DEPARTMENT OF AGRICULTURE

Forest Service Southern

Research Station

Resource Bulletin 

SRS–211

Publication Date 

April 2017

United States Department of Agriculture

Houston’s Urban Forest, 2015
Published by:

U.S. FOREST SERVICE

SOUTHERN RESEARCH STATION

200 W.T. WEAVER BLVD.

ASHEVILLE, NC 28804

April 2017

A copy of this resource bulletin is available 

for download at www.srs.fs.usda.gov/pubs/.

www.srs.fs.usda.gov

Abstract

An analysis of the urban forest in Houston, Texas, reveals that this area has an estimated 

33.3 million live trees with tree canopy that covers 18.4 percent of the city. Roughly 19.2 million 

of the city’s trees are located on private lands. The most common tree species are yaupon, Chinese 

tallowtree, Chinese privet, Japanese privet, and sugarberry. Trees in Houston currently store about 

2.0 million tons of carbon (7.5 million tons of carbon dioxide [CO2]); valued at $272 million. In 

addition, these trees remove about 140,000 tons of carbon per year (513,000 tons CO2 per year) 

($18.6 million per year) and about 2,400 tons of air pollution per year ($20.4 million per year). 

Houston’s urban forest is also estimated to provide 126 million cubic feet of net wood volume and 

to reduce annual residential energy costs by $53.9 million per year. Reduction in runoff provided 

by the trees in Houston is estimated at 173 million cubic feet per year with an associated value 

of $7.8 million per year. The compensatory value of the trees is estimated at $16.3 billion. The 

information presented in this report can be used to improve and augment support for urban forest 

management programs and to inform policy and planning to improve environmental quality and 

human health in Houston. The analysis also provides a basis for monitoring changes in the urban 

forest over time.

Acknowledgments

Special thanks are extended to the many Texas A&M Forest Service, City of Houston, U.S. Forest 

Service, and Davey Institute staff members who supported this field study.

We are grateful to Chris Brown, David Cahal, Trevor DoBell-Carlsson, Hannah Cruze, 

Lee Fleming, Daniel Gaskins, Zaina Gates, Thomas Harrell, Philip Martindale, Luke Masters, 

Frank McCook, Justin McCullough, Aaron McNeil, Mickey Merritt, Linda Drabek Mikeska, 

Josh Mizrany, Stacey O’Bannon, David Passauer, Crockett Pegoda, Mark Piggott, Paul Sowers, 

Aaron Thigpen, Forest Warren, Matt Weaver, and Ray Wright for field data collection, plot 

selection, and quality assurance and control (QA/QC); Alexis Ellis, Mark Majewsky, Jim Westfall, 

and Rebekah Zehnder for data management, data analysis, training, and programming; and 

Eric Kuehler and Mickey Merritt for report review.

All photographs courtesy of Texas Forest Service, unless otherwise noted.

Cover: Buffalo Bayou Park—a ribbon of greenspace through downtown Houston. 

Product Disclaimer

The use of trade or firm names in this publication is for 

reader information and does not imply endorsement by the 

U.S. Department of Agriculture of any product or service.
Houston’s Urban Forest, 2015

The Authors

DAVID J. NOWAK is a research forester and team leader with the U.S. Forest Service’s 

Northern Research Station, Syracuse, New York.

ALLISON R. BODINE is a research forester with Davey Tree’s Davey Institute, 

Syracuse, New York.

ROBERT E. HOEHN III is a forester with the U.S. Forest Service’s Northern Research 

Station, Syracuse, New York.

CHRISTOPHER B. EDGAR is a forest resource analyst with the Texas A&M Forest 

Service, College Station, Texas.

GRETCHEN RILEY is the U&CF partnership coordinator with the Texas A&M Forest 

Service, College Station, Texas.

DUDLEY R. HARTEL is center manager of Urban Forestry South with the U.S. Forest 

Service’s Southern Research Station, Athens, Georgia. 

KERRY J. DOOLEY is a forester with the U.S. Forest Service’s Southern Research 

Station, Knoxville, Tennessee.

SHARON M. STANTON is a natural resource specialist with the U.S. Forest Service’s 

Pacific Northwest Research Station, Portland, Oregon.

MARK A. HATFIELD is a forester with the U.S. Forest Service’s Northern Research 

Station, Durham, New Hampshire.

THOMAS J. BRANDEIS is a research forester with the U.S. Forest Service’s Southern 

Research Station, Knoxville, Tennessee.

TONYA W. LISTER is a research forester with the U.S. Forest Service’s Northern 

Research Station, Newtown Square, Pennsylvania.
ii

Urban trees in the heart of downtown Houston.
iii

CONTENTS

INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

METHODS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Field Measurements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Urban Forest Effects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

ASSESSMENT SUMMARY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Urban Forest Structure and Composition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Urban Forest Values. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Urban Forest Health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

MANAGEMENT IMPLICATIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Current Size Distribution and Potential Species Changes. . . . . . . . . . . . . . . . . . 54

Nonnative Invasive Species. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Insect and Disease Impacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Population Growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

CONCLUSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

LITERATURE CITED. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

APPENDIX 1—URBAN FIA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

APPENDIX 2—SPECIES SAMPLED IN THE HOUSTON URBAN FOREST. . . . . . 70

APPENDIX 3—LAND COVER CATEGORY DESCRIPTIONS. . . . . . . . . . . . . . . . . 72

APPENDIX 4—TREE SPECIES DISTRIBUTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

APPENDIX 5—RELATIVE TREE EFFECTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

APPENDIX 6—TREE SPECIES STATISTICS BY LAND COVER. . . . . . . . . . . . . . . 81

APPENDIX 7—GENERAL RECOMMENDATIONS FOR AIR QUALITY

IMPROVEMENT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

APPENDIX 8—DAMAGE TYPE AND MAINTENANCE OR SITE 

ISSUE STATISTICS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

APPENDIX 9—POTENTIAL INSECT AND DISEASE IMPACTS. . . . . . . . . . . . . . . 88
iv

Houston is the fourth largest city in the United States, with over 2.2 million people.
INTRODUCTION

Urban forests offer a wide range of environmental benefits, such as the provision of 

wildlife habitat, aesthetic appeal and visual barriers, reduced air temperatures, improved 

water quality, and mitigated air and noise pollution. Since 1930, the Forest Service, U.S. 

Department of Agriculture Forest Inventory and Analysis (FIA) program has provided 

information on the amount, status, and character of forest land across the country. FIA 

has collected data about trees within FIA-defined forest land, but usually excluded 

urban trees. Recognizing the importance of urban forests, and with direction from the 

2014 U.S. Farm Bill1

 to include urban forest monitoring in its strategic plan, FIA initiated 

an annualized urban inventory program. For this report, the urban forest includes all trees 

in the city, both within and outside forested areas, including street trees, trees on public 

and private lands, and trees that are planted and naturally occurring. FIA has partnered 

with the Forest Service’s i-Tree researchers, who have a long tradition of conducting 

urban forest inventories and delivering data about urban forests and ecosystems services. 

The partnership offers an opportunity to use the strengths of each group in the combined 

urban inventory effort. 

A new urban FIA framework has been designed with lessons learned from previous urban 

inventory pilot studies that were conducted at the State level (Cumming and others 

2007, Nowak and others 2007, Nowak and others 2011). This new initiative will build a 

strategic, consistent national inventory of urban forests. 

Houston, Texas, is the second city to complete a full inventory cycle under the FIA 

Urban Inventory Program (urban FIA). Like Austin, the first city to complete a full 

urban FIA inventory, this location is ideal because of the Forest Service’s established 

relationships with the State of Texas, and an enthusiasm and willingness on behalf of 

the Texas A&M Forest Service (TFS) to collaborate and support the program. With an 

increasing population in Texas and the growing recognition of the environmental and 

1 The Agricultural Act of 2014 (H.R. 2642; Pub. L. 113-79, also known as the 2014 Farm Bill).
2

economic benefits that trees contribute in urban areas, TFS has a pressing need to provide 

State agencies, city governments, nonprofit organizations, and consultants with accurate 

information to strengthen urban forest management and advocacy efforts. In Texas, these 

urban forests are located in areas where 85 percent of Texans live. TFS has welcomed a 

partnership with FIA to establish an urban forest inventory in Houston. TFS is applying 

the credibility and rigor of FIA inventory procedures to urban areas and solidifying TFS 

and FIA as trusted sources of science-based information about urban forests in Texas. 

New partnerships, cooperators, and supporters are involved to strengthen support for 

the sustainability of urban forests. With the implementation of urban FIA in Houston, 

seamless rural-to-urban resource monitoring continues. 

During the 2015 field season, data collection was accelerated and a full, intensified sample 

of urban FIA data were collected in Houston. To understand Houston’s urban forest, 

the collected data were analyzed using FIA methodologies and the i-Tree Eco modeling 

software (i-Tree 2016). This report is a summary of the findings of this analysis. Along 

with this report, an online querying application, My City’s Trees at www.mycitystrees.

com, has been developed to make the information from this analysis available to 

numerous stakeholders and to aid in understanding and managing Houston’s urban forest.
3

METHODS

Field Measurements

Within the city limits of Houston (fig. 1), data from 209 field plots were collected 

between March and September 2015. TFS and FIA crews located the urban forest 

inventory sampling locations using GPS units and aerial photographs. Two hundred of 

the 209 sampling locations (fig. 2) were accessible (i.e., were non-hazardous plots with 

§ ̈¦45

§ ̈¦10

§ ̈¦610

Harris

Brazoria

Liberty

Fort Bend

Montgomery

Waller

Galveston

 ̄ 0 1 5 0 20

Miles ^

Figure 1—Houston city boundaries as defined by 

the 2010 U.S. Census.

Figure 2—Approximate locations for 200 urban 

inventory plots, Houston, 2015.

 ̄ 0 5 10 20

Miles
4

landowner permission to access the plot). These plots were monumented by measuring 

distance and azimuth to witness objects. Every effort was made to avoid damaging private 

property and exposing plot location to maintain plot integrity through time.

Each urban forest inventory plot was a one-sixth acre circle with a radius of 48 feet 

(fig. 3). Each plot contained four nested microplots, each 1

/300 acre in size with a radius of 

6.8 feet and offset 12 feet horizontally in each cardinal direction from the plot center. For 

more information on urban FIA plots, including sampling design, remeasurement, and 

plot layout, see appendix 1.

In the urban plot, data were collected for all live and standing dead trees2 that had a 

diameter at breast height (d.b.h.) or diameter at root collar (d.r.c.) of 5 inches or greater. 

In the microplots, data were collected on all live trees with a d.b.h./d.r.c. of 1 inch 

through 4.9 inches (i.e., saplings). Data for standing dead saplings were not collected 

on microplots. In FIA, trees are defined based on a regional tree species list. For urban 

FIA, this list was expanded beyond the traditional FIA tree species list to include exotic 

and ornamental trees that are not usually seen on rural forest land. The complete urban 

FIA tree species list is available in the FIA field guide (U.S. Forest Service 2015). Woody 

perennial plants not meeting the parameters mentioned earlier are considered shrubs.

Generally, inventory crews measured the d.b.h. at 4.5 feet above the ground for each tree. 

For special situations, such as forked trees, urban FIA protocol was followed (U.S. Forest 

Service 2015). Diameter measurements were not taken at breast height for trees identified 

Figure 3—Urban forest inventory plot diagram, Houston, 

2015.

2 In general, FIA defines a tree as a perennial woody plant species that can attain a height of 15 feet at maturity. 

Trees are distinguished from shrubs, not by their height at the time of sample collection, but rather by the 

general growth form of the species in a particular region.
5

as woodland species on the regional tree species list. For woodland species, inventory 

crews measured the d.r.c. at the ground line or stem root collar, whichever was farthest 

from the ground. These d.b.h. and d.r.c. data are collectively referred to as diameter 

throughout this report.

In addition to diameter data, inventory crews identified tree species, measured tree 

length (i.e., measurement of tree from ground level to tree top), and described tree status, 

health, and presence of damages. (The complete lists of potential urban tree damages, 

pests, and diseases can be found in the urban FIA field manual [U.S. Forest Service 

2015].) Additional measurements and descriptions were made of each individual tree’s 

crown to further assess its health and leaf surface area. Crown variables recorded include 

crown ratio (as a percentage of total tree length), crown class (relative to the surrounding 

trees), crown light exposure, crown dieback, crown diameter, and the absence of foliage. 

Inventory crews also noted whether each tree was within a maintained (e.g., as evidenced 

by the presence of landscaping or maintenance activities) or riparian area, whether it was 

a street tree (e.g., located within 8 feet of the edge of a maintained, surfaced roadway) or a 

planted tree.

Texas A&M Forest Service forester marks plot center.
6

Additional data were collected for live and dead trees greater than 20 feet in height 

within 60 feet of residential buildings. These data (i.e., distance and direction to building) 

were used for estimating tree effects on building energy use. Space-conditioned structures 

(heated and perhaps cooled) were classified as buildings if they were no more than three 

stories (two stories plus attic) in height above ground level. i-Tree Eco uses an algorithm 

for single standing structures no larger than 4,000 square feet in total inhabitable 

(heated or cooled) space, although larger single-family homes or duplexes were included 

regardless of size. Unheated detached garages, sheds, or other outbuildings were not 

included. The building affected by the tree did not have to be on the plot. 

Data collection methods included the delineation of unique condition classes on the 

urban plot including the determination of whether a condition was forest land, nonforest 

land, water, etc. Forested conditions were further delineated based on forest type, stand 

size, reserve status, etc., in the same manner as traditional FIA methods. Condition 

classes on nonforest land were established based on land use, ownership, and reserved 

status (U.S. Forest Service 2015). For each condition on the plot, field crews estimated 

percentage covers for trees/saplings, shrubs/seedlings, buildings, impervious surfaces, 

permeable surfaces, herbaceous vegetation, and water.

Please note that the urban FIA data collection protocol described here differs somewhat 

from the data collection procedures typically prescribed by the i-Tree program. More 

technical information on the different methodologies is being developed and will be 

available at http://nrs.fs.fed.us/data/urban when completed.

Urban Forest Effects

The urban FIA field data were analyzed using FIA methodologies and the i-Tree Eco 

modeling software (Nowak and Crane 2000, Nowak and others 2008). Both the field data 

and modeling outputs are incorporated into this report and the newly constructed Urban 

FIA database (Urban FIADB) available at http://www.fia.fs.fed.us/tools-data/.

Results include information on forest structure and associated ecosystem services and 

monetary values. Structure is a measure of various physical attributes of the urban forest, 

including tree species composition, number of trees, tree density, tree health, leaf area, 

biomass, and species diversity. Ecosystem services are determined by forest structure 

and include such attributes as air pollution removal and carbon storage or sequestration. 

Monetary values are an estimate of the economic worth of the various forest functions.

Air pollution removal—Air pollution removal estimates are calculated by the i-Tree 

Eco model. Outputs are provided for ozone (O3), sulfur dioxide (SO2), nitrogen dioxide 

(NO2), and particulate matter less than 2.5 microns (PM2.5). Estimates are derived from 

calculated hourly tree-canopy resistances for O3, SO2, and NO2 based on a hybrid of 
7

big-leaf and multi-layer canopy deposition models (Baldocchi 1988, Baldocchi and others 

1987). Removal rates for PM2.5 varied with wind speed and leaf area (Nowak and others 

2013a). Particulate removal also incorporated variable resuspension rates (Nowak and 

others 2013a). 

Pollution removal value, which is also calculated by i-Tree Eco, is estimated as the 

economic value (i.e., cost of illness, willingness to pay, loss of wages, and the value of 

statistical life) associated with avoided human health impacts. Outputs from the U.S. 

Environmental Protection Agency’s (EPA) Environmental Benefits Mapping and 

Analysis Program (BenMAP) were used to estimate the monetary value that result 

from changes in NO2, O3, PM2.5, and SO2 concentrations due to pollution removal by 

trees. BenMAP is a Windows-based computer program that uses local pollution and 

population data to estimate the health impacts of human exposure to changes in air 

quality and calculates the associated economic value of those changes (Nowak and others 

2014, U.S. Environmental Protection Agency 2012).

Avoided runoff—Annual surface water runoff that was avoided (referred to as 

avoided surface runoff ) is estimated by i-Tree Eco based on rainfall interception 

and evapotranspiration by vegetation and ground surface storage and infiltration of 

precipitation, or more specifically, the difference between annual runoff with and without 

vegetation. Although tree leaves and bark may intercept precipitation and thus mitigate 

surface runoff, only the precipitation intercepted and water evapotranspired by leaves is 

accounted for in this analysis.

Buffalo Bayou, lined with parks and trails, meanders the entire east-west length of the city.
8

The monetary value associated with avoided runoff is based on estimated annual 

stormwater management fees for the Coastal Plain region which includes the city of 

Houston. This regional value is $0.045 per cubic foot of surface runoff as reported in 

McPherson and others (2006).

Carbon storage and sequestration—Carbon storage is the amount of carbon 

bound in the tissue of woody vegetation. The carbon data presented in this report are 

based on standard FIA methodology, the same that is used for the rural FIA inventory 

(Woodall and others 2011). Aboveground carbon is calculated by multiplying the 

aboveground dry-weight biomass of each component (i.e., bole, stump, and top) of trees 

≥5 inches in diameter by a factor of 0.5. Biomass of the different tree components is 

based on a combination of sound volume estimates that are derived from regional volume 

equations, biomass component ratios, and wood specific gravity estimates. For saplings or 

woodland species, the dry-weight biomass is also multiplied by a factor of 0.5. Biomass 

of woodland species is not broken down by component but is based on volume for the 

entire aboveground portion of the tree. The biomass of saplings is estimated directly from 

biomass equations.

Belowground carbon is equal to one-half the dry weight biomass of coarse roots, which 

is based on a modeled ratio estimate from the literature. FIA methods are based on 

studies of modeled tree volume and biomass for trees grown in forest settings, and no 

adjustments were made to account for the fact that these methods are being applied in 

urban, nonforest areas. Carbon storage presented in this report is for whole tree carbon, 

including above- and belowground carbon.

Carbon sequestration is the amount of carbon removed from the atmosphere and turned 

into tissue by a tree in a single year. Typically, carbon sequestration is estimated by FIA 

methodologies using remeasurement data. As this is the first complete cycle of Houston 

urban FIA data, carbon sequestration has been estimated based on projected tree growth. 

