1. 1
PRIORITY PLANTING AREAS
A System for Selecting Optimal Locations for Street Tree Restoration in Seattle
City of Seattle Department of Transportation,
Urban Forestry
August 2013

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“The forest of Compiegne. Look at it. Like a kind of
grandmother dozing in her rocking chair. Old trees practicing
curtsies in the wind because they still think Louis XIV is king.”
-Billy Wilder, Arise, My Love (1940)
Project Lead:
Jacob Pederson
Project Contributors:
Andy Chittick
Shane Dewald
Joshua Erikson
Barbara Gray
Chad Lynch
Joe Markovich
Craig Moore
Darren Morgan
Susan Paine
Nolan Rundquist
Lou Stubecki
Dana Trethewy
Jennifer Wieland
Shannon Whitney

3. CONTENTS
I. INTRODUCTION.....................................................................................................................................................4
II. METHODOLOGY....................................................................................................................................................5
The Tree Benefits Map ..............................................................................................................................................5
Tree Benefits Attributes........................................................................................................................................5
Attribute Processing and Map Interpretation ......................................................................................................7
The Street Tree Spacing Map ....................................................................................................................................8
Priority Streets Mapping ...........................................................................................................................................9
Using the Priority Streets Map..............................................................................................................................9
III. TOOLS FOR ANALYSIS..........................................................................................................................................11
Coverage Analysis Examples ...................................................................................................................................11
Existing Tree Benefits Analysis Examples................................................................................................................12
Developing Score Assignments ...............................................................................................................................13
IV. CONCLUSION.......................................................................................................................................................14
APPENDIX A—Reccomendations for Implementation ................................................................................................15
APPENDIX B—Distribution maps of Tree Benefit Attributes .......................................................................................16
APPENDIX C—GIS Data and Score Assignment for 2013 Tree Benefits Map...............................................................17
APPENDIX D – GSI Priority Areas .................................................................................................................................18

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I. INTRODUCTION
Since Seattle residents passed the Bridging the Gap Levy in 2007, SDOT Urban Forestry has planted approximately
800 new street trees each year. Street trees provide many social, environmental, and economic benefits to cities,
and can transform neighborhoods in significant ways. However, the current system for selecting planting locations
was established prior to the more data-driven methodologies used on other programs (e.g., the sidewalk
development program) and relies heavily on community support and available planting space. A more formal
system for determining where trees should be planted is needed, especially as SDOT embarks on planning for the
renewal of the Bridging the Gap levy.
This document describes a set of GIS tools developed to assist SDOT Urban Forestry staff in planning for street tree
restoration and stewardship in Seattle.
1
These tools are designed to allow for automated use of the most up-to-
date information available to create designed to:
1. Efficiently and objectively rank areas of the city according to potential social, environmental, and
economic value of trees planted in locations that support the city-wide policies—canopy cover, social
equity, and transportation safety.
2. Display the most current information on tree stocking levels in the right of way.
3. Identify areas where low stocking levels, available planting space, and high potential benefits intersect.
The ultimate goal of these maps is to guide SDOT Urban Forestry staff in identifying and evaluating specific areas,
called Priority Planting Areas (PPAs), where public investments in street trees are likely to yield the greatest
benefits. The PPA system recognizes that the level of benefits provided by trees is not constant from one area of a
city to the next. For example, it may be more beneficial to plant street trees in areas with lower average incomes,
lower rates of car ownership, and higher rates of obesity and disability—all data sets that SDOT maintains and
utilizes for project selection for other transportation assets. Planting trees in these areas can enhance residents’
experiences walking, running, and biking in their neighborhoods. Furthermore, urban reforestation programs risk
systematically discriminating in favor of owner-occupied properties.
2
Investment in PPAs will improve the
sustainability of the natural amenities in neighborhoods that may have previously been underserved or may not
have the current capacity to contribute time or resources to the urban forest.
These values, and others, are captured within the map tools described in this document, and may be changed,
pending further input from city departments and the public. In addition to forming the basis for establishing street
tree restoration priorities, PPAs provide an opportunity to take a retrospective look at past projects, allowing staff
to take stock of what values these projects have supported, and how future projects may improve or expand upon
them.
1
Full-size versions of many of the maps described in this report are available as separate documents. For access to
these maps, contact SDOT Urban Forestry.
2
Perkins, H. (2009). Inequitable Access to Urban Reforestation: The Impact of Urban Political Economy on Housing
Tenure and Urban Forests. Cities, 21(4), 291-299.

