Forest Service

U.S. DEPARTMENT OF AGRICULTURE

FS-1230 | December 2023

Forest Inventory and Analysis

Fiscal Year 2022 Business Report
Front and back cover photos: Seneca Rocks, Monongahela National Forest, WV. USDA Forest Service photos by Preston Keres.

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Forest Inventory and Analysis

Fiscal Year 2022 Business Report

Fiscal Year 2022 Business Report 

Prepared by

Katherine Renwick

U.S. Department of Agriculture, Forest Service

Research and Development, Forest Inventory and Analysis Program

Washington, DC

i
James Peak Wilderness, Roosevelt National Forest, CO. USDA Forest Service photo by Elaine Wells.
Contents

List of Figures and Tables. .

Executive Summary. 

Introduction. 

Changes From Previous Years’ Business Reports. 

Fiscal Year 2022 Program Overview. 

Program Resources. 

Investment in Partnerships and Partners’ Contributions. 

Outputs and Products. .

Data Availability. .

Quality Assurance. .

FIA Data Requests and Access. .

Spatial Data Services. .

Web Tools and Use. .

Consultations by FIA Staff. .

Program Safety. .

Program Safety Highlights. .

FIA Program Accomplishment Highlights. .

Interactions Among Wildfire, Forest Type, and 

Landscape Position Are Key Determinants of Boreal 

Forest Carbon Stocks. .

Innovative Wood Use Can Enable Carbon-Beneficial 

Forest Management in California. .

Optimal Survey Design for Forest Carbon Monitoring 

in Remote Regions Using Multi-Objective 

Mathematical Programming. .

Evaluating Terrestrial Laser Scanning in Southeastern 

Mixed Hardwood Forests  .

Modeling the Growth and Allometric Relationships 

of Caribbean Tree Species Using Long-Term 

Permanent Plot Data. .

Using FIA Data to Identify Factors Driving Variability 

in the Mesophication of Eastern U.S. Forests. .

Global Gridded Biomass Product Based on GEDI Data. .

Forest Disturbance Intensity Maps for Conterminous 

United States, 1986–2015. .

Aridity Controls Streamflow Response 

to Forest Disturbance. .

The ‘Hole’ Story About Wood Duck Nest Cavities: 

Forest Inventory Data Reveal Increased Potential 

Habitat in Northern Minnesota. .

Shifting Forests and Carbon. .

Interactive Web Tool Provides Information About 

the Spread and Potential Impacts of Nonnative 

Forest Insects and Diseases. .

Managing the FIA Program Nationally. .

The Director’s Awards for FIA Excellence. .

FIA Program Area Updates for FY 2022. .

Interior Alaska Inventory. .

Small Area Estimation. .

Carbon. .

Land Use and Land Cover Change  .

Forest Ecosystem Health Indicators  .

Urban Inventory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

i-Tree  .

National Resource Use Monitoring. .

National Woodland Owner Survey. .

National Inventory and Monitoring 

Applications Center. .

Digital Engagement. .

Community Engagement. .

Spanning Cultures. .

FY 2023 Anticipated FIA Program Direction. .

Long-Term Strategic Direction  .

Conclusions. .

Glossary of Terms Used in Appendixes. .

Appendix A: Contacts. .

Appendix B: Additional Data Tables. .

Fiscal Year 2022 Business Report iii
List of Figures and Tables

Figure 1. FIA appropriated funding level, FYs 2007–2022.

Figure 2. FIA Program total operational funds available (A) 

and total expenses by category (B), FY 2022. Salary

and expenses are not included in the operational 

budget or expenses.

Figure 3. Federal and State FIA-supported employees by job 

group, FY 2022.

Figure 4. Grants and agreements by recipient group, FY 2022.

Figure 5. FIA investment in external partnerships through 

grants and agreements, 1999–2022.

Figure 6. Publication year of FIA 5-year State reports, FY

2022.

Figure 7. Spatial data requests made to the FIA Spatial Data

Services team (total = 181), FY 2022.

Figure 8. Number of chargeable motor vehicle accidents by

FIA unit, FYs 2010–2022.

Figure 9. Number of OSHA recordable cases by FIA unit, FYs

2010–2022.

Figure 10. Overview of the University of Tennessee and Forest

Service terrestrial laser scanning (TLS) workshop 

showing (A) the 3D point cloud and probable stem 

locations on subplot 1, (B) field collection of TLS

scans, (C) stem maps comparing TLS and manually

detected trees on subplot 1, and (D) accuracy of TLS

tree height and DBH estimates versus FIA fieldmeasured trees. USDA Forest Service photo by Todd

Schroeder.

Figure 11. A variety of tree species make up the regeneration 

layer in a Southern Appalachian forest.

Understanding how species shift, such as the shift 

to more mesic species associated with 

mesophication, helps managers prioritize stands for 

restoration and make ecologically informed 

decisions. USDA Forest Service photo by Margaret 

Woodbridge.

Figure 12. FIA units in Interior Alaska.

Figure 13. Ongoing field plot progress for Interior Alaska

inventory. The Tanana and Susitna-Copper units are 

field completed, and data are available in FIADB. 

Flyover plots were visited via helicopter and deemed

 nonforest (not requiring a field visit).

Figure 14. Field-completed (black) and unvisited, anticipated 

forested (white) FIA field locations in the Southwest

and Lower Yukon units of southwestern Alaska. 

Green is mapped forested area.

Figure 15. Small area estimation dashboard: proportion of forest

land by county.

Figure 16. Carbon stock changes for forest land remaining 

forest land for the conterminous United States 

and Coastal Alaska by FIA region and ownership 

(MMT CO2 Eq.). (Ownership information was not 

available for forest land in Interior Alaska, so those

 lands were excluded from these estimates.)

Figure 17. Landing page for the interactive Land Resources 

Explorer dashboard.

Figure 18. Development status of forest health indicator 

objectives.

Figure 19. Status of implementing urban inventories.

Figure 20. Status and availability of urban inventory data and 

reports.

Figure 21. Growth in i-Tree tool users over time.

Figure 22. Development status of timber products monitoring 

objectives.

Figure 23. Development status of NIMAC objectives.

Figure 24. Status of digital engagement portfolio milestones.

Table 1. Overview of land area, forest area calculated based 

on the FIA and RPA Assessment definitions of 

forest, percentage of land area that is forested based 

on the FIA definition, and the number of FIA forested 

base grid plots.

Table 2. Annual appropriations received by the FIA Program

and allocation of FIA-appropriated and Statecontributed funds for fieldwork, FYs 2013–2022.

Table 3. FIA grants and agreements to partners and partner 

contributions by FIA unit, FY 2022.

Table 4. Number and percent change of FIA plots sampled by

FIA unit, 2021 and 2022.

Table 5. FIA Program Federal employee estimates for hours 

worked, miles driven, aircraft hours flown, and safety 

incidents reported, FY 2022.

Table 6. National performance measures of the FIA Program,

FYs 2013–2022.

iv Forest Inventory and Analysis
Fiscal Year 2022 Business Report 1

Executive Summary

For more than 90 years, the Forest Inventory and Analysis 

(FIA) program of the Forest Service, an agency of the 

U.S. Department of Agriculture, has played an integral 

role in providing information vital to the management and 

conservation of the Nation’s forest resources. In recent 

years, an increased number of major decisions regarding 

the Nation’s forests have been made with reference to and 

reliance on FIA findings and forest resource evaluations. 

Today, FIA provides authoritative data about forest carbon, 

forest products and services, biomass availability, economic 

development opportunities, land cover and land use change, 

incidence of nonnative invasive species, impacts of pests 

and diseases, and wildfire risk, and to support the sustainable 

management and conservation of forests, water resources, 

and biodiversity.

The current FIA strategic plan requires an annual business 

report that summarizes program activities and progress 

towards implementing the 2018 Farm Bill direction. This 

annual business report, the program’s 25th, describes 

program resources, accomplishments, and plans for the 

coming year. The continued success of FIA is due, in 

part, to the program’s commitment to accountability and 

transparency in delivering the best value, quality, and array 

of products in partnership with stakeholders. 

Key findings from the fiscal year (FY) 2022 business 

report include:

Progress on inventory. FIA conducted inventory activity 

in all 50 States, including Hawaii and Interior Alaska, and 

completed 12 percent of the forested sample locations in 

the FIA base grid. FIA crews prioritized measurement of 

the 2020 and 2021 plot backlog resulting from the impact 

of the coronavirus (COVID-19) pandemic and other natural 

disasters. By the end of 2022, 95 percent of all 2020 base 

grid plots and 80 percent of 2021 base grid plots had been 

sampled. Crews also measured 63 percent of the 2022 plots. 

Catchup efforts will continue in FY 2023.

For the third year, inventory efforts continued in the 

Southwest unit of Interior Alaska where field crews worked 

by helicopter and raft in roadless areas that had not been 

inventoried beyond its rivers before. The Southwest unit 

represents a total forest area sampled of 27 million acres. 

About 45 percent of the field plots in this unit have been 

measured to date. After a 2-year pause caused by the 

COVID-19 pandemic, the National Aeronautics and Space 

Administration (NASA) was able to resume remote sensing 

data acquisition using the G-LiHT (Goddard's LiDAR, 

Hyperspectral & Thermal) Imager to supplement field 

plot information. G-LiHT imagery was collected over an 

additional 19 percent of the Southwest unit, focusing on field 

plots and near field hubs planned for the 2022 and 2023 field 

seasons. A total of 42 percent of the unit now has G-LiHT 

coverage.

Funding and partners’ support. FIA operations were 

funded through appropriations at $22.197 million. Under 

the new budget structure, Congress appropriated $257.6 

million for the newly established salary and expense 

budget line item for the Forest and Rangeland Research 

account, which includes FIA. In addition to annual program 

appropriations, FIA received an additional $25 million to 

help clear the plot backlog caused by natural disasters and 

the agency’s COVID-19 response. Forest Service Research 

and Development also provided FIA with $176,000 for 

operations and $1.5 million in information technology (IT) 

dollars. State agencies, universities, other Forest Service 

programs, other Federal agencies, and nongovernmental 

organizations (NGOs) contributed 13 percent of the total 

available funds—$14.3 million, representing an increase of 

$2.2 million over the previous year.

Grants and agreements. FIA uses grants and agreements 

with external partners to achieve high-quality results through 

expanded capacity and expertise. The FIA Program invested 

$29.7 million in grants and agreements in FY 2022, an 

increase of $6.7 million over the previous year. This increase 

was largely due to the supplemental funding Congress 

provided to address the plot backlog. 