Average annual diameter and height growth was estimated using i-Tree Eco based on 

local climate, crown competition level, and tree condition and added to the existing 

tree measurements (in year x) to estimate tree diameter and height in year x+1. Carbon 

was then calculated for year x+1 using the standard FIA methodology and i-Tree Eco’s 

predicted future tree diameter and height. Carbon sequestration is the difference between 

the FIA’s carbon data for year x and year x+1.

Carbon storage and sequestration was also estimated in i-Tree Eco using methods 

described in Austin’s Urban Forest, 2014 report (Nowak and others 2016). Unlike the 

FIA methodologies, these model estimates include the carbon contribution of foliage for 

evergreen trees and applies an adjustment factor for trees in predominantly urban land 
9

uses. The i-Tree based carbon estimates are not reported here, but will be available online 

in the UFIADB at http://www.fia.fs.fed.us/tools-data/.

To estimate the monetary value of carbon storage and sequestration, tree carbon values 

were multiplied by $133.05 per ton of carbon based on the estimated social costs of 

carbon for 2015 using a 3-percent discount rate (Interagency Working Group 2013, U.S. 

Environmental Protection Agency 2015). The social cost of carbon is a monetary value 

that encompasses the economic impact of increased carbon emissions on factors such as 

agricultural productivity, human health, and property damages (Interagency Working 

Group 2013).

Wood volume—In forestry, volume is a measure of the solid content of the tree stem 

and used to estimate wood quantity. Volume data presented in this report are estimated 

using standard FIA methodology (Oswalt and Conner 2011, Woodall and others 2011), 

which are based on volume equations developed for forest grown trees, and include net 

cubic-foot volume by diameter class and species and net board-foot sawtimber volume 

by species. Net cubic-foot volume is an estimate of the gross volume in cubic feet minus 

deductions for rotten, missing, and broken-top cull. Net board-foot sawtimber volume is 

an estimate of the gross volume in board feet of the saw-log portion of sawtimber minus 

deductions for total board-foot cull. A sawtimber tree is a live tree of commercial species 

that is free of defects based on regional specifications and contains at least a 12-foot 

sawlog or two noncontiguous saw logs 8 feet or longer.

Energy consumption—The effect of trees on residential building energy use was 

calculated in i-Tree Eco using distance and direction of trees from residential structures, 

tree height, and tree condition data (McPherson and Simpson 1999). Savings in 

residential energy costs were calculated based on State average 2012 costs for natural 

gas (U.S. Energy Information Administration 2014b), 2012/2013 heating season fuel oil 

costs (U.S. Energy Information Administration 2014c), 2012 residential electricity costs 

(U.S. Energy Information Administration 2012a), and 2012 costs of wood (U.S. Energy 

Information Administration 2012b).

Compensatory value—Compensatory values were estimated in i-Tree Eco based 

on valuation procedures of the Council of Tree and Landscape Appraisers (2000) and 

reported here for all live trees (Nowak and others 2002a). Following these methods, 

adjustment factors were applied to each tree to account for the effects of tree species, 

diameter, condition, and land use on variations in perceived value. More information on 

i-Tree Eco methods (Nowak and others 2008, Nowak and Crane 2000, Nowak and others 

2002b) can be found at www.itreetools.org.
10

Large-diameter trees contribute significantly to ecosystem services.
11

ASSESSMENT SUMMARY

To assess Houston’s urban forest and establish a baseline for future monitoring, a field 

study was conducted in 2015 as part of FIA’s urban protocol. The standardized field data 

were processed using FIA methodologies and i-Tree Eco. Study results are summarized 

in table 1. Throughout this publication, except where explicitly noted, results are for live 

trees 1 inch in diameter and greater. Under the FIA field protocol for Houston, standing 

dead trees were only recorded for trees with diameters 5 inches and greater. Please refer 

to the Standing Dead Tree section for that component of the urban forest.

Table 1—Summary of the urban forest features, Houston, 2015

Feature Estimate

Number of treesa

Live saplings (1 to 4.9 inches in diameter) 23.9 million (72.0 percent of live trees)

Live trees (≥ 5 inches in diameter) 9.3 million (28.0 percent of live trees)

Standing dead trees (≥ 5 inches in diameter) 722,000

On private lands 19.2 million

Tree cover 18.4 percent

Most abundant species by:

Number of trees (live) Yaupon, Chinese tallowtree, Chinese

privet, Japanese privet, sugarberry

Leaf area Sugarberry, Chinese tallowtree, yaupon,

live oak, loblolly pine

Pollution removal 2,400 tons/year ($20.4 million/year)

VOC emissions 4,600 tons/year

Avoided runoff 173 million cubic feet/year ($7.8 million/

year)

Carbon storageb 2.0 million tons ($272 million)

Carbon sequestration 140,000 tons/year ($18.6 million/year)

Net volume 126 million cubic feet

Value of reduced building energy useb $53.9 million/year

Value of reduced carbon emissionsb $14.4 million/year

Compensatory value $16.3 billion

Note: ton = short ton (U.S.) (2,000 lbs.).

VOC = volatile organic compound.

a Diameter measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) for woodland 

species.

b These estimates are for the live and dead tree population. All other estimates are based on the live 

tree population only, except where noted.
12

Urban Forest Structure and Composition

Number of trees—Houston’s urban forest has an estimated 33.3 million trees (standard 

error [SE] of 5.3 million). The five most common species in the urban forest in terms 

of number of trees were yaupon, Chinese tallowtree, Chinese privet, Japanese privet, and 

sugarberry (fig. 4). The 10 most common species account for 74.2 percent of all live trees. 

Sixty-three unique tree species were sampled in Houston, including Osage-orange for 

which only dead trees were observed (table 2); these species and their relative abundance 

are presented in appendix 2. 

Yaupon

22.9%

Chinese tallowtree

17.1%

Chinese privet

6.9%

Japanese privet

5.7% Sugarberry

4.8%

Sweetgum

4.1%

Water oak

3.5%

Green ash

3.2%

Loblolly pine

2.9%

other species

28.9%

Figure 4—Urban forest species composition as a percentage of all live 

trees, Houston, 2015.

Table 2—Tree species sampled in the urban forest, Houston 2015

Genus Species Common name

Live trees Diametera

Diameter is

≥1 and <5 inches

Diameter is

≥5 inches Median Average

number %bnumber %b- - - - inches - - - -

Acer negundo Boxelder 328,000 1.4 205,000 2.2 3.8 6.3

Betula nigra River birch 0 0.0 24,000 0.3 7.4 7.4

Carpinus caroliniana American hornbeam 146,000 0.6 39,000 0.4 4.9 5.4

Carya aquatica Water hickory 0 0.0 53,000 0.6 7.0 7.1

Carya illinoinensis Pecan 0 0.0 376,000 4.0 11.0 12.8

Carya ovata Shagbark hickory 0 0.0 24,000 0.3 26.0 26.0

Celtis laevigata Sugarberry 786,000 3.3 799,000 8.6 5.0 5.5

Celtis occidentalis Hackberry 0 0.0 88,000 0.9 9.6 11.4

Citrus sinensis Sweet orange 769,000 3.2 12,000 0.1 3.5 3.1

Crataegus species Hawthorn spp. 655,000 2.7 13,000 0.1 3.0 2.7

Cupressus sempervirens Italian cypress 147,000 0.6 0 0.0 1.3 1.3

Cupressus species Cypress 0 0.0 12,000 0.1 15.0 15.0

Diospyros virginiana Common persimmon 456,000 1.9 12,000 0.1 1.5 1.6

Fraxinus americana White ash 0 0.0 26,000 0.3 13.1 10.5

Fraxinus berlandieriana Berlandier ash 0 0.0 59,000 0.6 14.0 14.6

Fraxinus caroliniana Carolina ash 0 0.0 12,000 0.1 22.4 22.4

continued
13

Table 2 (continued)—Tree species sampled in the urban forest, Houston 2015

Genus Species Common name

Live trees Diametera

Diameter is

≥1 and <5 inches

Diameter is

≥5 inches Median Average

number %bnumber %b- - - - inches - - - -

Fraxinus pennsylvanica Green ash 328,000 1.4 735,000 7.9 7.0 8.5

Fraxinus velutina Velvet ash 0 0.0 47,000 0.5 13.4 14.1

Gleditsia triacanthos Honeylocust 154,000 0.6 0 0.0 1.1 1.1

Ilex vomitoria Yaupon 7,599,000 31.7 12,000 0.1 1.5 1.6

Juniperus pinchotii Pinchot juniper 0 0.0 12,000 0.1 8.5 8.5

Juniperus virginiana Eastern redcedar 164,000 0.7 56,000 0.6 3.8 4.9

Lagerstroemia indica Crapemyrtle 0 0.0 279,000 3.0 9.4 11.1

Ligustrum amurense Amur privet 0 0.0 12,000 0.1 5.3 5.3

Ligustrum japonicum Japanese privetc 1,518,000 6.3 379,000 4.1 2.3 3.9

Ligustrum sinense Chinese privetc 2,293,000 9.6 0 0.0 2.2 2.3

Liquidambar styraciflua Sweetgum 638,000 2.7 715,000 7.7 5.3 6.1

Maclura pomifera Osage-oranged 0 0.0 0 0.0 N/a N/a

Magnolia grandiflora Southern magnolia 0 0.0 49,000 0.5 10.4 8.9

Melia azedarach Chinaberryc 0 0.0 204,000 2.2 8.8 11.0

Morus alba White mulberryc 0 0.0 49,000 0.5 31.5 18.8

Morus rubra Red mulberry 0 0.0 12,000 0.1 5.4 5.4

Nyssa sylvatica Blackgum 0 0.0 12,000 0.1 22.0 22.0

Ostrya virginiana Eastern hophornbeam 0 0.0 12,000 0.1 5.3 5.3

Phoenix dactylifera Date palm 0 0.0 12,000 0.1 22.6 22.6

Pinus palustris Longleaf pine 0 0.0 12,000 0.1 5.2 5.2

Pinus taeda Loblolly pine 328,000 1.4 648,000 7.0 6.9 8.9

Planera aquatica Water-elm 0 0.0 12,000 0.1 6.9 6.9

Platanus mexicana Mexican sycamore 0 0.0 12,000 0.1 31.5 31.5

Platanus occidentalis American sycamore 0 0.0 35,000 0.4 14.9 19.7

Poncirus trifoliata Hardy orangec 0 0.0 12,000 0.1 5.4 5.4

Pyrus calleryana Callery pearc 884,000 3.7 47,000 0.5 3.5 3.3

Pyrus communis Common pear 0 0.0 12,000 0.1 5.1 5.1

Quercus falcata Southern red oak 0 0.0 28,000 0.3 29.9 30.2

Quercus lyrata Overcup oak 0 0.0 13,000 0.1 18.9 18.9

Quercus nigra Water oak 594,000 2.5 577,000 6.2 3.8 8.3

Quercus pagoda Cherrybark oak 0 0.0 75,000 0.8 16.1 15.6

Quercus phellos Willow oak 0 0.0 288,000 3.1 12.3 12.4

Quercus shumardii Shumard oak 154,000 0.6 13,000 0.1 1.9 3.3

Quercus stellata Post oak 0 0.0 148,000 1.6 15.4 18.7

Quercus virginiana Live oak 0 0.0 676,000 7.3 13.6 15.7

Sabal mexicana Mexican palmetto 0 0.0 49,000 0.5 13.5 15.7

Salix nigra Black willow 0 0.0 237,000 2.5 7.6 7.4

Samanea saman Raintree 0 0.0 47,000 0.5 10.1 10.9

Tilia americana Carolina basswood 0 0.0 12,000 0.1 11.5 11.5

Triadica sebifera Chinese tallowtreec 4,289,000 17.9 1,404,000 15.1 2.3 3.7

Ulmus alata Winged elm 164,000 0.7 145,000 1.6 4.3 5.5

Ulmus americana American elm 737,000 3.1 296,000 3.2 2.9 5.0

Ulmus crassifolia Cedar elm 328,000 1.4 67,000 0.7 2.6 2.9

Ulmus parvifolia Chinese elmc 0 0.0 63,000 0.7 8.0 8.8

Ulmus rubra Slippery elm 0 0.0 12,000 0.1 13.4 13.4

Vaccinium arboreum Farkleberry 328,000 1.4 0 0.0 1.2 1.2

Zanthoxylum clava-herculis Hercules' club 164,000 0.7 26,000 0.3 4.8 4.8

N/a = not applicable.

a

Diameter measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) for woodland species. Median and average diameter 

measurements are estimated for live trees only.

b

Percent estimates represent the percent of trees in the diameter class. For example, 2.2 percent of live trees >5 inches diameter are 

boxelders.

c

Invasive species.

dOsage-orange was the only species sampled for which there were no live trees.
14

Table 3—Distribution of trees and plots among NLCD land cover 

categories, Houston, 2015

Land cover

Live trees

Plots

City land 

area

Diameter is ≥1 

and <5 inches

Diameter is 

≥5 inches

- - - - - - - - - - number - - - - - - - - - - percent

Developed–Medium 2,800,000 1,702,000 55 26.8

Developed–Low 1,230,000 1,402,000 39 19.8

Developed–High 584,000 563,000 28 18.1

Developed–Open 3,510,000 904,000 27 13.1

Forest/Scrub 15,724,000 4,747,000 24 13.1

Grass/Herb/Crop 100,000 0 14 4.6

Water 0 0 13 4.5

Total 23,948,000 9,318,000 200 100.0

NLCD = National Land Cover Database.

3 Land cover definitions provided at http://www.mrlc.gov/nlcd11_leg.php.

The city was divided into areas based on National Land Cover data to analyze variability 

of the urban forest across the city by land cover. Plots were categorized among the 

following land cover classes (table 3):

• Developed–Open: open space (mostly lawn) on developed land

• Developed–High: high intensity developed land

• Developed–Medium: medium intensity developed land

• Developed–Low: low intensity developed land

• Water: open water

• Grass/Herb/Crop: barren land, grassland/herbaceous, and pasture/hay lands

• Forest/Scrub: evergreen forest, deciduous forest, mixed forest, shrub/scrub, and 

woody wetland lands.

The land cover definitions3

 are based on the 2011 National Land Cover Database 

(NLCD) (Homer and others 2015) (for complete definitions of each category, see 

appendix 3). The distribution of the land cover classes across Houston shows that large 

contiguous areas of Forest/Scrub land are primarily in the western area of the city, as well 

as the northeastern side of the city and around Lake Houston (fig. 5). The central portion 

of the city, especially that which is encircled by Interstate-610, is primarily Developed, 

though Houston’s Memorial Park located in that region is visible as a large patch of 

Forest/Scrub land surrounded by Developed land cover. See appendix 4 for information 

on species distribution by land cover.
15

Figure 5—Land cover distribution based on National Land Cover Database (Homer and others 2015), 

Houston, 2015. Land was classified into one of seven land cover classes.

 ̄ 0 5 10 20

Miles

Land Cover and Percentage of Total

Developed-Open (13%)

Developed-Low (20%)

Developed-Medium (27%)

Developed-High (18%)

Forest/Scrub (13%)

Grass/Herb/Crop (5%)

Water (4%)

Plots were also classified in the field based on FIA land use categories (table 4). These 

land use categories, as opposed to the land cover classes described earlier, provide a 

specific look at how the land is being used by the local population in Houston. Developed 

land is used primarily by humans for purposes other than forestry or agriculture and 

include the following categories: Residential, Multi-family Residential, Rights-of-way, 

Commercial, and Other Developed (i.e., institutional, transportation, cultural, recreation, 

park, and golf course land uses). In Houston, Other Nonforest areas encompass 

agricultural land, managed wildlife openings, water, and land that does not fall into any of 

the classes described earlier.
16

Table 4—Distribution of trees among FIA land use categories, 

Houston, 2015

Land use

Live trees

City land 

area

Diameter is ≥1 

and <5 inches

Diameter is 

≥5 inches

- - - - - - - - number - - - - - - - - percent

Forest Land 19,534,000 5,092,000 12.1

Residential 1,807,000 2,263,000 24.2

Multi-family Residential 584,000 274,000 6.1

Rights-of-way 1,038,000 501,000 14.6

Commercial 831,000 219,000 16.0

Other Developed 0 933,000 17.9

Other Nonforest 154,000 36,000 9.1

Total 23,948,000 9,318,000 100.0

Sam Houston Park—28.5 percent of live trees were found on local and State government property.
17

0

50

100

150

200

250

300

350

400

0

5

10

15

20

25

Density (trees per acre)

Number of trees (millions)

Land cover

Number of trees

Density

Figure 6—Number of trees and tree density by land cover, Houston, 2015.

The majority of trees in Houston are located on FIA-defined Forest Land (81.6 percent 

for trees ≥1 and <5 inches in diameter, and 54.6 percent for trees ≥5 inches in diameter). 

However, Forest Land only covers 12.1 percent of Houston’s total area. Of the land uses 

recorded, Residential land (including Multi-family Residential) is the dominant class in 

Houston by area, comprising over 30 percent of the total area and 27.2 percent of the 

trees 5 inches in diameter and larger (table 4).

Tree density—The urban tree density in Houston is 83 trees per acre. Based on NLCD 

land cover categories, the highest density of 390 trees per acre occurs in the Forest/Scrub 

category, followed by Developed–Open (84 trees per acre) and Developed–Medium land 

(42 live trees per acre) (fig. 6). The Forest/Scrub land cover is present in 13.1 percent of 

the city and contains 61.5 percent of the trees. The Developed–Medium category covers 

26.8 percent of the land area and contains 13.5 percent of the trees. Based on the FIAdesignated land use categories, the greatest density of live trees is found on Forest Land 

(505.5 trees per acre). Of the developed land uses, Residential areas have the highest 

density with 41.7 trees per acre (fig. 7).

Tree density ranges from 6 to 1,602 trees per acre based on plots where trees are present 

(fig. 8). Live trees were observed on 107 of the 200 plots sampled. The majority of plots 

(77) with live trees present had less than 75 trees per acre. Twenty-one plots had a live 

tree density greater than 250 trees per acre and these are primarily located on the outer 

edges of the city where Forest/Scrub land tends to occur.
18

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 ̄ 0 5 10 20

Miles

(

Tree Density

(trees/acre)

1 - 75

76 - 250

251 - 800

> 800

Tree(s) present

No trees present !

Figure 8—Tree density by plot, Houston, 2015.