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II. METHODOLOGY
In order to identify PPAs, information must be available on the benefits provided by newly planted trees within
specific areas, and the current tree stocking levels in those areas. The two tools developed to capture these data
are the Tree Benefits Map and the Street Tree Spacing Map.
THE TREE BENEFITS MAP
Despite the large volume of information available on the benefits
that trees provide to cities, these benefits are notoriously difficult
to measure. The PPA system does not attempt to overcome this
challenge. Rather, it organizes known information to identify a
rationale for why planting trees on some streets may be favorable
to planting trees on others. This rationale is represented in terms
of the presence or absence of certain spatial attributes in a
geographic information system (GIS), called the Tree Benefits map.
The attributes included in the 2013 Tree Benefits Map are:
Areas within environmentally critical areas
Areas along proposed neighborhood greenways
Areas that can accommodate large trees
Areas within urban villages
Areas with relatively low canopy coverage
Areas near high-need populations
This list was developed by SDOT Urban Forestry staff, in
consultation with SDOT Policy and Planning, Seattle Public Utilities,
and others, and is designed to align urban forestry management
with citywide goals and objectives set out in the Comprehensive
Plan (see sidebar) and Urban Forest Stewardship Plan (UFSP).
However, future versions may feature different attributes and
attribute weights, depending on shifting program priorities,
emerging scientific or policy developments and further input from
the public and city departments.
TREE BENEFITS ATTRIBUTES
The following list will help users of the Tree Benefits Map
understand how potential tree benefits may be linked to the areas
defined by each attribute.
3
3
For distribution maps of tree benefit attributes, see Appendix A;
for technical information on data sources and analysis on attributes,
see Appendix B.
PPAs support several urban design (UD)
and land use (LU) policies in the City of
Seattle Comprehensive Plan.
UD3 Build with nature by integrating
ecological functions such as storm
water filtration or retention with
other infrastructure and
development.
UD8 Look for ways to connect new
developments to the public open
space system.
UD9 Connect open spaces into a
citywide network.
UD18 Design streets in urban villages to
be pedestrian-friendly by such
means as respecting street grids,
providing connections between
major activity centers,
incorporating public open spaces,
and having commercial buildings
with retail uses that abut the
sidewalk.
UD27 Encourage new approaches to
street design that expand the role
of streets as public spaces.
UD29 Consider the needs of growing
demographic and ethnic groups in
the design of public space.
UD30 Connect large parks and open
spaces to each other and to
population concentrations, such
as urban villages.
LU274 Prioritize and focus city
investments in transit
communities, in addition to urban
centers and urban villages, to
provide features that support a
highly livable, walkable urban
environment.
___