Data availability. Data for all States, Coastal Alaska, and the 

Tanana Valley and Susitna-Copper units of Interior Alaska 

were accessible online in FY 2022; however, just 47 percent 

of States with annual inventories had data available that were 

less than 2 years old. This was due to two factors. First, some 

FIA units have been waiting to publish data until after the 

new volume and biomass equations are released in FY 2023. 

Second, the FIA Program does not upload data for a given 

inventory year until all plots in a State have been completed, 

so the sampling backlog has resulted in further delays. FIA 

data supplied information for 181 spatial data requests and 

nearly 630,000 online data requests. FIA staff provided 1,276 

consultations; this required an investment of time equivalent 

to three full-time staff positions. 
2 Forest Inventory and Analysis

Reporting and publications. FIA published 143 

publications, including 55 core publications (reports specific 

to a complete survey unit, complete State, national forest, 

or national reports), and 72 journal articles. This year’s 

published core publications included new 5-year State 

reports for Maine, Minnesota, Kentucky, Tennessee, Nevada, 

and Interior Alaska. 

Relevant meetings. FIA held 12 user group meetings 

and 9 management meetings to ensure that the program 

is providing the highest quality service and meeting its 

objectives according to the goals stated in the strategic plan 

and ongoing commitments to partners. This was more than 

double the number of meetings held in FY 2021. 

Personnel. FIA employed the equivalent of 588 full-time 

employees, 25 more than the previous year. This included 

351 Federal employees paid with the FIA portion of agency 

salary and expense funds and 237 cooperators paid through 

grants, agreements, and contracts. Cooperators are integral 

to the efficient delivery of the FIA Program, comprising 

40 percent of the total FIA workforce. Seventy percent 

of employees supported by FIA were employed in data 

collection and quality assurance, 16 percent in analysis 

and research, 9 percent in information management, and 5 

percent in administration. 

National resource use monitoring. The FIA Program uses 

questionnaires and surveys to gather data on timber products 

output, harvest utilization, and the characteristics and 

management objectives of the Nation’s private woodland 

owners. Since FY 2000, FIA has collected such data from 

106,444 surveys and questionnaires, including 2,998 in FY 

2022. This information, in concert with FIA plot data, is 

critical to monitoring the sustainability of the Nation’s forest 

resources.

Information technology. In FY 2022, the FIA Program 

continued to invest in cloud services and application 

development to facilitate data access and analysis. The 

program also redesigned the DataMart web interface to 

create a more efficient and intuitive user experience and 

replaced the previous version of the EVALIDator web 

application with an updated web interface and application 

programming interface (API) that improve performance. 

Looking to 2023 and beyond. With the help of congressional 

funding relief and support from partners, FIA anticipates 

clearing the backlog of plot sampling needs over the 

next 2 years. Partnerships are critical to success, so FIA 

will continue to work with partners and stakeholders to 

accomplish the program of work and ensure that clients’ 

needs are met. Important goals for FY 2023 and beyond 

include:

• Prioritize data collection and information production to

reduce the backlog. Based on available resources:

◦ Complete the remaining FYs 2020 and 2021 plot

backlog and 80 percent of the FY 2022 scheduled plots

during the FY 2023 field season.

◦ Continue annualized inventory across the conterminous

United States and Coastal Alaska.

◦ Complete field inventory in the Southwest Alaska unit,

the third unit of six in Interior Alaska.

◦ Continue urban data collection in all partner cities.

◦ Publish all 5-year State reports that are currently in final

review and layout.

• Given increasing challenges of measuring more remote,

roadless units in Interior Alaska, continue exploring

possible modifications to the inventory design that

improve financial and logistical feasibility while keeping

safety a priority.

• Continue working toward achieving annual timber

products output survey collection and delivery of data

using a sample survey design with a sample size that varies

based on the surveyed region. Following the release of

2018 mill data for the South in FY 2020, FIA will release

2018 mill data for the North in early FY 2023 and will

release 2019 data by end of FY 2023.

• Continue investing in online applications that improve the

delivery of FIA information.

• New updated biomass modeling framework (National

Scale Volume and Biomass (NSVB)) will be finalized and

included in the National Information Management System

(NIMS) and FIA database. The new NSVB models will be

implemented in FIA’s National DataMart before the end of

FY 2023.

• Develop a new search tool that will query, by topic of

choice, all FIA publications in one place.

• Work with national users to standardize improved carbon

estimation and reporting.

• Continue to respond to the 2018 Farm Bill direction to find

efficiencies in the FIA Program through the improved use

and integration of advanced remote sensing technologies,

with the approach focused on implementing small area

estimation techniques.

• Use available authorities to gain efficiencies in the hiring

process and fill vacant positions with quality recruits at

levels required for successful program delivery.

Executive Summary
Fiscal Year 2022 Business Report 3

Introduction

The Forest Inventory and Analysis (FIA) program of 

the Forest Service, an agency of the U.S. Department of 

Agriculture (USDA), provides the information needed to 

assess the status, trends, and sustainability of America’s 

forests. This business report, which summarizes program 

activities in fiscal year (FY) 2022 (October 1, 2021, through 

September 30, 2022), gives FIA’s customers and partners 

a snapshot of past activities, current business practices, 

and future program direction. It is designed to increase our 

accountability and foster performance-based management 

of the FIA Program.1

The FIA Program has provided authoritative information 

on the Nation’s forest resources since 1930. FIA collects, 

analyzes, and reports information on the status and trends 

of America’s forests: how much forest exists, where it 

exists, who owns it, and how it is changing; how trees and 

other forest vegetation are growing; how much forest has 

died or been removed; and how harvested trees have been 

used in recent years. This information can be used in many 

ways, such as in evaluating wildlife habitat conditions, 

assessing sustainability of current ecosystem management 

practices, monitoring forest health, supporting planning and 

1

 This business report does not include statistical information about 

the forests of the United States. For this information, contact the 

appropriate regional or national FIA office listed in appendix A of this 

report or go to www.fs.usda.gov/research/programs/fia.

decision-making activities undertaken by public and private 

enterprises, predicting the effects of climate change, and 

providing authoritative data to the forest products industry. 

The FIA Program combines this information with related 

data on insects, diseases, and other types of forest damage 

to assess the current health of and potential risks to forests. 

These data are also used by the Forest Service Research 

and Development (R&D) Resources Planning Act (RPA) 

Assessment program to project how forests are likely to 

appear in 10 to 50 years; various scenarios evaluate whether 

current forest management practices are sustainable in the 

long run and assess whether current policies will enable 

future generations to enjoy the same benefits provided by 

America’s forests today.

As FIA continues to deliver a nationally consistent program, 

this report remains focused on program accomplishments 

and challenges while highlighting opportunities created 

by the joint efforts of the four regional FIA units housed 

at the Northern Research Station (NRS), the Southern 

Research Station (SRS), the Rocky Mountain Research 

Station (RMRS), and the Pacific Northwest Research Station 

(PNW), in close collaboration with national program leaders 

in the National Office.
4 Forest Inventory and Analysis

Changes From Previous Years’ Business Reports

In FY 2022, the FIA Program began work on standardizing 

the methods used for gathering and summarizing 

accomplishment data related to the Nationwide Forest 

Inventory. This will allow several key metrics to be 

calculated from queries on data stored in FIA databases, 

eliminating inconsistencies in how numbers have been 

reported over time and across FIA regions. Changes are 

noted in the relevant tables and include:

• The definition of forested base grid plots has been

clarified and now includes all plots containing either

“accessible forest” or “nonsampled (possibility of forest)”

on at least one condition found on the plot. The total

number of forested base grid plots (tables 1 and B-1)

can now be queried within the FIA database and updated

annually for this report. Previously, the number of forested

base grid plots was calculated by dividing the total land

area (table 1) by the sampling intensity (one plot per 6,000

acres), then multiplying this by the average percentage

of land with forest cover (see table B-1 in past business

reports).

• The method for calculating the number of forested base

grid plots completed has been updated to include plots

that could not be sampled due to hazardous conditions or

denied access. These are now reported in table B-1.

• The number reported for quality assurance (QA) plots

sampled is now defined as blind and cold checks

completed on forested base grid plots, eliminating some

prior inconsistencies in reporting QA plots across FIA 

regions.

These changes resulted in relatively minor adjustments to the 

numbers reported in past business reports but will complicate 

comparisons to historical accomplishment data. Table 4 

includes updated numbers for FY 2021 that were calculated 

using the new methodology to accurately show changes from 

the previous year.

For the second year, this report presents financial information 

in two tables: the Federal funds invested in FIA Federal 

salaries and expenses (S&E) (table B-2a) and a financial 

statement for operational funds appropriated by Congress 

directly to FIA (table B-2b). In FY 2021, based on legislative 

direction in the Further Consolidated Appropriations Act 

for FY 2020, the Forest Service adopted a new budget 

structure and changed internal budget policy, direction, and 

practices. This effort, also known as “budget modernization,” 

changed the way congressionally appropriated funds were 

allocated to FIA and other Forest Service programs. The 

new budget structure resulted in some changes in the way 

FIA can allocate and report on appropriated funding with the 

transparency expected by partners and stakeholders. 

The most significant changes to the agency budget were the 

elimination of cost pools and the establishment of budget 

line items for S&E. Previously, cost pools paid with program 

funds covered fixed operational costs such as business 

services and infrastructure, workers’ compensation programs, 

and unemployment compensation insurance. Under the new 

budget structure, FIA operational costs are paid through 

a new Forest Service operations account rather than with 

appropriated program funds. Similarly, employee salaries 

and related expenses (overtime, benefits, travel, training, and 

awards) are now paid through the S&E budget line items. 

FIA’s S&E budget is included within the agency’s Forest 

and Rangeland Research appropriation without a specific 

allocation. As a result, the FIA Program is only able to report 

the funds spent to cover FIA S&E (table B-2a) rather than 

funds allocated. These changes were intended to improve 

oversight by ensuring that agency spending is consistent with 

congressional direction and will help the Forest Service more 

clearly articulate financial needs and outcomes. The primary 

impact on this annual business report is that FIA cannot 

report a total amount of appropriated funding in a way that is 

fully comparable to prior years.