0

100

200

300

400

500

600

0

5

10

15

20

25

30

Density (trees per acre)

Number of trees (millions)

Land use

Number of trees

Density

Figure 7—Number of trees and tree density by land use, Houston, 2015.
19

Leaf area—Leaf area is an important measure as many ecosystem services are derived 

from leaves. Leaf area index (LAI) is a measure of the sum of all leaves’ surface area (one 

side) divided by the area of a land cover class. As each land cover class has a different 

amount of land area, LAI standardizes the leaf area on an equal area basis (acres of leaves 

per acre of land). Total leaf area is greatest in Forest/Scrub land cover (44.5 percent of 

Houston’s total leaf area) followed by Developed–Medium (23.1 percent) (fig. 9). Forest/

Scrub also had the highest LAI (3.5), followed by Developed—Low with an LAI of 

0.9 (fig. 9). Higher LAIs indicate a greater leaf surface area per acre of land. 

Leaf area among the FIA land use categories is greatest in Forest Land which contains 

more than half of all the leaf area in the city (fig. 10). Following Forest Land, the amount 

of leaf area is greatest in Residential (30.2 percent of all leaf area) and Other Developed 

(7.6 percent) areas. Leaf area index ranges from 4.4 in Forest Land to less than 0.1 in 

Other Nonforest.

Loblolly pine provides the 

greatest net volume in 

the city of Houston.
20

Leaf area has a positive correlation with environmental benefits (i.e., the greater the leaf 

area, the greater the benefit). In Houston’s urban forest, tree species with the greatest 

leaf area are sugarberry, Chinese tallowtree, and yaupon (fig. 11). Of trees accounting for 

at least 1.0 percent of the population, live oak, pecan, and sugarberry have the greatest 

average leaf area per tree (i.e., they are large trees). Small tree species that account for 

at least 1.0 percent of the population and have percent leaf area to percent population 

ratios less than 0.6 are yaupon, Chinese tallowtree, Chinese privet, Japanese privet, callery 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

20

40

60

80

100

120

140

160

180

200

Leaf area index (LAI)

Leaf area (thousands of acres)

Land cover

Leaf area

Leaf area index

Figure 9—Leaf area and leaf area index by land cover, Houston, 2015.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

0

50

100

150

200

250

Leaf area index (LAI)

Leaf area (thousands of acres)

Land use

Leaf area

Leaf area index

Figure 10—Leaf area and leaf area index by land use, Houston, 2015.
21

0

5

10

15

20

25

Sugarberry Chinese tallowtree Yaupon Live oak Loblolly

pine Water

oak Green ash American elm Pecan Sweetgum

Percent of total

Species

Leaf area

Abundance

Figure 11—Percentage of live tree population and total leaf area for 10 

most common species by leaf area, Houston, 2015.

pear, sweet orange, hawthorn species, common persimmon, cedar elm and farkleberry. 

These 10 common small species account for 63.3 percent of the population, but only 

27.2 percent of the leaf area, and have an average d.b.h. of 2.6 inches.

Importance values (IVs) are calculated using a formula that combines the relative leaf 

area and relative abundance. High importance values do not mean that these trees should 

be encouraged in the future; rather these species currently dominate the urban forest 

structure in terms of their population and leaf area (a representation of environmental 

services). The species in the urban forest with the greatest IVs are yaupon, Chinese 

tallowtree, and sugarberry (table 5). 

Table 5—Percentage of total population and leaf 

area and importance value of speciesa

, Houston, 

2015

Common name Population Leaf area IVb

- - - - - - percent - - - - - -

Yaupon 22.9 9.5 32.4

Chinese tallowtree 17.1 9.9 27.0

Sugarberry 4.8 10.4 15.2

Live oak 2.0 8.4 10.5

Water oak 3.5 6.0 9.5

Loblolly pine 2.9 6.0 9.0

Japanese privet 5.7 3.1 8.8

Chinese privet 6.9 1.9 8.8

Green ash 3.2 5.5 8.7

American elm 3.1 5.4 8.5

a List contains the 10 species with the highest importance 

values.

b IV = Population (%) + Leaf area (%).
22

Tree size—Tree size is an important characteristic of the urban forest structure. Average 

diameter of trees is highly variable, ranging from 1.0 to 34.9 inches on plots where trees 

are present (fig. 12). Plots containing trees with an average diameter >15 inches are 

scattered about the city, with a slightly greater prevalence in the interior areas than along 

the city’s edge. Of the 107 plots with live trees present, 28 had an average diameter of 

15 inches or more. Additionally, these plots generally have a lower tree density indicating 

that they are composed of few, mostly large diameter trees.

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 ̄ 0 5 10 20

Miles

Average Tree Diameter 

(inches)

0.1 - 4.9

5.0 - 9.9

10.0 - 14.9

15.0+

( Tree(s) present

No trees present !

Figure 12—Average tree diameter by plot, Houston, 2015.

Live oak in Glenwood Cemetery.
23

Large diameter trees generally have larger tree crowns than small diameter trees. 

Thus, healthy, large diameter trees contribute significantly to the ecosystem services 

provided by the urban forest primarily because leaf area has a positive correlation with 

environmental benefits (Nowak and others 2014). Trees with diameters <5 inches account 

for 72.0 percent of the tree population in Houston (fig. 13). Trees in this diameter 

class also contain 23.9 percent of the total leaf area. Four of the 10 most abundant tree 

species in Houston (i.e., yaupon, Chinese privet, Japanese privet, and Chinese tallowtree) 

have 75 percent or more of their population in the 1- to 5-inch diameter class (fig. 14). 

Trees that have diameters ≥ 15 inches account for 5.3 percent of the tree population, 

but comprise 32.6 percent of the total leaf area. Though these large diameter trees are a 

small percentage of the tree population, they are an important part of the urban forest 

in Houston. For more information about environmental benefits by diameter class, see 

appendix 5.

Species composition—Tree species composition varies between the small diameter 

(<5 inches) and large diameter trees (≥ 15 inches). The 10 most common species of 

small diameter trees are yaupon (31.7 percent of trees in d.b.h. class), Chinese tallowtree 

(17.9 percent), Chinese privet (9.6 percent), Japanese privet (6.3 percent), callery pear 

(3.7 percent), sugarberry (3.3 percent), sweet orange (3.2 percent), American elm 

(3.1 percent), hawthorn species (2.7 percent), and sweetgum (2.7 percent). The 10 most 

0

10

20

30

40

50

60

2468 10 12 14 16 18 20 22 24 26 28 30+

Percent of total

Diameter class (inches)

Leaf area

Abundance

Figure 13—Percentage of total population and leaf area by tree 

diameter class, Houston, 2015. Diameter classes are designated 

by their midpoint (e.g., 2 is actually 1 to 2.9 inches). Diameter 

measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) 

for woodland species.
24

Figure 14—Percentage of species population by diameter class for 10 most 

common species, Houston, 2015. Diameter classes are designated by their 

midpoint (e.g., 2 is actually 1 to 2.9 inches). Diameter measurements were taken 

at breast height (d.b.h.) or root collar (d.r.c.) for woodland species.

Yaupon

Chinese tallowtree

Chinese 

privet

Japanese privet

Sugarberry

Sweetgum

Water oak

Green ash

American

elm

Loblolly pine

0

10

20

30

40

50

60

70

80

90

100

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30+

Species

Species population (percent)

Diameter class

(inches)

common species of large diameter trees are live oak (15.0 percent of trees in class), water 

oak (12.8 percent), loblolly pine (8.5 percent), Chinese tallowtree (7.7 percent), green 

ash (7.1 percent), post oak (6.2 percent), pecan (6.2 percent), willow oak (3.8 percent), 

American elm (3.4 percent), and sweetgum (2.7 percent). Three species—Chinese 

tallowtree, American elm, and sweetgum—are among the 10 most common small 

diameter trees and the 10 most common large diameter trees (fig. 15).

Chinese privet, Japanese privet, and callery pear, three of the 10 most common small 

diameter trees, are classified as invasive. Chinese tallowtree is one of the 10 most common 

small and large diameter trees and is also classified as invasive. Mean and median 

diameter by species is presented in appendix 2. Mean and median diameter by land cover 

and species is presented in appendix 6.

Houston’s urban forest is a mix of native tree species and exotic species that were 

introduced by residents or other means. Urban forests often have higher tree species 

diversity than the surrounding native landscapes because of tree species introduced from 
25

0

1

2

3

4

5

6

7

8

Number of trees (milions)

Species

<5 inches

≥15 inches

Diameter class

Figure 15—Number of trees by size (small trees <5 inches; large trees ≥15 inches in 

diameter) made up by the most common tree species in those classes, Houston, 2015.

outside the region (Nowak 2010). Increased tree diversity can minimize the overall 

impact or destruction by a species-specific insect or disease (Lacan and McBride 2008, 

Santamour 1990), but the increase in the number of exotic plants can also pose a risk 

to native plants if exotic species are invasive and/or capable of displacing native species. 

In Houston, 60.4 percent of the trees (live and standing dead) are native to Texas. Trees 

with a native origin outside of North America are mostly from Asia and Australia 

(18.9 percent of live and standing dead trees).

Invasives—Invasive plant species are often characterized by their vigor, ability to adapt, 

reproductive capacity, and lack of natural enemies. These factors enable them to displace 

native plants and threaten natural areas (National Agriculture Library 2015). Eight of 

the 63 tree species sampled in Houston are identified on the local invasive species list 

(City of Houston 2010, U.S. Forest Service 2014b). These nonnative invasive species 

comprise 33.5 percent of the tree population and 18.8 percent of the city leaf area. The 

most common invasive species are Chinese tallowtree, Chinese privet, and Japanese privet 

(table 6). Of the 200 total plots, invasive tree species occurred on slightly less than a 

quarter of the plots (49 plots). Plots with invasives occur throughout the city and do not 

seem to be limited to specific areas within the city (fig. 16).
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 ̄ 0 5 10 20

Miles

Invasives

(percent)

0

1 - 20

21 - 50

51 - 80

> 80

( Tree(s) present

No trees present !

Figure 16—Proportion of invasive trees as a percent of all trees, by plot, Houston, 

2015.

Table 6—Tree species that are classified as invasivea and 

were observed in the inventory, Houston, 2015

Common name

Proportion 

of all live 

trees

Leaf area as a 

proportion of 

all leaf area

Number 

of plots 

foundb

- - - - - - - percent - - - - - - -

Chinese tallowtree 17.1 9.9 35

Chinese privet 6.9 1.9 3

Japanese privet 5.7 3.1 7

Callery pear 2.8 0.8 3

Chinaberry 0.6 1.5 5

Chinese elm 0.2 1.0 2

White mulberry 0.1 0.5 3

Hardy orange <0.1 <0.1 1

a Species is listed on Houston invasive species list (City of Houston 

2010, U.S. Forest Service 2014b).

b Number includes all plots that the species was found on whether 

the tree sampled was live or standing dead.
27

Some trees, like the Chinese tallowtree, while providing benefits, can be a source of concern as an invasive 

species.
28

Trees on Private lands—During field data collection, lands are classified into 

categories of ownership that include Private, State and Local Government, and Federal 

Government. The distribution of trees by ownership class can be an invaluable source of 

information for understanding and managing the urban forest. In Houston, 57.9 percent 

of the live tree population is found on Private lands (table 7). Nearly a quarter of the 

19.2 million trees on Private lands are yaupon, followed by Chinese privet (11.9 percent) 

and Japanese privet (9.9 percent) (table 8).

Table 7—Distribution of live saplings and trees among ownership classes, 

Houston, 2015

Ownership class

Live trees

City land 

areaa

Diameter is ≥1 

and <5 inches

Diameter is 

≥5 inches Total

percent

Private 57.4 58.9 57.9 65.2

State and Local Government 30.3 23.9 28.5 23.4

Federal Government 12.3 17.2 13.7 6.1

Total 100.0 100.0 100.0 94.7

a Remaining 5.3 percent of city land area is not assigned an ownership class as it is water.

Trees provide many social, 

economic, and environmental 

benefits to Houston residents.
29

Table 8—Species composition on Private lands, Houston, 2015 

For example, 24.2 percent of trees on Private lands are yaupon.

Species Trees Species Trees Species Trees

% % %

Yaupon 24.2 Crapemyrtle 0.8 River birch 0.1

Chinese privet 11.9 Honeylocust 0.8 White ash 0.1

Japanese privet 9.9 Italian cypress 0.8 Carolina ash 0.1

Sweetgum 6.5 American hornbeam 0.8 Date palm 0.1

Chinese tallowtree 5.5 Hackberry 0.5 Hardy orange 0.1

Callery pear 4.8 Post oak 0.4 Pinchot juniper 0.1

Sugarberry 4.3 Willow oak 0.4 American sycamore 0.1

Sweet orange 4.1 Cherrybark oak 0.4 Amur privet 0.1

Water oak 3.2 Chinese elm 0.3 Common pear 0.1

Live oak 2.6 Berlandier ash 0.3 Longleaf pine 0.1

Boxelder 2.6 Mexican palmetto 0.3 Mexican sycamore 0.1

Common persimmon 2.4 Southern magnolia 0.3 Red mulberry 0.1

Loblolly pine 1.9 Green ash 0.2 Shagbark hickory 0.1

Pecan 1.9 Raintree 0.2 Slippery elm 0.1

Farkleberry 1.7 Black willow 0.2 Blackgum 0.1

Eastern redcedar 1.1 Winged elm 0.2 Cypress 0.1

American elm 1.0 White mulberry 0.2 Eastern hophornbeam 0.1

Chinaberry 0.9 Southern red oak 0.1

Shumard oak 0.9 Cedar elm 0.1

Trees in maintained areas—Each tree was classified as to whether it was found in 

a maintained or nonmaintained area. Maintained areas are defined as those which are 

regularly impacted by mowing, weeding, herbicide applications, etc. If a tree is found in 

a maintained area, it does not necessarily imply it received maintenance. Examples of 

maintained areas include lawns, rights-of-way, and parks. 

Overall, 20.0 percent of trees (6.7 million) were classified as growing in maintained areas. 

The percentage of trees that are in maintained areas ranges from 0 percent on some plots, 

to 100 percent on other plots. There were 77 plots in Houston that had trees classified in 

maintained areas (fig. 17). Of these plots, only five also had trees in unmaintained areas. 

These five plots were distributed mostly around the edge of the city’s boundaries. 

Land covers with the highest proportion of trees in maintained areas are Developed–

High, Developed–Low, and Developed–Medium (table 9). One hundred percent of 

callery pear trees sampled were in maintained areas (table 10). Of the maintained 

tree population, 15.6 percent are Japanese privet, 14.0 percent are callery pear, and 

11.7 percent are sweet orange (table 11).
30

Table 9—Percentage of trees 

in maintained areas by land 

cover, Houston, 2015

Land cover Trees

percent

Developed–High 100.0

Developed–Low 85.2

Developed–Medium 64.5

Developed–Open 4.0

Forest/Scrub 0.9

Grass/Herb/Crop 0.0

Total 20.0

Table 10—Percentage of trees in maintained 

areas (minimum sample size = 10 live trees) 

by species, Houston, 2015

For example, 100 percent of callery pear trees 

are in maintained areas.

Species Trees Species Trees

% %

Callery pear 100.0 Loblolly pine 21.6

Live oak 96.5 Sugarberry 14.4

Crapemyrtle 95.6 American elm 10.5

Pecan 93.4 Green ash 7.4

Post oak 82.2 Chinese tallowtree 4.5

Japanese privet 54.7 Sweetgum 2.7

Water oak 35.0 Boxelder 2.5

Chinaberry 29.2 Yaupon 0.2

Willow oak 23.3

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(percent)

0

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8 - 50

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Figure 17—Percentage of trees on maintained area, by plot, Houston, 2015.
31

Table 11—Species composition in maintained areas, Houston, 2015 

For example, 15.6 percent of trees in maintained areas are Japanese privet.

Species Trees Species Trees Species Trees

% % %

Japanese privet 15.6 Hackberry 1.1 River birch 0.4

Callery pear 14.0 Willow oak 1.0 Cherrybark oak 0.4

Sweet orange 11.7 Chinese elm 0.9 Boxelder 0.2

Live oak 9.8 Chinaberry 0.9 White ash 0.2

Water oak 6.2 Berlandier ash 0.9 Carolina ash 0.2

Pecan 5.3 Eastern redcedar 0.8 Pinchot juniper 0.2

Crapemyrtle 4.0 Mexican palmetto 0.7 Date palm 0.2

Chinese tallowtree 3.8 Southern magnolia 0.7 Hardy orange 0.2

Sugarberry 3.4 Velvet ash 0.7 Yaupon 0.2

Loblolly pine 3.2 Raintree 0.7 Longleaf pine 0.2

Shumard oak 2.3 White mulberry 0.6 Mexican sycamore 0.2

Italian cypress 2.2 Sweetgum 0.6 Common pear 0.2

Post oak 1.8 American sycamore 0.5 Slippery elm 0.2

American elm 1.6 Southern red oak 0.4

Green ash 1.2 Cedar elm 0.4

Houston skyline framed by 

crapemyrtle along Buffalo 

Bayou trail.
32

Tree and ground cover—Estimates of tree and shrub cover in Houston were assessed 

in the field. Tree cover in Houston is estimated at 18.4 percent and shrub cover is 

7.5 percent, based on field crew assessments. Tree cover ranges from 2 to 95 percent 

on plots where trees are present, while shrub cover on plots ranges from 0 percent to 

85 percent (figs. 18 and 19). Plots with higher amounts of tree cover (>55 percent) mostly 

overlap with areas of Forest/Scrub land, particularly on the western side and around the 

outer portions of the city. Of the 200 plots sampled, 112 had some shrub cover. The plots 

with more than 26 percent shrub cover are more prevalent around the outer edges of the 

city where Forest/Scrub land cover is common (fig. 19).

Ground cover in Houston was also estimated by field crews; ground cover categories 

include all manmade and natural cover types within the plots, including cover beneath 

trees and shrubs. Herbaceous cover (grass and other nonwoody plants) accounts for 

37.4 percent of all ground cover. Herbaceous cover is the most common ground cover 

type in the following land cover areas: Developed–Open, Developed–Low, Grass/Herb/

Crop, and Forest/Scrub (fig. 20). Developed–Medium and Developed–High land covers 

were dominated by impervious ground covers, while areas of the Water land cover were 

dominated by water.

The dominant ground cover type varies across the 200 plots in Houston (fig. 21). 