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AREAS WITHIN ENVIRONMENTALLY CRITICAL AREAS:
Three criteria are included in order to promote the overall environmental benefits of street tree plantings. These
are proximity to wetlands, proximity to riparian zones, and proximity to Washington Department of Fish and
Wildlife designated habitat corridors.
Many characteristics of the streetscape constrain which tree species may be planted in the right of way, and
therefore the potential environmental benefits that they provide in terms of expanding native plant communities
and wildlife habitat. For example, power lines, underground utilities, narrow planting strips, curbs, sidewalks,
concrete, and compacted soils all limit the establishment and long-term health of trees. Nevertheless, all trees
planted where the public right of way intersects environmentally critical areas are likely to provide greater
environmental benefits than those planted elsewhere. Street tree projects can help “soften the edges” between
natural areas and the concrete-dominated landscapes of the city by providing shade over surface water, filtering
storm water runoff, and improving cover for wildlife moving between habitat patches.
AREAS ALONG PROPOSED NEIGHBORHOOD GREENWAYS:
Neighborhood greenways are designed to provide Seattle’s residents with safe and attractive places to walk, ride a
bike, skate, and run. SDOT Urban Forestry plays an important role in putting the “green” into greenways by
focusing on tree restoration within these areas.
AREAS THAT CAN ACCOMMODATE LARGE TREES:
The tree size potential category takes into account those areas where the planting strip between the sidewalk and
the street is wide enough to accommodate large trees and where tree pits can be dug. Large trees provide much
greater benefits in terms of carbon sequestration, pollution mitigation, energy savings, storm water management,
and—perhaps most importantly—canopy coverage.
AREAS WITHIN URBAN VILLAGES:
The urban village strategy is a part of Seattle’s comprehensive plan and focuses on further developing the densest
neighborhoods of the city in order to absorb regional growth, improve delivery of services, increase the value of
public investments in infrastructure, and ensure a sustainable future for the City. Increasing the focus on planting
and maintaining trees within urban villages will help the city maintain and improve the quality of the natural
amenities within these areas. In urban villages, the social and environmental benefits of each tree are accessible to
a greater number of Seattle’s residents. Urban villages also have the most potential for pedestrian activity given
the transit-supportive land uses, higher residential densities and vital small business districts.
AREAS WITH RELATIVELY LOW CANOPY COVERAGE:
The neighborhood canopy category favors planting trees in neighborhoods (census tracts) with less than ten
percent canopy coverage, an area covering approximately one quarter of the city. Many city streets have
characteristics that constrain or prohibit tree planting, such as lack of curbs, narrow or missing planting strips,
overhead power lines, and underground utilities. As a result, some streets are candidates for new trees, while
others are not. When constraints to tree plantings are concentrated within neighborhoods, this can lead to
inequitable results. By focusing tree plantings in neighborhoods with relatively low canopy coverage, we are able

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to mitigate for this possibility by raising the visibility of available planting spaces where trees are most scarce.
While we may not be able to provide trees to all streets, we can provide trees to all neighborhoods.
AREAS NEAR HIGH-NEED POPULATIONS:
The high-need areas category accounts for areas with low automobile ownership, low average income, high
densities of people with disabilities, high rates of diabetes rates, low physical activity rates, and high obesity rates.
This attribute is based on the equity score developed in 2009 as a component part of the Pedestrian Master Plan
(PMP). Including this attribute in the PPA system facilitates SDOT Urban Forestry’s participation in improving
pedestrian access and walkability, as well as recognizing areas where planting trees may have the greatest benefits
to health.
The 2013 Tree Benefits Map separates this category into two levels: highest-need areas (equity scores of 10 or 15)
and high-need areas (equity scores of 20 or greater). This was done to captures some of the variation in equity
scores in the PMP. Future versions of the Tree Benefits Map may include different interpretations of the PMP
Social Equity Score (or different data sets) as indicators of social equity.
ATTRIBUTE PROCESSING AND MAP INTERPRETATION
After maps of each category or attribute area are prepared, they can be combined in to a single map that
demonstrates the intersections of these areas. Processing attributes into a single map involves four steps:
1) Create an ArcGIS feature class composed of 150x150 foot squares. Any square that does not intersect
Seattle’s right of way is eliminated.
2) Develop a scoring system that defines how each attribute will be weighted in the final map.
3) Assign scores to grid squares when they intersect an attribute layer.
4) Calculate a total score for or each square in a new field, called “PP_Score” (planting priority score).
The final product of this process is the Tree Benefits Map, composed of grid squares that are assigned colors
according to planting priority score (see Figure 1). In the 2013-2014 Tree Benefits Map, planting priority scores
range from 0 to 50. Although the Tree Benefits Map displays color information determined by a scale that is based
on the presence of attributes associated with tree benefits, it is not correct to say that it conveys quantitative
estimations of the benefits provided by street trees (i.e., a tree planted in a area with a score of 50 is not assumed
to produce twice the benefits provided by a tree planted in an area with a score of 25). Rather, the map shows
where areas that should be prioritized overlap. The map allows managers to easily identify clusters throughout the
city where we can correctly say, “In these areas, we have identified several reasons why it will be good to plant a
tree.” If managers deem some attributes more important than others, these preferences can be reflected in the
scores assigned to attributes.