Operational funds, also called program funds, are used to 

support grants, agreements, contracts, procurement, and 

related expenses. As in previous years, FIA is able to report 

on operational funds appropriated to the program (table 

B-2b). Reporting of program expenditures also remains

unchanged.
Fiscal Year 2022 Business Report 5

Fiscal Year 2022 Program Overview

In FY 2022, the FIA Program completed its 24th year 

of implementing inventories annually, as outlined in the 

“Strategic Plan for Forest Inventory and Analysis” (hereafter 

strategic plan) written in response to the Agricultural 

Research, Extension, and Education Reform Act of 1998 

(Public Law 105–185). FIA operations use a systematic 

survey sample design with a grid of 6,000-acre hexagons 

(the base grid) laid over the entire United States with one 

plot located within each hexagon. The primary goal of the 

FIA Program’s Nationwide Forest Inventory is to measure 

at least 10 percent of FIA forested base grid plots per year 

in the Western United States and 15 percent of FIA forested 

base grid plots per year in the Eastern United States. Table 

1 shows the land area, forest area based on the FIA and 

RPA Assessment definitions, percentage of forest (forest 

area divided by land area), and the overall distribution of 

FIA forested base grid plots for the United States, including 

Puerto Rico, the U.S. Virgin Islands, and U.S. territories 

and affiliated islands in the Pacific. Interior Alaska, Hawaii, 

and other islands are sampled on a different schedule due to 

logistical constraints and not included in the annual sampling 

targets.

The base program includes annual compilations of the most 

recent year’s information, with full State-level reporting at 

5-year intervals. All States have the option to contribute the

resources necessary to bring the program up to a full sample

intensity of 20 percent per year or to make other valueadded contributions such as funding more frequent plot

measurements (temporal acceleration) or adding additional

sample locations (spatial intensification).

Table 1. Overview of land area, forest area calculated based on the FIA and RPA Assessment definitions of forest,a a percentage of land area 

that is forested based on the FIA definition, and the number of FIA forested base grid plots.

FIA Region

Land area Forest area 

(FIA)

Forest area 

(RPA)

% Forest 

(FIA)

FIA base grid plotsb

(forested)

Million acres Percent Plots

Northern 607 183 183 30% 37,636 

Southern 533 268 246 50% 52,846 

Rocky Mountain 548 153 124 28% 29,318 

Pacific Coast (CA, OR, WA) 204 89 83 44% 16,059 

Coastal Alaska 39 14 14 36% 2,238 

Interior Alaska 327 114 114 35% 4,286 

Islands (including Hawaii) 7 3 3 43% 1,386 

Total 2,264 824 767 38% 143,769 

FIA = Forest Inventory and Analysis; RPA = Resources Planning Act; CA = California; OR = Oregon; WA = Washington.

Estimates of land and forest area (using both the FIA and RPA Assessment definitions) were taken from “Forest Resources of the United States, 2017: A Technical 

Document Supporting the Forest Service 2020 RPA Assessment.” Forest area estimates from the current FIA database may not match due to the inclusion of 

more recent inventory data.

a

 The RPA Assessment and FIA definitions of forest differ. The RPA Assessment definition requires at least 10-percent canopy cover by trees at least 5 m (16.5 

feet) tall or trees able to reach these thresholds in situ, while the FIA definition includes trees of any height and thus includes woodlands where trees are shorter. 

Because the FIA definition includes woodlands, estimates of forest area using the FIA definition will be higher in arid to semiarid regions.

b

 The FIA base grid consists of one plot per 6,000 acres in the conterminous United States except for Delaware and Rhode Island, which are sampled at double 

intensity due to the small land area. Forested base grid plots are defined as plots containing either “accessible forest” or “nonsampled (possibility of forest)” on at 

least one condition found on the plot. 
6 Forest Inventory and Analysis

FY22 Program Overview

Program Resources

In FY 2022, Congress appropriated $22.197 million for FIA 

operations. Other funding made available to the program 

included S&E for FIA staff ($44.05 million), information 

technology (IT) funding ($1.55 million), and the agency’s 

indirect costs of common business services ($10.4 million in 

FY 2020, the last year this was tracked). Of the operational 

funds, congressional direction required that approximately 

$3.4 million be allocated for specific purposes, with the 

largest share ($2 million) directed at efforts to refine county 

and State biomass estimates (i.e., small area estimation). 

Under the new budget structure, FIA does not receive 

specific appropriations for S&E or indirect costs, which 

makes it difficult to estimate the total funding available in a 

way that is comparable to prior years (figure 1). 

Operational funding appropriations in FY 2022 were 

bolstered by the addition of $25 million in disaster 

supplemental funding that was provided to support plot, 

timber products output (TPO), and harvest utilization (HU) 

data collection catchup in areas affected by fire, hurricanes, 

or other natural disasters. The disaster supplement is 

intended to support catchup work over the next 3–4 years. 

This addition, coupled with partner contributions, brought 

the total investment in the FIA Program to $108.6 million for 

FY 2022 (figure 2).

In addition to the $1.55 million in IT funds received from 

FY 2022 appropriations, FIA also received $1.5 million from 

other Forest Service R&D IT funds (table B-2b), without 

which the program would not have been able to meet its IT 

needs. Partners, including the National Forest System (NFS), 

contributed $3.1 million to the base program and $11.2 

million in added value (table B-4). Value-added contributions 

fund work such as new research, new measurements, spatial 

intensification (>1 plot per 6,000 acres) and temporal 

acceleration (plots sampled more frequently).

Figure 1. FIA appropriated funding level, FYs 2007–2022.

FIA = Forest Inventory and Analysis; FY = fiscal year; S&E = salary and expenses under the new Forest Service budget structure.

Federal appropriations = initial FIA funds added to base + secondary funds added to base. For FYs 2021–2022, this also includes information technology (IT) 

funding. S&E spent is shown for FYs 2021 and 2022 because S&E were not paid out of FIA’s Federal appropriations as in previous years. 

The FY 2021 business report displayed congressional S&E intent rather than S&E spent. Because there was no congressional intent statement for FIA funding 

in 2022, this number was updated to dollars spent for consistency.
Fiscal Year 2022 Business Report 7

Figure 2. FIA Program total operational funds available (A) and 

total expenses by category (B), FY 2022. Salary and expenses are 

not included in the operational budget or expenses.

(A)

(B)

FIA = Forest Inventory and Analysis; FY = fiscal year.

In FY 2022, FIA employed the equivalent of 351 full-time 

Federal workers (full-time equivalents (FTEs); table B-3a), 

19 more than in FY 2021 but still 27 fewer than in FY 2020. 

Efforts to fill vacant positions have been hindered by ongoing 

staffing shortages in Human Resources Management, a 

highly competitive job market, and prohibitively expensive 

housing in some locations. Cooperators, especially State 

natural resources agencies, accomplished much of the 

work done by FIA, contributing an additional 237 full-time 

employees (table B-3b) for a total FIA workforce of 588 

(table B-3c). Cooperator employees made up 40 percent of 

the total FIA workforce. The majority of the FIA workforce 

(70 percent) was engaged in data collection (figure 3). 

Contributions from States remained critical to helping the 

FIA Program complete its annual fieldwork (table 2).

Investment in Partnerships and 

Partners’ Contributions

In the 1998 Farm Bill, the 2014 Farm Bill, and the 2018 

Farm Bill, Congress directed the FIA Program to partner 

with States and other entities. This is accomplished through 

grants and agreements to partners that support the FIA 

program of work. In some cases, partners provide expertise 

that complements or is not available within FIA; in other 

cases, they share the workload in data collection, information 

management, and research in techniques development. Over 

the last 10 years, FIA has invested over $191.1 million in its 

partners to implement an efficient inventory. During the same 

period, partners have contributed $106.9 million to leverage 

Federal dollars, which has reduced inventory cycles, 

increased the density of plots, and provided for other annual 

inventory enhancements. 

FIA Investment Through Grants and Agreements. In FY 

2022, FIA invested $29.7 million in grants and agreements 

with partners including State agencies, universities, 

nongovernmental organizations and companies, other Forest 

Service programs, and other Federal agencies (figure 4, 

table B-5). The growing trend of FIA investment in external 

partnerships over time demonstrates a high reliance on 

collaborations to efficiently complete program work (figure 5).

Through annual agreements, State agencies received 33 

percent of this investment (figure 4). In turn, State agencies 

leverage FIA’s on-the-ground resources to contribute funds 

and in-kind resources for additional data collection and 

analysis to meet their local needs (table 2). State fieldwork 

employees provided through these partnerships made up over 

one-third of the FIA workforce (figure 3). 

FY22 Program Overview

Figure 3. Federal and State FIA-supported employees by job 

group, FY 2022.

FIA = Forest Inventory and Analysis; FY = fiscal year.
8 Forest Inventory and Analysis

Table 2. Annual appropriations received by the FIA Program and allocation of FIA-appropriated and State-contributed funds for 

fieldwork, FYs 2013–2022.

Category

Fiscal Year

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Thousand dollars

Total appropriated funds received 65,567 66,805 70,000 75,000 77,000 77,000 78,000a 77,000 57,786 67,637

FIA data collection grants to States 5,338 7,098 5,173 8,428 8,945 9,652 10,633 9,755 11,148 9,742

Number of States recieving grants 16 17 16 18 17 20 18 18 17 17

Average grants to participating States 334 418 323 323 526 482 591 542 656 573 

Percent of FIA-received appropriated 

funding to States for data collection 8% 11% 7% 11% 12% 13% 14% 13% 19% 14%

State contributions for leveraged data 

collection 3,962 3,919 4,324 5,506 5,205 6,568 5,239 6,809 5,491 2,479

Number of fund-contributing States 

and U.S. islands 38 36 37 34 36 41 37 41 51 38

Average contribution from States 104 109 117 162 145 151 142 166 108 65 

FIA = Forest Inventory and Analysis; FY = fiscal year. 

Starting in FY 2021, the indirect costs of operations (former costs pools) were paid through the new Forest Service Operations Treasury Symbol account. 

The new salary and expense budget line Items related to Research and Development paid for the staff providing indirect support at the stations. These 

indirect costs were previously paid with FIA Program funds.

a

 Includes $1 million supplemental appropriation for hurricane relief.

Figure 4. Grants and agreements by recipient group, FY 2022.

Recipient Group Grant amount ($) No. of recipients

States 9,741,675 17

Universities 10,918,309 49

NGOs and companies 7,216,324 55

Forest Service 1,151,341 8

Other Federal agencies 640,516 9

Total 29,668,165 138

FY = fiscal year; NGO = nongovernmental organization.

FY22 Program Overview
Fiscal Year 2022 Business Report 9

Figure 5. FIA investment in external partnerships through grants and agreements, 1999–2022.

FIA = Forest Inventory and Analysis.

Partners’ Contributions to FIA. At their discretion, 

partners may contribute the resources needed for FIA to 

sample the full 20 percent of base grid plots per year (5-

year cycle) that is included in the authorizing legislation 

(1998 Farm Bill). In addition, or as an alternative, 

partners may choose to contribute resources to enhance 

the FIA Program, such as intensifying the base FIA 

sample location grid to support analysis at finer spatial 

resolutions, funding additional types of measurements on 

FIA sample locations, or providing analyses or reporting 

beyond that provided by FIA. The willingness of partners 

to contribute resources demonstrates the inherent value 

of the FIA Program as a flexible framework providing 

information on issues of interest.

