United States

Department of

Agriculture

Forest Service

Northern

Research Station

General Technical

Report NRS-63

Urban and Community Forests

of the Mountain Region

Arizona Nevada

Colorado New Mexico

Idaho Utah

Montana Wyoming

David J. Nowak

Eric J. Greenfield
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

June 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 Arizona, 

Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming by community 

(incorporated and census designated places), county subdivision, and county. Specifically 

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 

benefits. 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

Arizona’s Urban and Community Forests	 11

Colorado’s Urban and Community Forests	 19

Idaho’s Urban and Community Forests	 27

Montana’s Urban and Community Forests	 35

Nevada’s Urban and Community Forests	 43

New Mexico’s Urban and Community Forests	 51

Utah’s Urban and Community Forests	 59

Wyoming’s Urban and Community Forests	 67

Literature Cited	 75

Appendix	 78

GTR-NRS-63	 

INTRODUCTION

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

first 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 first 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 files) 

(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-specific urban and community forestry data.

This report includes information for the following states: Arizona, Colorado, Idaho, 

Montana, Nevada, New Mexico, Utah, and Wyoming.

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 defined legal or statistical divisions. “County”1 refers t

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 

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

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)
GTR-NRS-63

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

• Classified land-cover characteristics

• Relative comparisons of urban and community 

forests

• Priority areas for tree planting

• Urban tree benefits

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 field 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 findings 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 definitions overlap: “community” 

and “urban”. The definition of community is based 

on jurisdictional or political boundaries delimited by 

U.S. Census definitions 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 definition of urban is based on population density 

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

definition: 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-63	

More specifically, 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 definition tends to be more restrictive than the 

1990 U.S. Census urban definition and encompasses 

many areas typically considered suburban. The 2000 

Census definition 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 definition) and community 

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

communities that are recognized by their geopolitical 

boundaries (political definition), both definitions 

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 definitions. 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 benefits. 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 filled 

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 influences on urban 

air temperatures and water flows 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 
GTR-NRS-63

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).

Classified Land-cover Characteristics

Land-cover types also are summarized using 2001 

Landsat satellite data that were classified with the U.S. 

Geological Survey land cover categorization scheme 

based on a modified Anderson land-cover classification 

(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 

defined 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 

classified 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 classification accuracy and efficiency (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-63	

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
	 GTR-NRS-63

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 Benefits

Urban and community forests are important for human 

and ecological health (Nowak and Dwyer 2007). The 

benefits 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 

benefits 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-63	

To estimate pollution by urban trees in each state, state 

pollutant flux 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 flux 

rates were adjusted to 2000 values based on average 

regional pollution concentration changes between

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

flux rate = deposition velocity * pollution

concentration,

the ratio of the pollution concentration between years 

was used to update the flux 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 flux 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
GTR-NRS-63

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 finer 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 simplified 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 

simplification 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 coefficients 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 (Greenfield et al. 2009). 

These findings 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 significantly among 

geographic units. Despite the potential underestimates 

in tree canopy cover values, relative comparisons 

3

Nowak, D.J.; Greenfield, E.J. Tree and impervious cover 

in the conterminous United States: Testing of NLCD cover 

estimates by mapping zone. In review. 
GTR-NRS-63	

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 refined and locally 

appropriate data, local field 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 field 

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 significant environmental benefits. 

