United States

Department of

Agriculture

Forest Service

Northern

Research Station

General Technical

Report NRS-65

Urban and Community Forests

of the Pacifi c Region

California

Oregon

Washington

David J. Nowak

Eric J. Greenfi eld
Printed on Recycled Paper

Published by: For additional copies:

U.S. FOREST SERVICE U.S. Forest Service

11 CAMPUS BLVD SUITE 200 Publications Distribution

NEWTOWN SQUARE, PA 19073 359 Main Road

 Delaware, OH 43015

July 2010 Fax: (740) 368-0152

Visit our homepage at: http://www.nrs.fs.fed.us/

The Authors

DAVID J. NOWAK is a research forester and project leader, and ERIC J. GREENFIELD is 

a forester with the Forest Service’s Northern Research Station at Syracuse, NY.

Manuscript received for publication October 2009

Abstract

This report details how land cover and urbanization vary within the states of California, 

Oregon, and Washington by community (incorporated and census designated places), 

county subdivision, and county. Specifi cally this report provides critical urban and 

community forestry information for each state including human population characteristics 

and trends, changes in urban and community lands, tree canopy and impervious surface 

cover characteristics, distribution of land-cover classes, a relative comparison of urban 

and community forests among local government types, determination of priority areas for 

tree planting, and a summary of urban tree benefi ts. Report information can improve the 

understanding, management, and planning of urban and community forests. The data 

from this report is reported for each state on the CD provided in the back of this book, 

and it may be accessed by state at: http://www.nrs.fs.fed.us/data/urban.
CONTENTS

 Introduction 1

 Report Overview 2

 Urban Forest Attributes 2

 Summary 10

 Acknowledgments 10

 California’s Urban and Community Forests 11

 Oregon’s Urban and Community Forests 19

 Washington’s Urban and Community Forests 27

 Literature Cited 35

 Appendix 38
GTR-NRS-65 1

INTRODUCTION

As part of the Forest and Rangeland Renewable Resources Planning Act of 1974, the 

fi rst national assessment of urban forests was completed in 2000 (Dwyer et al. 2000, 

Nowak et al. 2001b). This assessment used 1-km resolution Advanced Very-High 

Resolution Radiometer (AVHRR) data (Zhu 1994) and 1990 U.S. Census Bureau 

(2007) population and geographic data to assess urban tree cover. The assessment 

concluded that urban areas in the conterminous United States doubled in size 

between 1969 and 1994 and covered 3.5 percent of the total land area. Urban areas 

were estimated to contain approximately 3.8 billion trees with an average tree canopy 

cover of 27 percent.

To update this fi rst report, higher resolution (30 m) tree canopy and impervious 

surface cover maps were used (from 2001 Landsat satellite imagery and published 

in 2007) (Homer et al. 2007, U.S. Geol. Surv. 2007) in conjunction with 1990 and 

2000 census and geographic data (1:5,000,000 scale cartographic boundary fi les) 

(U.S. Census Bureau 2007) to assess current urban and community forest attributes. 

These results are being published for each of the lower 48 United States to provide 

information on urban change and state-specifi c urban and community forestry data.

This report includes information for the following states: California, Oregon, and 

Washington.

Data are reported for the state, county, county subdivision, and community 

jurisdictions. The jurisdictional units used in this report are derived from U.S. Census 

(2007) geographic data and defi ned legal or statistical divisions. “County”1

 refers to 

the primary subdivision within states. “County subdivisions” are primary divisions 

of a county and are statistically equivalent entities for the reporting of census data. 

They include census county divisions (CCD), census sub areas, minor civil divisions 

(MCD), and unorganized territories. “Communities” are incorporated and census 

designated places, and consolidated cities (U.S. Census Bureau 2007). For detailed 

defi nitions, see http://www.census.gov/geo/www/cob/cs_metadata.html (2007).

1

The primary legal divisions of most states are termed “counties.” In Louisiana, these 

divisions are known as “parishes.” In four states (Maryland, Missouri, Nevada, and Virginia), 

there are one or more incorporated places that are independent of any county organization 

and thus constitute primary divisions of their states; these incorporated places are known as 

“independent cities” and are treated as equivalent to counties for statistical purposes. (For 

some statistical purposes they may be treated as county subdivisions and places.) The District 

of Columbia has no primary divisions, and the entire area is considered equivalent to a county 

for statistical purposes. (http://www.census.gov/geo/www/cob/co_metadata.html, 2007)
2 GTR-NRS-65

REPORT OVERVIEW

The information in this report can aid local and 

regional managers and planners of urban and 

community forest resources. This report provides 

urban and community forest reference information 

and data from the state to local level on the following 

attributes related to the urban and community forest 

resource:

• Human population characteristics and trends

• Urban and community land

• Tree canopy cover characteristics 

• Impervious surface cover characteristics

• Classifi ed land-cover characteristics

• Relative comparisons of urban and community 

forests 

• Priority areas for tree planting

• Urban tree benefi ts

Information in this report can be used by urban and 

community forestry professionals to:

• Understand general land-cover characteristics 

and urbanization trends at several geographic 

scales

• Compare tree canopy cover among similar 

communities

• Determine areas of greatest growth and areas of 

highest tree planting priority

• Relate urban and community forests to pollution 

removal and carbon storage

• Promote more detailed and/or locally appropriate 

urban and community forest inventories, 

censuses, or fi eld surveys (e.g., i-Tree – 

www.itreetools.org) 

• Establish local to statewide standards related to 

urban and community forestry

• Support urban and community forestry programs 

• Improve urban and community forest 

management and planning

The remainder of this section details how information 

was derived for each attribute reported for the urban 

and community areas. The subsequent state summaries 

detail the fi ndings for each state in this region. Most 

tables for each state are not given in this report, rather 

they can be found on the CD provided with this report 

or accessed at: http://www.nrs.fs.fed.us/data/urban.

URBAN FOREST ATTRIBUTES

Human Population Characteristics and 

Trends

Human population and population density changes 

over time, and geographic distribution are important 

measurements of the urban environment because 

human populations are an integral part of community 

and urban forest dynamics. Within divisions of state, 

county, county subdivision, and community, total 

population, population changes from 1990 to 2000 and 

population density are detailed based on U.S. Census 

data (U.S. Census Bureau 2007).

Urban and Community Land

Two geographic defi nitions overlap: “community” 

and “urban”. The defi nition of community is based 

on jurisdictional or political boundaries delimited by 

U.S. Census defi nitions of places (U.S. Census Bureau 

2007). Community lands are places of established 

human settlement that may include all, some, or no 

urban land within their boundaries.

The defi nition of urban is based on population density 

as delimited using the U.S. Census Bureau’s (2007) 

defi nition: all territory, population, and housing units 

located within urbanized areas or urban clusters. 

Urbanized area and urban cluster boundaries 

encompass densely settled territories, which are 

described by one of the following:

• One or more block groups or census blocks with 

a population density of at least 386.1 people/ 

km2

 (1,000 people/mile2)

• Surrounding block groups and census blocks 

with a population density of 193.1 people/km2

(500 people/mile2

)

• Less densely settled blocks that form enclaves 

or indentations, or are used to connect 

discontinuous areas
GTR-NRS-65 3

More specifi cally, urbanized areas consist of territory 

with 50,000 or more people. Urban clusters, a concept 

new to the 2000 Census, consist of territory with at 

least 2,500 people but fewer than 50,000 people. This 

new defi nition tends to be more restrictive than the 

1990 U.S. Census urban defi nition and encompasses 

many areas typically considered suburban. The 2000 

Census defi nition of urban was applied to 1990 Census 

geographic data to analyze change in urban land 

between 1990 and 2000 (Nowak et al. 2005).

As urban land reveals the more heavily populated areas 

(population density-based defi nition) and community 

land indicates both urban and rural (i.e., non-urban) 

communities that are recognized by their geopolitical 

boundaries (political defi nition), both defi nitions 

provide information related to human settlements and 

the forest resources within those settlements. As some 

urban land exists beyond community boundaries and 

not all community land is urban (i.e., communities 

are often a mix of urban and rural land), the category 

of “urban or community” was created to understand 

forest attributes accumulated by the union of these 

two defi nitions. The “urban or community” term used 

throughout this report encompasses both urban land 

and land in communities.

Percent urban land is a ratio of urban land over total 

land within a census geographic division, and percent 

community land is a ratio of community land over 

total land within the geopolitical unit. In addition, 

changes in urban land and changes in community land 

are reported between 1990 and 2000.