Table B-4 lists all partner contributions to the FIA Program 

in FY 2022. These resources include staff time, vehicle use, 

office space, equipment, travel costs, and other noncash 

items that support or add value to the FIA Program. For 

reporting purposes, contributions are assessed in terms of 

the cost for Federal FIA staff to provide the same service, 

which may not necessarily be the same as the actual cost 

to the partner making the contribution. Overall, partners 

contributed $3.1 million toward the base program as defined 

by option B of the FIA strategic plan. Partners also provided 

another $11.2 million in contributions that add value to the 

FIA Program for a total of $14.3 million (table 3). 

Table 3. FIA grants and agreements to partners and partner contributions by FIA unit, FY 2022.

Unit

Total FIA G&A Total partner contributions

Amount 

(dollars) Percent Number Percent Amount 

(dollars) Percent Number Percent

Pacific Northwest 4,878,437 17% 20 18% 2,388,711 17% 16 19%

Rocky Mountain 5,120,796 18% 22 20% 637,788 4% 7 8%

Southern 8,683,668 30% 26 23% 2,156,748 15% 11 13%

Northern 7,898,621 27% 37 33% 8,022,374 56% 46 55%

National Office 2,666,712 9% 7 6% 1,097,591 8% 3 4%

Total 29,248,234 100% 112 100% 14,303,212 100% 83 100%

FIA = Forest Inventory and Analysis; FY = fiscal year; G&A = grants and agreements. 

Percentages may not add to totals because of rounding.

FY22 Program Overview
10 Forest Inventory and Analysis

Outputs and Products

Table B-1 summarizes funding and performance measures 

for each of the FIA units. In FY 2022, FIA sampled 13,844 

base grid forest plots throughout the 50 States, including 

Hawaii and the Southwest unit of Interior Alaska (the first 

unit where all plots are only accessible by air). Nationally, 

11 percent of forested base grid plots were completed (table 

B-1). Spatial intensification and temporal acceleration efforts

sampled an additional 4,923 plots. Plot data collection

for spatial intensification and temporal acceleration relied

on State and contracted crews and was financed by State

agencies, Forest Service regions, and other Federal agencies.

In FYs 2020 and 2021, impacts from the coronavirus 

(COVID-19) pandemic, hazardous conditions and poor air 

quality induced by catastrophic wildfires, and field staff 

shortages in all units delayed sampling efforts and made 

it difficult for the FIA Program to meet its annual data 

collection and delivery targets. In FY 2022, field crews 

prioritized measurement of the remaining 2020 and 2021 

plots while also working to complete 2022 plots where 

capacity allowed. The addition of supplemental disaster 

funding allowed for a large increase in the number of plots 

sampled (tables 4 and B-1); however, ongoing challenges 

with hiring Federal employees and limited contracting 

options in some FIA regions continue to hinder data 

collection. By the end of 2022, crews had completed 95 

percent of the plots scheduled for inventory in 2020, 80 

percent of the plots scheduled for 2021, and 63 percent of 

the plots scheduled for 2022. 

The conterminous United States and Coastal Alaska use an 

annualized2

 survey, and Interior Alaska, Hawaii, and the 

U.S.-affiliated islands implement a periodic3 survey. FIA’s

legislative direction, most recently from the Forest and

Rangeland Renewable Resources Research Act of 1978

(PL 95–307, as amended through P.L. 115–334, enacted

Dec. 20, 2018), states that the Nation’s Trust Territories

and Freely Associated States are to be treated as States

for research purposes. Since 2000, in compliance with

this mandate, periodic inventories have been completed in

the Commonwealth of Puerto Rico, U.S. Virgin Islands,

Federated States of Micronesia, American Samoa, Guam, the

Republic of Palau, the Republic of the Marshall Islands, and

the Commonwealth of the Northern Mariana Islands, all of

which are exempt from the annualized system.

2 Annualized inventory measures 10 to 20 percent of all plots in each 

State each year.

3 Periodic inventory measures plots once every few years. State-level 

inventory is based on a full measurement of existing plots.

Table 4. Number and percent change of FIA plots sampled by FIA unit, FYs 2021 and 2022.

Pacific Northwest Rocky Mountain Southern Northern Total

Base grid (forested 

and possibly foresteda) 2021 2022 Change 2021 2022 Change 2021 2022 Change 2021 2022 Change 2021 2022 Change

Field-sampled 1,667 1,425 -15% 1,964 2,958 51% 5,551 4,945 -11% 4,218 4,516 7% 13,400 13,844 3%

Nonsampled hazard 54 98 81% 14 37 164% 55 55 0% 13 17 31% 136 207 52%

Nonsampled denied 

accessb 133 100 -25% 199 406 104% 559 500 -11% 865 1,000 16% 1,756 2,006 14%

Base forest quality 

assurance plots 66 65 -2% 101 202 100% 558 429 -23% 220 289 31% 945 985 4%

% field-sampled base 

grid with QA 4% 5% 15% 5% 7% 33% 10% 9% -14% 5% 6% 23% 7% 7% 1%

Additional plots sampled (forested and nonforest)

Spatial intensification 912 994 9% - - - 297 280 -6% 1,490 1,519 2% 2,699 2,793 3%

Temporal acceleration 206 281 - - - - 1,611 1,480 -8% 353 369 5% 2,170 2,130 -2%

Urban plots 31 46 48% - 85 - 188 175 -7% 2,272 1,508 -34% 2,491 1,814 -27%

Special study plotsc 483 23 -95% - - - 33 - -100% - - - 516 23 -96%

FIA = Forest Inventory and Analysis; FY = fiscal year; QA = quality assurance. 

a

 Plots that are forested or appear to be forested based on a prior field visit or remote sensing data but could not be sampled due to hazardous conditions or 

denied access are classified as “nonsampled (possibility of forest).”

b Landowner permission is required to sample plots on private land; some plots could not be sampled because the landowner denied access.

c

 Special study plots are typically post-disturbance measurements taken after wildfires or hurricanes.

Numbers presented here for FY 2021 may not match the FY 2021 business report because all numbers were updated using consistent database query methods 

outlined within this business report to allow for accurate comparisons.

FY22 Program Overview
Fiscal Year 2022 Business Report 11

FIA measures approximately 550 inventory field plots 

throughout Hawaii’s forests over a 3-year period every 

10 years. Field plots are on the islands of Hawai`i, Maui, 

Moloka`i, Lanai, O`ahu, Kaho`olawe, and Kauai. The second 

measurement of these field plots began in 2019 and was 

completed in March 2022, and Hawaii’s third inventory 

measurement is planned for 2029–2031. 

The approximately 600 inventory field plots spread across 

Puerto Rico (mainland Puerto Rico and the islands of 

Vieques, Culebra, and Mona) and the U.S. Virgin Islands 

(St. Croix, St. Thomas, and St. John) have been remeasured 

every 5 years since implementation of the nationalized 

inventory design there in 2001. Puerto Rico is currently on 

its seventh inventory, which will be complete in 2024 (two 

10-year periodic inventories in 1980 and 1990 preceded the

inventories of 2003, 2009, 2014, and 20194 ). The forests

of the U.S. Virgin Islands have been inventoried three

times (2004, 2009, and 2014), but the fourth inventory had

to be suspended before completion due to the COVID-19

pandemic. Sampling is scheduled to resume in 2024,

following completion of Puerto Rico’s seventh inventory.

Table B-1 summarizes other key FIA Program 

accomplishments from FY 2022. Some highlights include:

• FIA staff produced 143 publications, including 55 core

reports and 72 peer-reviewed journal articles.

• The number of consultations requested by FIA customers

(table B-6) totaled 1,276, an increase of 83 percent over

FY 2021, although the total hours spent on consultations

decreased somewhat to 6,398.

• FIA processed 629,374 online data retrievals and fulfilled

181 spatial data requests (table B-7).

• FIA held 12 user group meetings and 9 management

meetings. National and regional user group meetings

provided a mechanism for users and stakeholders to track

FIA accomplishments, provide feedback on performance,

and present emerging issues and information needs.

Data Availability

The FIA Program mission is to provide continually updated, 

accurate, and reliable information on the status and trends 

of the Nation’s forest resources. FIA’s legislative mandate 

results in program objectives that include: (1) providing 

annual access to current and past data for all forested lands 

sampled as part of the annualized inventory system; (2) 

producing analytical forest reports for all States on a 5-year 

cycle; (3) providing information on forest land ownership 

and the attitudes, behaviors, and other characteristics of 

America’s private forest owners; and (4) delivering data to 

assess a variety of issues regarding timber resource use.

4 Puerto Rico’s 2019 5-year report is still in preparation; no link is 

available yet.

An interactive map displays current online data availability

(this information is also listed in table B-11). The FIA 

Program strives to provide data no more than 2 years old; 

at the end of FY 2022, 47 percent of States with annualized 

inventories met that target, while 47 percent had data 

that was 3 years old and the remaining 6 percent had data 

that was 4 years old. The delay in sampling caused by 

the COVID-19 pandemic also resulted in a delay in data 

publication to the public FIA database because to ensure an 

unbiased sample, data cannot be published for a given State 

until all plots are complete. The FIA Program is working to 

load the remaining backlog of data in FY 2023.

The latest forest inventory data for the Hawaiian Islands 

is available to the public through a State-specific online 

inventory database. Data for the Tanana Valley and SusitnaCopper units in Interior Alaska are also available to the 

public through a Microsoft Access database. Continued 

improvements to data processing and in the National 

Information Management System (NIMS) are creating 

efficiencies across FIA units in the processing of plot data 

and publishing to the public FIA database (FIADB). The 

development of Universal NIMS (UNIMS)—the nextgeneration replacement for NIMS—to internally store 

and process plot data will accommodate newer sampling 

protocols and subsequent data, such as from Interior Alaska, 

urban areas, and special studies, among others. As with 

NIMS, data from UNIMS will be exported to the FIADB for 

use by analysts and software tools. 

In FY 2022, updated 5-year State reports were published 

for Maine, Minnesota, Kentucky, Tennessee, Nevada, and 

the Tanana unit of Interior Alaska (figure 6). In addition, 

draft versions of interactive reports were made available 

online for Connecticut, Delaware, Indiana, Iowa, Maine, 

Massachusetts, Michigan, Pennsylvania, Rhode Island, West 

Virginia, and Wisconsin. Final versions of these reports were 

in final layout and awaiting official publication. Table B-11 

shows the most recent inventory year included in the 5-year 

FIA report for each State as well as the year of publication.