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 

Margin 	 Significant

Mapping zone a n b NLCD c PI d Difference e of error f difference g

6 996 35.6% 58.9% 23.3% 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

15 423 23.4% 35.1% 11.7% 4.6% Yes

16 998 27.5% 34.7% 7.2% 2.9% Yes

17 992 6.8% 16.2% 9.5% 2.3% Yes

18 983 2.2% 9.1% 7.0% 1.9% Yes

19 977 31.0% 42.5% 11.5% 2.6% Yes

20 992 3.9% 21.0% 17.1% 2.4% Yes

21 995 34.3% 40.9% 6.6% 2.9% Yes

22 993 1.8% 8.3% 6.5% 1.7% Yes

23 929 11.2% 16.8% 5.6% 2.4% Yes

24 600 11.4% 14.3% 2.9% 2.8% Yes

25 942 6.2% 14.7% 8.5% 2.3% Yes

26 866 0.8% 8.5% 7.8% 1.9% Yes

27 997 3.3% 8.3% 5.1% 1.7% Yes

28 827 37.9% 47.7% 9.7% 3.2% Yes

29 977 6.3% 9.9% 3.5% 1.8% Yes

30 771 1.1% 1.8% 0.8% 0.9% No

31 624 1.9% 3.8% 1.9% 1.4% Yes

33 761 0.3% 1.0% 0.7% 0.7% Yes

34 929 1.2% 8.1% 6.9% 1.7% Yes

a NLCD mapping zones e PI value minus NLCD value b Number of photo-interpreted sample points f 95% confidence interval of PI value c

 Percent tree canopy value derived from NLCD data g Significant difference between NLCD and PI values if NLCD value d Percent tree canopy derived from photo-interpreted data	 is outside of 95% confidence interval of PI va
10 GTR-NRS-63

in stream flow 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

• Determine areas of greatest population growth, 

urbanization, and development (sprawl) to direct 

urban and community forestry to minimize 

negative impacts and maximize environmental 

benefits 

• 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 benefits of urban and community forests

• Promote more detailed and/or locally 

appropriate urban and community forest 

inventories, censuses, or field 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 

specific 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-63 A

Statewide Summary

Urban or community land in Arizona comprises about 5.3 percent of the state 

land area in 2000, an increase from 3.3 percent in 1990. Statewide tree canopy 

cover averages 9.3 percent and tree cover in urban or community areas is about 

6.3 percent, with 8.2 percent impervious surface cover and 6.9 percent of the 

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

land in Arizona has an estimated 47.2 million trees, which store about 9.0 million 

metric tons of carbon ($205.2 million), and annually remove about 297,000 

metric tons of carbon ($6.8 million) and 8,760 metric tons of air pollution 

($71.3 million) (Table AZ-1).

Tables AZ-2 through AZ-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.

Arizona’s Urba

and Communit

Forests
12 GTR-NRS-63 

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

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

 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). 

Arizona Statewide Urban a Community b

 Urban or

Community c

Population

2000 5,130,632 4,523,535 4,651,044 n/a

1990 3,665,228 3,206,973 3,078,005 n/a

% Change (1990-2000) 40.0 41.1 51.1 n/a

% Total population (2000) 100.0 88.2 90.7 n/a

Total area 

km2 (2000) 295,254.2 4,350.7 15,370.4 15,791.6

km2 (1990) 295,254.2 3,139.0 9,220.9 9,739.7

% Change (1990-2000) 0.0 38.6 66.7 62.1

Land area 

km2 (2000) 294,538.6 4,341.5 15,310.9 15,731.4

% Land area (2000) 100.0 1.5 5.2 5.3

km2 (1990) 294,538.6 3,133.3 9,196.0 9,714.8

% Land area (1990) 100.0 1.1 3.1 3.3

% Change (1990-2000) 0.0 38.6 66.5 61.9

Population density 

 (people/land area km2)

2000 17.4 1,041.9 303.8 n/a

1990 12.4 1,023.5 334.7 n/a

% Change (1990-2000) 40.0 1.8 -9.2 n/a

Tree canopy cover (2000)

km2 27,354.5 191.9 969.1 990.5

% Land area 9.3 4.4 6.3 6.3

Per capita (m2/person) 5,331.6 42.4 208.4 n/a

% Canopy green space d 9.3 5.9 6.9 6.9

Total green space (2000) e km2 292,662.0 3,239.4 14,060.7 14,433.8

% Land area 99.4 74.6 91.8 91.8

Available green space (2000) f km2 265,309.0 3,048.5 13,092.8 13,444.6

% Land area 90.1 70.2 85.5 85.5

Impervious surface cover 

 (2000)

km2 1,876.5 1,102.1 1,250.2 1,297.6

% Land area 0.6 25.4 8.2 8.2

Per capita (m2/person) 365.8 243.6 268.8 n/a

Urban tree benefits (2000)