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Figure 2 - Street Tree Spacing Map
Figure 1 The Tree Benefits Map (in green) is a visualization tool that helps SDOT determine where to
plant new street trees. Attribute maps are combined by determining weights, and summing them in a
matrix of 150x150 foot “grid squares.”
THE STREET TREE SPACING MAP
The Street Tree Spacing Map is designed to make the most current
information about street tree stocking levels readily available in a visual and
intuitive format. This is accomplished by running an automated GIS model
that joins information within the City’s street tree database to a map of the
City’s streets, based on spatial proximity. The output layer displays streets by
color according to stocking levels:
Fully planted (average tree spacing < 30 ft)
Planted (average tree spacing of 31-60 feet)
Underplanted (average tree spacing of 61-180 ft)
Very few or no trees (average tree spacing >180 ft)
Unlike the Tree Benefits Map, the Tree Spacing Map can be easily updated
without large investments of time spent developing a list of attributes and
the data layers used to represent them. Rather, a new Tree Spacing Map
may be produced on-demand.
Attribute Layers
Tree Benefits Map

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PRIORITY STREETS MAPPING
In combination, the Tree Benefits map and the Street Tree
Spacing map can be used to produce the Priority Streets map:
the intersection of potential benefits and available planting
space. The map is produced by following these steps in ArcMap:
1. Add the Tree Benefits Map and an updated Street Tree
Spacing Map to a GIS Project.
2. From the Tree Benefits Map, select features with high
PP_Score values. Create a new layer from this selection.
3. From the Tree Spacing Map, select features with low
stocking levels. Create a new layer from this selection.
4. Using the “select by location” tool, select the features
from the new streets layer that intersect the new
benefits layer.
5. Display the new streets layer over the original Tree
Benefits Map.
USING THE PRIORITY STREETS MAP
Once a Priority Street map is made, it can be used to support
work toward several goals of SDOT street tree and landscape
management activities.
IDENTIFYING PRIORITY STREET CLUSTERS
Identifying spatially-distinct clusters of priority streets (blue
circles in Figure 3) is the first step in creating a list of candidate
neighborhoods for street tree restoration projects. This initial list
is where the value of the PPA system begins to emerge, providing focal points for field visits, community
engagement activities, and other management and planning efforts. Using the clusters list, managers can develop
formal tools for evaluating the tradeoffs between pursuing planting projects in different neighborhoods. In the
example matrix shown in Table 1, clusters are compared according to additional information not captured in the
Tree Benefits map, in addition to PP_Score values.
Table 1 – An example of a matrix used to evaluate priority streets clusters generated by the PPA system. Values in the matrix are
hypothetical.
Neighborhood Community
Support
Available Space
for 100 + trees
Utility
Obstructions
PP_Score
Range
Cluster 1 Low Y Extensive 35-50
Cluster 2 Medium N Minimal 35-40
Cluster 3 Low Y Minimal 35-45
Cluster 4 High Y Moderate 40-45
… … … … …
Figure 3 - Intersection map showing priority streets
(red), and clusters (blue).

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LANDSCAPE MAINTENANCE
Clusters have the potential to inform street landscape and street tree management plans. Pruning, mulching,
watering, and mowing are all important actions carried out by the city, but the city cannot reach every tree every
year. Priority streets mapping will inform the development of future landscape and street tree management plans,
and provide guidance on where public (as opposed to private) ownership of trees in the right of way makes the
most sense.
STREET TREE ASSESSMENT AND MONITORING
Priority Streets represent the most important areas of the city for maintaining an accurate tree asset inventory.
Focusing limited capacity and resources for assessment activities in these areas will enhance the PPA system’s
ability to match available space with potential tree benefits.
STRATEGIC PARTNERSHIPS
Priority streets mapping helps SDOT UF access where street tree and landscape management activities may
intersect with other programs that impact the right of way. One of these programs, Seattle Neighborhood
Greenways, is explicitly included as an attribute in the Tree Benefits map, while others are not. These include the
Parklets program, Seattle Public Utility’s Green Stormwater Infrastructure (GSI) program
4
, and Seattle ReLeaf’s
Trees for Neighborhoods and Tree Ambassador programs. Ensuring that coordination between multiple projects
exists within these areas will protect and enhance the sustainability of natural amenities in Seattle. Additional
partnerships can be sought out with community groups, organizations, and businesses to enhance outreach
efforts. Priority streets, and especially street clusters, are excellent locations to seek out these opportunities.
4
Street trees support green storm water infrastructure (GSI) goals because they reduce storm water by intercepting rain before it reaches the
ground, recharging water holding capacity in soils, and reducing peak flows in creeks and streams. In order to avoid conflicts that can arise from
working in the same areas of the city, street tree planting program managers should identify which candidate areas and priority streets fall
within GSI priority areas. These areas are summarized in Appendix D.