The FIA Program compiles information on forest and 

woodland ownership through the National Woodland Owner 

Survey (NWOS). An interactive online tool, the NWOS 

Dashboard, allows users to explore the latest forest landowner 

data and make comparisons across States and regions. 

The FIA Program also provides a National Resource Use 

Monitoring (NRUM) TPO toolkit to deliver estimates of timber 

products, mill residue, logging residue, residential fuelwood, 

and other wood removals. The TPO toolkit includes three 

reporting tools: the TPO Interactive Reporting Tool (currently 

populated with States and years available in the FIADB with 

full coverage expected in the coming years), the TPO Data 

Download, and TPO One-Click factsheets (currently displaying 

processed data for Northern and Southern States with plans to 

add States as they get processed in FY 2023).

FY22 Program Overview
12 Forest Inventory and Analysis

Figure 6. Publication year of FIA 5-year State reports, FY 2022.

FIA = Forest Inventory and Analysis; FY = fiscal year.

Publication year of State report does not match the range of data collection dates shown in the publication.

U.S. islands and territories are not shown; the publication years are as follows: Republic of Palau (2007); Commonwealth of the Northern Mariana Islands, Republic 

of the Marshall Islands, and Federated States of Micronesia (2012); Puerto Rico (2019); Guam, American Samoa, and the U.S. Virgin Islands (2020); Hawaii (in press).

Quality Assurance

The FIA Program collects, analyzes, and publishes 

tremendous amounts of data annually. A large part of this 

work consists of designing, implementing, and carrying 

out procedures to ensure the data can generate unbiased 

estimates of forest attributes at appropriate spatial scales 

(States or large landscapes). Toward this end, FIA’s QA 

program employs a framework to promote consistency 

during all stages of the national core FIA inventory process: 

• A national prefield guide and rigorous QA protocols define

a nationally consistent process to collect information about

FIA plots before field visits. The updated version of the

National Prefield Guide 9.2 was released in 2022.

• Up-to-date FIA national field guides ensure consistent core

program and core optional data collection.

• A field-level data collection QA guide assists in promoting

field QA consistency from across FIA regions.

• FIA’s national field data entry program, the Mobile

Integrated Data Acquisition System (MIDAS), is

integrated into the overall FIA information management

structure and provides consistent logic and error checking

in the field.

• The UNIMS database and UNIMS Compilation System

(UNIMS-CS) will provide additional error checks and

consistently calculate and provide access to a variety of

derived variables.

• A national R&D QA plan establishes research standards

and procedures for all organizational units and personnel

within Forest Service R&D.

• FIA’s national Band System and structure promote

communication across units nationally and across FIA 

functional areas. The system and structure were revamped

in 2021, leading to increased communication and efforts to

improve national consistency.

FY22 Program Overview
Fiscal Year 2022 Business Report 13

FIA Data Requests and Access

Spatial Data Services

The FIA Spatial Data Services (SDS) team5 provides 

customers with the information they need in a way that does 

not compromise the security of plot locations. Spatial data 

requests are cataloged as one of four types: spatial, summary, 

knowledge, or miscellaneous. Spatial requests are those 

for which FIA spatial data are provided without additional 

analysis. Summary requests refer to FIA data aggregated for 

a specific geographic area(s). Knowledge requests are those 

that require additional spatial data analysis by SDS. 

Early in FY 2022, FIA leadership spent more time evaluating 

spatial data requests prior to approving to ensure the 

FIA Program is meeting its legal obligations related to 

confidentiality. Despite this, the SDS team processed 181 

requests in FY 2022 (figure 7), down from 257 requests in 

FY 2021. 

FIA enters into formal agreements with clients whose access 

to confidential FIA data is necessary to execute projects 

that clearly benefit the FIA Program. FIA confidential 

data includes plot coordinates, landowners’ personally 

identifiable information, and nonpublic forest product 

producer information. In FY 2022, the SDS team used 

Material Transfer Agreements (MTAs) and Memorandums 

of Agreements (MOAs) as the legally binding agreement 

instruments to establish a framework for cooperation. Terms 

and conditions included in these agreements ensure the full 

protection of FIA confidential data according to current 

legislation, including the Food Security Act.

When plot coordinates are shared, the agreed terms prohibit 

the client from sharing the data with anyone not covered 

by the agreement, as well as from visiting the plot with 

the intention of manipulating FIA data or intentionally 

altering the condition of a plot such that it is not reflective of 

management conditions in the surrounding area. 

5

 In FY 2022, SDS staff consisted of: Tom Thompson, National SDS 

team chair; Charles Paulson and John Higham, Northern Research 

Station; John Chase and Brett Davis, Pacific Northwest Research 

Station; Chris Toney and Karen Schleeweis, Rocky Mountain 

Research Station; and Carol Perry, Tracy Roof, and Andres BaezaCastro, Southern Research Station.

Additionally, a Data Security Plan is required to document 

the transfer, storage, use, and disposal of the shared 

confidential data. Cooperators who are Federal employees 

are asked to sign a Letter of Intent that reminds them of 

their legal obligations regarding confidential data. NonFederal employees directly hired by the Forest Service, such 

as contractors, who have a demonstrated need to access 

confidential FIA data to perform their work duties must sign 

a nondisclosure agreement. 

During FY 2022, FIA entered into national data-sharing 

agreements (MTAs) with the University of Tennessee, 

the University of Idaho, the University of Maryland, and 

the University of Nevada, Las Vegas, and entered into 

regional agreements with many others. SDS work continued 

with a variety of partners including: NASA, several U.S. 

Department of the Interior (DOI) agencies, the Oregon 

Department of Forestry, the University of Washington and 

other universities, the Cary Institute of Ecosystem Studies, 

and the NFS and other non-FIA programs within the Forest 

Service such as the Geospatial Technology and Applications 

Center (GTAC), the LANDFIRE Program, the Forest Health 

Assessment and Applied Sciences Team (FHAAST), and the 

RPA Assessment Program.
14 Forest Inventory and Analysis

Figure 7. Spatial data requests made to the FIA Spatial Data Services team (total = 181), FY 2022.

FIA = Forest Inventory and Analysis; FY = fiscal year; NFS = National Forest System; NGO = nongovernmental organization; NRS = Northern Research Station; 

PNW = Pacific Northwest Research Station; RMRS = Rocky Mountain Research Station; SRS = Southern Research Station.

Web Tools and Use

The FIA Program currently supports a variety of tools that 

provide access to FIA data. These include: 

• The EVALIDator web interface, which allows users to

generate customized estimates using FIA data. In FY 2022,

the previous version of the EVALIDator web application

was replaced with the updated API and EVALIDator 2.0

web interface. This change enables better performance

and more capabilities while relying on a smaller, more

accessible codebase and a continuous deployment

pipeline. A team of developers has also been assembled

to quickly address bugs and implement changes based on

user response.

• EVALIDator API, which allows users to enter hypertext

markup language (HTML) to query the FIADB.

• FIA DataMart, which allows users to download FIA data

as comma-delimited files (CSV) or as an SQLite database

that is readable by the Forest Vegetation Simulator (FVS).

In FY 2022, the DataMart web repository received a

newly designed interface intended to create a more

efficient and intuitive user experience. The file generation

script, which runs every weeknight to update the files

hosted on DataMart, was also updated to make it easier

to maintain and bring it in line with accumulated changes

to the FIADB. Lingering issues with file availability due

to a faulty permissions structure on the server have more

recently been addressed with a server upgrade.

• The NWOS Table Maker and NWOS Dashboard.

• The State Factsheets tool, an interactive dashboard that

displays common estimates for each State.

• The TPO toolkit (soon to be relabeled as the NRUM

toolkit).

• My City’s Trees, an online tool developed in partnership

with Texas A&M Forest Service to allow users access to

FIA’s urban inventory.

• The Design and Analysis Toolkit for Inventory and

Monitoring (DATIM), which has been in use since FY

2015 and entered operations and maintenance mode at the

end of FY 2022. This indicates that the program is mature

with minor issues being addressed in future releases.

FY 2022 saw a large increase in use of the TPO toolkit, 

which was expanded to include data from additional FIA 

regions, and a decline in both data downloads and use of 

EVALIDator (table B-7). The decrease is likely due to 

some breaks in availability while these tools were being 

updated. There may also be an ongoing decrease in activity 

attributable to the effects of the COVID-19 pandemic on 

research. Records also indicate a drop in requests to the 

updated EVALIDator API; this is believed to be largely due 

to intermittent breaks in service and lack of request logging 

during the initial deployment.

By FIA region By type By requestor

FIA Data Requests and Access
Fiscal Year 2022 Business Report 15

Consultations by FIA Staff

Since the earliest days of the FIA Program, consulting 

with the public has been a priority. In 1930, “consulting” 

meant face-to-face interaction with landowners and forestry 

professionals, or answering handwritten questions received 

in the mail. While the mechanisms for interactions between 

customers and FIA representatives may have evolved, the 

reasons for cooperation remain the same. The amount of 

information (both data and analyses) made available on the 

web continues to increase as customers demand more and 

varied information from FIA data and analyses. Questions 

pertaining to a single administrative unit (e.g., a single 

State or national forest) are frequently referred to partners 

within that administrative unit (e.g., State foresters or 

NFS analytical staff) who can often provide better context 

and customer service. When questions span multiple 

administrative units, FIA staff members assist the customer 

with finding an answer. FIA staff members do not compete 

with private-sector consultants; rather, they answer questions 

about FIA’s methods and help customers (including private 

consultants) use FIA data to answer their own or their 

clients’ questions. 

A significant consultation is defined as any dialogue with 

a customer that requires more than 1 hour of FIA staff 

time and that is not part of the normal course of business 

in collecting, analyzing, and reporting FIA information. 

Historically, consultations have fluctuated slightly from 

year to year, depending on broader outside interests, while 

showing regional variations. Since 2006, Federal and 

State government agencies have consistently remained the 

program’s major clients. Consultations from this group 

include any internal discussions within other Forest Service 

programs.

In 2022, FIA customer inquiries increased to 1,276, 

compared to 696 in 2021 and 1,434 in 2020. The associated 

number of consultation hours (6,398) was less than the hours 

in 2021 (8,285). Table B-6 shows the number and hours of 

significant consultations provided by FIA staff in FY 2022 

by responding unit and type of customer. FIA employees 

also provide assistance to the NFS through a variety of larger 

partnerships focused on analysis and information delivery.

FIA Data Requests and Access
16 Forest Inventory and Analysis

Jolanda Lake, Okanogan-Wenatchee National Forest, WA. USDA Forest Service Photo by Robin DeMario.
Fiscal Year 2022 Business Report 17

Program Safety

Physical, psychological, and social safety are core values 

uniting Forest Service employees, contractors, and State 

partners, both on and off the job. Employees are entitled to 

a workplace environment where they treat one another with 

respect, empower one another, model integrity, protect one 

another, and learn from mistakes. FIA takes these values 

seriously and makes these commitments whether in the field, 

in the office, or working remotely. 

