Cooling Effect of ecosystems (InVEST Urban Cooling)
InVEST model Urban Cooling Effect is primarily aimed at assessing the cooling effect of green spaces within urban areas. However, it also allows for evaluating this effect over large areas outside of cities. Since the assessment of urban ecosystem services is not a goal of our project, we focused primarily on the entire territory of Armenia and its impact on settlements. Green spaces within settlements was not the focus of the assessment.
The InVEST Urban Cooling model calculates an index of heat mitigation based on cooling capacity of green spaces and distance from them. The model computes the cooling capacity (CC) index for each pixel based on local shade, evapotranspiration, and albedo. СС is used to estimate a temperature reduction by ecosystems.
Heat Mitigation index (HM) estimates the cooling effect of large green spaces (>2 ha) on surrounding urban areas. In our case, it shows the impact of the surrounding area on the settlements. HM is equal to CC if the pixel is unaffected by any large green spaces, but otherwise set to a distance-weighted average of the CC values from the large green spaces and the pixel of interest.
The model calculations are based on indicators of evapotranspiration, albedo, the proportion of area in LULC classes that is covered by tree canopy (shade), air temperature in a rural reference area, and the UHI Effect (Urban Heat Index). The last coefficient shows the difference between the rural reference temperature and the maximum temperature observed in the city. UHI is incorporated into the model as a single value. Calculations based on a single UHI value for all of Armenia are impractical due to the significant variation in conditions across different cities. Thermal images (Landsat 8 Surface temperature data courtesy of the U.S. Geological Survey; Scene ID: LC08_L2SP_170032_20240823_02_T1) show that during the hottest period (August), Yerevan is cooler than the surrounding areas, Gyumri has approximately the same temperature, and Dilijan is warmer.
Yerevan
Gyumri
Dilijan
Data from Global Surface UHI Explorer confirm that there is no single UHI coefficient for Armenia. The coefficient varies not only from city to city (Yerevan is cooler, Gyumri is warmer than surrounding area) but also across different parts of the same city.
Therefore, we used UHI=0, meaning we did not account for the influence of this factor.
The main results of ES modeling and mapping
InVEST model outputs are proxy variables that should be interpreted in relative terms, rather than physical quantities. Nevertheless, the identified values are useful for analyzing the spatial distribution of services across the country’s territory and their balance with indicators of service utilization by the population and the economy.
This section presents preliminary results of testing models for assessing and mapping ecosystem services. In the future, if a decision is made to use these models, they should be calibrated using meteorological measurements made in Armenia.
Since the model is primarily focused on the cooling effect within settlements, one of its features is that it maps the service within a rectangle that encompasses all settlements. As a result, small areas near the boundaries were excluded from the modeling. In our case, this introduces a minor error that can be ignored. However, this flaw should be taken into account in future analyses.
We used in this model the same evapotranspiration coefficients, climatic zones, and scenarios as in the SWY.
The methodology and results will be described in detail in a forthcoming publication.
1. ES evaluation and mapping in physical indicators
The ratio of the coefficients for evapotranspiration, albedo, and tree canopy cover (shade) that we used determined that the highest Cooling Capacity (CC) is associated with forests, followed by croplands in arid and humid climate zones, then water and built-up areas, then croplands in moderate dry and cool climate zones, then bare ground. The lowest CC values are attributed to grasslands. The high CC values for croplands in arid and humid climate zones is explained by the large proportion of orchard areas in those regions (according to ArmStat data). The relatively high CC values for built-up areas are due to our assumption that, on average, 20% of the area in settlements is covered by trees (shadow=0.2). Сhanging any of the coefficients determining СС (evapotranspiration, albedo, and tree canopy cover (shade) can alter the ratio of CC among different land cover classes. This highlights the need for model calibration if a decision is made to use it in the future.

The CC values are represented on the resulting maps of this ES. In the Bare Ground scenario, where all forests and grasslands are replaced with bare ground, CC significantly decreases for forest areas and slightly increases for grassland areas. This is because, with the coefficients we used, the CC of bare ground is slightly higher than that of grasslands. Thus, with the coefficients we used, the influence of natural vegetation is expressed as significant cooling in forested areas and slight warming in grassland areas. Accordingly, this ES cools provinces Tavush, Lori, Syunik, Kotaik, but warms provinces where there are no forests.
Сooling capacity – Land cover 2023 Heat Mitigation index – Land cover 2023
ES represented as the difference between
CC with 2023 land cover and CC with bare
Сooling capacity – Bare ground scenario ground scenario
For details see maps in the section “Ecosystem Services/Urban Cooling”

CC in settlements is determined by the CC of the surrounding area, as well as by the geometry of the settlement boundaries, i.e., the proportion of the settlement’s area influenced by the surrounding territory. Following the InVEST recommendation, we set Maximum Cooling Distance (distance over which green areas larger than 2 hectares have a cooling effect) = 450 m. Average CC in settlements ranges from 0.5 (half of the maximum possible values) to 0.06 (Table of CC values for 1,016 settlements in Armenia).
2. ES changes from 2017 to 2023
All changes identified are determined only by changes in the landcover. Weather and climate changes are not taken into account. From 2017 to 2023, there were slight changes in CC oppositely directed in different provinces. Significant decrease in CC occurred in the Syunik due to replacement of some forests with grasslands, as well in the Ararat due to replacement of some croplands with grasslands and built-up areas. Increase in CC occurred in the Shirak and the Lori due to replacement of some grasslands with croplands (for changes in land cover see here).
Changes in cooling capacity from 2017 to 2023
For details see maps in the section “Ecosystem Services/Urban Cooling/Dynamics”

Changes in CC in settlements range from a decrease of 61% to an increase of 65% (Table of CC value changes in settlements).