For each state, Tables 1 through 4 summarize the 

population, and urban and community land attributes 

for the state, communities, county subdivisions, and 

counties respectively (CD and http://www.nrs.fs.fed.

us/data/urban).

Tree Canopy Cover Characteristics

Tree canopy cover is a critical measure of the urban 

and community forest resource. Tree canopy cover 

gives a broad indication of the overall forest resource 

and its associated benefi ts. To assess urban and 

community land cover characteristics, the multiresolution land characteristics consortium’s National 

Land Cover Database (NLCD) was used (Homer et 

al. 2004, U.S. Geol. Surv. 2007, Yang et al. 2003). 

The NLCD, released in early 2007, was processed 

from 2001 Landsat satellite imagery and provides 

estimates of percentage tree canopy and impervious 

surface cover within 30-m pixels or cells across the 

state. The tree canopy percentages in this report are 

calculated using the land area (not including water) 

of the geopolitical units derived from the U.S. Census 

cartographic boundary data and NLCD. In addition 

to percentage tree cover, four other canopy cover 

attributes, derived from the same data, were assessed:

• Tree canopy cover per capita—Tree canopy 

cover (m2

) divided by the number of people 

within the area of analysis.

• Total green space—Total area minus impervious 

and water cover (ha). This attribute estimates 

pervious cover (i.e., grass, soil, or tree-covered 

areas).

• Canopy green space—Tree cover divided by 

total green space (percent). This value is the 

proportion of the total green space that is fi lled 

by tree canopies.

• Available green space—Total green space minus 

tree canopy cover (ha). This value is the amount 

of grass and soil area not covered with tree 

canopies and potentially available for planting.

Impervious Surface Cover 

Characteristics

Similar to tree cover, impervious surface cover 

provides another piece of valuable information 

related to the urban environment. Impervious surface 

cover gives an indication of an area’s developed 

hardscape, which has important infl uences on urban 

air temperatures and water fl ows and also yields 

information on limitations to urban tree cover. 

Impervious surface cover also was derived from 

the NLCD database (U.S. Geol. Surv. 2007). The 

impervious surface cover percentages in this report are 

calculated using the land area (not including water) 

of the geopolitical units derived from the U.S. Census 
4 GTR-NRS-65

cartographic boundary data and NLCD. Impervious 

surface per capita is calculated from NLCD 2001 and 

U.S. Census data.

For each state, Tables 1, and 5 through 7 summarize 

the tree canopy and impervious surface cover attributes 

for the state, communities, county subdivisions, and 

counties respectively (CD and http://www.nrs.fs.fed.

us/data/urban).

Classifi ed Land-cover Characteristics

Land-cover types also are summarized using 2001 

Landsat satellite data that were classifi ed with the U.S. 

Geological Survey land cover categorization scheme 

based on a modifi ed Anderson land-cover classifi cation 

(U.S. Geol. Surv. 2007). Land area, tree canopy cover, 

and available green space within generalized land 

cover categories vary among communities, county 

subdivisions, counties, and state. The percentages 

are calculated from the NLCD 2001 and U.S. Census 

cartographic boundary data. The land-cover categories 

defi ned here are derived from established NLCD 2001 

land-cover classes. These generalized land-cover 

categories or types may not be present in some states.

• Developed—NLCD classes 21 (developedopen space), 22 (developed-low intensity), 

23 (developed-medium intensity), and 24 

(developed-high intensity) 

• Barren—NLCD class 31 (barren land [rock/

sand/clay])

• Forested—NLCD classes 41 (deciduous forest), 

42 (evergreen forest), and 43 (mixed forest)

• Shrub/Scrub—NLCD class 52 (shrub/scrub)

• Grassland—NLCD class 71 (grassland/

herbaceous)

• Agriculture—NLCD classes 81 (pasture/hay) 

and 82 (cultivated crops)

• Wetland—NLCD classes 90 (woody wetlands) 

and 95 (emergent herbaceous wetlands)

For each state, Tables 8 through 10 summarize the 

classifi ed land-cover characteristics for communities, 

county subdivisions, and counties and state 

respectively (CD and http://www.nrs.fs.fed.us/data/

urban).

Relative Comparisons of Tree Cover

A question commonly asked in evaluating the urban 

and community forest resource is, “How does my 

community compare with other communities?”

To help answer this question, tree canopy cover was 

compared among the counties, county subdivisions, 

and communities relative to other areas with 

comparable population density and within the same 

NLCD mapping unit (ecoregion). For this comparison, 

seven population density classes were established:

• Density class 1 — 0 to 38.6 people/km2

(0 to 99.9 people/mile2

)

• Density class 2 — 38.7 to 96.5 people/km2

(100 to 249.9 people/mile2

)

• Density class 3 — 96.6 to 193.1 people/km2

(250 to 499.9 people/mile2

)

• Density class 4 — 193.2 to 289.6 people/km2

(500 to 749.9 people/mile2

)

• Density class 5 — 289.7 to 386.2 people/km2

(750 to 999.9 people/mile2

) 

• Density class 6 — 386.3 to 1931.2 people/km2

(1000 to 4999.9 people/mile2

) and 

• Density class 7 — 1931.3 or greater people/km2

(5000 or greater people/mile2

)

Mapping zones were delimited within the NLCD to 

increase classifi cation accuracy and effi ciency (Fig. A). 

The mapping units represent relatively homogeneous 

ecological conditions (Homer and Gallant 2001). 

To locate geopolitical units within a mapping zone, 

centroid (geometric center) points of the local 

governments were used.

For three or more geographic units in the same 

mapping zone and population density class, a 

standardized tree canopy score based on the range of 

values within that zone and class was assigned to each 

unit. The standardized score is calculated as:

Standardized score = (tree canopy percent of unit 

– minimum tree canopy percentage in class)/range of 

tree canopy percent in class.
GTR-NRS-65 5

Communities, county subdivisions, and counties were 

assigned to one of the following categories based on 

their standardized score:

• Excellent—Standardized score of 0.9 to 1.0

• Very Good—0.7 to 0.89

• Good—0.5 to 0.69

• Fair—0.3 to 0.49

• Poor—0 to 0.29

To help understand the variability of tree cover, 

minimum, median, maximum, and weighted 

mean values for percent tree canopy cover in each 

population density class of each political subdivision 

are reported in Table 11 for each mapping zone 

(CD and http://www.nrs.fs.fed.us/data/urban). This 

information can be used to understand the actual range 

and values used for the assessment.

For each state, Tables 12 through 14 summarize the 

urban and community forest ratings for communities, 

county subdivisions, and counties respectively (CD 

and http://www.nrs.fs.fed.us/data/urban).

Figure A.—The mapping zones of the continental United States relative to states and land cover (NLCD 2001).

Priority Areas for Tree Planting

NLCD (U.S. Geol. Survey 2007) and 2000 U.S. 

Census data (2007) were used to produce an index that 

prioritizes tree planting areas for communities, county 

subdivisions, and counties. An index was developed 

to help identify areas with relatively low tree canopy 

cover and high population density (high priority 

tree-planting areas). This index provides one form 

of prioritization. States and local governments may 

design their own prioritization method incorporating 

individual and diverse value systems. The index used 

in this report combines three criteria.

• Population density—The greater the population 

density, the greater the priority for tree planting

• Canopy green space—The lower the value, the 

greater the priority for tree planting

• Tree canopy cover per capita—The lower the 

amount of tree canopy cover per person, the 

greater the priority for tree planting

9

4

51

46

37

44

1

38

7

12

34

41

49

6

29

35

39

32

33

8

31

26 55

47

10

36

13

43

50

30

28

27

20

24

42

40

22

23

17

66

3

58

5

60 61

25

19

15

2

18

56

14

62

63

52

65

45 54

64

53

48

59

21

16

57
6 GTR-NRS-65

Each criterion above was standardized2 on a scale of 

0 to 1, with 1 representing the maximum population 

density and minimum canopy green space and tree 

cover per capita. The standardized values were 

weighted to produce a combined score: 

I = (PD * 40) + (CG * 30) + (TPC * 30)

Where I is the combined index score 

PD is the standardized population density value 

CG is the standardized canopy green space value, and 

TPC is the standardized tree cover per capita value. 

The combined score was standardized again and 

multiplied by 100 to produce the planting priority index. 

The tree planting priority index (PPI) ranks each state’s 

communities, county subdivisions, and counties with 

values from 100 (highest priority) to 0 (lowest priority). 

This index is a type of “environmental equity” index 

with areas of higher human population density and 

lower canopy green space and tree cover per capita 

tending to get the higher index value.