Herbaceous ground cover is dominant on the greatest number of plots, while water is the 

dominant ground cover on the fewest plots. Of the plots with no trees present, herbaceous 

cover is the most common dominant ground cover, occurring on 33 plots. Impervious 

ground cover was the second most common, occurring on 29 plots.

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Tree Cover

(percent)

0

1 - 15

16 - 30

31 - 55

> 55

. Tree(s) present

( No trees present

Figure 18—Percentage of tree cover by plot, Houston, 2015.
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Shrub Cover

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0

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11 - 25

26 - 50

> 50

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( No trees present

Figure 19—Percentage shrub cover by plot, Houston, 2015.

0 10 20 30 40 50 60 70 80 90 100

Developed–High

Developed–Low

Developed–Medium

Developed–Open

Forest/Scrub

Grass/Herb/Crop

Water

Houston

Percent of land cover 

Land cover

herbaceous building

permeable (e.g., soil) impervious (excluding buildings)

water

Ground cover classes

Figure 20—Ground cover distribution by land cover type, Houston, 2015.
34

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Dominant Ground Cover

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Herbaceous

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Water

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Figure 21—Dominant ground cover by plot, Houston, 2015.

Urban Forest Values

The urban forest values associated with air pollution removal, volatile organic compound 

(VOC) emissions, avoided runoff, carbon sequestration, and compensatory value exclude 

dead trees as these benefits are based mainly on existing leaf area, leaf biomass, or live tree 

conditions. However, standing dead trees do contribute to and are included in estimates 

of carbon storage and energy effects.

Air pollution removal—Poor air quality is a common problem in many urban areas. 

It can damage landscape material, adversely affect ecosystem processes, and reduce 

visibility. Air pollution is also associated with significant human health effects that 

impact the pulmonary, cardiac, vascular, and neurological systems and human mortality 

(e.g., Pope and others 2002). The urban forest can help improve air quality by directly 

removing pollutants from the air and reducing energy consumption in buildings, which 

consequently reduces air pollutant emissions from power plants and other sources. While 

trees emit VOCs that can contribute to ozone formation, integrative studies have revealed 

that an increase in tree cover tends to lead to reduced ozone formation (Nowak and 

Dwyer 2000).

Pollution removal by trees in Houston was estimated using the 2015 field data and hourly 

pollution and weather data for the year 2013. Pollution removal was greatest for O3

(1,888 tons removed per year), followed by NO2 (376 tons/year), PM2.5 (116 tons/year), 

and SO2 (34 tons/year) (fig. 22). The value associated with pollution removal was greatest 
35

for PM2.5 ($14.8 million), followed by O3 ($5.4 million), NO2 ($229,000), and SO2

($8,000). It is estimated that trees alone remove 2,400 tons of air pollution (NO2, O3, 

PM2.5, and SO2) per year with an associated value of $20.4 million.

Decreases in pollution concentration due to pollution removal by trees also have a positive 

effect on human health in Houston. The economic value of pollution removal is based 

on avoided health effects due to lower pollution concentrations (Nowak and others 2014, 

U.S. Environmental Protection Agency 2012). For example, in 2015, reductions in NO2

concentration resulted in an estimated 119 fewer cases of acute respiratory symptoms 

with an associated value of $3,766 (table 12).

In 2015, trees in Houston emitted an estimated 4,552 tons of VOCs (4,086 tons of 

isoprene and 466 tons of monoterpenes). Emissions vary among species based on 

species characteristics (e.g., some genera such as oaks are high isoprene emitters) and 

leaf biomass. Ninety percent of the urban forest’s VOC emissions were from oak and 

sweetgum genera (fig. 23). These VOCs are precursor chemicals to ozone formation.4

 

General recommendations for improving air quality with trees are given in appendix 7.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

NO O PM SO

Value (million dollars/year)

Pollution removed (thousand tons/year)

Pollutant

Pollution removed

Value

2 3 2.5 2

Figure 22—Annual air pollution removal and value by urban trees, Houston, 

2015.

4 Some economic studies have estimated VOC emission costs. These costs are not included here as there is a 

tendency to add positive dollar estimates of ozone removal effects with negative dollar values of VOC emission 

effects to determine whether tree effects are positive or negative in relation to ozone. This combining of dollar 

values to determine tree effects should not be done; rather estimates of VOC effects on ozone formation (e.g., 

via photochemical models) should be conducted and directly contrasted with ozone removal by trees (i.e., 

ozone effects should be directly compared, not dollar estimates). In addition, air temperature reductions by trees 

have been shown to significantly reduce ozone concentrations (Cardelino and Chameides 1990, Nowak and 

others 2000) but are not considered in this analysis. Photochemical modeling that integrates tree effects on air 

temperature, pollution removal, VOC emissions, and emissions from power plants can be used to determine the 

overall effect of trees on ozone concentrations.
36

Table 12—Associated value ($/year) and incidence (number of cases/year) of avoided health effects from 

changes in pollution concentrations due to pollution removal by trees, Houston, 2015

Health effect NO2 SO2 O3 PM2.5

$/year

cases/

year $/year

cases/

year $/year

cases/

year $/year

cases/

year

Acute bronchitis N/a N/a N/a N/a N/a N/a 197 2.24

Acute myocardial infarction N/a N/a N/a N/a N/a N/a 40,952 0.46

Acute respiratory symptoms 3,766 119.27 123 3.91 201,811 2,360.69 116,099 1,184.47

Asthma exacerbation 153,215 1,832.86 3,101 39.22 N/a N/a 77,515 953.54

Chronic bronchitis N/a N/a N/a N/a N/a N/a 255,953 0.92

Emergency room visits 655 1.57 63 0.15 493 1.18 618 1.49

Hospital admissions 71,609 2.37 4,894 0.16 58,430 1.89 N/a N/a

Hospital admissions,

cardiovascular N/a N/a N/a N/a N/a N/a 10,131 0.26

Hospital admissions,

respiratory N/a N/a N/a N/a N/a N/a 7,032 0.22

Lower respiratory symptoms N/a N/a N/a N/a N/a N/a 1,507 29.02

Mortality N/a N/a N/a N/a 5,010,646 0.64 14,239,079 1.83

School loss days N/a N/a N/a N/a 98,910 1,007.33 N/a N/a

Upper respiratory symptoms N/a N/a N/a N/a N/a N/a 953 21.24

Work loss days N/a N/a N/a N/a N/a N/a 41,192 199.54

Total value 229,246 N/a 8,182 N/a 5,370,290 N/a 14,791,231 N/a

N/a indicates that the value is not estimated for that pollutant and health effect. The same health effects were not analyzed for each 

pollutant.

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000

Citrus

Hackberry

Maple

Sycamore

Holly

Hickory

Willow

Pine

Sweetgum

Oak

VOCs emitted (tons)

Tree genera

Isoprene

Monoterpene

VOCs emitted

Figure 23—Annual volatile organic compounds (VOCs) emitted by tree genera with 

greatest emissions, Houston, 2015.
37

Avoided runoff—Surface water runoff (commonly referred to as surface runoff or 

stormwater runoff ) can be a cause for concern in many urban areas as it can contribute 

pollution to streams, wetlands, rivers, lakes, and oceans. During precipitation events, some 

portion of the precipitation is intercepted by vegetation (trees and shrubs) while the other 

portion reaches the ground. The portion of the precipitation that reaches the ground 

and does not infiltrate into the soil or end up in surface depression storage becomes 

surface runoff (Hirabayashi 2012). In urban areas, the large extent of impervious surfaces 

increases the amount of surface runoff.

Urban trees are beneficial in reducing surface runoff. Trees intercept precipitation while 

their root systems promote infiltration and water storage in the soil. Avoided runoff due 

to trees is estimated by contrasting runoff estimates with and without trees. Avoided 

runoff is less than tree interception estimates, as in many cases soils would absorb some 

of the precipitation that would be intercepted by trees. The trees of Houston help to 

reduce runoff by an estimated 173 million cubic feet per year, with an estimated value of 

$7.8 million/year. Tree species with the greatest overall impact on runoff are sugarberry, 

Chinese tallowtree, and yaupon due to their large leaf surface area (fig. 24).

0

2

4

6

8

10

12

14

16

18

20

Sugarberry Chinese

tallowtree

Yaupon Live oak Loblolly pineWater oak Green

ash

American

elm

Pecan Sweetgum

Avoided runoff (million cubic feet/year)

Species

Figure 24—Avoided runoff for species with greatest overall impact on runoff, 

Houston, 2015. Avoided runoff by species is proportional to leaf area as runoff 

reduction is estimated on a city-wide basis.
38

Carbon storage and sequestration—Climate change is an issue of global 

concern that threatens to impact species existence, vulnerable ecosystems (e.g., coral 

reefs, polar and coastal areas), food production, water resources, and human health 

(Intergovernmental Panel on Climate Change 2014). Trees can help mitigate climate 

change by annually sequestering atmospheric carbon (from carbon dioxide [CO2]) and 

storing it in its accumulated plant tissue. They can also reduce the amount of energy 

used to heat or cool buildings, thus reducing CO2 emissions from fossil-fuel based power 

sources (Abdollahi and others 2000).

When a tree dies and decays (or is burned), it releases much of the stored carbon back 

into the atmosphere. Thus, carbon storage is an indication of the amount of carbon that 

can be released if trees are allowed to die and decompose. Although tree maintenance 

practices (e.g., pruning) can contribute to carbon emissions, maintaining healthy trees 

helps to maximize the amount of carbon stored in trees (Nowak and others 2002c). Using 

removed trees for wood products is one way to help forestall carbon emissions due to 

wood decomposition. Wood from removed trees can also be used to produce energy (e.g., 

Urban trees support activities that can improve human health.
39

heat buildings), helping reduce fossil-fuel based carbon emissions. Trees in Houston store 

an estimated 2.0 million tons of carbon (7.5 million tons of CO2) valued at $272 million.

Average carbon storage is highly variable, ranging from 0.0 to 44.7 tons per acre based on 

plots where trees are present (fig. 25). Plots with greater average carbon storage generally 

have higher tree density and/or more large trees.

In addition to carbon storage, which accounts for past carbon sequestration/accumulation, 

healthy trees continue to annually sequester carbon in new tissue growth. The amount 

of carbon annually sequestered is increased with healthier and larger diameter trees. 

Gross sequestration by urban trees in Houston is about 140,000 tons of carbon per year 

(513,000 tons per year of CO2) with an associated value of $18.6 million per year.

Of all the species sampled, live oak stores the most carbon, estimated at 14.7 percent of 

total carbon stored, and annually sequesters the most carbon, estimated at 11.0 percent 

of all sequestered carbon (figs. 26 and 27). Trees >30 inches in diameter store the most 

carbon in the city. They also store the most carbon on a per tree basis (figs. 28 and 29).

Wood volume—Understanding the net volume of wood provided by a community’s 

trees can serve a variety of purposes. From a management perspective, a thorough 

knowledge of wood volume can help predict potential storm damage and can support 

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Carbon Storage

(tons/acre)

1 - 5

6 - 15

16 - 30

> 30

( Tree(s) present

No trees present !

Figure 25—Average carbon storage per acre by plot, Houston, 2015.
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Figure 26—Estimated annual carbon storage and value for urban tree species with the 

greatest storage, Houston, 2015.

0

5

10

15

20

25

30

35

40

0

50

100

150

200

250

300

350

Live oak Loblolly

pine

Water

oak

Green ash Chinese

tallowtree

Pecan Sweetgum Post oak Willow

oak

Sugarberry

Value (million dollars)

Storage (thousand tons)

Species

Carbon storage

Value

0.0

0.5

1.0

1.5

2.0

2.5

0

2

4

6

8

10

12

14

16

Live oak Water

oak

Loblolly

pine

Chinese

tallowtree

Green

ash

Sweetgum Pecan Sugarberry Yaupon Post

oak

Value (million dollars/year)

Sequestration (thousand tons/year)

Species

Carbon sequestration

Value

Figure 27—Estimated annual carbon sequestration and value for urban tree species with 

the greatest sequestration, Houston, 2015.
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0

2

4

6

8

10

12

14

16

0

50

100

150

200

250

300

350

400

2468 10 12 14 16 18 20 22 24 26 28 30+

Total sequestration (thousand tons/year)

Total storage (thousand tons)

Diameter class (inches)

Carbon storage

Carbon sequestration

Figure 28—Estimated total carbon storage and sequestration by tree diameter class, 

Houston, 2015. Diameter classes are designated by their midpoint (e.g., 2 is actually 1 

to 2.9 inches). Diameter measurements were taken at breast height (d.b.h.) or root collar 

(d.r.c.) for woodland species.

Figure 29—Estimated average per tree carbon storage and sequestration by tree diameter 

class, Houston, 2015. Diameter classes are designated by their midpoint (e.g., 2 is actually 

1 to 2.9 inches). Diameter measurements were taken at breast height (d.b.h.) or root collar 

(d.r.c.) for woodland species.

0

20

40

60

80

100

120

140

0

1

2

3

4

5

6

246 8 10 12 14 16 18 20 22 24 26 28 30+

Average sequestration (lbs/year)

Average storage (thousand lbs)

Diameter class (inches)

Carbon storage

Carbon sequestration
42

pre-planning for post-disaster recovery. Volume data can also inform urban wood 

markets, which add value to aging or downed trees and incentivize their use for wood 

products, such as lumber and other building materials, handcrafted furniture, naturebased landscape supplies, and biofuel.

In Houston, trees are estimated to contain 126 million cubic feet of net volume and 

219 million board feet of net sawtimber volume. Loblolly pine contributes the most 

net cubic-foot volume at 12.8 percent of the city total (table 13). Loblolly pine also 

contributes 35.7 percent of the total net board-foot sawtimber volume (table 14). By 

diameter class, the greatest net cubic-foot volume is provided by trees 29 inches or greater 

in diameter (fig. 30).

Energy consumption—Trees affect energy consumption by shading buildings, 

providing evaporative cooling, and blocking winter winds. Trees tend to reduce building 

energy consumption in the summer months and can either increase or decrease building 

energy use in the winter months, depending on the location of trees around the building. 

Estimates of tree effects on energy use are based on field measurements of tree distance 

and direction to space-conditioned residential buildings (McPherson and Simpson 1999). 

In Houston, interactions between trees and buildings are projected to annually decrease 

energy requirements by 319,000 million British Thermal Units (MBTUs) and 13,000 

megawatt-hours (MWHs) during the heating season (table 15). Based on average energy 

costs in 2012 (U.S. Energy Information Administration 2012a, 2012b, 2014b, 2014c), 

Table 13—Net cubic-foot volume for 

species with the greatest net volume, 

Houston, 2015

Common name Net volume

cubic feet percent

Loblolly pine 16,145,000 12.8

Live oak 14,220,000 11.3

Water oak 13,957,000 11.0

Green ash 9,899,000 7.8

Chinese tallowtree 7,795,000 6.2

Sweetgum 7,628,000 6.0

Pecan 6,782,000 5.4

Post oak 5,655,000 4.5

Sugarberry 5,282,000 4.2

Willow oak 5,108,000 4.0

Other species 33,902,000 26.8

Total 126,373,000 100.0

Table 14—Net board-foot sawtimber 

volume for species with the greatest 

net volume, Houston, 2015

Common name Net volume

board feet percent

Loblolly pine 78,176,000 35.7

Green ash 28,551,000 13.0

Water oak 19,208,000 8.8

Willow oak 18,243,000 8.3

Southern red oak 17,126,000 7.8

Pecan 11,945,000 5.4

American

sycamore 10,168,000 4.6

Sweetgum 9,262,000 4.2

Live oak 7,774,000 3.5

Cherrybark oak 5,342,000 2.4

Other species 13,436,000 6.1

Total 219,231,000 100.0
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0

5

10

15

20

25

6 8 10 12 14 16 18 20 22 24 26 28 30+

Net volume (million cubic feet)

Diameter class (inches)

Figure 30—Net cubic-foot volume by tree diameter class, Houston, 2015. Diameter 

classes are designated by their midpoint (e.g., 6 is actually 5 to 6.9 inches). Diameter 

measurements were taken at breast height (d.b.h.).

Table 15—Annual energy savingsa (MBTU, MWH, or tons) due to 

trees near residential buildings, Houston, 2015

Reduced energy use and emissions Heating Cooling Total

MBTUb 319,000 N/a 319,000

MWHc 13,000 439,000 452,000 

Carbon avoided (tons)d 12,000 97,000 109,000 

N/a = Not applicable (MBTUs are not used to quantify cooling effects).

a Negative values indicate an increase in energy requirements.

b MBTU = Million British Thermal Units.

c MWH = Megawatt-hour.

d To convert carbon estimates to CO2 , multiply carbon value by 3.667.

this projected decrease in energy requirements is associated with a decrease in energy 

costs of $4.9 million per year (table 16). During the cooling season, energy requirements 

are projected to decrease by an estimated 439,000 MWHs with an associated value of 

$49.0 million per year. The net effect of trees on residential energy costs is a decrease of 

$53.9 million annually. Trees also provide an additional $14.4 million in value per year by 

reducing 109,000 tons of carbon emissions (398,000 tons of CO2) from fossil-fuel-based 

power sources (tables 15 and 16). 
44

Table 16—Annual monetary savingsa,b in residential energy 

expenditures during heating and cooling seasons, Houston, 2015

Reduced energy use and emissions Heating Cooling Total

U.S. dollars

MBTUc

 ($) 3,446,000 N/a 3,446,000

MWHd

 ($) 1,444,000 49,040,000 50,484,000 

Carbon avoided ($) 1,543,000 12,889,000 14,432,000 

N/a = Not applicable (MBTUs are not used to quantify cooling effects).

a Based on 2012 statewide energy costs (U.S. Energy Information Administration 2012a, 

2012b, 2014b, 2014c) and 2015 social cost of carbon (Interagency Working Group 

2013, U.S. Environmental Protection Agency 2015).

b Negative values indicate an increase in energy requirements.

c MBTU = Million British Thermal Units.

d MWH = Megawatt-hour.

Trees tend to reduce summertime energy consumption due to shading and evaporative cooling.
45

Structural and functional values—The city’s forest has a structural value based 

on the tree itself that includes compensatory value and carbon storage value. The 

compensatory value is an estimate of the value of the forest as a structural asset (e.g., 

how much should one be compensated for the loss of the physical structure of the tree). 