Estimated number of trees n/a 9,200,000 46,200,000 47,200,000

Carbon

Carbon stored (metric tons) n/a 1,700,000 8,800,000 9,000,000

Carbon stored ($) n/a $38,800,000 $200,600,000 $205,200,000

Carbon sequestered (metric tons/year) n/a 58,000 291,000 297,000

Carbon sequestered ($/year) n/a $1,322,000 $6,635,000 $6,772,000

Pollution

CO removed (metric tons/year) n/a 62 313 320

CO removed ($/year) n/a $87,100 $440,000 $449,700

NO2 removed (metric tons/year) n/a 280 1,412 1,443

NO2 removed ($/year) n/a $2,770,700 $13,989,100 $14,298,300

O3 removed (metric tons/year) n/a 664 3,353 3,427

O3 removed ($/year) n/a $6,579,000 $33,216,000 $33,950,000

SO2 removed (metric tons/year) n/a 46 234 239

SO2 removed ($/year) n/a $112,200 $566,400 $578,900

PM10 removed (metric tons/year) n/a 645 3,257 3,329

PM10 removed ($/year) n/a $4,266,700 $21,542,200 $22,018,200

Total pollution removal (metric tons/year) n/a 1,700 8,570 8,760

Total pollution removal ($/year) n/a $13,800,000 $69,800,000 $71,300,000

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

cover, and urban tree benefits in urban, community, and urban or community areas.
GTR-NRS-63 Ari

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

relative to community boundaries.

Figure AZ-2.—2000 population within county 

subdivision boundaries.

Human Population Characteristics

and Trends

The population in Arizona increased 40.0 percent, from 

3,665,228 in 1990 to 5,130,632 in 2000 (Table AZ-1). 

In Arizona, 88.2 percent of the State’s population is 

in urban areas (Fig. AZ-1), and 90.7 percent of the 

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

Urban and Community Land

Urban land comprises 1.5 percent of the land area 

of Arizona, while lands within communities make up 

5.2 percent of the State (Fig. AZ-1). Between 1990 and 

2000, urban area increased 38.6 percent, while community 

land increased from 3.1 to 5.2 percent (Table AZ-1). 

Urban area in Arizona is projected to increase to 

5.1 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. AZ-3; Tables AZ-2 

through 4).

Figure AZ-3.—Percent of county subdivision area 

classified as urban land in 2000.

Total Population

2 - 25,608

25,609 - 74,488

74,489 - 215,998

215,999 - 756,298

756,299 - 2,608,349

Percent

0% - 1.1%

1.2% - 4.2%

4.3% - 10.4%

10.5% - 19.2%

19.3% - 61.8%
14 GTR-NRS-63 

Tree Canopy Cover Characteristics

Tree canopy cover in Arizona averages 9.3 percent 

(Fig. AZ-4), with 99.4 percent total green space, 

9.3 percent canopy green space, and 5,331.6 m2 of

canopy cover per capita. Average tree cover in urban 

areas in Arizona was 4.4 percent, with 74.6 percent 

total green space, 5.9 percent canopy green space, and 

42.4 m2

 of canopy cover per capita. Within community 

lands in Arizona, average tree cover was 6.3 percent, 

with 91.8 percent total green space, 6.9 percent canopy 

green space, and 208.4 m2

 of canopy cover per capita 

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

and tree cover per capita varied among communities, 

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

Tables AZ-5 through 7).

Figure AZ-4.—Percentage tree canopy cover.

Figure AZ-6.—Percentage tree canopy green space 

in county subdivisions.

Figure AZ-5.—Percentage tree canopy cover within 

county subdivisions.

Percent

0.1% - 2.6%

2.7% - 6.7%

6.8% - 15.2%

15.3% - 27.8%

27.9% - 65.7%

Percent

0.1% - 2.6%

2.7% - 6.7%

6.8% - 15.3%

15.4% - 28%

28.1% - 65.8%
GTR-NRS-63 Ari

Figure AZ-7.—Percentage impervious surface cover.