For each state, Tables 15 through 17 summarize the 

tree planting priority index for communities, county 

subdivisions, and counties respectively (CD and 

http://www.nrs.fs.fed.us/data/urban).

Urban Tree Benefi ts

Urban and community forests are important for human 

and ecological health (Nowak and Dwyer 2007). The 

benefi ts ascribed to urban and community trees include:

2

Standardized value for population density (PD) was 

calculated as PD=(n–min)/r, where PD is the value 0-1, 

n is the value for the geopolitical unit (population/km2), 

min is the minimum value for all units, and r is the range 

of values among all units (maximum value – minimum 

value). Standardized value for canopy green space (CG) was 

calculated as CG=(max–n)/r, where CG is the value 0-1, 

max is the maximum value for all geopolitical units, n is the 

value for the unit (tree canopy cover m2/total green space 

m2), and r is the range of values. Standardized value for tree 

cover per capita (TPC) was calculated as TPC=(max–n)/r, 

where TPC is the value (0-1), max is the maximum value for 

all geographic units, n is the value for the geopolitical unit 

(m2/capita), and r is the range of values among all units.

• Carbon storage and sequestration

• Air pollution removal

• Surface air temperature reduction 

• Reduced building energy use

• Absorption of ultraviolet radiation

• Improved water quality

• Reduced noise pollution

• Improved human comfort

• Increased property value

• Improved human physiological and 

psychological well-being

• Improved aesthetics

• Improved community cohesion 

To understand the contribution and magnitude of the 

forest resource in urban or community areas, the total 

number of trees, carbon storage and annual carbon 

uptake (sequestration), air pollution removal, and the 

associated dollar values for carbon and air pollution 

benefi ts are estimated.

Carbon sequestration and storage values were 

estimated from tree cover (m2

) multiplied by average 

carbon storage (9.1 kg C/m2

), and sequestration 

(0.3 kg C/m2

) density values derived from several U.S. 

communities (e.g., Nowak and Crane 2002). Monetary 

values associated with urban tree carbon storage and 

sequestration were based on the 2001-2010 projected 

marginal social cost of carbon dioxide emissions, 

$22.8/t C (Fankhauser 1994). The number of urban 

and community trees was estimated in a similar 

manner multiplying tree canopy cover (m2

) by average 

tree density per hectare of canopy cover from several 

U.S. cities (Table A).

Air pollution removal estimates are derived from the 

Urban Forest Effects (UFORE) model (Nowak and 

Crane 2000) and 2000 weather and pollution data 

(National Climatic Data Center 2000, U.S. EPA 2008). 

The UFORE model was used to integrate hourly 

pollution and weather data with urban or community 

tree cover data to estimate annual pollution removal 

in each state (Nowak and Crane 2000, Nowak et al. 

2006d).
GTR-NRS-65 7

To estimate pollution by urban trees in each state, state 

pollutant fl ux rates (grams of pollution removal per 

square meter of canopy per year) were derived from 

a study of national pollution removal by urban trees 

for the year 1994 (Nowak et al. 2006d). As pollution 

concentrations vary through time, the 1994 fl ux 

rates were adjusted to 2000 values based on average 

regional pollution concentration changes between 

1994 and 2000 (U.S. EPA 2003). As

fl ux rate = deposition velocity * pollution 

concentration,

the ratio of the pollution concentration between years 

was used to update the fl ux rate. Arithmetic mean 

concentration values were used for nitrogen dioxide, 

particulate matter less than 10 microns, and sulfur 

dioxide, 2nd Max. 8-hr average for carbon dioxide, 

and 4th Max. 8-hr average for ozone, to determine 

the ratio of change between 1994 and 2000 (U.S. EPA 

2003). The new 2000 fl ux rates were multiplied by 

urban or community tree cover in the state to estimate 

total pollution removal by trees.

Pollution removal dollar value estimates were 

calculated using 1994 national median externality 

values used in energy decision making (Murray et 

al. 1994, Ottinger et al. 1990). The 1994 values were 

adjusted to 2007 dollars based on the producer price 

index (U.S. Dept. of Labor 2008). These values, in 

dollars/metric ton (t) are: 

• Nitrogen dioxide (NO2

) = $9,906/t

• Particulate matter less than 10 microns (PM10) = 

$6,614/t

• Sulfur dioxide (SO2

) = $2,425/t

• Carbon monoxide (CO) = $1,407/t

Table A.—Average number of trees, carbon storage, and carbon 

sequestration rates per unit of canopy cover for several U.S. cities

a Unpublished data analyzed using UFORE model

b Nowak 1994a,b

c

 Nowak et al. 2006a

d Nowak et al. 2006b

e Nowak et al. 2007a

f

 Nowak et al. 2007b

g Nowak et al. 2007c

h Nowak et al. 2001a

i

 Nowak 1993; Nowak and Crane 2002

j

 Nowak et al. 2006c

 Carbon

 Trees Storage Sequestration

City (no./ha cover) (kg C/m2 cover) (kg C/m2 cover)

Atlanta, GA a 751.5 9.7 0.3

Baltimore, MD a 598.1 12.3 0.3

Boston, MA a 371.7 9.1 0.3

Chicago, IL b 618.0 12.9 n/a

Casper, WY c 252.8 7.0 0.2

Freehold, NJ a 275.0 10.4 0.3

Jersey City, NJ a 308.7 4.4 0.2

Minneapolis, MN d 245.5 5.7 0.2

Moorestown, NJ a 547.9 9.9 0.3

Morgantown, WV a 829.6 10.6 0.3

New York, NY e 312.0 7.3 0.2

Philadelphia, PA f

 394.3 9.0 0.3

San Francisco, CA g 468.1 12.3 0.3

Syracuse, NY h 583.1 10.5 0.3

Oakland, CA i 570.0 5.2 n/a

Washington, DC j

 423.4 10.4 0.3

Woodbridge, NJ a 557.3 8.2 0.3

Mean 476.9 9.1 0.3
8 GTR-NRS-65

Externality values for ozone (O3) were set to equal the 

value for NO2

. Externality values can be considered 

the estimated cost of pollution to society that is not 

accounted for in the market price of the goods or 

services that produced the pollution.

For each state, Table 1 summarizes carbon storage and 

air pollution removal estimates for urban, community, 

and urban or community trees statewide.

Data Accuracy and Application

The data presented in this report yield the most 

comprehensive and up-to-date assessment of 

continental U.S. urban and community forests. 

The data allows for relative comparisons among 

geographies and provides baseline information for 

assessing relative changes in urban and community 

forest cover in the future. As stated previously, tree 

cover information was based on fi ner resolution data 

than used in the original urban forest assessment 

(Dwyer et al. 2000). As the methodologies for 

quantifying tree cover have changed between the 

original and current assessment, evaluating changes 

is not possible since the detected changes could 

be caused by either actual landscape changes or 

differences in methodology.

The U.S. Census generalized cartographic boundary 

data are a simplifi ed and smoothed extracts of the 

Topologically Integrated Geographic Encoding and 

Referencing (TIGER) database, with a target scale 

range of 1:5,000,000 (U.S. Census Bureau 2007). 

Because of this scale and generalization, border 

simplifi cation impacts attribute measurements that are 

derived from the boundary data, especially for small 

areas and at the local scale. In particular, percentages 

(unitless ratios) generated from attribute measurements 

made for the smallest communities or county 

subdivisions may be under- or overstated depending 

upon the relative location of the smoothed border of 

the geopolitical unit.

While the 2001 NLCD is a substantial improvement 

over the 1991 AVHRR data (30-m versus 1-km 

resolution), it also has local-scale data and application 

limitations. Initial tree canopy cover results revealed 

mean absolute errors (mean of the absolute difference 

between predicted and actual values) from 8.4 percent 

to 14.1 percent, with correlation coeffi cients between 

predicted and actual values ranging from 0.78 to 

0.93. Impervious surface cover results revealed mean 

absolute errors from 4.6 percent to 7 percent, with 

r-values from 0.83 to 0.91 (Homer et al. 2004).

A more recent analysis of 127 community and 

20 county geographies sampled throughout the 

continental United States compared NLCD tree 

canopy and impervious surface cover estimates 

with high resolution (1-m or less resolution) aerial 

photo-interpreted estimates. This analysis revealed 

that NLCD underestimates both tree canopy and 

impervious surface cover compared to photointerpreted values. NLCD underestimates of tree 

cover vary by mapping zone, while underestimates of 

impervious surface cover, which are relatively minor, 

varies by population density (Greenfi eld et al. 2009). 