The compensatory value (Nowak and others 2002a) of the trees in Houston is about 

$16.3 billion (fig. 31). For small trees, a replacement cost can be used; for larger trees, 

several estimation procedures are used (Nowak and others 2002a). The structural value of 

the forest resource tends to increase with an increase in the number and size of healthy 

trees. Note that some invasive tree species are listed with a high compensatory value 

(fig. 31) because the methods used to estimate compensatory value do not account for 

management preferences (e.g., noninvasive species). Additionally, despite their status as 

an invasive, these species still contribute ecosystem services (see table 6 and table 26 for 

importance values, abundance, and leaf area data by species).

Compensatory value varies across the plots in Houston (fig. 32). It is a function of the 

number and condition of trees, types of species, diameter of trees, and land use found on 

each plot. Compensatory value per acre is greater than $200,000 per acre for six plots 

in Houston. On these plots, the average tree diameter is 15 inches or greater. Forests 

also have functional values (either positive or negative) based on the functions the trees 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Live

oak

Water oakChinese tallowtreeGreen

ash

Loblolly

pine

Pecan Post oakSugarberryCrapemyrtleAmerican elm

Compensatory value (billions of dollars)

Species

Figure 31—Tree species with the greatest collective compensatory value, Houston, 2015.
46

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Compensatory Value

(dollars/acre)

1 - 50,000

50,001 - 100,000

100,001 - 200,000

> 200,000

( Tree(s) present

No trees present !

Figure 32—Average compensatory value per acre by plot, Houston, 2015.

perform, including sequestering carbon, removing air pollutants, and reducing the amount 

of energy used to heat or cool buildings. Annual functional values also tend to increase 

with increased number and size of healthy trees and are usually on the order of several 

million dollars per year. There are many other functional values of the forest, though they 

are not quantified here (e.g., reduction in ultraviolet radiation, aesthetics, and wildlife 

habitat). Thus, the functional estimates provided in this report represent only a portion 

of the total forest functional values. Through proper management, urban forest values 

can be increased. However, the values and benefits can also decrease as the amount of 

healthy tree cover declines. There are also various monetary costs associated with urban 

forest management, such as tree pruning, inspection, removal and disposal, which are not 

accounted for in this assessment (McPherson and others 2005).

Urban trees in Houston have the following structural values:

• Compensatory value: $16.3 billion

• Carbon storage: $272 million

Urban trees in Houston have the following annual functional values:

• Carbon sequestration: $18.6 million

• Pollution removal: $20.4 million 

• Reduced energy costs: $53.9 million

• Stormwater runoff: $7.8 million

• Avoided emissions: $14.4 million
47

Urban Forest Health

A healthy urban forest will provide greater benefits to society than an unhealthy one. This 

report highlights tree damage variables, crown measurements, and the number of standing 

dead trees as indicators of urban forest health in Houston. 

Crews were asked to note the presence or absence of seven different damage variables that 

are commonly seen among trees in urban areas. These urban forest health indicators are 

of specific interest to arborists and plant health specialists.

In addition to damage variables, field crews collected crown data for all trees > 1 inch 

in diameter (see U.S. Forest Service 2015 for details). The crown dieback variable helps 

illustrate tree health and is defined as recent mortality of small branches and twigs in the 

upper and outer portion of the tree’s crown.

The number of standing dead trees is another measure of urban forest health and can 

be an indication of a specific problem, such as a pest or disease, within the urban forest. 

However, one must be cautious in interpreting health issues based on standing dead 

trees as removal rates vary among land use classes. That is, standing dead trees will likely 

remain standing long in low use areas (e.g., forests) and are removed more rapidly in 

high use areas (e.g., street trees, residential areas). Based on urban FIA protocols, all trees 

5 inches or greater in diameter that were standing dead were recorded as such. 

Although drought took its toll on trees in Memorial Park, it continues to be a highly used community 

greenspace.
48

Damage indicators of tree health—Urban FIA protocols were used to collect 

data on the following seven damage variables: (1) trunk bark inclusion, (2) root/stem 

girdling, (3) conflict with overhead wires, (4) topping/pruning, (5) sidewalk-root conflict, 

(6) excessive mulch, and (7) improper planting. For a detailed description and images of 

these variables, see U.S. Forest Service (2015). The presence or absence of these damage 

variables, along with the location of the damage, were recorded for all trees at least 1 inch 

in diameter. Damage at the root level or tree bole can potentially be more significant in 

terms of tree health as compared to damages in branches or upper bole. The severity of 

the damage was also recorded. All observed damages were recorded for each tree, with 

inspections starting at the roots and bole and progressing up to the crown (U.S. Forest 

Service 2015). 

Trunk bark inclusions were the most common damage and occurred on 6.4 percent of 

the trees in Houston. Trunk bark inclusions are places where branches are not strongly 

attached to the tree. A weak union occurs when two or more branches grow so closely 

together that bark grows between the branches and inside the union. This ingrown, or 

included, bark does not have the structural strength of wood, and the union can become 

very weak. The inside bark may also act as a wedge and force the branch union to split 

apart. The FIA-designated land use with the greatest proportion of trees with trunk bark 

inclusions is Rights-of-way (table 17). Poor pruning practices can result in the formation 

of included trunk bark. Species with the highest percent of its population with trunk bark 

inclusions were callery pear, pecan, and sugarberry (table 18).

Table 17—Percentage of trees with various types of damage by land use, Houston, 2015

For example, 68.7 percent of trees in the Rights-of-way land use had trunk bark inclusion

Damage

class

Land cover

Forest

Land

ResidentialRightsof-wayCommercialOther

Developed

Multifamily

Residential

Other

Nonforest Total

percent

Trunk bark

inclusion 1.2 17.3 68.7 1.1 3.8 1.8 6.5 6.4

Topping/

pruning 0.0 12.7 69.8 4.9 6.3 3.6 0.0 5.2

Sidewalkroot conflict 0.0 6.6 7.0 7.1 10.1 83.6 0.0 3.8

Overhead

wires 0.0 11.4 4.6 1.1 15.7 0.0 12.5 2.2

Excess

mulch 0.0 1.2 3.2 0.0 1.3 0.0 0.0 0.3

Root/stem

girdling 0.1 0.6 0.0 0.0 1.7 0.0 0.0 0.2

Improper

planting 0.0 0.6 0.0 0.0 1.3 0.0 0.0 0.1
49

Table 18—Species with greatest proportion of their population 

with damage, by damage type, Houston, 2015

For example, 97.5 percent of callery pear had trunk/bark inclusion

Damage type

and species Class

Damage type

and species Class

percent percent

Trunk bark inclusion Sidewalk-root conflict

Callery pear 97.5 Live oak 31.6

Pecan 32.3 Japanese privet 31.4

Sugarberry 28.4 Willow oak 14.9

Live oak 16.3 Water oak 9.5

Green ash 9.1 Pecan 6.6

Root/stem girdlinga Excess mulcha

Chinaberry 5.8 Willow oak 4.3

Boxelder 2.5 Pecan 3.3

Overhead wires

Loblolly pine 2.5

Live oak 1.7

Chinaberry 34.6

Improper plantinga Sugarberry 20.1

Pecan 9.7 Live oak 3.5

Water oak 9.5 Sugarberry 0.7

Post oak 8.0

Topping/pruning

Callery pear 96.2

Chinaberry 23.2

Live oak 20.4

Pecan 19.8

Crapemyrtle 18.3

Note: Only species with minimum sample size of 10 live trees are included 

in this analysis to minimize effect of small sample size on percentage 

estimates. All species values are given in appendix 8.

a There were not five species having the specific damage type of root/stem 

girdling, excess mulch, or improper planting with a minimum sample size of 

10 trees.

Topping/pruning was the second most common damage and occurred on 5.2 percent 

of the trees in Houston. Severe topping or poor pruning is the result of improper 

maintenance techniques where the stem or branches of the tree crown are removed or cut 

incorrectly and sometimes in excessive amounts. In Rights-of-way areas, topping/pruning 

was found on 69.8 percent of the trees (table 17). Callery pear, chinaberry, and live oak 

were the species with the highest proportion of their population exhibiting this damage 

(table 18).
50

Sidewalk-root conflicts were the third most common damage recorded. In 3.8 percent of 

the trees in Houston, tree root conflicts with sidewalks were observed. This conflict occurs 

when tree roots grow under sidewalks and asphalt and is noted where direct damage is 

readily apparent. The FIA-designated land use with the greatest proportion of trees with 

sidewalk conflicts was Multi-family Residential (table 17). Live oak, Japanese privet, 

and willow oak trees had the highest proportion of their population with sidewalk-root 

conflicts (table 18).

Crown indicators of tree health—Measurement of tree crowns can be used as an 

indicator of tree health. Large, dense crowns are often indicative of vigorously growing 

trees, while small, sparsely foliated crowns signal trees with little or no growth and 

possibly in a state of decline. One measurement of crown health used to estimate tree 

condition is dieback.

Trees with crown dieback >25 percent may be in decline, for both hardwoods and 

conifers (Steinman 1998). Based on the live tree population with at least 10 trees in the 

sample, species with the highest average dieback were boxelder and willow oak (table 19). 

Higher levels of dieback may indicate a potential insect, disease, or environmental 

problem associated with this species, and further evaluation is warranted. 

Standing dead trees—Seven percent of the urban tree population 5 inches in diameter 

and greater was standing dead. Twenty-two plots had standing dead trees. Plot estimates 

range from 6.0 to 42.1 standing dead trees per acre. Most plots with the highest dead tree 

densities are located in the outer (more forested) areas of the city (fig. 33). The species 

with the highest percentage of its population in standing dead trees were Osage-orange, 

Table 19—Species with greatest average dieback 

(minimum sample size = 10 trees), Houston, 2015

Species Sample

Average 

dieback

Trees with 

>25% dieback

number - - - - - - percent - - - - - -

Boxelder 18 5.6 2.5

Willow oak 22 4.5 6.9

Sweetgum 60 3.8 12.6

Chinese tallowtree 136 3.5 3.7

Sugarberry 69 2.5 1.6

Live oak 38 2.4 1.7

American elm 29 1.0 0.0
51

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Dead Tree Density

(trees/acre)

0

1 - 10

11 - 20

21 - 30

> 30

( Tree(s) present

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Figure 33—Number of standing dead trees per acre by plot, Houston, 2015.

southern red oak, willow oak, white mulberry, and loblolly pine (table 20). Of the standing 

dead tree population, 21.6 percent are loblolly pine, 14.5 percent are Chinese tallowtree, 

and 14.4 percent are sugarberry (table 21).

Higher proportions of standing dead trees may indicate potential insect, disease, or 

environmental problems associated with a specific species. In Houston, where droughts 

are a common concern, climate conditions may cause or exacerbate health problems 

among certain species. Further evaluation and monitoring of these species is warranted. 

A high percentage of dead trees does not necessarily indicate a health problem with the 

species; rather, it could be due to the fact that some trees will naturally remain standing 

as dead trees for longer periods, or that they might be left standing dead depending upon 

the land cover, risk associated with dead trees, and maintenance activities related to their 

removal. Thus, some species may have a higher proportion of dead trees as they are in 

locations where they are not immediately removed and therefore have a higher probability 

of being sampled as dead. For example, 100 percent of Osage-orange trees that were 

observed in the field were standing dead, but the species had a sample size of 4 trees, all 

of which were found in the Forest/Scrub land cover. Long-term monitoring of plots can 

help determine actual species mortality rates. Land covers with the highest estimated 

number of standing dead trees were Forest/Scrub, Developed–Low, and Developed–Open 

(table 22).
52

Table 20—Perentage of tree population classified 

as standing dead by species, Houston, 2015

For example, 100 percent of Osage-orange trees are 

standing dead

Common name Samplea Standing dead trees

- - - - number - - - - percent

Osage-orange 4 53,000 100.0

Southern red oak 1 12,000 30.7

Willow oak 7 91,000 23.9

White mulberry 1 12,000 20.2

Loblolly pine 12 156,000 19.4

Cedar elm 1 13,000 16.4

Cherrybark oak 1 13,000 14.9

Sugarberry 8 104,000 11.5

Water oak 4 49,000 7.8

Chinese tallowtree 8 104,000 6.9

Sweetgum 4 53,000 6.8

Black willow 1 13,000 5.3

Crapemyrtle 1 12,000 4.1

Green ash 2 25,000 3.3

Live oak 1 12,000 1.8

a Sample is the number of dead trees sampled for each 

species.

Table 21—Species composition of 

standing dead trees, Houston, 2015 

For example, 21.6 percent of standing 

dead trees are loblolly pine

Common name

Standing 

dead trees

percent

Loblolly pine 21.6

Chinese tallowtree 14.5

Sugarberry 14.4

Willow oak 12.5

Sweetgum 7.3

Osage-orange 7.3

Water oak 6.8

Green ash 3.4

Cherrybark oak 1.8

Black willow 1.8

Cedar elm 1.8

White mulberry 1.7

Southern red oak 1.7

Live oak 1.7

Crapemyrtle 1.6

Table 22—Percentage of tree population 

classified as standing dead by land 

cover, Houston, 2015

Land cover

Standing dead 

trees

number percent

Forest/Scrub 526,000 10.0

Developed–Low 87,000 5.8

Developed–Open 82,000 8.3

Developed–High 16,000 2.7

Developed–Medium 12,000 0.7

Grass/Herb/Crop 0 N/a

Water 0 N/a

Total 722,000 7.2

N/a = not applicable; percent not estimated for 

land covers with no standing dead trees.
53

MANAGEMENT IMPLICATIONS

The urban forest of Houston and its associated benefits vary across the city and inevitably 

will change over time. An important aspect of managing the urban forest for current 

and future residents is to understand how to sustain the benefits for all city residents. 

This report details urban forest benefits and provides a baseline for making decisions to 

improve forest management. Future monitoring is important as long-term urban forest 

plot data can be used to more accurately assess changes in species composition, size 

class distribution, and environmental benefits, in addition to assessing tree growth and 

mortality (Nowak and others 2004, 2013b).

Urban forest managers must consider prioritizing areas to protect or enhance the existing 

tree cover. An accepted paradigm is the “right tree in the right place” so that the trees 

can provide desired services and survive with minimal maintenance. While current tree 

cover for all of Houston is estimated at 18.4 percent, it ranges from 0.2 percent in the 

Water land areas to 53.6 percent in the Forest/Scrub lands. This tree-cover variability 

corresponds to variability in urban forest benefits across the city. 

Houston’s tree canopy frames Heritage Plaza.
54

Additional issues to consider in urban forest management are the forces that can cause 

species changes and alterations to the structure and composition of the urban forest over 

time and thus the provision of environmental benefits. Natural forces that could play a 

role in shaping the future urban forest include the current tree size distribution, nonnative 

invasive species, and potential pest infestations. Human activities, such as development 

and population growth, can have a large impact on the future urban forest as well. Other 

factors that will influence future forest structure include land cover changes, climate 

change, changing infrastructure, and natural resource management.

Current Size Distribution and Potential Species Changes

Change in species composition and tree size structure of Houston’s urban forest may have 

a significant influence on the benefits provided by the urban forest for the next several 

decades. These changes are likely to require a different approach in forest management 

strategies that affect species composition. These strategies include pest management, 

regeneration, and restoration efforts.

The future urban forest will be determined, in part, by the structure and composition of 

today’s urban forest. Younger trees will grow to larger sizes, and older trees will eventually 

decline and die. Houston has more small trees than large trees (this leads to an inverse 

J-shaped distribution of diameter structure; see fig. 13). This pattern is a favorable 

indication of long-term sustainability of tree cover. The shape of the diameter distribution 

curve is dependent on many factors such as mortality rates, growth rates, and influx rates 

(i.e., the number of trees being planted or naturally regenerating each year, which is not 

analyzed in this report). 

By comparing the species composition of small trees (<5 inches diameter) with that of 

the large trees (15 inches diameter or greater), the future urban forest can be predicted. 

Several of the most common large diameter tree species, particularly live oak, pecan, post 

oak, and willow oak, are underrepresented among the small diameter trees (fig. 15). This 

indicates that there may not be enough regeneration and planting of these species to 

maintain the current species mix in the future. Species that dominate the small diameter 

class and appear to be regenerating well are Chinese tallowtree and American elm. 

Some other species dominating the small diameter class, such as Chinese privet and 

Japanese privet, do not attain a large stature at maturity. If these individual small trees 

are replacing large trees in the urban landscape, this could lead to lower canopy levels and 

altered size structure. 
55

Nonnative Invasive Species

Nonnative invasive species are another concern in Houston (City of Houston 2010, U.S. 

Forest Service 2014b). Invasive tree species account for 11.1 million live trees with a leaf 

area of 77,000 acres. The invasive species observed in Houston can alter the urban forest 

composition through time as they spread into the surrounding landscape, potentially 

displacing native species and altering local ecosystems (Pimentel and others 2000). 

Management of invasive species (i.e., eradication) must consider loss of environmental 

services and the subsequent need for increased management of desirable species to offset 

losses.

Insect and Disease Impacts

Insects and diseases can infest urban forests, potentially killing trees and reducing the 

health, value, and sustainability of the urban forest. Various pests have different tree hosts, 

so the potential damage or risk of each pest will differ. We evaluated 20 exotic insects/

diseases for their potential impact using range maps of the pests in the coterminous 

United States and host species information (U.S. Forest Service 2013, 2014a; Worrall 

2007). For a complete list of the 20 exotic insects/diseases, see appendix 9.

In Houston, concerns about insect and disease impacts are compounded by the local 

climate. During periods of prolonged droughts, trees can become distressed, making 

them more vulnerable to pest infestations and diseases. Texas has historically experienced 

intense droughts, most notably the drought that lasted from 1950 to 1957. In more recent 

years, the State recorded one of its most extreme 12-month precipitation deficits from 

October 2010 to September 2011 (Nielsen-Gammon 2011).

Although there are additional pests that could impact Houston’s urban forest, gypsy moth 

(GM), Asian longhorned beetle (ALB), oak wilt (OW), Dutch elm disease (DED), and 

emerald ash borer (EAB) pose the most serious threats, each putting more than 1 million 

trees at risk to infestation (table 23). At the time of this study (2015), OW and DED 

were confirmed present in Harris, Fort Bend, and Montgomery Counties where Houston 

is located. Potential loss from OW is 2.6 million trees with an associated compensatory 

value of $6.7 billion, while DED could impact 1.7 million trees ($616 million compensatory value). EAB, which was detected in Harrison County, TX, in April 2016, is located 

within 250 miles of Harris, Fort Bend, and Montgomery Counties. Potential loss of 
56

trees from EAB is 1.2 million ($1.4 billion compensatory value). GM and ALB have 

not been found within 750 miles of Harris, Fort Bend, and Montgomery Counties, but 

the impacts of these two pests could be devastating. Potential loss of trees from GM is 

5.9 million ($7.5 billion in compensatory value) and ALB is 3.7 million ($2.1 billion in 

compensatory value). 