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III. TOOLS FOR ANALYSIS
The PPAs objectively identify areas of the city where trees provide exceptional benefits to inform project design
and, hopefully, increase the overall value of public investment in street trees. However, because of the difficulties
involved in quantifying benefits that street trees provide to a city, measuring the overall impact PPAs is a
challenging endeavor. It will be useful to find alternative evaluation tools that will provide information about how
implementation of the PPA system will change the pattern of service delivery in the city. Evaluation of the PPA
system includes two main techniques:
1) Coverage analysis of tree benefit attributes
2) Evaluation of benefits captured by individual trees
COVERAGE ANALYSIS EXAMPLES
Coverage analysis of tree benefit attributes shows how much of the city is covered by each attribute and the
extent to which attributes overlap. This tells us how likely it is that a new tree planted in a random location will fall
within the boundaries of a specific attribute. Naturally, some attributes cover large spaces, while others are
relatively small.
Table 2 displays the portions of total map area covered by each attribute alone (figures in bold), and each attribute
in combination with all other attributes. For example, grid squares containing wetlands cover 3.4 percent of the
total area, while grid squares containing both wetland and riparian areas cover 1.6 percent of the total area.
Intersect probability tells us how likely it is that a tree planted randomly within the bounds of one attribute will
also exist within the bounds of another. In other words, it indicates how well each attribute predicts the existence
of other attributes, relative to its size. Highest-need areas are the strongest predictors, with over 23 percent of all
squares capturing other benefits. The poorest predictor is Tree Size potential, suggesting that by focusing plantings
only on streets that accommodate large trees, we are least likely to capture other benefits, relative to planting
within other attribute areas.
Wetlands
Riparian
Wildlife
Urban
Village
Greenways
LowCanopy
TreeSize
Need–high
Need–
highest
Intersect
Probability
Wetlands 0.034 0.016 0.012 0.003 0.003 0.002 0.005 0.005 0.002 0.171
Riparian 0.034 0.011 0.003 0.003 0.001 0.008 0.003 0.001 0.170
Wildlife 0.062 0.011 0.005 0.003 0.011 0.009 0.005 0.134
Urban Village 0.301 0.032 0.124 0.162 0.132 0.055 0.216
Greenway 0.115 0.031 0.084 0.023 0.008 0.208
Low Canopy 0.219 0.157 0.072 0.033 0.152
Tree Size 0.532 0.119 0.042 0.078
Need –highest 0.222 X 0.234
Need – high X 0.095 0.222
Table 2 – In this attribute distribution matrix for the 2013 Tree Benefits Map, attribute combinations with the highest
coverage appear in red, while combinations with less coverage appear in yellow (medium) and green (low). The numbers
represent the percentage of the city covered by the combination of attributes on each axis.