These fi ndings are consistent with Walton (2008), who 

found a consistent under-prediction bias for the 2001 

NLCD derived tree canopy cover values in census 

places (communities) of western New York.

The tree cover and impervious cover data given in this 

report are directly from the NLCD database. To help 

understand the potential underestimate in the cover 

values, each U.S. mapping zone was photo-interpreted 

using Google Earth images3

. Table B provides a 

comparison of results from NLCD versus photointerpreted data for mapping zones applicable to this 

collection of states.

Comparisons between NLCD impervious surface 

cover estimates and photo-interpreted values were 

not reported because differences were related to 

population density, which can vary signifi cantly among 

geographic units. Despite the potential underestimates 

in tree canopy cover values, relative comparisons 

3

Nowak, D.J.; Greenfi eld, E.J. Tree and impervious cover 

in the conterminous United States: Testing of NLCD cover 

estimates by mapping zone. In review. 
GTR-NRS-65 9

Margin Signifi cant

Mapping zone a n b NLCD c

 PI d Difference e of error f difference g

 1 488 57.7% 65.4% 7.7% 3.9% Yes

 2 998 53.0% 69.7% 16.8% 2.2% Yes

 3 998 43.9% 72.4% 28.5% 2.4% Yes

 4 1000 11.5% 37.4% 25.9% 2.6% Yes

 5 1000 5.5% 11.0% 5.5% 1.9% Yes

 6 996 35.6% 58.9% 23.3% 2.8% Yes

 7 995 40.7% 61.9% 21.2% 2.8% Yes

 8 639 1.3% 3.2% 1.8% 1.3% Yes

 9 903 12.6% 18.9% 6.3% 2.6% Yes

 10 965 47.8% 72.1% 24.3% 2.6% Yes

 12 998 5.9% 11.2% 5.3% 2.0% Yes

 13 983 0.7% 8.4% 7.7% 1.8% Yes

 14 671 1.0% 20.3% 19.3% 3.1% Yes

 18 983 2.2% 9.1% 7.0% 1.9% Yes

a NLCD mapping zones e PI value minus NLCD value b Number of photo-interpreted sample points f

 95% confi dence interval of PI value c

 Percent tree canopy value derived from NLCD data g Signifi cant difference between NLCD and PI values if NLCD value d Percent tree canopy derived from photo-interpreted data is outside of 95% confi dence interval of PI value

Percent tree canopy cover

Table B.—Comparison of NLCD versus photo-interpretation (PI) derived values of percent tree canopy 

cover by NLCD mapping zones

of tree cover among geographies in this report (e.g., 

planting priority index and the ratings of excellent to 

poor for local government tree cover) are reasonable 

as the under-prediction of tree cover is fairly 

consistent within each mapping zone. However, it is 

important to note that the tree canopy and impervious 

surface cover could be underestimated, as well as 

their associated ecosystem services and values. A 

forthcoming analysis will better assess the accuracy of 

the NLCD cover maps (Homer et al. 2007), but these 

maps and data provide comprehensive, consistent, 

and comparable estimates (with an inherent degree of 

error and uncertainty) of tree canopy and impervious 

surface cover to help urban and community forest 

management, planning and policy making. Higher 

resolution cover data may provide more accurate 

results at the local scale, but the NLCD cover maps 

provide a cost-effective means to consistently 

assess and compare the relative differences of urban 

cover types regionally. For more refi ned and locally 

appropriate data, local fi eld or high resolution 

(1 m or less) image analyses are recommended 

(e.g., i-Tree – www.itreetools.org; UTC – 

www.nrs.fs.fed.us/urban/utc).

Because of limited urban and community forest fi eld 

data, data from several urban and community forests 

were used to estimate the number of trees and carbon 

storage by trees. These coarse estimates reveal that 

urban and community forests contain a large number 

of trees and provide signifi cant environmental benefi ts. 

Field data are needed from all states to help improve 

these estimates as well as to estimate other forest 

effects (e.g., building energy conservation and changes 

in stream fl ow and water quality). Data from longterm monitoring of urban and community forests used 

in conjunction with satellite-based cover maps will 

provide essential information to assess forest health 

and change, and to improve urban and community 

forest management.

Practical Applications for Managers

The data from this report can be used to aid urban 

forest management at both the state and local levels. 

Data can be used to:

• Determine the extent, magnitude, and variation 

in the urban and community forestry resource
10 GTR-NRS-65

• Determine areas of greatest population growth, 

urbanization, and development (sprawl) to direct 

urban and community forestry to minimize 

negative impacts and maximize environmental 

benefi ts 

• Evaluate existing tree canopy, impervious 

surface cover, and available planting space 

(available green space) to direct current and 

future urban and community forestry efforts 

such as planting programs

• Compare tree canopy cover for similar 

geopolitical units and set tree canopy goals 

• Prioritize tree planting based on population 

density, tree canopy green space, and tree 

canopy cover per person

• Understand the pollution removal and carbon 

storage benefi ts of urban and community forests

• Promote more detailed and/or locally 

appropriate urban and community forest 

inventories, censuses, or fi eld surveys 

(e.g. i-Tree – www.itreetools.org)

• Establish statewide to local standards related to 

urban and community forestry (e.g., establishing 

minimum goals of percent canopy green space 

or tree cover per capita and directing resources 

so that communities can reach the minimum 

standards)

• Improve urban and community forest 

management and cost estimation by providing 

an estimate of the number of trees in each 

geopolitical unit (i.e., urban area size (ha) *

percent tree cover * 477 trees/ha, or local tree 

density information from local data)

• Guide policy decisions related to urban sprawl 

and urban and community forest management

SUMMARY

The data presented in this report provide a better 

understanding of urban and community forests. 

This information can be used to advance urban and 

community forest policy and management that could 

improve environmental quality and human health 

throughout the state. The following sections detail 

specifi c urban and community forestry data for the 

states in this regional report.

ACKNOWLEDGMENTS

This research was funded, in part, by the U.S. Forest 

Service’s RPA Assessment Staff, State and Private 

Forestry’s Urban and Community Forestry Program, 

and Northeastern Area State and Private Forestry. 

Thanks also goes to Chris Sorrentino for assistance 

with report compilation, Nana Efua Imbeah for 

assistance with data processing, and Mike Boarman 

for assistance with image processing.
GTR-NRS-65 California 11

Statewide Summary

Urban or community land in California comprises about 8.6 percent of the state 

land area in 2000, an increase from 7.5 percent in 1990. Statewide tree canopy 

cover averages 18.0 percent and tree cover in urban or community areas is about 

11.4 percent, with 20.1 percent impervious surface cover and 14.3 percent of the 

total green space covered by tree canopy cover. Statewide, urban or community 

land in California has an estimated 188.5 million trees, which store about 

36.0 million metric tons of carbon ($820.8 million), and annually remove about 

1.2 million metric tons of carbon ($27.0 million) and 48,280 metric tons of air 

pollution ($392.3 million) (Table CA-1).

Tables CA-2 through CA-17 are not printed in this report but are available on the 

CD located on the inside back cover and at http://nrs.fs.fed.us/data/urban.

CALIFORNIA’S URBAN 

AND COMMUNITY FORESTS
12 GTR-NRS-65 California

a Urban land is based on population density and was delimited using the United States Census defi nitions of urbanized areas and urban clusters. b Community 

land is based on jurisdictional or political boundaries of communities based on United States Census defi nitions of incorporated or census designated places. c

 Urban or communities is land that is urban, community, or both. Communities may include all, some, or no urban land within their boundaries. d Canopy green 

space is the tree canopy cover divided by total green space. e Total green space (TGS) is total area – impervious surface cover – water. f Available green space 

(AGS) is total green space – tree canopy cover (if the calculated value is less than 0, then value set at 0). 