In 2016, the Forest Service began a transition period 

and cultural reorganization promoting critical thinking 

and giving voice to safety concerns, inviting a reversal 

of the lingering hierarchical command that historically 

characterized the agency. In 2018, the Forest Service 

introduced organizational changes in the wake of the 

agency’s public reckoning with sexual misconduct, including 

a revamped harassment-reporting center, changes to 

investigation procedures, an updated statement of codes and 

commitments, and the creation of the Work Environment and 

Performance Office (WEPO) within the Office of the Chief. 

WEPO’s mission is to “improve and sustain a workplace 

culture where all employees feel safe, valued, respected, and 

supported.”

Along with WEPO’s mission, the FIA Program continues 

to work toward an improved vision of employee well-being 

and work environment. Program managers, supervisors, 

and safety teams within FIA units actively monitor and 

address physical, psychological, and social safety issues and 

concerns as they emerge through daily engagement, annual 

staff surveys, and direct reporting. 

Job hazard analyses (JHAs) and training for field and office 

staff are continually reviewed and improved to reduce 

employees’ risk exposure. These JHAs include but are not 

limited to use of alternative plot access such as watercrafts 

and aviation, working alone or in hostile environments, 

urban field safety, lightning hazards, bears, illicit grow 

sites, road and backcountry travel, psychological safety 

and harassment, bystander intervention on inappropriate 

behavior, and check-in/check-out systems for field and 

office. Office safety focuses on workstation ergonomics; 

filtering eyewear for computer work; travel safety; active 

shooter; sexual harassment; bystander intervention; 

bullying; cybersecurity; preparedness for earthquakes, 

fires, and other weather disasters; and first-aid training 

including cardiopulmonary resuscitation and use of an 

automatic external defibrillator. Field crews are equipped 

with mobile phones, Garmin inReach® devices, ergonomic 

data recorders, and satellite phones. Personal protective 

equipment (PPE) includes hard hats, safety goggles, gloves, 

safety boots, trekking poles, and aerosol sprays for wild 

and domesticated animals. International security training is 

required for all international travelers. In every unit, FIA is 

committed to reducing employee risk through multiple layers 

of defense. People are the FIA Program’s greatest asset—all 

take great pride in and responsibility for their own and each 

other’s safety.

The total annual number of vehicle accidents reached a record 

low of one in FY 2022 despite logging nearly 2 million miles 

driven (figure 8). The total number of work-related injuries 

and illnesses increased slightly in FY 2022 but remains 

low relative to the long-term average (figure 9). Table 5 

summarizes the program’s safety record for FY 2022. 
18 Forest Inventory and Analysis

Figure 8. Number of chargeable motor vehicle accidents by FIA unit, FYs 2010–2022.

FIA = Forest Inventory and Analysis; FY = fiscal year; NRS = Northern Research Station; PNW = Pacific Northwest Research Station; RMRS = Rocky Mountain 

Research Station; SRS = Southern Research Station.

A chargeable motor vehicle accident is any occurrence involving the use of a Government-owned or Government-leased motor vehicle (automobile, truck, 

or bus) that results in a combined total damage of $1,500 or more. This definition also applies to privately owned vehicles when used for official Government 

business.

Figure 9. Number of OSHA recordable cases by FIA unit, FYs 2010–2022.

FIA = Forest Inventory and Analysis; FY = fiscal year; NRS = Northern Research Station; OSHA = Occupational Safety and Health Administration; PNW = Pacific 

Northwest Research Station; RMRS = Rocky Mountain Research Station; SRS = Southern Research Station.

An OSHA-recordable incident is a work-related injury or illness resulting in any of the following: death, days away from work, restricted work or transfer to 

another job, medical treatment beyond first aid, or loss of consciousness.

Program Safety
Fiscal Year 2022 Business Report 19

Table 5. FIA Program Federal employee estimates for hours worked, miles driven, aircraft hours flown, and safety incidents reported, FY 2022.

Category

FIA Unit

PNW RMRS SRS NRS National 

Office Total

 Base data

 Federal FTEsa 84 100 72 93 2 351 

 Total estimated hours workedb 175,136 208,832 150,384 192,816 3,536 730,704 

 Total vehicle miles driven 375,484 581,294 427,518 548,857 0 1,933,153 

 Total flight hours logged 333 10 0 0 0 343 

 Incidents by class

 OSHA recordable injuriesc 5 3 0 3 0 11 

 Chargeable motor vehicle accidentsd 1 0 0 0 0 1 

 Aircraft accidentse 0 0 0 0 0 0 

 Aircraft incidentsf 1 0 0 0 0 1 

 Safety incident frequency rate

 Recordable injury rate per 100 FTEs 6 3 0 3 0 3 

 Motor vehicle accidents per million miles driven 3 0 0 0 0 1 

 Aircraft accidents per 100,000 flight hours 0 0 0 0 0 0 

FIA = Forest Inventory and Analysis; FTE = full-time equivalent; FY = fiscal year; NRS = Northern Research Station; OSHA = Occupational Safety and Health 

Administration; PNW = Pacific Northwest Research Station; RMRS = Rocky Mountain Research Station; SRS = Southern Research Station. 

a Estimated number of Federal FTEs (based on appendix table B-3a).

b Number of Federal employees times 2,080 hours per FTE (based on appendix table B-3a). Note: a small percentage of overtime is not included in estimate. 

c Work-related injury or illness resulting in any of the following: death, days away from work, restricted work or transfer to another job, medical treatment beyond 

first aid, or loss of consciousness. 

d Any occurrence involving the use of a Government-owned or Government-leased motor vehicle (automobile, truck, or bus) that results in a total combined 

damage of $1,500 or more. This definition also applies to privately owned vehicles when used on official Government business.

e

 Aircraft accidents are those resulting in death or serious injury, or substantial damage to the aircraft.

f

 Aircraft incidents are those affecting, or which could affect, the safety of aircraft operations. (This is a new metric introduced in FY 2020 per safety committee 

recommendation.)

Program Safety
20 Forest Inventory and Analysis

Program Safety Highlights

Since the COVID-19 pandemic was declared in early 2020, 

FIA prioritized the safety of crews above established annual 

program objectives and field data collection targets by 

adopting additional mitigation measures, field requirements, 

and travel limitations. Each FIA regional unit embraced 

a revised set of goals determined primarily by State and 

regional pandemic status, while also complying with Centers 

for Disease Control and Prevention (CDC) and Occupational 

Safety and Health Administration (OSHA) guidance. In 

summary, some of the common mitigation efforts across all 

FIA units included:

• Development of regional Deliberative Risk Assessments

for conducting field work that mitigates risk to employees

and the communities where they work.

• Distribution of CDC-recommended PPE.

• Revision of vehicle-use standards to accommodate one

crew member per vehicle to maintain guidelines for social

distancing.

Pacific Northwest Research Station

Amid the ongoing pandemic and increasing frequency 

and extent of wildfires and poor air quality, PNW FIA was 

successful in completing its planned work while keeping 

employees safe and well. Data collection teams developed 

numerous templates and procedures to assess and mitigate risk 

of exposure to COVID-19 and poor air quality or fire hazard, 

including:

• Risk assessment worksheets that identified and mitigated 

risks associated with field work in different States

• A “Go, No-Go” decision-making matrix for each day

• A daily self-check-in form for staff to evaluate their physical 

and mental health

• A COVID-19 polymerase chain reaction (PCR) testing plan 

developed in collaboration with public health officials from 

the State of Alaska

Additionally, extensive efforts were made to research and obtain 

specialized and additional equipment for staff, in response to 

near-miss incident reporting and for COVID-19-related needs, 

including:

• Renting additional equipment and vehicles to allow for 

socially distanced transportation (one-person, one-car policy) 

to field plots in collaboration with local Forest Service 

districts and the General Services Administration.

• Analyzing safety reports (near-miss data), identifying the 

need for improved head protection, and adopting OSHAapproved climbing-style hard hats, a type of hard hat more 

suitable for very steep, brushy, rocky terrain. 

• Providing ergonomic home-office equipment to staff to 

facilitate healthier remote work environments.

PNW continued to pilot new Satellite Emergency 

Notification Devices (SENDs) to explore alternative 

communication options for staff working in remote areas 

of Coastal and Interior Alaska. Garmin inReach® SENDs 

provided substantially improved aviation communication 

operations including flight following, communicating 

with dispatch, and two-way communication between 

crews while both crews were outside of cellular phone 

reception. Implementing the use of these inReach® SENDs 

may eventually lead to decreased pack weight if they can 

ultimately replace other communication devices or global 

positioning system (GPS) units. All Alaska crew leaders 

will be provided with these devices for the FY 2023 field 

season. Likewise, in Oregon, Washington, and California, 

while many crews were still reliant on SPOT X® devices 

throughout the FY 2022 field season as their SENDs, several 

opted to switch over to the inReach®. Because the inReach® 

was so well received due to overall performance and user 

preference, the decision was made to transition all crews 

in these States to this model of SEND in the FY 2023 field 

season.

Over the past year, PNW FIA continued to implement 

a safety-buck program to recognize actions promoting 

health, safety, a positive work environment, and wellness. 

A new employee resumed management of the program after 

the previous manager left the agency. Also in the past 12 

months, the program safety committee supported an overhaul 

of the Safety SharePoint site to better organize information 

and to improve accessibility overall for both office and 

field-based staff. At the beginning of the field season, over 

30 FIA employees from California, Oregon, and Washington 

attended an in-person wilderness first aid/first responder 

training, the first in-person gathering attempted by the 

program since the beginning of the COVID-19 pandemic. 

Organizing this training required significant planning and 

implementation of risk mitigation measures in coordination 

with the training provider. Because of this training, field staff 

were able to maintain their medical certifications, as required 

by the USDA.

Rocky Mountain Research Station

RMRS FIA continued to see decreasing accident and 

injury rates and fewer lost duty and light duty days. The 

program again experienced fewer serious injuries reported 

and no serious vehicle accidents. In leading indicators, the 

program presented multiple safety awards for employees’ 

proactive safety attitudes, behaviors, and actions; shared 

many learning stories throughout the year; made countless 

phones calls to employees to maintain a sense of connection; 

managed multiple in-person employee training opportunities; 

made multiple leadership field visits; and held regular staff 

meetings (formal and informal) in which well-being and 

mental health and the utilization of the new agency resources 

were discussed. The program also offered an all-day 

Program Safety
Fiscal Year 2022 Business Report 21

retirement benefits training to help employees plan now for 

their futures. The program focused on employees and amidst 

another challenging year was successful by all accounts. 