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Table 3 provides information on us what values we can expect to plant for, given a planting project that targets a
specific range of PP_Score values. For example, the Proposed Greenways attribute appears in 3 percent of grid
squares with PP_Score values of 0 to 10, 17 percent of squares with values of 15 to 20, and so on. At the highest
PP_Score levels, only 2 to 3 percent of the total area contains critical areas attributes (red box in Table 2). New
trees in these areas may provide the greatest benefits of all, given that they provide opportunities to plant for rare
attributes, while simultaneously supporting most others. We may also wish to know what ranges we should
consider designing projects for given the desire to plant for a particular value. For example, a PP_Score range of
25-30 provides the best chance of planting in close proximity to the highest need populations in the city (25
percent).
Table 3 - This Matrix show the percentages of PP_Score ranges that contain each of the attributes used in the
2013 Tree Benefits Map. Large percentages are displayed in red, with medium values displayed in yellow and
low values displayed in green.
PP_SCORE VALUES
ATTRIBUTES 0-10 15-20 25-30 35-40 45-50
Need-highest 0.02 0.13 0.25 0.20 0.19
Need-high 0.07 0.29 0.41 0.70 0.80
Tree Class Size 0.37 0.65 0.72 0.96 0.99
Neighborhood Canopy 0.03 0.23 0.58 0.87 0.99
Urban Villages 0.06 0.38 0.75 0.95 1.00
Proposed Greenways 0.03 0.17 0.23 0.27 0.97
Wetlands 0.03 0.05 0.02 0.02 0.02
Riparian Corridors 0.03 0.05 0.02 0.02 0.03
Wildlife Habitat 0.06 0.09 0.05 0.02 0.02
Portion of Total Grid 0.54 0.26 0.13 0.07 0.01
EXISTING TREE BENEFITS ANALYSIS EXAMPLES
The Tree Benefits Map may be used to evaluate the values of past planting projects. This is done by creating a
selection of trees (based on water year) in ArcMap, and joining the data within the Tree Benefits Map to each tree
that lies within it. Figure 4 shows the results of this analysis for 2714 BTG trees planted from 2011 to 2013,
revealing how some tree values have been systematically favored over others.
The most striking example of this is Tree Class Size. Over 95 percent of the trees planted within this period were
within areas identified as being suitable for large trees, a characteristic that applies to approximately half the city.
As Table 2 shows, the highest-need areas cover 9.5 percent of the city, while only 4.2 percent of the city is covered
by both the Highest-need and Tree Size attributes. In other words, by planting almost exclusively within areas that
include the Tree Size attribute, more than half of the Highest-need areas are excluded from consideration for new
trees.

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Figure 4 – The attributes represented by BTG trees planted from 2011 to 2013 (red) are compared to the percentage of
the Tree Benefits Map covered by each attribute (blue).
We can also ask whether past planting projects have produced more benefits than are provided by the average
grid square. Using the 2013 Tree Benefits Map, the answer is yes. The average PP_Score for all grid squares is
14.33, while the 2714 BTG trees planted from 2011 to 2013 produced benefits, as measured by the PP_Score, of
22.57. Once again, the PP_Score scale represents a rough measurement not of the actual benefits provided by
trees, but the number of reasons we have identified to plant trees within particular areas. On average, we have
captured a greater number of benefits (or, “reasons”) in past planting programs than we would have had locations
of new street trees been entirely random.
DEVELOPING SCORE ASSIGNMENTS
The results of these analyses depends not only on the number of attributes (i.e. benefits) that are captured by grid
squares and the trees planted within them, but also on how city managers decide to weight each attribute. The
weights assigned to attributes influence the PP_Score in each grid square, and therefore change which streets
become “priority streets” and which streets do not. In this way, decisions about scores change the way managers
visualize the data that they have deemed important. In the 2013 Tree Benefits Map, the critical areas attributes,
including wetlands, riparian zones, and wildlife corridors, and the High-need areas attribute (as opposed to the
Highest-need area attribute), were assigned scores of 5, while others were assigned scores of 10. Decisions on
score assignments are the result of a collaborative process involving a pilot mapping project and multiple
opportunities for SDOT staff to provide feedback on how attributes relate to the mission, goals, and responsibilities
of the city in managing street trees.
9.0%
31.3%
95.7%
51.0%
27.9% 25.2%
2.6% 0.4% 1.1% 1.1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Total Grid Proportion
BTG Trees 2011-2013

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IV. CONCLUSION
The PPA system is designed primarily to increase the level of benefits provided by public investments in street
trees in Seattle. This is accomplished by using two mapping tools, the Tree Benefits Map and the Tree Spacing
Map, as a framework for choosing optimal planting locations in the city. The framework is adaptable to emergent
issues and public input. As SDOT receives feedback both internally and from the wider community on the spatial
attributes used to define street tree benefits, this information may easily be integrated into future maps.
As the 2013-2014 Tree Benefits Map shows, tree planting projects conducted by SDOT Urban Forestry have
targeted areas where street trees provide greater than average benefits compared to the average city tree. Future
plantings can and will do better. In addition to providing intuitive tools for enhancing the environmental, social,
and economic value of street trees in Seattle, the process of implementing the PPA system leads to additional
benefits. These include identifying strategic opportunities and partnerships, guiding management of the street tree
inventory, and informing community outreach and education activities.
The tree benefits analyses in this report also show how one value—the potential to plant large trees—has
dominated past planting projects. Because it is the simplest and best indicator of urban forest coverage and
benefits, much of the discussion among urban forestry professionals and community stakeholders has centered on
this topic. Indeed, Seattle has set a strong and achievable goal of reaching 30 percent canopy coverage by 2037,
and some have suggested aggressively planting trees in single-family residential neighborhoods because these
areas are more likely to accommodate large trees. However, it is important to remember that this policy would
direct tree planting away from all other land uses in the city. This is an unnecessary cost. By taking advantage of
existing data resources maintained by SDOT, the PPA system supports the canopy goal without forsaking other
benefits.