California Statewide Urban a Community b

 Urban or

Community c

Population

2000 33,871,648 31,989,663 31,171,082 n/a

1990 29,760,021 27,571,321 26,688,792 n/a

% Change (1990-2000) 13.8 16.0 16.8 n/a

% Total population (2000) 100.0 94.4 92.0 n/a

Total area 

km2 (2000) 423,969.6 20,695.7 30,929.8 35,168.9

km2 (1990) 423,969.6 20,514.7 24,903.9 30,790.4

% Change (1990-2000) 0.0 0.9 24.2 14.2

Land area 

km2 (2000) 404,362.1 20,512.8 30,402.5 34,596.8

% Land area (2000) 100.0 5.1 7.5 8.6

km2 (1990) 404,362.1 20,431.8 24,455.2 30,328.2

% Land area (1990) 100.0 5.1 6.0 7.5

% Change (1990-2000) 0.0 0.4 24.3 14.1

Population density 

 (people/land area km2)

2000 83.8 1,559.5 1,025.3 n/a

1990 73.6 1,349.4 1,091.3 n/a

% Change (1990-2000) 13.8 15.6 -6.1 n/a

Tree canopy cover (2000)

km2 72,872.4 1,378.5 3,564.6 3,952.5

% Land area 18.0 6.7 11.7 11.4

Per capita (m2/person) 2,151.4 43.1 114.4 n/a

% Canopy green space d 18.4 9.7 15.0 14.3

Total green space (2000) e km2 395,949.0 14,148.4 23,822.7 27,633.9

% Land area 97.9 69.0 78.4 79.9

Available green space (2000) f km2 323,081.0 12,772.4 20,260.9 23,684.5

% Land area 79.9 62.3 66.6 68.5

Impervious surface cover 

 (2000)

km2 8,413.1 6,364.4 6,579.8 6,962.9

% Land area 2.1 31.0 21.6 20.1

Per capita (m2/person) 248.4 199.0 211.1 n/a

Urban tree benefi ts (2000)

Estimated number of trees n/a 65,700,000 170,000,000 188,500,000

Carbon

Carbon stored (metric tons) n/a 12,500,000 32,400,000 36,000,000

Carbon stored ($) n/a $285,000,000 $738,700,000 $820,800,000

Carbon sequestered (metric tons/year) n/a 414,000 1,069,000 1,186,000

Carbon sequestered ($/year) n/a $9,439,000 $24,373,000 $27,041,000

Pollution

CO removed (metric tons/year) n/a 482 1,245 1,381

CO removed ($/year) n/a $677,500 $1,752,000 $1,942,600

NO2 removed (metric tons/year) n/a 2,666 6,892 7,642

NO2 removed ($/year) n/a $26,404,600 $68,276,200 $75,705,300

O3 removed (metric tons/year) n/a 6,973 18,031 19,993

O3 removed ($/year) n/a $69,075,000 $178,613,000 $198,048,000

SO2 removed (metric tons/year) n/a 896 2,317 2,569

SO2 removed ($/year) n/a $2,173,000 $5,618,900 $6,230,300

PM10 removed (metric tons/year) n/a 5,822 15,056 16,694

PM10 removed ($/year) n/a $38,509,800 $99,577,600 $110,412,600

Total pollution removal (metric tons/year) n/a 16,840 43,540 48,280

Total pollution removal ($/year) n/a $136,800,000 $353,800,000 $392,300,000

Table CA-1.—Statewide summary of population, area, population density, tree canopy and impervious surface land 

cover, and urban tree benefi ts in urban, community, and urban or community areas.
GTR-NRS-65 California 13

Figure CA-1.—Urban or community land in 2000; urban area 

relative to community boundaries.

Figure CA-2.—2000 population within county 

subdivision boundaries.

Human Population Characteristics 

and Trends 

The population in California increased 13.8 percent, 

from 29,760,021 in 1990 to 33,871,648 in 2000 

(Table CA-1). In California, 94.4 percent of the State’s 

population is in urban areas (Fig. CA-1), and 92.0 percent 

of the population is within communities (Fig. CA-2).

Urban and Community Land 

Urban land comprises 5.1 percent of the land area of 

California, while lands within communities make up 

7.5 percent of the State (Fig. CA-1). Between 1990 and 

2000, urban area increased 0.4 percent, while community 

land increased from 6.0 to 7.5 percent (Table CA-1). 

Urban area in California is projected to increase to 

15.0 percent by 2050, based on average urban growth 

pattern of the 1990s (Nowak and Walton 2005). Both 

urban land (attaining minimum population density) and 

community land (political boundaries) increased from 

1990 to 2000. The percentages are calculated using the 

total (water and land) area of the geopolitical units 

derived from U.S. Census cartographic boundary data. 

Percent urban land varied across the State (Fig. CA-3; 

Tables CA-2 through 4).

Figure CA-3.—Percent of county subdivision area 

classifi ed as urban land in 2000.
14 GTR-NRS-65 California

Tree Canopy Cover Characteristics

Tree canopy cover in California averages 18.0 percent 

(Fig. CA-4), with 97.9 percent total green space, 

18.4 percent canopy green space, and 2,151.4 m2

 of 

canopy cover per capita. Average tree cover in urban 

areas in California was 6.7 percent, with 69.0 percent 

total green space, 9.7 percent canopy green space, and 

43.1 m2

 of canopy cover per capita. Within community 

lands in California, average tree cover was 11.7 percent, 

with 78.4 percent total green space, 15.0 percent canopy 

green space, and 114.4 m2

 of canopy cover per capita 

(Table CA-1). Tree canopy cover, canopy green space, 

and tree cover per capita varied among communities, 

county subdivisions, and counties (Fig. CA-5 through 6; 

Tables CA-5 through 7).

Figure CA-4.—Percentage tree canopy cover.

Figure CA-6.—Percentage tree canopy green space 

in county subdivisions.

Figure CA-5.—Percentage tree canopy cover within 

county subdivisions.
GTR-NRS-65 California 15

Figure CA-7.—Percentage impervious surface cover. Figure CA-8.—Percentage impervious surface cover 

within county subdivisions.

Impervious Surface Cover Characteristics

Average impervious surface cover in California is 2.1 percent of the land area 

(Fig. CA-7), with 248.4 m2

 of impervious surface cover per capita. Average 

impervious surface cover in urban areas was 31.0 percent, with 199.0 m2

 of 

impervious surface cover per capita. Within community lands in California, 

average impervious surface cover was 21.6 percent with 211.1 m2

 of impervious 

surface cover per capita (Table CA-1). Impervious surface cover varied across 

the State (Fig. CA-8; Tables CA-5 through 7).
16 GTR-NRS-65 California

Figure CA-9.—Classifi ed land cover. Figure CA-10.—Relative comparisons of tree 

cover for county subdivisions.

Classifi ed Land-cover Characteristics

California’s land cover is dominated by scrub/shrub land (Fig. CA-9). 

The characteristics as a percent of the total land area in California are 

(Tables CA-8 through 10):

• Scrub/Shrub – 40.3 percent

• Forested – 24.1 percent

• Grassland – 13.2 percent

• Agricultural – 10.4 percent

• Developed – 6.5 percent

• Barren – 5.0 percent

• Wetland – 0.5 percent

Relative Comparisons of Tree Cover

Out of the 1,081 California communities, 50 received a rating of excellent and 

758 received a rating of poor (Table CA-12). Of the 387 county subdivisions, 

35 had a rating of excellent and 196 were rated poor (Fig. CA-10, Table CA-13); 

and out of 58 counties, 10 were given a rating of excellent and 14 were given a 

rating of poor (Table CA-14). Variability of assessment scores is a product of the 

difference in land-cover distributions and the percentage of canopy cover within 

the population density classes and mapping zones (Fig. CA-10; Tables CA-11 

through 14). 
GTR-NRS-65 California 17

Priority Areas for Tree Planting

Priority areas for planting tend to be highest in more urbanized areas due to 

higher population density (Fig. CA-11; Tables CA-15 through 17). These index 

values can also be produced using high resolution cover data to determine local 

planting priority areas (e.g., neighborhoods). 

Urban Tree Benefi ts

The following forest attributes are estimated for the urban or community land 

in California (Table CA-1). These are rough estimates of values. More localized 

data are needed for more precise estimates, but these values reveal fi rst-order 

approximations. 

 188.5 million trees

 36.0 million metric tons of C stored ($820.8 million value)

 1.2 million metric tons/year of C sequestered ($27.0 million value)

 48,280 metric tons/year total pollution removal ($392.3 million value)

▪ 1,381 metric tons/year of CO removed ($1.9 million value)

▪ 7,642 metric tons/year NO2

 removed ($75.7 million value)

▪ 19,993 metric tons/year of O3

 removed ($198.0 million value)

▪ 2,569 metric tons/year of SO2

 removed ($6.2 million value) 

▪ 16,694 metric tons/year of PM10 removed ($110.4 million value)

Figure CA-11.—Planting priority index for county 

subdivisions. The higher the index value, the greater 

priority for planting.
18 GTR-NRS-65 California

Summary

The data presented in this report provide a better understanding of California’s 

urban and community forests. This information can be used to advance urban 

and community forest policy and management that could improve environmental 

quality and human health throughout the State. 