Oak wilt has posed a threat to the large population of oak trees in Houston over the last 

few decades. Efforts to prevent the spread of oak wilt are motivated by the fact that oak is 

a significant tree in Houston. There were eight different oak species sampled in Houston 

though water oak, live oak, and willow oak make up more than 83 percent of the total 

number of oak trees. Citywide, oaks account for 7.7 percent of the trees in the urban 

forest and more than a quarter of the carbon stored and sequestered there. It is found in 

five of the seven land cover categories.

In more recent years, emerald ash borer has become a greater threat to Houston’s urban 

forest. The pest’s detection in Harrison County, TX, in April 2016 and ability to spread 

rapidly have spurred the call for mitigation and preparedness planning in the Houston 

Table 23—Potential risk to trees by insect or disease, Houston, 2015

Code

Scientific 

name Common name

Trees at 

risk

As proportion 

of all trees

Compensatory 

value

number percent $ millions

GM Lymantria

dispar

Gypsy moth 5,866,000 17.6 7,537 

ALB Anoplophora

glabripennis

Asian longhorned

beetle

3,701,000 11.1 2,122 

OW Ceratocystis

fagacearum

Oak wilta 2,566,000 7.7 6,683 

DED Ophiostoma

novo-ulmi

Dutch elm

diseasea 1,747,000 5.3 616 

EAB Agrilus

planipennis

Emerald ash

borer

1,207,000 3.6 1,435 

SPB Dendroctonus

frontalis

Southern pine

beetle

988,000 3.0 912 

PSB Tomicus

piniperda

Pine shoot

beetlea 988,000 3.0 912 

SW Sirex noctilio Sirex woodwasp 988,000 3.0 912 

LAT Choristoneura

conflictana

Large aspen

tortrix

260,000 0.8 82 

AL Phyllocnistis

populiella

Aspen leafminer 237,000 0.7 63 

SOD Phytophthora

ramorum

Sudden oak

death

28,000 0.1 323 

a Confirmed present in Harris, Fort Bend, and/or Montgomery Counties.
57

area (Texas A&M Forest Service 2016). The ash population in Houston consists of 

five different ash species, a total number of 1.2 million live trees (table 24), and is found 

in five of the seven land cover categories (table 25). With a contribution of 7.2 percent 

of the city’s leaf area (table 24), ash trees are providing a moderate amount of the urban 

forest’s ecosystem services. Ash species are most prominent in Forest/Scrub areas, 

comprising 18.8 percent of the total tree population in that land cover. On a plot basis, 

ash tree density ranged from 6.0 to 147.2 trees per acre, though ash trees were only 

observed on 20 plots in Houston (fig. 34). However, only 2 of the 200 plots sampled had 

densities equivalent to more than 100 ash trees per acre. These higher ash density plots 

occurred on the western side of the city.

Table 24—Ash estimates, Houston, 2015

Estimate type Units Estimate

Proportion 

of all trees

Population Number 1,207,000 3.6%

Density Trees per acre 3.0 N/a

Carbon stored Tons 183,000 9.0%

Carbon sequestered Tons per year 11,000 7.6%

Leaf area Acres 30,000 7.2%

Leaf biomass Tons 9,000 5.0%

Trees, diameter < 5 inchesa Number 328,000 27.1%b

Trees, diameter ≥15 inchesa Number 173,000 14.4%b

N/a = not applicable; density cannot be described as a proportion of all trees.

a Diameter measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) 

for woodland species.

b Percentage of all ash trees.

Table 25—Ash trees by land cover, Houston, 2015

Land covera Ash trees

Ash tree 

density

Proportion of 

trees in land 

cover that are ash

number trees per 

acre

percent

Forest/Scrub 985,000 18.8 4.8

Developed–Medium 142,000 1.3 3.2

Developed–Low 37,000 0.5 1.4

Developed–High 31,000 0.4 2.7

Developed–Open 12,000 0.2 0.3

Houston 1,207,000 3.0 3.6

a No ash trees were found on Grass/Herb/Crop land cover; no trees were 

found on Water land cover.
58

Population Growth

One anthropogenic force that could shape Houston’s future urban forest is population 

growth. In 2015, Houston’s population reached 2,296,000 people, an increase of 

8.9 percent from 2010 (U.S. Census Bureau 2010). Continued population growth in 

Houston can have many implications for the urban forest. Most notably, development 

of land to support growing housing and economic needs could impact the land cover 

composition of the city and change local infrastructure.

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Ash Tree Density

(trees/acre)

0

1 - 10

11 - 30

31 - 100

> 100

( Tree(s) present

No trees present !

Figure 34—Number of ash trees per acre by plot, Houston, 2015.
59

CONCLUSION

The Houston urban forest contributes significantly to the environment, the economy, and 

residents’ well-being. Throughout the city, an estimated 33.3 million trees, representing 

more than 63 species, provide a canopy cover of 18.4 percent. That canopy, particularly 

leaf surface area, provides a wide range of important environmental benefits including air 

pollution removal, reduced carbon emissions, carbon storage and sequestration, reduced 

energy use for buildings, stormwater capture, and many others. 

There are a number of change forces that will impact Houston’s forest structure and 

health, as well as the environmental benefits provided to the city’s residents in the future. 

Some of these forces include insect and disease infestations, invasive trees and other 

plants, aging and loss of larger trees, expansion of opportunistic species, changes in the 

management and use of the forest, and human population growth. 

This analysis provides a baseline for future monitoring. While data from this report 

captures the current urban forest resource and the ecosystem services and values provided 

by it, future monitoring will be necessary to identify how the forest is changing over time. 

One-fifth of the plots established in the city of Houston will be remeasured every year as 

part of the continuing urban FIA program. Future analyses of the city’s forest can be used 

to determine the role that natural and human forces play in shaping forest structure and 

composition.

For now, managers can use these data to inform long-term management plans and 

policies to sustain a healthy urban tree population and ecosystem services for future 

generations. Planning and management of the urban forest resource can help sustain 

vital ecosystem services and values for current and future generations in Houston. In the 

future, change analyses can be used to evaluate the success of urban forest management 

programs.

More information on trees in Houston can be found at: FIA Tools (http://www.fia.fs.fed.

us/tools-data/) or My City’s Trees (www.mycitystrees.com).
60

Houston’s urban forest helps manage stormwater runoff.
61

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68

APPENDIX 1—URBAN FIA 

Sampling Design

The FIA program maintains a systematic grid of permanent plots (FIA core plots) across 

the United States that is used to inventory and monitor the Nation’s forests (Reams and 

others 2005). The urban FIA inventory uses the same sampling frame as the core FIA 

program and data are used to produce estimates of the quantity, health, composition, and 

benefits of urban trees. The urban FIA protocol follows a city-based model where urban 

inventory plots are located in the U.S. Census-defined urban areas and urban clusters 

(UAUC), within a chosen core-based statistical area (CBSA). Houston city limits are 

defined by the 2010 U.S. Census.

There are two zones of interest in the urban FIA sample design (fig. 35). Urban FIA plots 

within the CBSA-confined UAUC boundaries are established at the same location as the 

FIA core plots, and tree measurements are taken at all sample sites regardless of whether 

they are forested or not. Collocated urban plots are measured at the same intensity and on 

the same timeline as the rest of the FIA core plots in the region. 

The second zone of interest in the urban FIA sample design is the city boundary that 

is associated with the chosen CBSA. Urban plots within the city boundary may include 

§ ̈¦45

§ ̈¦10

Harris

Polk Tyler

Brazoria

Liberty

Hardin

Wharton

Walker

Grimes

Matagorda

Colorado

Jackson

Austin

Fort Bend

Montgomery

Brazos

Waller

Robertson

Burleson

Chambers

Madison

San Jacinto

Washington

Galveston

 ̄ 0 12.5 25 50

Miles

 Houston FIA 

City

UAUC

CBSA

Figure 35—Location of Houston city boundary and urban areas and urban 

clusters (UAUC), within the Houston core-based statistical area (CBSA).
69

some plots that are collocated with established core FIA plots, but also consist of an 

intensified set of urban-design only plots. In general, sampling within the target city will 

be intensified to the point of reaching a total of approximately 200 plots.

In Houston, there were 38 established FIA core plots within the CBSA-confined UAUC 

boundary that were being sampled in the year of the study (i.e., 2015 field season), but 

only 11 were located in the Houston city boundaries. Intensification within Houston city 

boundaries added 198 additional urban plots, bringing the total number of urban FIA 

plots to 209. The estimates contained within this report are based only on that sample of 

200 accessible plots in the city boundaries of Houston.

Data Collection

With support from State and city cooperators, data collection on the intensified plots 

in Houston was accelerated so that all data collection took place during the 2015 field 

season. Ordinarily, under the standard urban FIA protocol, the intensified plots within 

the city limits are measured on the same timeline as core FIA plots in the State, using 

the FIA panel system (Reams and others 2005). The proportion of the total sample plots 

measured in a given year is related to the cycle length. States with a cycle length of 5 years 

will have 1

/5th of the total number of plots sampled each year, and remeasurement will 

begin in the 6th year. The Houston urban plots will be remeasured on a 5-year cycle, as 

are the FIA core plots in eastern Texas.

As data collection continues annually, there will be additional data collected in the 

CBSA-confined UAUC boundary, and analysis and reporting will be expanded to 

include this new urban zone. Also, annual plot remeasurements will begin on a portion 

of intensified plots within the city beginning in the 2016 field season, allowing for urban 

monitoring and analyses of change in future reports.

Plot Layout

Each urban forest inventory plot consisted of one circular plot 1

/6 acre in size with a radius 

of 48 feet. Each plot contained four nested microplots; each 1

/300 acre in size, with a radius 

of 6.8 feet and offset 12 feet horizontal in each cardinal direction from the plot center. 

Urban FIA and core FIA plot layouts are the same in total sampled area but differ in 

configuration. The single circular urban plot has the same total area as the FIA core plot 

consisting of a cluster of four subplots. The urban nested microplots are the equivalent of 

the nested microplots of an FIA core plot, with each being the same diameter. For more 

details on the FIA core plot layout, see Bechtold and Scott (2005).
70

APPENDIX 2—SPECIES SAMPLED IN THE 

HOUSTON URBAN FOREST

Table 26—Scientific and common names of tree species sampled in the urban forest, with estimated metrics for species, 

Houston, 2015

Genus Species Common name Live trees

Leaf 

area IVa

Diameterb

Basal areac

Structural 

Median Average value

number % % inches inches ft 2 $ millions

Acer negundo Boxelder 533,000 1.6 1.8 3.4 3.8 6.3 167,000 185

Betula nigra River birch 24,000 0.1 0.0 0.1 7.4 7.4 7,000 19

Carpinus caroliniana American hornbeam 186,000 0.6 0.6 1.2 4.9 5.4 30,000 27

Carya aquatica Water hickory 53,000 0.2 0.1 0.3 7.0 7.1 15,000 10

Carya illinoinensis Pecan 376,000 1.1 4.1 5.3 11.0 12.8 405,000 901

Carya ovata Shagbark hickory 24,000 0.1 0.4 0.5 26.0 26.0 93,000 174

Celtis laevigata Sugarberry 1,585,000 4.8 10.4 15.2 5.0 5.5 488,000 669

Celtis occidentalis Hackberry 88,000 0.3 0.7 1.0 9.6 11.4 75,000 155

Citrus sinensis Sweet orange 781,000 2.3 0.9 3.3 3.5 3.1 45,000 122

Crataegus species Hawthorn spp. 668,000 2.0 0.2 2.2 3.0 2.7 30,000 27

Cupressus sempervirens Italian cypress 147,000 0.4 0.0 0.5 1.3 1.3 1,000 8

Cupressus species Cypress 12,000 0.0 0.1 0.2 15.0 15.0 14,000 12

Diospyros virginiana Common persimmon 468,000 1.4 0.2 1.6 1.5 1.6 9,000 11

Fraxinus americana White ash 26,000 0.1 0.2 0.2 13.1 10.5 16,000 21

Fraxinus berlandieriana Berlandier ash 59,000 0.2 0.6 0.8 14.0 14.6 85,000 217

Fraxinus caroliniana Carolina ash 12,000 0.0 0.2 0.2 22.4 22.4 34,000 80

Fraxinus pennsylvanica Green ash 1,063,000 3.2 5.5 8.7 7.0 8.5 708,000 977

Fraxinus velutina Velvet ash 47,000 0.1 0.7 0.9 13.4 14.1 58,000 139

Gleditsia triacanthos Honeylocust 154,000 0.5 0.0 0.5 1.1 1.1 1,000 4

Ilex vomitoria Yaupon 7,610,000 22.9 9.5 32.4 1.5 1.6 116,000 143

Juniperus pinchotii Pinchot juniper 12,000 0.0 0.1 0.1 8.5 8.5 5,000 15

Juniperus virginiana Eastern redcedar 220,000 0.7 0.6 1.3 3.8 4.9 33,000 79

Lagerstroemia indica Crapemyrtle 279,000 0.8 1.2 2.1 9.4 11.1 229,000 510

Ligustrum amurense Amur privet 12,000 0.0 0.0 0.0 5.3 5.3 2,000 7

Ligustrum japonicum Japanese privetd 1,897,000 5.7 3.1 8.8 2.3 3.9 270,000 332

Ligustrum sinense Chinese privet d

 2,293,000 6.9 1.9 8.8 2.2 2.3 77,000 74

Liquidambar styraciflua Sweetgum 1,353,000 4.1 3.8 7.9 5.3 6.1 477,000 451

Maclura pomifera Osage-oranged,e 0 0.0 0.0 0.0 n/a n/a 10,000 0

Magnolia grandiflora Southern magnolia 49,000 0.1 0.3 0.4 10.4 8.9 22,000 59

Melia azedarach Chinaberryd

 204,000 0.6 1.5 2.1 8.8 11.0 168,000 264

Morus alba White mulberryd

 49,000 0.1 0.5 0.6 31.5 18.8 142,000 209

Morus rubra Red mulberry 12,000 0.0 0.1 0.1 5.4 5.4 2,000 7

Nyssa sylvatica Blackgum 12,000 0.0 0.2 0.2 22.0 22.0 31,000 25

Ostrya virginiana Eastern hophornbeam 12,000 0.0 0.1 0.1 5.3 5.3 2,000 2

Phoenix dactylifera Date palm 12,000 0.0 0.2 0.3 22.6 22.6 35,000 17

Pinus palustris Longleaf pine 12,000 0.0 0.0 0.1 5.2 5.2 2,000 7

Pinus taeda Loblolly pine 976,000 2.9 6.0 9.0 6.9 8.9 828,000 905

Planera aquatica Water-elm 12,000 0.0 0.1 0.1 6.9 6.9 3,000 3

Platanus mexicana Mexican sycamore 12,000 0.0 0.1 0.2 31.5 31.5 64,000 150

continued
71

Table 26 (continued)—Scientific and common names of tree species sampled in the urban forest, with estimated metrics 

for species, Houston, 2015

Genus Species Common name Live trees

Leaf 

area IVa

Diameterb

Basal areac

Structural 

Median Average value

number % % inches inches ft 2 $ millions

Platanus occidentalis American sycamore 35,000 0.1 0.8 1.0 14.9 19.7 96,000 184

Poncirus trifoliata Hardy oranged

 12,000 0.0 0.0 0.1 5.4 5.4 2,000 7

Pyrus calleryana Callery peard

 931,000 2.8 0.8 3.6 3.5 3.3 65,000 193

Pyrus communis Common pear 12,000 0.0 0.0 0.1 5.1 5.1 2,000 6

Quercus falcata Southern red oak 28,000 0.1 0.7 0.8 29.9 30.2 165,000 323

Quercus lyrata Overcup oak 13,000 0.0 0.1 0.1 18.9 18.9 26,000 25

Quercus nigra Water oak 1,171,000 3.5 6.0 9.5 3.8 8.3 855,000 1,531

Quercus pagoda Cherrybark oak 75,000 0.2 0.9 1.1 16.1 15.6 126,000 155

Quercus phellos Willow oak 288,000 0.9 2.2 3.0 12.3 12.4 366,000 384

Quercus shumardii Shumard oak 167,000 0.5 0.8 1.3 1.9 3.3 31,000 33

Quercus stellata Post oak 148,000 0.4 2.3 2.7 15.4 18.7 316,000 670

Quercus virginiana Live oak 676,000 2.0 8.4 10.5 13.6 15.7 1,171,000 3,562

Sabal mexicana Mexican palmetto 49,000 0.1 0.1 0.3 13.5 15.7 67,000 35

Salix nigra Black willow 237,000 0.7 0.8 1.5 7.6 7.4 79,000 63

Samanea saman Raintree 47,000 0.1 0.7 0.8 10.1 10.9 35,000 85

Tilia americana Carolina basswood 12,000 0.0 0.1 0.1 11.5 11.5 8,000 20

Triadica sebifera Chinese tallowtreed

 5,693,000 17.1 9.9 27.0 2.3 3.7 880,000 1,245

Ulmus alata Winged elm 308,000 0.9 1.1 2.1 4.3 5.5 55,000 56

Ulmus americana American elm 1,032,000 3.1 5.4 8.5 2.9 5.0 269,000 483

Ulmus crassifolia Cedar elm 394,000 1.2 0.6 1.8 2.6 2.9 48,000 54

Ulmus parvifolia Chinese elmd

 63,000 0.2 1.0 1.2 8.0 8.8 27,000 78

Ulmus rubra Slippery elm 12,000 0.0 0.3 0.4 13.4 13.4 12,000 23

Vaccinium arboreum Farkleberry 328,000 1.0 0.1 1.1 1.2 1.2 2,000 5

Zanthoxylum clava-herculis Hercules’ club 190,000 0.6 0.6 1.2 4.8 4.8 24,000 20

N/a = not applicable; median and average diameter cannot be estimated for species that have no live trees.

a IV = importance value (% live population + % leaf area).

b Diameter measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) for woodland species. Median and average diameter 

measurements are estimated for live trees only.

c Basal area is the cross sectional area of the tree stems measured at the diameter. This is estimated for live and dead trees.

d Invasive species. 

e Osage-orange was the only species sampled for which there were no live trees.
72

APPENDIX 3—LAND COVER CATEGORY 

DESCRIPTIONS

Table 27—Land cover categories and descriptions, based on aggregation of the 

2011 National Land Cover classes (Homer and others 2015)

Land cover 

category

NLCD

code

NLCD

class

Land cover

description

Water 11 Open Water Areas of open water, generally with 

< 25 percent cover of vegetation or 

soil.

