Tree Equity Score Methodology

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A Tree Equity Score is a metric that helps cities assess how well they are delivering equitable tree canopy cover to all residents. The score combines measures of tree canopy cover need and priority for trees in urban neighborhoods (defined as Census Block Groups). It is derived from tree canopy cover, climate, demographic and socioeconomic data.

The score is calculated at the neighborhood (block group) level and aggregated to the municipal level.

The following describes our science-driven methodology for calculating Tree Equity Score in any city in the country.

Step 1: A Neighborhood Goal

Density Adjusted Canopy Target

The canopy target – which is meant to be equitable, aspirational and achievable – requires the following data:

  • Tree canopy cover. High resolution tree canopy where available, the National Land Cover Database where it is not.
  • Census American Community Survey (ACS) 2018 5-year Block Group population estimates
  • Census ACS 2018 5-year city and block group Median Income estimates

To identify a baseline canopy target, we use generalized natural biome baseline targets selected in conjunction with the USDA Forest Service. We select the baseline target based on the location of the municipality.

  • Forest: 40%
  • Grassland: 20%
  • Desert: 15%

This target is then adjusted based on population density to estimate a neighborhood goal. Based on research completed by The Nature Conservancy, adjustments are made using the following table:

Population Density (ppl/km2)Target Canopy Adjustment factor
Very low (<2k)1.2
Low (2k-4k)1
Moderate (4k-8k)0.8
High (>8k)0.5

Adjusting for population density makes for more achievable targets, while recognizing differences in plantable areas suitable for tree canopy. Note: Neighborhood goals are capped at 150% of the natural biome baseline target.

The formula for each neighborhood goal, GOAL, is as follows:

GOAL = Baseline target * Density adjustment factor

Step 2: The Canopy Gap

The neighborhood canopy gap, GAP, is calculated by subtracting the existing neighborhood canopy from the density adjusted target, that is: GAP = GOAL – EC, where EC is % existing canopy for that neighborhood

The canopy Gap is then normalized to a score from 0-100.

GAPScore = 100 * GAP / GAPmax , where:

  • GAPmax is the maximum GAP value citywide for that indicator; and

Notes: If the GAP is negative (i.e. Existing canopy is greater than the neighborhood goal), it is adjusted to 0 before normalizing to create the gap score. Also, if Gapmax = 0, then GapScore is set to 0 as well.

Step 3: The Priority Index

The Priority Index is developed to help prioritize the need for planting to achieve Tree Equity. The priority index includes the following equally-weighted characteristics:

  • Income: Percentage of population below 200% of poverty
  • Employment: Unemployment rate
  • Race: Percentage of people who are not white non-Hispanic
  • Age: Ratio of seniors and children to working-age adults
  • Climate: Urban Heat Island severity
  • Health: Prevalence of poor mental, physical, respiratory, and cardiac health (composite index)

These measures are normalized and combined to create a simple priority index from 0 to 1, where 1 indicates a greater amount of inequity. The indices, N, are calculated as follows:

Ni = (xi - xi,min ) / (xi,max - xi,min) , where, for each indicator, Ni,

  • xi is the value for that neighborhood for that indicator, i;
  • xi,max is the maximum value citywide for that indicator, i; and
  • xi,min is the minimum value citywide for that indicator, i.

The Priority index, E, is then calculated as follows: E = (N1 + N2 + N3 + N4 + N5 + N6) / 6 , where Ni refers to each indicator value (income, employment, race, age, or climate)

Step 4: Tree Equity Score

Tree Equity Score, TES, is calculated by multiplying the Baseline Gap Score by the Priority Index, simply:

TES = 100 (1 - GAPScore E)

A lower Tree Equity Score indicates a greater priority for closing the tree canopy gap.

Impact Measures

Achieving Tree Equity in cities provides numerous life-saving and quality of life benefits. Utilizing the power of i-Tree Landscape and new research funded by American Forests on job creation, we were able to quantify the co-benefits of achieving Tree Equity.

Estimating Number of Trees from Tree Canopy

To estimate a general number of trees associated with an increase in tree canopy, we utilize a basic multiplier of 600 sq-ft (55.74 sq-m) of canopy area per urban tree assuming a medium-size urban tree crown width of 25-30 ft.

Ecosystem services

The Tree Equity Score National Explorer calculate the ecosystem services benefit for the following year-over-year climate, air, and water benefits:

  • Carbon sequestration in annual tons
  • Carbon Monoxide (CO) in annual tons
  • Nitrogen Dioxide (NO2) in annual tons
  • Sulfur Dioxide (SO2) in annual tons
  • Particulate Matter less than 2.5 Microns (PM2.5) in annual tons
  • Particulate Matter less than 10 and greater than 2.5 Microns (PM10*) in annual tons
  • Ozone (O3) in annual tons
  • Rain Interception in cubic meters
  • Stormwater runoff avoided in cubic meters
  • Total annual economic benefit for all of the ecosystem services

For each of the measures, a county-specific multiplier has been provided by i-Tree and multiplied by the proposed additional canopy cover area in each block group. For more information the methods used to make these estimations, you can review the Summary of i-Tree Programs and methods.

Jobs supported

Tree Equity is a job producer and sustainer. American Forests supported research that used the U.S. Bureau of Economic Analysis’ Regional Input-Output Modeling System II (RIMS) to estimate the direct, indirect, and induced jobs from investing in urban forestry. Our jobs calculations rely on the following estimates and calculations:

  • For every $1 million invested in the urban forest, 25.7 jobs will be supported

  • It costs, on average, $283 to plant an urban tree

  • Jobs estimated include full-time, part-time, and seasonal jobs- they are NOT full-time equivalent jobs

  • These jobs do not carry a specific time dimension- the number of jobs would be divided by the number of years over which the investment occurs to get the average number of jobs supported each year.

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Tree canopy data provided
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