These data establish a baseline to assess future change and can be used to 

understand:

• Extent of the urban and community forest resource

• Variations in the resource across the State

• Magnitude and value of the urban and community forest resource

• Urban growth in California

• Implications of policy decisions related to urban sprawl and urban and 

community forest management
GTR-NRS-65 Oregon 19

Statewide Summary

Urban or community land in Oregon comprises about 1.5 percent of the state 

land area in 2000, an increase from 1.3 percent in 1990. Statewide tree canopy 

cover averages 28.5 percent and tree cover in urban or community areas is about 

15.0 percent, with 23.6 percent impervious surface cover and 19.7 percent of the 

total green space covered by tree canopy cover. Statewide, urban or community 

land in Oregon has an estimated 27.6 million trees, which store about 5.3 million 

metric tons of carbon ($120.8 million), and annually remove about 173,000 

metric tons of carbon ($3.9 million) and 4,090 metric tons of air pollution 

($31.4 million) (Table OR-1).

Tables OR-2 through OR-17 are not printed in this report but are available on the 

CD located on the inside back cover and at http://nrs.fs.fed.us/data/urban.

OREGON’S URBAN 

AND COMMUNITY FORESTS
20 GTR-NRS-65 Oregon

a Urban land is based on population density and was delimited using the United States Census defi nitions of urbanized areas and urban clusters. b Community 

land is based on jurisdictional or political boundaries of communities based on United States Census defi nitions of incorporated or census designated places. c

 Urban or communities is land that is urban, community, or both. Communities may include all, some, or no urban land within their boundaries. d Canopy green 

space is the tree canopy cover divided by total green space. e Total green space (TGS) is total area – impervious surface cover – water. f Available green space 

(AGS) is total green space – tree canopy cover (if the calculated value is less than 0, then value set at 0). 

Oregon Statewide Urban a Community b

 Urban or

Community c

Population

2000 3,421,399 2,694,144 2,565,695 n/a

1990 2,842,321 2,003,271 1,983,683 n/a

% Change (1990-2000) 20.4 34.5 29.3 n/a

% Total population (2000) 100.0 78.7 75.0 n/a

Total area 

km2 (2000) 254,804.7 2,663.7 3,177.2 3,948.4

km2 (1990) 254,804.7 2,283.4 2,665.3 3,319.0

% Change (1990-2000) 0.0 16.7 19.2 19.0

Land area 

km2 (2000) 249,013.1 2,636.5 3,081.8 3,843.0

% Land area (2000) 100.0 1.1 1.2 1.5

km2 (1990) 249,013.1 2,262.1 2,585.0 3,229.3

% Land area (1990) 100.0 0.9 1.0 1.3

% Change (1990-2000) 0.0 16.6 19.2 19.0

Population density 

 (people/land area km2)

2000 13.7 1,021.9 832.5 n/a

1990 11.4 885.6 767.4 n/a

% Change (1990-2000) 20.4 15.4 8.5 n/a

Tree canopy cover (2000)

km2 71,046.7 364.7 462.7 577.8

% Land area 28.5 13.8 15.0 15.0

Per capita (m2/person) 20,765.4 135.4 180.3 n/a

% Canopy green space d 28.7 19.9 20.4 19.7

Total green space (2000) e km2 247,322.0 1,835.7 2,272.6 2,934.6

% Land area 99.3 69.6 73.7 76.4

Available green space (2000) f km2 176,286.0 1,471.4 1,810.4 2,357.4

% Land area 70.8 55.8 58.7 61.3

Impervious surface cover 

 (2000)

km2 1,691.5 800.9 809.2 908.4

% Land area 0.7 30.4 26.3 23.6

Per capita (m2/person) 494.4 297.3 315.4 n/a

Urban tree benefi ts (2000)

Estimated number of trees n/a 17,400,000 22,100,000 27,600,000

Carbon

Carbon stored (metric tons) n/a 3,300,000 4,200,000 5,300,000

Carbon stored ($) n/a $75,200,000 $95,800,000 $120,800,000

Carbon sequestered (metric tons/year) n/a 109,000 139,000 173,000

Carbon sequestered ($/year) n/a $2,485,000 $3,169,000 $3,944,000

Pollution

CO removed (metric tons/year) n/a 162 205 256

CO removed ($/year) n/a $227,400 $288,400 $360,200

NO2 removed (metric tons/year) n/a 464 588 734

NO2 removed ($/year) n/a $4,592,200 $5,825,500 $7,274.900

O3 removed (metric tons/year) n/a 993 1,260 1,574

O3 removed ($/year) n/a $9,842,000 $12,485,000 $15,591,000

SO2 removed (metric tons/year) n/a 298 373 472

SO2 removed ($/year) n/a $722,100 $916,000 $1,143,900

PM10 removed (metric tons/year) n/a 666 845 1,056

PM10 removed ($/year) n/a $4,407,700 $5,591,600 $6,982,700

Total pollution removal (metric tons/year) n/a 2,580 3,280 4,090

Total pollution removal ($/year) n/a $19,800,000 $25,100,000 $31,400,000

Table OR-1.—Statewide summary of population, area, population density, tree canopy and impervious surface land 

cover, and urban tree benefi ts in urban, community, and urban or community areas.
GTR-NRS-65 Oregon 21

Figure OR-3.—Percent of county subdivision area 

classifi ed as urban land in 2000.

Human Population Characteristics 

and Trends 

The population in Oregon increased 20.4 percent, from 

2,842,321 in 1990 to 3,421,399 in 2000 (Table OR-1). 

In Oregon, 78.7 percent of the State’s population is 

in urban areas (Fig. OR-1), and 75.0 percent of the 

population is within communities (Fig. OR-2).

Urban and Community Land 

Urban land comprises 1.1 percent of the land area of 

Oregon, while lands within communities make up 

1.2 percent of the State (Fig. OR-1). Between 1990 

and 2000, urban area increased 16.6 percent, while 

community land increased from 1.0 to 1.2 percent 

(Table OR-1). Urban area in Oregon is projected to 

increase to 3.5 percent by 2050, based on average urban 

growth pattern of the 1990s (Nowak and Walton 2005). 

Both urban land (attaining minimum population density) 

and community land (political boundaries) increased 

from 1990 to 2000. The percentages are calculated using 

the total (water and land) area of the geopolitical units 

derived from U.S. Census cartographic boundary data. 

Percent urban land varied across the State (Fig. OR-3; 

Tables OR-2 through 4).

Figure OR-2.—2000 population within county 

subdivision boundaries.

Figure OR-1.—Urban or community land in 2000; 

urban area relative to community boundaries.
22 GTR-NRS-65 Oregon

Figure OR-4.—Percentage tree canopy cover.

Figure OR-5.—Percentage tree canopy cover within 

county subdivisions.

Figure OR-6.—Percentage tree canopy green space 

in county subdivisions.

Tree Canopy Cover Characteristics

Tree canopy cover in Oregon averages 28.5 percent 

(Fig. OR-4), with 99.3 percent total green space, 

28.7 percent canopy green space, and 20,765.4 m2

 of 

canopy cover per capita. Average tree cover in urban 

areas in Oregon was 13.8 percent, with 69.6 percent 

total green space, 19.9 percent canopy green space, 

and 135.4 m2

 of canopy cover per capita. Within 

community lands in Oregon, average tree cover was 

15.0 percent, with 73.7 percent total green space, 

20.4 percent canopy green space, and 180.3 m2

 of 

canopy cover per capita (Table OR-1). Tree canopy 

cover, canopy green space, and tree cover per capita 

varied among communities, county subdivisions, 

and counties (Fig. OR-5 through 6; Tables OR-5 

through 7).
GTR-NRS-65 Oregon 23

Figure OR-7.—Percentage impervious surface cover.

Figure OR-8.—Percentage impervious surface cover within 

county subdivisions.

Impervious Surface Cover Characteristics

Average impervious surface cover in Oregon is 0.7 percent of the land area 

(Fig. OR-7), with 494.4 m2

 of impervious surface cover per capita. Average 

impervious surface cover in urban areas was 30.4 percent, with 297.3 m2

 of 

impervious surface cover per capita. Within community lands in Oregon, average 

impervious surface cover was 26.3 percent with 315.4 m2

 of impervious surface 

cover per capita (Table OR-1). Impervious surface cover varied across the State 

(Fig. OR-8; Tables OR-5 through 7).
24 GTR-NRS-65 Oregon

Figure OR-9.—Classifi ed land cover.

Figure OR-10.—Relative comparisons of tree cover for 

county subdivisions.