Developed–Open 21 Developed, Open 

Space

Areas with a mixture of some 

constructed materials, but mostly 

vegetation in the form of lawn 

grasses. Impervious surfaces 

account for < 20 percent of total 

cover. These areas most commonly 

include large-lot single-family 

housing units, parks, golf courses, 

and vegetation planted in developed 

settings for recreation, erosion 

control, or aesthetic purposes.

Developed–Low 22 Developed, Low 

Intensity

Areas with a mixture of constructed 

materials and vegetation. Impervious 

surfaces account for 20 to 49 percent 

of total cover. These areas most 

commonly include single-family 

housing units.

Developed–Medium 23 Developed, 

Medium Intensity

Areas with a mixture of constructed 

materials and vegetation. Impervious 

surfaces account for 50 percent to 

79 percent of the total cover. These 

areas most commonly include singlefamily housing units.

Developed–High 24 Developed, High 

Intensity

Highly developed areas where 

people reside or work in high 

numbers. Examples include 

apartment complexes, row 

houses and commercial/industrial. 

Impervious surfaces account for 

80 percent to 100 percent of the total 

cover.

Grass/Herb/Crop 31 Barren Land Areas of bedrock, desert pavement, 

scarps, talus, slides, volcanic 

material, glacial debris, sand dunes, 

strip mines, gravel pits and other 

accumulations of earthen material. 

Generally, vegetation accounts for 

less than 15 percent of total cover.

continued
73

Table 27 (continued)—Land cover categories and descriptions, based on 

aggregation of the 2011 National Land Cover classes (Homer and others 2015)

Land cover 

category

NLCD

code

NLCD

class

Land cover

description

Grass/Herb/Crop

(continued)

71 Grassland/

Herbaceous

Areas dominated by gramanoid or 

herbaceous vegetation, generally 

greater than 80 percent of total 

vegetation. These areas are not 

subject to intensive management 

such as tilling, but can be utilized for 

grazing.

81 Pasture/Hay Areas of grasses, legumes, or grasslegume mixtures planted for livestock 

grazing or the production of seed or 

hay crops, typically on a perennial 

cycle. Pasture/hay vegetation 

accounts for greater than 20 percent 

of total vegetation.

Forest/Scrub 41 Deciduous Forest Areas dominated by trees generally 

greater than 5 meters tall, and 

greater than 20 percent of total 

vegetation cover. More than 

75 percent of the tree species shed 

foliage simultaneously in response to 

seasonal change.

42 Evergreen Forest Areas dominated by trees generally 

greater than 5 meters tall, and 

greater than 20 percent of total 

vegetation cover. More than 

75 percent of the tree species 

maintain their leaves all year. Canopy 

is never without green foliage.

43 Mixed Forest Areas dominated by trees generally 

greater than 5 meters tall, and 

greater than 20 percent of total 

vegetation cover. Neither deciduous 

nor evergreen species are greater 

than 75 percent of total tree cover.

52 Shrub/Scrub Areas dominated by shrubs; less 

than 5 meters tall with shrub canopy 

typically greater than 20 percent of 

total vegetation. This class includes 

true shrubs, young trees in an early 

successional stage or trees stunted 

from environmental conditions.

90 Woody Wetlands Areas where forest or shrubland 

vegetation accounts for greater than 

20 percent of vegetative cover and 

the soil or substrate is periodically 

saturated with or covered with water.
74

APPENDIX 4—TREE SPECIES 

DISTRIBUTION

This appendix illustrates various species distributions for the Houston urban forest. 

During field data collection, sampled trees are identified to the most specific classification 

possible. Some trees have been identified to the species or genus level.

The species distributions for each land cover are illustrated for the 20 most common 

species or all species if there are less than 20 species in the land cover category. The Water 

land cover category has 0 trees and is not depicted.

0 5 10 15 20 25

Willow oak

Cedar elm

Common persimmon

Pecan

Boxelder

Hawthorn spp.

Sweet orange

Callery pear

Live oak

American elm

Loblolly pine

Green ash

Water oak

Sweetgum

Sugarberry

Japanese privet

All Species

Chinese privet

Chinese tallowtree

Yaupon

Total population (percent)

Species Figure 36—The 20 most common tree species as a percent of the total urban tree population, 

Houston, 2015.
75

0

10

20

30

40

50

60

70

80

90

100

Yaupon Chinese

tallowtree

Chinese

privet

Japanese

privet

SugarberrySweetgum Water

oak

Green

ash

American

elm

Loblolly

pine

Land cover population (percent)

Species

Developed-High Developed-Low

Developed-Medium Developed-Open

Forest/Scrub Grass/Herb/Crop

Land cover category

Figure 37—Proportion of the total tree population found in each land cover category for the 10 most 

common species, Houston, 2015. For example, yaupon comprises 49.7 percent of the tree population 

in the Developed–Open land cover.

0

10

20

30

40

50

60

70

80

90

100

Yaupon Chinese tallowtreeChinese privetJapanese privetSugarberrySweetgum Water

oak

Green

ash

American elm Loblolly

pine

Species population (percent)

Species

Developed-High Developed-Low

Developed-Medium Developed-Open

Forest/Scrub Grass/Herb/Crop

Land cover category

Figure 38—Distribution of each species’ total citywide population among each land cover category for 

the 10 most common species, Houston, 2015. For example, 100 percent of Chinese privet in Houston 

is located in the Forest/Scrub land cover.
76

0 10 20 30 40 50 60

Southern red oak

Chinese tallowtree

Chinese elm

Cedar elm

Willow oak

Green ash

Eastern redcedar

Pecan

Water oak

Crapemyrtle

Live oak

Japanese privet

Percent of trees

Species

Figure 39—Percentage of trees in Developed–High land cover category, Houston, 2015.

0 5 10 15 20 25 30 35

Chinaberry

Carolina ash

Boxelder

Eastern redcedar

White mulberry

Southern magnolia

Mexican palmetto

Post oak

American elm

Hackberry

Crapemyrtle

Sugarberry

Live oak

Shumard oak

Honeylocust

Loblolly pine

Pecan

Chinese tallowtree

Water oak

Sweet orange

Percent of trees

Species Figure 40—Percentage of trees in Developed–Low land cover category, Houston, 2015.
77

0 5 10 15 20 25

Loblolly pine

Cherrybark oak

Green ash

American sycamore

Velvet ash

Raintree

Post oak

Chinese elm

Berlandier ash

Chinaberry

Pecan

Crapemyrtle

Italian cypress

Water oak

Chinese tallowtree

Live oak

Japanese privet

Sugarberry

American elm

Callery pear

Percent of trees

Species

Figure 41—Percentage of trees in Developed–Medium land cover category, Houston, 2015.

0 10 20 30 40 50

Green ash

Eastern hophornbeam

Cypress

Cherrybark oak

Cedar elm

Carolina basswood

Blackgum

Boxelder

Willow oak

Live oak

American elm

Loblolly pine

Chinaberry

Sugarberry

American hornbeam

Sweetgum

Common persimmon

Water oak

Chinese tallowtree

Yaupon

Percent of trees

Species Figure 42—Percentage of trees in Developed–Open land cover category, Houston, 2015.
78

0 5 10 15 20 25 30

American elm

Eastern redcedar

Common persimmon

Hercules' club

Willow oak

Black willow

Water oak

Winged elm

Farkleberry

Cedar elm

Boxelder

Hawthorn spp.

Loblolly pine

Japanese privet

Sugarberry

Green ash

Sweetgum

Chinese privet

Chinese tallowtree

Yaupon

Percent of trees

Species

Figure 43—Percentage of trees in Forest/Scrub land cover category, Houston, 2015.

0 20 40 60 80 100

Chinese tallowtree

Percent of trees

Species Figure 44—Percentage of trees in Grass/Herb/Crop land cover category, Houston, 2015.
79

APPENDIX 5—RELATIVE TREE EFFECTS

The urban forest in Houston provides benefits that include carbon storage, carbon 

sequestration, and air pollutant removal. These benefits vary across diameter classes 

(table 28). The relative value of tree benefits is calculated to show how carbon storage and 

sequestration, and air pollutant removal vary by tree size and equates to municipal carbon 

emissions, passenger automobile emissions, and household emissions.

Table 28—Average tree effects by tree diameter class, Houston, 2015

Diametera Carbon storage

Carbon 

sequestration

Pollution 

removal

inches Lbs. $ milesb lbs/yr. $/yr. milesb lbs/yr. $/yr.

2 4 0.29 17 1.7 0.12 7 0.04 0.18

4 25 1.69 101 3.5 0.23 14 0.07 0.29

6 53 3.52 212 7.3 0.48 29 0.16 0.69

8 114 7.59 457 11.5 0.77 46 0.25 1.05

10 197 13.09 788 19.2 1.28 77 0.36 1.50

12 341 22.71 1,367 23.8 1.58 95 0.41 1.74

14 470 31.27 1,883 29.9 1.99 120 0.45 1.90

16 593 39.46 2,376 34.6 2.30 139 0.58 2.45

18 635 42.22 2,541 39.5 2.62 158 0.57 2.39

20 1,045 69.53 4,186 64.3 4.28 257 0.89 3.76

22 1,142 75.97 4,573 60.2 4.01 241 0.83 3.52

24 1,253 83.38 5,019 64.8 4.31 260 1.04 4.38

26 2,054 136.67 8,227 97.8 6.51 392 1.23 5.18

28 2,431 161.72 9,735 124.7 8.30 499 1.55 6.55

30+ 2,986 198.66 11,959 119.5 7.95 479 1.32 5.57

a Diameter classes are designated by their midpoint (e.g., 2 is actually 1 to 2.9 inches). 

Diameter measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) for 

woodland species.

b Miles = number of automobile miles driven that produces emissions equivalent to tree effect.

General tree information:

Number of live trees sampled = 882

Number of species sampled, including Osage-orange for which only dead trees were 

observed = 63

Municipal carbon emissions are based on 2010 U.S. per capita carbon emissions (World 

Bank 2010). Per capita emissions were multiplied by city population to estimate total city 

carbon emissions.

Light duty vehicle emission rates (grams per mile) for carbon monoxide (CO), nitrogen 

oxides (NOX), VOCs, particulate matter less than 10 microns (PM10), SO2 for 2010 
80

(Heirigs and others 2004, U.S. Bureau of Transportation Statistics 2010), and CO2 for 

2011 (U.S. Environmental Protection Agency 2010) were multiplied by average miles 

driven per vehicle in 2011 (U.S. Federal Highway Administration 2013) to determine 

average emissions per vehicle. 

Household emissions are based on average electricity kWh usage, natural gas Btu 

usage, fuel oil Btu usage, kerosene Btu usage, LPG Btu usage, and wood Btu usage per 

household in 2009 (U.S. Energy Information Administration 2013, 2014a).

CO2, SO2, and NOX power plant emission per kWh are from Leonardo Academy 2011. 

CO emission per kWh assumes one-third of 1 percent of C emissions (U.S. Energy 

Information Administration 1994).

CO2, NOX, SO2, and CO emission per Btu for natural gas, propane, and butane (average 

used to represent LPG), Fuel #4 and #6 (average used to represent fuel oil and kerosene) 

(Leonardo Academy 2011).

CO2 emissions per Btu of wood (U.S. Energy Information Administration 2014a).

CO, NOX, and sulfur oxides (SOX) emission per Btu based on total emissions and wood 

burning (tons) (British Columbia Ministry 2005, Georgia Forestry Commission 2009).

Total annual pollution removal per pollutant was contrasted with annual emissions per 

city, vehicle, and household to determine offset equivalents of urban forests versus city, 

vehicle, and household emissions.

The trees in Houston provide:

Carbon storage equivalent to:

Amount of carbon (C) emitted in region in 67 days, or

Annual C emissions from 1,446,000 automobiles, or

Annual C emissions from 592,500 single family homes

Nitrogen dioxide removal equivalent to:

Annual nitrogen dioxide emissions from 53,800 automobiles, or

Annual nitrogen dioxide emissions from 24,300 single family homes

Sulfur dioxide removal equivalent to:

Annual sulfur dioxide emissions from 373,000 automobiles, or

Annual sulfur dioxide emissions from 1,000 single family homes

Annual carbon sequestration equivalent to:

Amount of C emitted in region in 5 days, or

Annual C emissions from 98,900 automobiles, or

Annual C emissions from 40,500 single family homes
81

APPENDIX 6—TREE SPECIES 

STATISTICS BY LAND COVER

Table 29—Tree statistics by land cover and species, Houston, 2015

Land cover and species Trees

Basala

area

Diameterb

Average Median

number ft 2

/acre inches

Developed–High

Cedar elm 15,600 0.1 9.9 9.9

Chinese elm 15,600 0.1 10.5 10.5

Chinese tallowtree 15,600 0.2 12.1 12.1

Crapemyrtle 62,600 0.3 8.2 8.0

Eastern redcedar 31,300 0.1 6.6 6.6

Green ash 31,300 0.2 8.5 8.5

Japanese privet 584,400 0.3 2.4 2.3

Live oak 234,600 5.5 16.4 14.4

Pecan 46,900 0.2 7.5 6.4

Southern red oak 15,600 1.0 29.9 29.9

Water oak 62,600 0.8 12.8 12.4

Willow oak 31,300 0.6 16.1 16.1

Developed–Low

American elm 62,000 1.2 15.1 11.8

Boxelder 12,400 0.3 19.5 19.5

Carolina ash 12,400 0.4 22.4 22.4

Chinaberry 12,400 0.0 7.0 7.0

Chinese tallowtree 198,500 3.0 12.7 13.3

Crapemyrtle 86,900 0.9 12.1 13.9

Date palm 12,400 0.4 22.6 22.6

Eastern redcedar 24,800 0.2 9.8 9.8

Green ash 12,400 0.6 25.8 25.8

Hackberry 74,400 0.8 11.1 9.5

Hardy orange 12,400 0.0 5.4 5.4

Honeylocust 153,800 0.0 1.1 1.1

Japanese privet 12,400 0.0 6.1 6.1

Live oak 99,300 2.7 15.2 13.4

Loblolly pine 161,300 2.2 12.9 10.6

Mexican palmetto 37,200 0.6 14.8 13.5

Pecan 186,100 2.3 12.8 12.9

Pinchot juniper 12,400 0.1 8.5 8.5

Post oak 49,600 1.7 21.6 21.8

continued
82

Table 29 (continued)—Tree statistics by land cover and species, 

Houston, 2015

Land cover and species Trees

Basala

area

Diameterb

Average Median

number ft 2

/acre inches

Developed–Low (continued)

Shumard oak 153,800 0.0 1.9 1.9

Southern magnolia 37,200 0.3 9.9 10.4

Southern red oak 12,400 1.1 30.5 30.5

Sugarberry 99,300 0.8 7.8 6.0

Sweet orange 781,400 0.6 3.1 3.5

Water oak 240,600 2.8 9.2 3.3

Water-elm 12,400 0.0 6.9 6.9

White ash 12,400 0.1 7.8 7.8

White mulberry 37,200 1.8 23.1 31.5

Willow oak 12,400 0.0 7.2 7.2

Developed–Medium

American elm 819,500 0.7 3.4 2.9

American sycamore 35,500 0.9 19.7 14.9

Amur privet 11,800 0.0 5.3 5.3

Berlandier ash 59,100 0.8 14.6 14.0

Callery pear 931,400 0.6 3.3 3.5

Cherrybark oak 23,600 0.4 18.0 18.0

Chinaberry 70,900 0.5 10.6 10.0

Chinese elm 47,300 0.2 8.3 7.9

Chinese tallowtree 265,600 1.2 7.1 2.5

Common pear 11,800 0.0 5.1 5.1

Crapemyrtle 130,000 1.2 11.8 10.4

Green ash 35,500 1.6 29.5 31.5

Italian cypress 147,300 0.0 1.3 1.3

Japanese privet 453,900 0.3 3.3 3.6

Live oak 295,600 4.8 16.0 13.2

Loblolly pine 23,600 0.2 12.5 12.5

Longleaf pine 11,800 0.0 5.2 5.2

Mexican palmetto 11,800 0.2 18.4 18.4

Mexican sycamore 11,800 0.6 31.5 31.5

Pecan 118,200 1.5 14.4 11.7

Post oak 47,300 0.7 16.2 15.2

Raintree 47,300 0.3 10.9 10.1

Red mulberry 11,800 0.0 5.4 5.4

River birch 23,600 0.1 7.4 7.4

Shagbark hickory 23,600 0.9 26.0 26.0

Slippery elm 11,800 0.1 13.4 13.4

continued
83

Table 29 (continued)—Tree statistics by land cover and species, 

Houston, 2015

Land cover and species Trees

Basala

area

Diameterb

Average Median

number ft 2

/acre inches

Developed–Medium (continued)

Sugarberry 483,900 0.9 4.9 2.8

Sweetgum 23,600 0.4 17.8 17.8

Velvet ash 47,300 0.5 14.1 13.4

Water oak 241,900 2.5 9.6 1.8

White mulberry 11,800 0.0 5.3 5.3

Yaupon 11,800 0.1 9.3 9.3

Developed–Open

American elm 58,700 1.1 12.1 8.7

American hornbeam 146,200 0.4 4.9 4.9

Blackgum 11,700 0.6 22.0 22.0

Boxelder 35,200 0.3 8.7 8.6

Carolina basswood 11,700 0.2 11.5 11.5

Cedar elm 11,700 0.1 6.8 6.8

Cherrybark oak 11,700 0.1 7.9 7.9

Chinaberry 93,900 1.0 9.5 8.8

Chinese tallowtree 497,400 0.5 2.8 2.6

Common persimmon 304,200 0.2 1.9 1.8

Cypress 11,700 0.3 15.0 15.0

Eastern hophornbeam 11,700 0.0 5.3 5.3

Green ash 11,700 1.3 19.5 19.5

Live oak 47,000 0.7 11.3 9.7

Loblolly pine 82,200 3.1 13.7 10.0

Pecan 11,700 0.8 25.1 25.1

Post oak 11,700 0.5 20.5 20.5

Southern magnolia 11,700 0.0 5.9 5.9

Sugarberry 129,100 1.0 8.3 7.5

Sweetgum 298,900 2.1 6.2 5.7

Water oak 362,900 1.5 4.0 3.8

Willow oak 47,000 1.3 12.7 11.4

Yaupon 2,193,500 0.6 1.6 1.6

Forest/Scrub

American elm 92,000 0.8 8.8 8.5

American hornbeam 39,400 0.2 7.2 7.2

Black willow 236,700 1.5 7.4 7.6

Boxelder 485,400 2.4 5.8 3.8

Cedar elm 367,000 0.7 2.4 2.6

continued
84

Table 29 (continued)—Tree statistics by land cover and species, 

Houston, 2015

Land cover and species Trees

Basala

area

Diameterb

Average Median

number ft 2

/acre inches

Forest/Scrub (continued)