Figure AZ-8.—Percentage impervious surface cover 

within county subdivisions.

Impervious Surface Cover Characteristics

Average impervious surface cover in Arizona is 0.6 percent of the land area 

(Fig. AZ-7), with 365.8 m2

 of impervious surface cover per capita. Average 

impervious surface cover in urban areas was 25.4 percent, with 243.6 m2 of

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

impervious surface cover was 8.2 percent with 268.8 m2

 of impervious surface 

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

(Fig. AZ-8; Tables AZ-5 through 7).

Percent

0% - 0.6%

0.7% - 2.2%

2.3% - 6%

6.1% - 10.9%

11% - 23.9%
16 GTR-NRS-63 

Figure AZ-9.—Classified land cover.

Figure AZ-10.—Relative comparisons of tree 

cover for county subdivisions.

Classified Land-cover Characteristics

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

characteristics as a percent of the total land area in Arizona are (Tables AZ-8 

through 10):

• Scrub/Shrub – 72.1 percent

• Forested – 15.3 percent

• Grassland – 6.1 percent

• Barren – 2.4 percent

• Agricultural – 2.2 percent

• Developed – 2.0 percent

• Wetland – 0.1 percent

Relative Comparisons of Tree Cover

Out of the 250 Arizona communities, 16 received a rating of excellent and 

191 received a rating of poor (Table AZ-12). Of the 78 county subdivisions, 

three had a rating of excellent and 52 were rated poor (Fig. AZ-10, Table AZ-13); 

and out of 15 counties, one was given a rating of excellent and four were given a 

rating of poor (Table AZ-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. AZ-10; Tables AZ-11 

through 14). 
GTR-NRS-63 Ar

Priority Areas for Tree Planting

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

higher population density (Fig. AZ-11; Tables AZ-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 Benefits

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

in Arizona (Table AZ-1). These are rough estimates of values. More localized 

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

approximations. 

 47.2 million trees

 9.0 million metric tons of C stored ($205.2 million value)

 297,000 metric tons/year of C sequestered ($6.8 million value)

 8,760 metric tons/year total pollution removal ($71.3 million value)

▪ 320 metric tons/year of CO removed ($449,700 value)

▪ 1,443 metric tons/year NO2 removed ($14.3 million value)

▪ 3,427 metric tons/year of O3 removed ($34.0 million value)

▪ 239 metric tons/year of SO2 removed ($578,900 value) 

▪ 3,329 metric tons/year of PM10 removed ($22.0 million value)

Figure AZ-11.—Planting priority index for county 

subdivisions. The higher the index value, the greater 

priority for planting.

Index Value

0.0 - 19.5

19.6 - 35.0

35.1 - 43.8

43.9 - 56.0

56.1 - 100.0
18 GTR-NRS-63 

Summary

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

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

community forest management
GTR-NRS-63 Col

Statewide Summary

Urban or community land in Colorado comprises about 2.6 percent of the state 

land area in 2000, an increase from 1.9 percent in 1990. Statewide tree canopy 

cover averages 18.3 percent and tree cover in urban or community areas is 

about 11.6 percent, with 14.5 percent impervious surface cover and 13.6 percent 

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

community land in Colorado has an estimated 39.0 million trees, which store 

about 7.4 million metric tons of carbon ($168.7 million), and annually remove 

about 246,000 metric tons of carbon ($5.6 million) and 5,050 metric tons of air 

pollution ($42.2 million) (Table CO-1).

Tables CO-2 through CO-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.

Colorado’s Urba

and Community Fores
20 GTR-NRS-63 

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

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

 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). 