Classifi ed Land-cover Characteristics

Oregon’s land cover is dominated by scrub/shrub land (Fig. OR-9). The 

characteristics as a percent of the total land area in Oregon are (Tables OR-8 

through 10):

• Scrub/Shrub – 43.7 percent

• Forested – 37.8 percent

• Agricultural – 8.4 percent

• Grassland – 5.1 percent

• Developed – 2.6 percent

• Barren – 1.4 percent

• Wetland – 0.8 percent

Relative Comparisons of Tree Cover

Out of the 309 Oregon communities, 19 received a rating of excellent and 

192 received a rating of poor (Table OR-12). Of the 211 county subdivisions, 

28 had a rating of excellent and 64 were rated poor (Fig. OR-10, Table OR-13); 

and out of 36 counties, four were given a rating of excellent and eight were given 

a rating of poor (Table OR-14). Variability of assessment scores is a product of 

the difference in land-cover distributions and the percentage of canopy cover 

within the population density classes and mapping zones (Fig. OR-10; Tables 

OR-11 through 14). 
GTR-NRS-65 Oregon 25

Figure OR-11.—Planting priority index for county 

subdivisions. The higher the index value, the greater 

priority for planting.

Priority Areas for Tree Planting

Priority areas for planting tend to be highest in more urbanized areas due to 

higher population density (Fig. OR-11; Tables OR-15 through 17). These index 

values can also be produced using high resolution cover data to determine local 

planting priority areas (e.g., neighborhoods). 

Urban Tree Benefi ts

The following forest attributes are estimated for the urban or community land 

in Oregon (Table OR-1). These are rough estimates of values. More localized 

data are needed for more precise estimates, but these values reveal fi rst-order 

approximations. 

 27.6 million trees

 5.3 million metric tons of C stored ($120.8 million value)

 173,000 metric tons/year of C sequestered ($3.9 million value)

 4,090 metric tons/year total pollution removal ($31.4 million value)

▪ 256 metric tons/year of CO removed ($360,200 value)

▪ 734 metric tons/year NO2

 removed ($7.3 million value)

▪ 1,574 metric tons/year of O3

 removed ($15.6 million value)

▪ 472 metric tons/year of SO2

 removed ($1.1 million value) 

▪ 1,056 metric tons/year of PM10 removed ($7.0 million value)
26 GTR-NRS-65 Oregon

Summary

The data presented in this report provide a better understanding of Oregon’s 

urban and community forests. This information can be used to advance urban 

and community forest policy and management that could improve environmental 

quality and human health throughout the State. 

These data establish a baseline to assess future change and can be used to 

understand:

• Extent of the urban and community forest resource

• Variations in the resource across the State

• Magnitude and value of the urban and community forest resource

• Urban growth in Oregon

• Implications of policy decisions related to urban sprawl and urban and 

community forest management
GTR-NRS-65 Washington 27

Statewide Summary

Urban or community land in Washington comprises about 5.2 percent of the state 

land area in 2000, an increase from 3.8 percent in 1990. Statewide tree canopy 

cover averages 36.6 percent and tree cover in urban or community areas is about 

27.7 percent, with 18.7 percent impervious surface cover and 34.1 percent of the 

total green space covered by tree canopy cover. Statewide, urban or community 

land in Washington has an estimated 118.4 million trees, which store about 

22.6 million metric tons of carbon ($515.3 million), and annually remove about 

745,000 metric tons of carbon ($17.0 million) and 20,370 metric tons of air 

pollution ($156.1 million) (Table WA-1).

Tables WA-2 through WA-17 are not printed in this report but are available on the 

CD located on the inside back cover and at http://nrs.fs.fed.us/data/urban.

WASHINGTON’S URBAN 

AND COMMUNITY FORESTS
28 GTR-NRS-65 Washington

a Urban land is based on population density and was delimited using the United States Census defi nitions of urbanized areas and urban clusters. b Community 

land is based on jurisdictional or political boundaries of communities based on United States Census defi nitions of incorporated or census designated places. c

 Urban or communities is land that is urban, community, or both. Communities may include all, some, or no urban land within their boundaries. d Canopy green 

space is the tree canopy cover divided by total green space. e Total green space (TGS) is total area – impervious surface cover – water. f Available green space 

(AGS) is total green space – tree canopy cover (if the calculated value is less than 0, then value set at 0). 

Washington Statewide Urban a Community b

 Urban or

Community c

Population

2000 5,894,121 4,831,106 4,667,234 n/a

1990 4,866,692 3,717,948 3,360,668 n/a

% Change (1990-2000) 21.1 29.9 38.9 n/a

% Total population (2000) 100.0 82.0 79.2 n/a

Total area 

km2 (2000) 184,665.2 5,556.6 8,010.8 9,318.3

km2 (1990) 184,665.2 4,564.0 5,718.0 6,912.8

% Change (1990-2000) 0.0 21.7 40.1 34.8

Land area 

km2 (2000) 172,506.3 5,466.1 7,676.2 8,955.6

% Land area (2000) 100.0 3.2 4.4 5.2

km2 (1990) 172,506.3 4,522.0 5,444.8 6,629.9

% Land area (1990) 100.0 2.6 3.2 3.8

% Change (1990-2000) 0.0 20.9 41.0 35.1

Population density 

 (people/land area km2)

2000 34.2 883.8 608.0 n/a

1990 28.2 822.2 617.2 n/a

% Change (1990-2000) 21.1 7.5 -1.5 n/a

Tree canopy cover (2000)

km2 63,140.5 1,415.3 2,085.4 2,483.4

% Land area 36.6 25.9 27.2 27.7

Per capita (m2/person) 10,712.5 292.9 446.8 n/a

% Canopy green space d 37.2 35.2 33.8 34.1

Total green space (2000) e km2 169,716.0 4,026.0 6,170.3 7,277.4

% Land area 98.4 73.7 80.4 81.3

Available green space (2000) f km2 106,655.0 2,623.6 4,098.2 4,809.5

% Land area 61.8 48.0 53.4 53.7

Impervious surface cover 

 (2000)

km2 2,790.1 1,440.2 1,505.9 1,678.2

% Land area 1.6 26.3 19.6 18.7

Per capita (m2/person) 473.4 298.1 322.7 n/a

Urban tree benefi ts (2000)

Estimated number of trees n/a 67,500,000 99,500,000 118,400,000

Carbon

Carbon stored (metric tons) n/a 12,900,000 19,000,000 22,600,000

Carbon stored ($) n/a $294,100,000 $433,200,000 $515,300,000

Carbon sequestered (metric tons/year) n/a 425,000 626,000 745,000

Carbon sequestered ($/year) n/a $9,690,000 $14,273,000 $16,986,000

Pollution

CO removed (metric tons/year) n/a 616 908 1,081

CO removed ($/year) n/a $867,000 $1,277,500 $1,521,400

NO2 removed (metric tons/year) n/a 1,799 2,651 3,157

NO2 removed ($/year) n/a $17,819,700 $26,256,800 $31,268,400

O3 removed (metric tons/year) n/a 4,822 7,105 8,461

O3 removed ($/year) n/a $47,765,000 $70,380,000 $83,813,000

SO2 removed (metric tons/year) n/a 1,533 2,259 2,690

SO2 removed ($/year) n/a $3,718,200 $5,478,600 $6,524,300

PM10 removed (metric tons/year) n/a 2,841 4,186 4,985

PM10 removed ($/year) n/a $18,790,400 $27,687,200 $32,971,900

Total pollution removal (metric tons/year) n/a 11,610 17,110 20,370

Total pollution removal ($/year) n/a $89,000,000 $131,100,000 $156,100,000

Table WA-1.—Statewide summary of population, area, population density, tree canopy and impervious surface land 

cover, and urban tree benefi ts in urban, community, and urban or community areas.
GTR-NRS-65 Washington 29

Figure WA-1.—Urban or community land in 2000; urban area 

relative to community boundaries.

Figure WA-2.—2000 population within county subdivision 

boundaries.

Figure WA-3.—Percent of county subdivision area classifi ed 

as urban land in 2000.

Human Population Characteristics 

and Trends 

The population in Washington increased 21.1 percent, 

from 4,866,692 in 1990 to 5,894,121 in 2000 (Table 

WA-1). In Washington, 82.0 percent of the State’s 

population is in urban areas (Fig. WA-1), and 

79.2 percent of the population is within communities 

(Fig. WA-2).

