured from satellite data. We estimate albedo from the Sentinel-2 satellite data using the methods of Bonafoni and Sekertekin (2020). 

Plantable areas

This layer shows the estimated plantable area for street trees for the scenario. Plantable area is defined as the area within 5-meters of roads that is not covered by a building or a water body, is not within 5-meters of buildings or 9-meters of intersections and does not have existing tree cover.  

Pedestrian areas

This layer shows places where people could walk. Pedestrian areas are spaces along roads that are not occupied by buildings or water. Pedestrian areas are produced by taking a 5 meter area around low traffic volume roads. Building footprints,, water, and the roads themselves are excluded from pedestrian areas.  

Parks

This layer shows public parks , including sports and recreation areas, green space, and open space.   Parks are derived from OpenStreetMap as areas tagged as common, disc golf course, dog park, forest, forest compartment, garden, golf course, national park, nature reserve, park, pitch, playground, protected area, recreation ground 

Shade structures

This layer shows a possible implementation of shade structures added to parks. The structures are 5X by 5 meters in area and 2.44 meters tall based on [commercially available shade structures](https://srpshade.caddetails.com/products/square-hip-shades-4430/80366).    Shade structures are placed in areas that are unshaded at 12pm local time to increase shade access for park users or those seeking respite from heat. Showing  one possible implementation of shade in parks, they serve to demonstrate the effects on local temperature of adding shade. 

Pedestrian roads

Description of dataset

Tree cover (Achiveable scenario)

This layer shows a possible implementation of street tree planting. Trees are randomly added to plantable areas until the percentage of tree cover in pedestrian areas reaches the achievable potential. New trees are modeled with the height and crown size of existing trees in the area and have a minimum between-tree spacing of 5 meters. 

Tree cover (Baseline)

This layer shows the existing tree canopy in a city. Created in 2024 by WRI and Meta and incorporating data from 2009-2020 with a focus on data from 2018-2020 , the dataset is derived from a deep learning model trained on high-resolution aerial Maxar imagery. It is currently the only published global very-high resolution tree canopy dataset.    The tree canopy source data provides both canopy extent and height, with a mean absolute vertical error of 2.8 m. Here, we show only tree cover, without height.