Cherrybark oak 39,400 1.5 16.4 16.1

Chinaberry 26,300 1.2 19.5 19.5

Chinese privet 2,293,100 1.5 2.3 2.2

Chinese tallowtree 4,615,800 9.1 3.3 2.2

Common persimmon 163,800 0.0 1.1 1.1

Eastern redcedar 163,800 0.2 3.8 3.8

Farkleberry 327,600 0.0 1.2 1.2

Green ash 971,900 7.8 7.3 6.5

Hackberry 13,100 0.2 13.2 13.2

Hawthorn spp. 668,300 0.6 2.7 3.0

Hercules' club 190,100 0.5 4.8 4.8

Japanese privet 846,400 4.1 5.3 2.2

Loblolly pine 708,900 7.7 7.3 5.4

Overcup oak 13,100 0.5 18.9 18.9

Pecan 13,100 0.1 7.4 7.4

Post oak 39,400 1.6 17.5 12.3

Shumard oak 13,100 0.5 19.7 19.7

Sugarberry 872,700 5.3 5.1 3.3

Sweetgum 1,030,500 6.1 5.8 5.0

Water hickory 52,600 0.3 7.1 7.0

Water oak 263,000 4.2 11.3 11.8

White ash 13,100 0.2 13.1 13.1

Willow oak 197,200 4.7 12.1 11.3

Winged elm 308,400 1.1 5.5 4.3

Yaupon 5,405,100 1.5 1.6 1.5

Grass/Herb/Crop

Chinese tallowtree 99,800 0.0 1.0 1.0

a Basal area is the cross-sectional area of the tree stems measured at the 

diameter. This is estimated for live and dead trees.

b Diameter measurements were taken at breast height (d.b.h.) or root collar (d.r.c.) 

for woodland species. Median and average diameter measurements are estimated 

for live trees only.
85

APPENDIX 7—GENERAL 

RECOMMENDATIONS FOR

AIR QUALITY IMPROVEMENT

Urban vegetation can directly and indirectly affect local and regional air quality by 

altering the urban atmospheric environment. Four main ways that urban trees affect air 

quality are:

1. Temperature reduction and other microclimatic effects

2. Removal of air pollutants

3. Emission of volatile organic compounds (VOC) and tree maintenance emissions

4. Energy conservation on buildings and consequent power plant emissions

The cumulative and interactive effects of trees on climate, pollution removal, VOC, and 

power plant emissions determine the overall impact of trees on air pollution. Cumulative 

studies involving urban tree impacts on ozone have revealed that increased urban canopy 

cover, particularly with low VOC-emitting species, leads to reduced ozone concentrations 

in cities. Local urban forest management decisions also can help improve air quality.

Urban forest management strategies to help improve air quality include:

Strategy Reason

Increase the number of healthy trees Increases pollution removal

Sustain existing tree cover Maintains pollution removal levels

Maximize use of low VOC-emitting trees Reduces ozone and carbon monoxide

formation

Sustain large, healthy trees Large trees have greatest per-tree

effects

Use long-lived trees Reduces long-term pollutant

emissions from planting and removal

Use low maintenance trees Reduces pollutant emissions from

maintenance activities

Reduce fossil fuel use in maintaining vegetation Reduces pollutant emissions

Plant trees in energy conserving locations Reduces pollutant emissions from

power plants

Plant trees to shade parked cars Reduces vehicular VOC emissions

Supply ample water to vegetation Enhances pollution removal and

temperature reduction

Plant trees in polluted or heavily populated areas Maximizes tree air quality benefits

Avoid pollutant-sensitive species Improves tree health

Utilize evergreen trees for particulate matter Provides year-round removal of

particles
86

APPENDIX 8—DAMAGE TYPE AND 

MAINTENANCE OR SITE ISSUE 

STATISTICS

Table 30—Percent of live trees identified with damage or maintenance or site issues, Houston, 2015

Species Sample

Damage variable

Trunk 

bark 

inclusion

Root/

stem 

girdling

Overhead 

wires

Topping/

pruning

Sidewalkroot 

conflict

Excess 

mulch

Improper 

planting

n - - - - - - - - - - - - - - - - - - - - - - - - percent - - - - - - - - - - - - - - - - - - - - - - - -

American elm 29 2.3 0.0 3.4 3.4 0.0 0.0 0.0

American hornbeam 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0

American sycamore 3 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Amur privet 1 0.0 0.0 0.0 100.0 0.0 0.0 0.0

Berlandier ash 5 100.0 0.0 0.0 80.0 0.0 0.0 0.0

Black willow 18 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Blackgum 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Boxelder 18 0.0 2.5 0.0 0.0 0.0 0.0 0.0

Callery pear 10 97.5 0.0 0.0 96.2 1.3 0.0 0.0

Carolina ash 1 100.0 0.0 0.0 100.0 0.0 0.0 0.0

Carolina basswood 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Cedar elm 7 44.5 4.0 0.0 0.0 4.0 0.0 0.0

Cherrybark oak 6 0.0 0.0 15.8 31.6 0.0 0.0 0.0

Chinaberry 17 5.8 5.8 34.6 23.2 5.8 0.0 0.0

Chinese elm 5 0.0 0.0 0.0 0.0 0.0 75.1 0.0

Chinese privet 14 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Chinese tallowtree 136 0.0 0.0 0.4 0.4 0.5 0.0 0.0

Common pear 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Common persimmon 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Crapemyrtle 22 0.0 0.0 0.0 18.3 4.2 0.0 0.0

Cypress 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Date palm 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Eastern hophornbeam 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Eastern redcedar 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Farkleberry 5 0.0 0.0 0.0 14.2 0.0 0.0 0.0

Green ash 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Hackberry 58 9.1 0.0 0.0 2.3 0.0 0.0 0.0

Hardy orange 7 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Hawthorn spp. 1 100.0 0.0 0.0 0.0 100.0 0.0 0.0

continued
87

Table 30 (continued)—Percent of live trees identified with damage or maintenance or site issues, 

Houston, 2015

Species Sample

Damage variable

Trunk 

bark 

inclusion

Root/

stem 

girdling

Overhead 

wires

Topping/

pruning

Sidewalkroot 

conflict

Excess 

mulch

Improper 

planting

n - - - - - - - - - - - - - - - - - - - - - - - - percent - - - - - - - - - - - - - - - - - - - - - - - -

Hercules' club 5 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Honeylocust 3 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Italian cypress 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Japanese privet 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Live oak 38 0.0 0.0 0.0 0.0 31.4 0.0 0.0

Loblolly pine 52 16.3 0.0 3.6 20.4 31.6 1.7 3.5

Longleaf pine 53 0.0 0.0 0.0 0.0 2.5 2.5 0.0

Mexican palmetto 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Mexican sycamore 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Overcup oak 1 0.0 0.0 100.0 100.0 100.0 0.0 0.0

Pecan 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Pinchot juniper 30 32.3 0.0 9.7 19.8 6.6 3.3 0.0

Post oak 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Raintree 12 0.0 0.0 8.0 16.0 0.0 0.0 0.0

Red mulberry 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0

River birch 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Shagbark hickory 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Shumard oak 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Slippery elm 1 0.0 100.0 0.0 0.0 100.0 0.0 0.0

Southern magnolia 4 50.7 0.0 25.3 25.3 25.3 0.0 0.0

Southern red oak 2 0.0 0.0 0.0 0.0 55.8 0.0 0.0

Sugarberry 69 28.4 0.0 20.1 8.3 3.0 0.0 0.7

Sweet orange 6 0.0 0.0 1.6 0.0 0.0 0.0 0.0

Sweetgum 60 0.0 0.0 0.0 0.9 0.0 0.0 0.0

Velvet ash 4 100.0 0.0 0.0 100.0 100.0 0.0 0.0

Water hickory 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Water oak 49 4.3 0.0 9.5 5.2 9.5 0.0 0.0

Water-elm 1 100.0 0.0 0.0 0.0 0.0 0.0 0.0

White ash 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0

White mulberry 4 0.0 0.0 24.1 0.0 0.0 0.0 0.0

Willow oak 22 0.0 0.0 0.0 5.4 14.9 4.3 0.0

Winged elm 12 4.3 0.0 0.0 0.0 0.0 0.0 0.0

Yaupon 49 0.0 0.0 0.0 0.0 0.2 0.0 0.0

All trees 882 6.4 0.2 2.2 5.2 3.8 0.3 0.1

This table includes only the live tree population in Houston. Osage-orange is not included as it is the only the species for which 

only standing dead trees were sampled.
88

APPENDIX 9—POTENTIAL INSECT AND 

DISEASE IMPACTS

We evaluated 20 insects and diseases, along with their tree hosts in the Houston area, to 

quantify their potential impact on the urban forest. The number of trees at risk (table 31) 

reflects only the known host tree species that could experience mortality due to the pest.

Pest range maps (U.S. Forest Service 2013, 2014a; Worrall 2007) were used to determine 

the proximity of each pest to the area. For Houston, proximity was classified for insects 

Table 31—Selected insect or disease threats and the potential risk to Houston trees, 

2015

Code Scientific name Common name

Trees at 

risk

Compensatory 

value

number $ millions

AL Phyllocnistis populiella Aspen leafminer 237,000 63 

ALB Anoplophora glabripennis Asian longhorned beetle 3,701,000 2,122 

BBD Cryptococcus fagisuga Beech bark disease 0 0

BC Sirococcus clavigignentijuglandacearumButternut canker 0 0

CB Cryphonectria parasitica Chestnut blight 0 0

DA Discula destructive Dogwood anthracnose 0 0

DED Ophiostoma novo-ulmi Dutch elm disease 1,747,000 616 

DFB Dendroctonus

pseudotsugae

Douglas-fir beetle 0 0

EAB Agrilus planipennis Emerald ash borer 1,207,000 1,435 

FR Cronartium fusiforme Fusiform rust 0 0

GSOB Agrilus auroguttatus Goldspotted oak borer 0 0

GM Lymantria dispar Gypsy moth 5,866,000 7,537 

LAT Choristoneura conflictana Large aspen tortrix 260,000 82 

LWD Raffaelea lauricola Laurel wilt 0 0

OW Ceratocystis fagacearum Oak wilt 2,566,000 6,683 

PSB Tomicus piniperda Pine shoot beetle 988,000 912 

SOD Phytophthora ramorum Sudden oak death 28,000 323 

SPB Dendroctonus frontalis Southern pine beetle 988,000 912 

SW Sirex noctilio Sirex woodwasp 988,000 912 

TCD Pityophthorus juglandis

and Geosmithia spp.

Thousand canker

disease

0 0
89

and diseases in Harris, Fort Bend, and Montgomery Counties; within 250 miles of any of 

these three counties; between 250 and 750 miles of the counties; or greater than 750 miles 

away. Since there are no pest range maps for Dutch elm disease and chestnut blight, 

the ranges of these pests were based on known occurrence and the known host range, 

respectively (U.S. Forest Service 2013, 2014a; Worrall 2007).

Proximity data for 11 insects and diseases, along with the numbers of trees potentially 

affected and their compensatory values, are illustrated in fig. 45.

Figure 45—Number of trees at risk of insect and disease and the associated compensatory 

value, Houston, 2015. This figure does not include the pests and diseases that were not a 

threat to any of the species sampled in the city. For a complete list of the pests and diseases 

assessed, see table 31.

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0

1

2

3

4

5

6

OW

DE

D

SPBEABPSB

LA

T

GM

ALB

SW

AL

SO

D

Compensatory value

(billions of dollars)

Number of trees (millions)

Pest/Disease

Trees at risk

Compensatory value

Within counties

Within 250 miles of counties

Between 250 and 750 miles of counties

Greater than 750 miles away

T

L
90

Based on the host tree species for each pest and the current range of the pest, it is possible 

to estimate the risk of attack by one of these insects or diseases for each tree species 

sampled in Houston. In table 32, species risk is designated as one of the following: 

• Red—tree species is at risk to at least one pest within counties

• Orange—tree species has no risk to pests within counties, but has a risk to at least 

one pest within 250 miles from the counties

• Yellow—tree species has no risk to pests within 250 miles of counties, but has a risk 

to at least one pest that is 250 to 750 miles from the counties

• Green—tree species has no risk to pests within 750 miles of counties, but has a risk 

to at least one pest that is greater than 750 miles from the counties.

Tree species that were sampled in Houston, but are not listed in this matrix, are not 

known to be hosts to any of the 20 insects and diseases evaluated. This table also excludes 

the pests and diseases that were not a threat to any of the species sampled in the city. For 

a complete list of the pests and diseases assessed, see table 31. Tree species groups with 

the greatest risk to existing pest infestations in Houston are pines, oaks, and elms.

The majority of observed trees were in maintained areas such as lawns, rights-of-way, and parks.
91

Table 32—Potential insect and disease risk for tree species, Houston, 2015 Spp. riska Risk weightb

Common name

Pestsc

OWDEDSPBEABPSBLATGMALBSWALSOD

7 Loblolly pine

7 Longleaf pine

6 Southern red oak

5 Water oak

5 American elm

5 Live oak

5 Cedar elm

5 Winged elm

5 Willow oak

5 Shumard oak

5 Post oak

5 Cherrybark oak

5 Overcup oak

5 Slippery elm

4 Green ash

3 Berlandier ash

3 Velvet ash

3 White ash

3 Carolina ash

5 Black willow

4 River birch

2 Chinese elmd

1 Sweetgum

1 Callery peard

1 Hawthorn spp.

1 Boxelder

1 American sycamore

1 Eastern hophornbeam

1 Carolina basswood

aSpecies risk: Red indicates that the tree species is at risk to at least one pest within Harris County, Fort Bend 

County, or Montgomery County. Orange indicates that the tree species has no risk to pests within Harris County, 

Fort Bend County, or Montgomery County, but has a risk to at least one pest within 250 miles of the county. 

Yellow indicates that the tree species has no risk to pests within 250 miles of Harris County, Fort Bend County, or 

Montgomery County, but has a risk to at least one pest that is 250 to 750 miles from the county. Green indicates that 

the tree species has no risk to pests within 750 miles of Harris County, Fort Bend County, or Montgomery County, 

but has a risk to at least one pest that is greater than 750 miles from the county.

b Risk weight: Numerical scoring system based on sum of points assigned to pest risks for species. Each pest that 

could attack tree species is scored as 4 points if red, 3 points if orange, 2 points if yellow, and 1 point if green. 

cPest color codes: Red indicates pest is within Harris County, Fort Bend County, or Montgomery County. Orange 

indicates pest is within 250 miles of Harris County, Fort Bend County, or Montgomery County. Yellow indicates pest 

is within 750 miles of Harris County, Fort Bend County, or Montgomery County. Green indicates pest is outside of 

these ranges.

dSpecies in bold text indicate that species is on the local invasive species list.

Nowak, David J.; Bodine, Allison R.; Hoehn, Robert E., III; Edgar, Christopher B.; Riley, 

Gretchen; Hartel, Dudley R.; Dooley, Kerry J.; Stanton, Sharon M.; Hatfield, Mark A.; 

Brandeis, Thomas J.; Lister, Tonya W. 2017. Houston’s Urban Forest, 2015. Resour. Bull. 

SRS–211. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research 

Station. 91 p.

An analysis of the urban forest in Houston, Texas, reveals that this area has an estimated 

33.3 million live trees with tree canopy that covers 18.4 percent of the city. Roughly 19.2 million of 

the city’s trees are located on private lands. The most common tree species are yaupon, Chinese 

tallowtree, Chinese privet, Japanese privet, and sugarberry. Trees in Houston currently store 

about 2.0 million tons of carbon (7.5 million tons of carbon dioxide [CO2]); valued at $272 million. 

In addition, these trees remove about 126,000 tons of carbon per year (462,000 tons CO2 per 

year) ($16.8 million per year) and about 2,400 tons of air pollution per year ($20.4 million per 

year). Houston’s urban forest is also estimated to provide 126 million cubic feet of net wood 

volume and to reduce annual residential energy costs by $54.6 million per year. Reduction in 

runoff provided by the trees in Houston is estimated at 173 million cubic feet per year with an 

associated value of $7.8 million per year. The compensatory value of the trees is estimated at 

$16.3 billion. The information presented in this report can be used to improve and augment 

support for urban forest management programs and to inform policy and planning to improve 

environmental quality and human health in Houston. The analysis also provides a basis for 

monitoring changes in the urban forest over time.

Keywords: Air pollution removal, carbon sequestration, ecosystem services, tree value, urban 

forestry inventory.

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civil rights regulations and policies, the USDA, its Agencies, offices, and employees, 

and institutions participating in or administering USDA programs are prohibited from 

discriminating based on race, color, national origin, religion, sex, gender identity 

(including gender expression), sexual orientation, disability, age, marital status, family/

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bases apply to all programs). Remedies and complaint filing deadlines vary by program or incident. 

Persons with disabilities who require alternative means of communication for program information 

(e.g., Braille, large print, audiotape, American Sign Language, etc.) should contact the responsible 

Agency or USDA’s TARGET Center at (202) 720-2600 (voice and TTY) or contact USDA through the 

Federal Relay Service at (800) 877-8339. Additionally, program information may be made available in 

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To file a program discrimination complaint, complete the USDA Program Discrimination Complaint 

Form, AD-3027, found online at http://www.ascr.usda.gov/complaint_filing_cust.html and at any USDA 

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DEPARTMENT OF AGRICULTURE

Southern Research Station

www.srs.fs.usda.gov