Colorado Statewide Urban a Community b

 Urban or

Community c

Population

2000 4,301,261 3,633,185 3,556,187 n/a

1990 3,294,394 2,715,517 2,685,910 n/a

% Change (1990-2000) 30.6 33.8 32.4 n/a

% Total population (2000) 100.0 84.5 82.7 n/a

Total area 

km2 (2000) 269,601.1 3,295.9 6,437.6 7,137.6

km2 (1990) 269,601.1 2,725.0 4,672.4 5,285.1

% Change (1990-2000) 0.0 21.0 37.8 35.1

Land area 

km2 (2000) 268,532.1 3,249.9 6,373.0 7,055.5

% Land area (2000) 100.0 1.2 2.4 2.6

km2 (1990) 268,532.1 2,685.5 4,626.7 5,223.4

% Land area (1990) 100.0 1.0 1.7 1.9

% Change (1990-2000) 0.0 21.0 37.7 35.1

Population density 

 (people/land area km2)

2000 16.0 1,117.9 558.0 n/a

1990 12.3 1,011.2 580.5 n/a

% Change (1990-2000) 30.6 10.6 -3.9 n/a

Tree canopy cover (2000)

km2 49,027.5 240.1 763.5 818.5

% Land area 18.3 7.4 12.0 11.6

Per capita (m2/person) 11,398.4 66.1 214.7 n/a

% Canopy green space d 18.4 10.0 14.1 13.6

Total green space (2000) e km2 266,858.0 2,401.6 5,432.8 6,036.0

% Land area 99.4 73.9 85.2 85.5

Available green space (2000) f km2 217,831.0 2,161.9 4,669.7 5,217.8

% Land area 81.1 66.5 73.3 74.0

Impervious surface cover 

 (2000)

km2 1,674.2 848.3 940.1 1,019.6

% Land area 0.6 26.1 14.8 14.5

Per capita (m2/person) 389.2 233.5 264.4 n/a

Urban tree benefits (2000)

Estimated number of trees n/a 11,400,000 36,400,000 39,000,000

Carbon

Carbon stored (metric tons) n/a 2,200,000 6,900,000 7,400,000

Carbon stored ($) n/a $50,200,000 $157,300,000 $168,700,000

Carbon sequestered (metric tons/year) n/a 72,000 229,000 246,000

Carbon sequestered ($/year) n/a $1,642,000 $5,221,000 $5,609,000

Pollution

CO removed (metric tons/year) n/a 17 53 57

CO removed ($/year) n/a $23,500 $74,800 $80,200

NO2 removed (metric tons/year) n/a 297 945 1,013

NO2 removed ($/year) n/a $2,942,300 $9,358,000 $10,033,000

O3 removed (metric tons/year) n/a 629 2,001 2,145

O3 removed ($/year) n/a $6,232,000 $19,821,000 $21,251,000

SO2 removed (metric tons/year) n/a 86 274 294

SO2 removed ($/year) n/a $209,200 $665,200 $713,200

PM10 removed (metric tons/year) n/a 451 1,433 1,537

PM10 removed ($/year) n/a $2,980,800 $9,480,300 $10,164,100

Total pollution removal (metric tons/year) n/a 1,480 4,710 5,050

Total pollution removal ($/year) n/a $12,400,000 $39,400,000 $42,200,000

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

cover, and urban tree benefits in urban, community, and urban or community areas.


























































Nowak, David J.; Greenfield, Eric J. 2010. Urban and community forests of the Mountain region: 

Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming. Gen. Tech. Rep. NRS-63. 

Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. 78 p. 

[Includes CD-ROM].

This report details how land cover and urbanization vary within the states of Arizona, Colorado, Idaho, 

Montana, Nevada, New Mexico, Utah, and Wyoming by community (incorporated and census designated 

places), county subdivision, and county. Specifically 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 benefits. 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, classified land cover, ecosystem services, 

urbanization

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of 

race, color, national origin, age, disability, and, where applicable, sex, marital status, familial status, parental status, 

religion, sexual orientation, genetic information, political beliefs, reprisal, or because all or part of an individual’s 

income is derived from any public assistance program. (Not all prohibited bases apply to all programs.) Persons with 

disabilities who require alternate means for communication of program information (Braille, large print, audiotape, 

etc.) should contact USDA’s TARGET Center at (202) 720-2600 (voice and TDD). To file a complaint of discrimination, 

write to USDA, Director, Office of Civil Rights, 1400 Independence Avenue S.W., Washington, DC 20250-9410, or call 

(800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA is an equal opportunity provider and employer.
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