Initial training for new employees and refresher training 

for experienced employees are important administrative 

controls for managing risk, but these have been challenging 

to navigate in recent years given the increased risk of inperson events during the COVID-19 pandemic. RMRS FIA 

provided multiple trainings throughout the year including a 

weeklong virtual training for data collection employees in 

the spring that included safety, aviation, and wellness-related 

trainings. Instead of one large centrally located in-person 

training, the program offered three separate trainings: one 

northern area training for returning employees, one southern 

area training for returning employees, and one centrally 

located training for new employees. While there were a 

few known COVID-19 exposures, there were no known 

COVID-19 transmissions due to any in-person training or 

work. The program also made numerous office position hires 

and provided individual virtual training sessions throughout 

the year for these new employees and increased efforts to 

welcome and connect these new employees with their virtual 

colleagues.

RMRS FIA continued to encourage employee engagement 

through the program’s safety committee, which met 10 times 

during FY 2022. The committee explored and implemented 

multiple employee suggestions for improving safety and 

efficiency. Some topics researched and implemented include 

the review of an annual data collection debriefing survey; 

using fat-tire mountain bikes for plot access; full per diem 

rate for camping; all-terrain vehicle (ATV) preventative 

maintenance checklist and assigning preventative 

maintenance responsibility for shared ATVs; an alternative 

to door shields for vehicles in some areas; and an update to 

the aviation safety plan. The safety committee has always 

been a virtual team and focused on maintaining connections 

by making time for personal check-ins at every meeting. 

For the next year, the safety committee will continue to 

track progress on issues identified in the yearly debriefing, 

exploring the use of electronic bikes and many more topics. 

Southern Research Station

SRS FIA has continued to hold its example of few motor 

vehicle incidents and reportable injuries. For FY 2022, 

there were only five vehicle incidents, none of which 

were chargeable, while driving almost 450,000 miles. 

This distance is well below the pre-COVID-19 mileage of 

700,000 miles. Continued defensive driving courses help 

maintain safety practices. Only two injuries, neither of 

which were recordable, occurred during FY 2022. SRS FIA 

continues to strive to prevent all injuries and manage risk 

through all phases of work. The recent success is a credit to 

all the field collection crews and supervisors.

The safety committee has moved to becoming a more 

virtual team in the COVID-19 and post-COVID-19 periods; 

however, it hasn’t slowed efforts to bring subjects to the 

forefront. It has continued to update and assist all employees 

with the latest knowledge available through national and 

local efforts. The committee continues to author monthly 

briefings on subjects such as driving, boating safety, and 

PPE. It will soon begin work to update safety plans and 

JHAs for the coming year, including the newest COVID-19 

mitigation measures.

The program continues to provide necessary PPE to 

mitigate COVID-19 risk following all prescribed guidelines. 

N95 masks and COVID-19 test kits are now available to 

employees at their request. Data collection crews are now 

traveling with minimal restrictions and beginning to build 

relationships with State cooperators. The SRS FIA Program 

has tried to put in place safeguards for everyone’s comfort 

level; every individual needs to determine their degree of 

risk acceptance when traveling or in day-to-day operations. 

Northern Research Station

NRS FIA continues to closely follow agency direction 

for travel and office capacity regarding the COVID-19 

pandemic. N95 masks were provided to staff early in the 

fiscal year. Field data collection crews are allowed to travel 

and work in multiperson crews with permission and based on 

their comfort level. 

All SENDs for Federal field employees were upgraded to the 

newest Garmin inReach Explorer®+. In addition to having 

the most current satellite connection and communication 

capabilities, it also includes a weather app that field 

employees can use to track weather in the area. Recreational 

GPS devices used for navigation were upgraded to the 

Garmin GPSMAP® 64sx. Federal and contract field crews 

were equipped with traffic cones, informational signs, 

and orange vests for increased visibility when working in 

populated areas. 

The Federal data collection crew continues to maintain safe 

driving practices, driving 548,857 miles safely with no traffic 

accidents; only two instances of off-road damage to vehicles 

were reported. A total of three time-lost recordable injuries 

and illnesses were reported among Federal employees. 

The safety and health committee (composed of field, office, 

and management staff) continues to ensure staff is current 

on all safety- and health-related trainings. In addition to 

monthly meetings, committee members annually review JHA 

documents to incorporate the changing needs of office and 

field staff. 

Program Safety
22 Forest Inventory and Analysis

FIA Program Accomplishment Highlights

This section provides information on select FIA 

accomplishments and outcomes throughout the country. 

Some of these achievements have a nationwide impact, 

while others are regional but equally important. More 

detailed information is available from the contact listed 

with each highlight.

Interactions Among Wildfire, Forest 

Type, and Landscape Position Are Key 

Determinants of Boreal Forest Carbon 

Stocks

Impact: Boreal forest soils contain large stocks of soil 

carbon that may be sensitive to changes in climate and 

disturbance. Destabilization of boreal forest soil carbon 

through changes in inputs, belowground carbon pools, and/or 

wildfire could accelerate rising atmospheric carbon dioxide 

(CO2) concentration. Additionally, increasing frequency of 

severe fires may be changing the dominant forest types and 

reshaping aboveground carbon stocks. Although controls 

on ecosystem carbon pools have received considerable 

attention, many studies have been limited to locations 

near the road system, leading to uncertainty in current and 

future carbon stocks across boreal Alaska. Here, researchers 

leveraged 545 randomly selected and spatially balanced FIA 

plots across ~13.5 million ha in Interior Alaska to examine 

the factors governing soil and live tree carbon pools.

Outcome: Results highlight the nuanced interactions among 

wildfire, landscape position, and forest type that will play 

important roles in shaping future boreal ecosystem carbon 

stocks. Forest type mediated the effects of mean summer 

air temperature and near-surface permafrost on soil carbon. 

Meanwhile, forest type, stand age, and aspect were the 

primary drivers of live tree carbon. Overall, plots with a 

known history of wildfire during the past 70years did not 

have significantly different soil carbon stocks than plots 

without a known history of fire, likely due to the historical 

predominance of low-severity fires. Where wildfire likely 

initiated a transition to deciduous trees (19 percent of 

plots), live tree and soil carbon pools were reduced by 

16 and 20 percent, respectively. Ecosystem carbon likely 

recovered over time, as maturing deciduous stands rapidly 

gained carbon in live trees. Deciduous stands without a 

known fire had comparatively very large live tree carbon 

stocks, suggesting a significant change in the distribution of 

ecosystem carbon following severe fire.

Contact: Sean Cahoon, sean.cahoon@usda.gov

Links:

Cahoon, S.M.P.; Sullivan, P.F.; Gray, A.N. 2022. Interactions

among wildfire, forest type and landscape position are 

key determinants of boreal forest carbon stocks. Journal 

of Ecology. 110(10): 2475–2492.

https://doi.org/10.1111/1365-2745.13963.

Innovative Wood Use Can Enable 

Carbon-Beneficial Forest Management 

in California

Impact: This work represents an important first step 

toward understanding the full breadth of impacts that 

increased use of mass timber in new construction could 

have on forests and climate mitigation around the globe. 

As the need to address climate change grows more urgent, 

policymakers, businesses, and others are seeking innovative 

approaches to remove CO2 emissions from the atmosphere 

and decarbonize hard-to-abate sectors. Forests can play 

a role in reducing atmospheric carbon. However, there is 

disagreement over whether forests are most effective in 

reducing carbon emissions when left alone versus managed 

for sustainable harvesting and wood product production. 

Cross-laminated timber is at the forefront of the mass timber 

movement, which is enabling designers, engineers, and other 

stakeholders to build taller wood buildings. The prospect of 

increased utilization of wood products as a climate solution 

also raises questions about the impact of increased demand 

for wood on forest carbon stocks, on forest condition, 

and on the provision of the many other critical social and 

environmental benefits that healthy forests can provide. 

A holistic assessment of the total climate impact of forest 

product demand across product substitution, carbon storage 

in materials, current and future forest carbon stock, and 

forest area and condition is challenging, but it is important 

to understand the impact of increased mass timber utilization 

on forests and climate, and therefore also on which 

safeguards might be necessary to ensure positive outcomes.

Outcome: To assess the potential impacts, both positive 

and negative, of greater mass timber utilization on forests 

ecosystems and emissions associated with the built 

environment, The Nature Conservancy initiated a global 

mass timber impact assessment (GMTIA), a five-part, highly 

collaborative research program focused on understanding 

the potential benefits and risks of increased demand for 

mass timber products on forests and identifying strategies to 
Fiscal Year 2022 Business Report 23

ensure the benefits outweigh the risks. The series of projects 

has been collaboratively designed to answer pressing 

questions in the discussion of mass timber impacts, both 

negative and positive, on carbon sequestration and forest 

health.

Contact: Jeremy Fried, jeremy.s.fried@usda.gov

Links: 

Cabiyo, B.; Fried, J.S.; Collins, B.M.; Sanchez, D.L. 2021. 

Innovative wood use can enable carbon-beneficial forest 

management in California. Proceedings of the National 

Academy of Sciences. 118(49): e2019073118.

https://doi.org/10.1073/pnas.2019073118.

Optimal Survey Design for Forest 

Carbon Monitoring in Remote Regions 

Using Multi-Objective Mathematical 

Programming

Impact: Cost-effective monitoring of forest carbon 

resources is critical to the development of national policies 

and enforcement of international agreements aimed at 

reducing carbon emissions and mitigating the impacts of 

climate change. While carbon monitoring systems are often 

based on national forest inventories utilizing a large sample 

of field plots, in remote regions, the lack of transportation 

infrastructure often requires heavier reliance on remote 

sensing technologies, such as airborne lidar (Light Detection 

and Ranging). The efficacy of estimating carbon with 

lidar varies across the various carbon pools within forest 

ecosystems. Lidar measurements are typically highly 

correlated with aboveground tree carbon but are less strongly 

correlated with other carbon pools, such as down woody 

materials (DWM) and soil. Field measurements are essential 

to both (1) estimate soil and DWM carbon directly and (2) 

develop regression models to estimate tree carbon indirectly 

using lidar. With limited budgets and time, however, many 

decision makers desire an optimal way to combine field 

measurements with lidar to minimize standard errors in 

carbon estimates for the various pools.

Outcome: Using national forest inventories and airborne 

lidar data from a remote boreal forest region of Interior 

Alaska, researchers demonstrate the operational feasibility 

of the method and suggest that it is generalizable to other 

carbon sampling projects because of its generic mathematical 

structure. This work introduces a multi-objective binary 

programming formulation that quantifies the tradeoffs behind 

the competing objectives of minimizing standard errors for 

tree carbon, DWM carbon, and soil carbon.