Urban and Community Land 

Urban land comprises 3.2 percent of the land area of 

Washington, while lands within communities make up 

4.4 percent of the State (Fig. WA-1). Between 1990 

and 2000, urban area increased 20.9 percent, while 

community land increased from 3.2 to 4.4 percent 

(Table WA-1). Urban area in Washington is projected 

to increase to 9.2 percent by 2050, based on average 

urban growth pattern of the 1990s (Nowak and Walton 

2005). Both urban land (attaining minimum population 

density) and community land (political boundaries) 

increased from 1990 to 2000. The percentages are 

calculated using the total (water and land) area of 

the geopolitical units derived from U.S. Census 

cartographic boundary data. Percent urban land varied 

across the State (Fig. WA-3; Tables WA-2 through 4).
30 GTR-NRS-65 Washington

Figure WA-4.—Percentage tree canopy cover.

Figure WA-5.—Percentage tree canopy cover within county 

subdivisions.

Figure WA-6.—Percentage tree canopy green space in 

county subdivisions.

Tree Canopy Cover Characteristics

Tree canopy cover in Washington averages 

36.6 percent (Fig. WA-4), with 98.4 percent total 

green space, 37.2 percent canopy green space, and 

10,712.5 m2

 of canopy cover per capita. Average tree 

cover in urban areas in Washington was 25.9 percent, 

with 73.7 percent total green space, 35.2 percent 

canopy green space, and 292.9 m2

 of canopy cover 

per capita. Within community lands in Washington, 

average tree cover was 27.2 percent, with 80.4 percent 

total green space, 33.8 percent canopy green space, 

and 446.8 m2

 of canopy cover per capita (Table 

WA-1). Tree canopy cover, canopy green space, 

and tree cover per capita varied among communities, 

county subdivisions, and counties (Fig. WA-5 

through 6; Tables WA-5 through 7).
GTR-NRS-65 Washington 31

Figure WA-7.—Percentage impervious surface cover.

Figure WA-8.—Percentage impervious surface cover within 

county subdivisions.

Impervious Surface Cover Characteristics

Average impervious surface cover in Washington is 1.6 percent of the land area 

(Fig. WA-7), with 473.4 m2

 of impervious surface cover per capita. Average 

impervious surface cover in urban areas was 26.3 percent, with 298.1 m2

 of 

impervious surface cover per capita. Within community lands in Washington, 

average impervious surface cover was 19.6 percent with 322.7 m2

 of impervious 

surface cover per capita (Table WA-1). Impervious surface cover varied across 

the State (Fig. WA-8; Tables WA-5 through 7).
32 GTR-NRS-65 Washington

Figure WA-9.—Classifi ed land cover.

Figure WA-10.—Relative comparisons of tree cover for 

county subdivisions.

Classifi ed Land-cover Characteristics

Washington’s land cover is dominated by forest land (Fig. WA-9). The 

characteristics as a percent of the total land area in Washington are (Tables 

WA-8 through 10):

• Forested – 43.5 percent

• Scrub/Shrub – 24.0 percent

• Agricultural – 18.5 percent

• Developed – 5.8 percent

• Grassland – 5.6 percent

• Barren – 1.5 percent

• Wetland – 0.8 percent

Relative Comparisons of Tree Cover

Out of the 522 Washington communities, 27 received a rating of excellent and 

268 received a rating of poor (Table WA-12). Of the 242 county subdivisions, 

31 had a rating of excellent and 71 were rated poor (Fig. WA-10, Table WA-13); 

and out of 39 counties, six were given a rating of excellent and 14 were given a 

rating of poor (Table WA-14). Variability of assessment scores is a product of the 

difference in land-cover distributions and the percentage of canopy cover within 

the population density classes and mapping zones (Fig. WA-10; Tables WA-11 

through 14). 
GTR-NRS-65 Washington 33

Figure WA-11.—Planting priority index for county 

subdivisions. The higher the index value, the greater priority 

for planting.

Priority Areas for Tree Planting

Priority areas for planting tend to be highest in more urbanized areas due to 

higher population density (Fig. WA-11; Tables WA-15 through 17). These index 

values can also be produced using high resolution cover data to determine local 

planting priority areas (e.g., neighborhoods). 

Urban Tree Benefi ts

The following forest attributes are estimated for the urban or community land in 

Washington (Table WA-1). These are rough estimates of values. More localized 

data are needed for more precise estimates, but these values reveal fi rst-order 

approximations. 

 118.4 million trees

 22.6 million metric tons of C stored ($515.3 million value)

 745,000 metric tons/year of C sequestered ($17.0 million value)

 20,370 metric tons/year total pollution removal ($156.1 million value)

▪ 1,081 metric tons/year of CO removed ($1.5 million value)

▪ 3,157 metric tons/year NO2

 removed ($31.3 million value)

▪ 8,461 metric tons/year of O3

 removed ($83.8 million value)

▪ 2,690 metric tons/year of SO2

 removed ($6.5 million value) 

▪ 4,985 metric tons/year of PM10 removed ($33.0 million value)
34 GTR-NRS-65 Washington

Summary

The data presented in this report provide a better understanding of Washington’s 

urban and community forests. This information can be used to advance urban 

and community forest policy and management that could improve environmental 

quality and human health throughout the State. 

These data establish a baseline to assess future change and can be used to 

understand:

• Extent of the urban and community forest resource

• Variations in the resource across the State

• Magnitude and value of the urban and community forest resource

• Urban growth in Washington

• Implications of policy decisions related to urban sprawl and urban and 

community forest management
GTR-NRS-65 35

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GTR-NRS-65 37

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for mapping large-area impervious surfaces: synergistic use of Landsat7 ETM+ and high spatial resolution imagery. Canadian Journal of Remote 

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38 GTR-NRS-65

APPENDIX

Urban Forest Data: States of the Pacifi c Region

The following tables are generated to support state reports on urban and community forests 

of the Pacifi c states of California, Oregon, and Washington. For specifi c state data tables use 

the CD accompanying this publication and search within the regional or state folder, or go to: 

http://www.nrs.fs.fed.us/data/urban.

State Specifi c Tables:

Table 1.—Statewide summary of population, area, population density, tree canopy and 

impervious surface land cover, and urban tree benefi ts in urban, community, and urban or 

community areas.

Table 2.—2000 population characteristics, population change (1990-2000), and percent of land 

classifi ed as urban within communities.

Table 3.—2000 population characteristics, population change (1990-2000), percent of land 

classifi ed as urban or as communities within county subdivisions.

Table 4.—2000 population characteristics, population change (1990-2000), percent of land 

classifi ed as urban or as communities within counties.

Table 5.—Tree canopy and impervious surface cover characteristics by community.

Table 6.—Tree canopy and impervious surface cover characteristics by county subdivision.

Table 7.—Tree canopy and impervious surface cover characteristics by county.

Table 8.—Land area, tree canopy cover, and available green space distributed within generalized 

land cover categories for communities.

Table 9.—Land area, tree canopy cover, and available green space distributed within generalized 

land cover categories for county subdivisions.

Table 10.—Land area, tree canopy cover, and available green space distributed within 

generalized land cover categories for counties.

Table 11.—Statistical summary of mapping zone values used to calculate urban and community 

forestry assessment.

Table 12.—Urban and community forestry assessment by community.

Table 13.—Urban and community forestry assessment by county subdivisions.

Table 14.—Urban and community forestry assessment by counties.

Table 15.—Planting priority index for communities.

Table 16.—Planting priority index for county subdivisions.

Table 17.—Planting priority index for counties.
Nowak, David J.; Greenfi eld, Eric J. 2010. Urban and community forests of the Pacifi c region: 

California, Oregon, Washington. Gen. Tech. Rep. NRS-65. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station. 38 p. [Includes CD-ROM].

This report details how land cover and urbanization vary within the states of California, Oregon, and 

Washington by community (incorporated and census designated places), county subdivision, and county. 

Specifi cally this report provides critical urban and community forestry information for each state including 

human population characteristics and trends, changes in urban and community lands, tree canopy and 

impervious surface cover characteristics, distribution of land-cover classes, a relative comparison of urban 

and community forests among local government types, determination of priority areas for tree planting, 

and a summary of urban tree benefi ts. Report information can improve the understanding, management, 

and planning of urban and community forests. This data is reported for each state on the CD provided in 

the back of this book and may be accessed by state at: http://www.nrs.fs.fed.us/data/urban.

KEY WORDS: urban forestry, tree cover, impervious cover, classifi ed land cover, ecosystem services, 

urbanization

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Capitalizing on the strengths of existing science 

capacity in the Northeast and Midwest to attain a more 

integrated, cohesive, landscape-scale research program

www.nrs.fs.fed.us