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APPENDIX A—RECCOMENDATIONS FOR IMPLEMENTATION
The following flowchart recommends a process for implementing street tree planting projects using the PPA
system.
BEFORE PROJECT:
Evaluate results of previous planting project
Ensure that recently planted trees have been entered in the street tree database
Create a new Tree Spacing Map
Combine Tree Spacing and Tree Benefits maps to create a Priority Streets map
Identify candidate planting areas and the benefits associated with those areas
Identify overlaps between Priority Streets and GSI priority areas
Conduct field visits
Select project location
DURING PROJECT:
Distribute information to staff on the benefits associated with the project
Use benefits to inform outreach materials
Publish project information on Seattle.gov
AFTER PROJECT:
Enter new trees into street tree database
Quantify numbers of trees planted within each attribute area
Evaluate how workflow and policy changes may increase the benefits of future plantings
Pursue workflow and policy changes

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APPENDIX B—DISTRIBUTION MAPS OF TREE BENEFIT ATTRIBUTES
Proposed Greenways
Large Tree Potential
Low Neighborhood Canopy
Critical Areas Urban Villages

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APPENDIX C—GIS DATA AND SCORE ASSIGNMENT FOR 2013 TREE BENEFITS MAP
Attribute GIS Data Used Score Assignment Score
Wetlands DPD.wetlands Grid squares at intersection of data layer 5
Wildlife Habitat DPD.wildlife Grid squares at intersection of data layer 5
Riparian Zones DPD.ripcorr Grid squares at intersection of data layer 5
Greenways
Greenways polyline (still in
development)
Grid squares at intersection of data layer 10
Tree Size HANSEN_RPT.MVW_GIS_SDW
Grid squares at intersection with selection: FILLERTYPE = 'TR/PCC' OR FILLERTYPE
= 'PVCC' OR FILLERTYPE = 'SWALE' OR FILLERTYPE = 'TR/AC' OR FILLERTYPE =
'TR/BR' OR FILLERTYPE = 'TR/O' OR FILLERTYPE = 'LSCP' OR FILLERTYPE = 'UND'
AND FILLERWID >= 72
10
Urban Villages DPD.uvmfg_polygon Grid squares at intersection of data layer 10
Canopy Cover
DPR.UFCanopy
CENSUS.tract10_shoreline
Data layer created by calculating canopy coverage within each census tract as
percent of total area. Scores assigned to grid squares at intersection with
selection: pct_canopy < 0.10
10
High-Need
Areas
SDOT.Socioeconomic_Score
Grid squares at intersection with selection: SOEH_SCORE = 10 OR SOEH_SCORE =
15
Grid squares at intersection with selection: SOEH_SCORE = 20 OR SOEH_SCORE =
25 OR SOEH_SCORE = 30
5
10

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APPENDIX D – GSI PRIORITY AREAS

19. 19

20. 20

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APPENDIX D—PPA FACT SHEET
The following is a list of talking points resulting from the 2013-2014 PPA Mapping project:
The sites selected for SDOT BTG 1 street tree planting projects have yielded greater than average benefits.
95 percent of BTG 1 trees have been planted in areas identified as supporting large trees.
Planting only in areas that support large trees, the portions of other categories that may receive a tree are
reduced. Some areas are affected more than others:
o 15% of wetlands remain
o 24% of riparian zones remain
o 18% of wildlife areas remain
o 54% of urban villages remain
o 73% of proposed greenways remain
o 71% of low canopy areas remain
o 54% of high need areas remain
o 44% of highest need areas remain
Total benefits from plantings can be increased without changing the status quo of favoring large tree
areas. This can be done by ensuring that areas that are planted overlap with other values.
37.6 percent of large tree areas do not intersect with any other values.