Contact: Hans Andersen, hans.andersen@usda.gov

Links: 

Tóth, S.F.; Oken, K.L.; Stawitz, C.C.; Andersen, H.-E. 

2022. Optimal survey design for forest carbon monitoring 

in remote regions using multi-objective mathematical 

programming. Forests. 13(7): 972. 

https://doi.org/10.3390/f13070972.

Evaluating Terrestrial Laser Scanning 

in Southeastern Mixed Hardwood 

Forests 

Impact: Use of terrestrial laser scanning (TLS) to 

measure tree and stand attributes in forests is increasing in 

popularity, particularly for mensuration and forest inventory 

applications that require assessment of tree architecture and 

size. Although use of this new technology is expanding, 

access to the equipment and software required to collect 

and process this type of data is still not widely available 

to students or forest managers. Once collected, TLS data 

contain millions of points which require basic programming 

skills to manipulate and analyze. 

Outcome: The FIA Program partnered with the University 

of Tennessee (UT) to host a training to help raise awareness 

and access to TLS technology (figure 10). This training 

held at the UT Arboretum provided students, arboretum 

staff, FIA field crews, and scientists a hands-on introduction 

to the collection, processing, and analysis of TLS data for 

tree size (height and diameter at breast height (DBH)) and 

stand density estimation (basal area and trees per acre). 

TLS data were collected and analyzed using various opensource processing scripts and visualization tools to examine 

potential for using this new technology in multistory 

hardwood stands. Group discussions centered on identifying 

potential uses of TLS technology including rapid assessment 

after hurricanes and other natural disasters, training broadscale leaf area index (LAI) models, and mapping understory 

and subcanopy vegetation.

Contact: Todd Schroeder, todd.schroeder@usda.gov
24 Forest Inventory and Analysis

Figure 10. Overview of the University of Tennessee and Forest Service terrestrial laser scanning (TLS) workshop showing (A) the 3D point 

cloud and probable stem locations on subplot 1, (B) field collection of TLS scans, (C) stem maps comparing TLS and manually detected 

trees on subplot 1, and (D) accuracy of TLS tree height and DBH estimates versus FIA field-measured trees. USDA Forest Service photo by 

Todd Schroeder.

DBH = diameter at breast height; FIA = Forest Inventory and Analysis.

Modeling the Growth and Allometric 

Relationships of Caribbean Tree 

Species Using Long-Term Permanent 

Plot Data

Impact: Accurate estimates of tree volume, biomass, and 

carbon change over time sometimes require prediction of 

certain tree parameters. For example, reconstructing the 

broken top of a tree from its DBH depends on understanding 

the allometric relationships between those two parts of the 

tree. Projecting growth depends on having annual diameter 

increment models. These relationships and models have been 

developed for many species measured by the FIA Program 

in the temperate and boreal forests in which it operates but 

much less so in the subtropical forests of the Caribbean. 

While Caribbean-specific models have been developed for 

the FIA Program in the past, this two-phase effort draws 

upon remeasurement data from FIA plots in Puerto Rico and 

the U.S. Virgin Islands and permanent plots in Jamaica and 

Trinidad.

Outcome: In this first phase of a larger project, models 

were fit to the relationships between DBH and total height 

using Random Forest (RF) and Mixed-Effects Random 

Forests (MERF) algorithms. Potential variables were ranked 

by score, submodels sequentially fit, and final variables 

selected. Then, parametric mixed models with and without 

environmental variables were finalized. Pseudo R-squared 

values ranged from 0.81 to 0.30, varying by island, with 

MERF models showing higher precision. On all islands, 

very tall tree heights were underpredicted while very short 

tree heights were overpredicted in Puerto Rico and Trinidad. 

Models developed without environmental variables could be 

used in the FIA NIMS to replace the current default models 

for most Caribbean tree species, improving the accuracy of 

volume, biomass, carbon, and growth estimates.

Contacts:

Thomas J. Brandeis, thomas.j.brandeis@usda.gov; 

Sheng-I Yang, syang47@utk.edu; 

Humfredo Marcano, humfredo.marcano@usda.gov

Links: 

Yang, S-I.; Brandeis, T.J.; Helmer, E.H.; Oatham, 

M.P.; Heartsill-Scalley, T.; Marcano-Vega, H.

2022. Characterizing height-diameter relationships

for Caribbean trees using mixed-effects random forest

algorithm. Forest Ecology and Management. 524:

120507. https://doi.org/10.1016/j.foreco.2022.120507.

FIA Program Accomplishments Highlights
Fiscal Year 2022 Business Report 25

Using FIA Data to Identify 

Factors Driving Variability in the 

Mesophication of Eastern U.S. Forests

Impact: Altered disturbance regimes (particularly fire), 

historic forest management practices, and climate patterns 

have resulted in an increase in shade-tolerant tree species 

associated with wetter conditions throughout the Eastern 

United States. At the same time, disturbance-adapted, 

xerophytic species have decreased. These changes in 

composition have the potential to negatively impact a wide 

array of ecosystem services. They may decrease the viability 

of ecologically and economically important species like 

oaks and decrease forest resiliency to disturbances such 

as drought. There is also evidence that this replacement 

of disturbance-adapted species with shade-tolerant, mesic 

species is a self-reinforcing process, called mesophication 

(figure 11). The development of effective management 

practices to address mesophication depends on answering 

two questions: (1) How does mesophication vary at stand 

scales and (2) how are the functional conditions of forests 

(e.g., drought, fire, and shade tolerances) changing?

Outcome: Experts from SRS FIA (Oswalt) and the Center 

for Forest Restoration and Management (Keyser) partnered 

to address these research needs utilizing the powerful extent 

and detail of FIA data. FIA data made it possible to not only 

address these questions across the entire Eastern United 

States but to model both the predicted change through time 

and potential future forest change. Results showed that 

mesophication was more pronounced in older stands, in 

stands with more variable diameters, and in wetter sites. 

However, the method for evaluating shifts and the functional 

trait examined (e.g., drought versus fire tolerance) sometimes 

resulted in differing relationships and thus highlights the 

value of using FIA data to examine complex questions. 

The results provide evidence that stand-scale conditions 

impact current and potential future changes in the functional 

makeup of forests across the Eastern United States but not 

always in consistent or expected ways.

Contacts:

Margaret Woodbridge, margaret.woodbridge@usda.gov; 

Chris Oswalt, christopher.oswalt@usda.gov; 

Tara Keyser, tara.keyser@usda.gov

Links: 

Woodbridge, M.; Keyser, T.; Oswalt, C. 2022. Stand 

and environmental conditions drive functional shifts 

associated with mesophication in eastern US forests. 

Frontiers in Forests and Global Change. 5: 991934. 

https://doi.org/10.3389/ffgc.2022.991934.

Figure 11. A variety of tree species make up the regeneration layer in a Southern Appalachian forest. Understanding how species shift, such 

as the shift to more mesic species associated with mesophication, helps managers prioritize stands for restoration and make ecologically 

informed decisions. 

USDA Forest Service photo by Margaret Woodbridge.

FIA Program Accomplishments Highlights
26 Forest Inventory and Analysis

Global Gridded Biomass Product 

Based on GEDI Data

Impact: Accurate estimation of aboveground forest 

biomass stocks is required to assess the impacts of land 

use changes such as deforestation and subsequent regrowth 

on concentrations of atmospheric CO2. FIA provided data 

and forest sampling expertise for development of the new 

global gridded biomass product, which was produced using 

data collected by NASA’s Global Ecosystem Dynamics 

Investigation (GEDI) mission. GEDI collects a global 

sample of small-footprint waveform lidar data with the 

purpose of characterizing forest canopy height, canopy 

vertical structure, and surface elevation, which allows 

mapping of aboveground biomass density when coupled 

with plot data collected by FIA. 

Outcome: The global 1-km biomass map product and 

corresponding 1-km estimates of the standard error of the 

mean are now available for all regions of the world covered 

by the International Space Station (between latitudes of 

51.6 degrees north and 51.6 degrees south). This product 

represents a globally consistent, transparent, and spatially 

explicit assessment of forest carbon stocks. GEDI data are 

now supporting several mapping projects in the United 

States and elsewhere. The global biomass product can be 

combined with Landsat data to estimate carbon emissions 

and sequestration due to land use change and vegetation 

regrowth. 

Contact: Sean Healey, sean.healey@usda.gov

Links: 

Dubayah, R.O.; Armston, J.; Healey, S.P.; Yang, Z.; 

Patterson, P.L.; Saarela, S.; Stahl, G.; Duncanson, 

L.; Kellner, J.R. 2022. GEDI L4B gridded aboveground 

biomass density, version 2. Oak Ridge, TN: Oak Ridge 

National Laboratory, Distributed Active Archive Center 

for Biogeochemical Dynamics. 

https://doi.org/10.3334/ORNLDAAC/2017. 

Dubayah, R.; Armston. J.; Healey, S.P.; Bruening, 

J.M.; Patterson, P.L.; Kellner, J.R.; Duncanson, L.;

Saarela, S.; Ståhl, G.; Yang, Z. 2022. GEDI launches a

new era of biomass inference from space. Environmental

Research Letters. 17(9): 095001.

https://doi.org/10.1088/1748-9326/ac8694.

Saarela, S.; Holm, S.; Healey, S.P.; Patterson, P.L.; 

Yang, Z.; Andersen, H.-E.; Dubayah, R.O.; Qi, W.; 

Duncanson, L.I.; Armston, J.D.; Gobakken, T.; 

Næsset, E.; Ekström, M.; Ståhl, G. 2022. Comparing 

frameworks for biomass prediction for the Global 

Ecosystem Dynamics Investigation. Remote Sensing of 

Environment. 278: 113074. 

https://doi.org/10.1016/j.rse.2022.113074.

Patterson, P.L.; Healey, S.P.; Ståhl, G.; Saarela, 

S.; Holm, S.; Andersen, H.-E.; Dubayah, R.O.; 

Duncanson, L.; Hancock, S.; Armsto, J. 2019. 

Statistical properties of hybrid estimators proposed 

for GEDI—NASA’s global ecosystem dynamics 

investigation. Environmental Research Letters. 14(6): 

065007. https://doi.org/10.1088/1748-9326/ab18df.

Forest Disturbance Intensity Maps 

for Conterminous United States, 

1986–2015

Impact: Forest disturbances can have broad impacts on the 

climate, local environment, and regeneration of the forest 

ecosystem. The nature and magnitude of such impacts are 

largely driven by disturbance intensity. The combination of 

FIA data and Landsat imagery offered a novel way of using 

FIA remeasurement data to map disturbance magnitude 

at 30-m resolution from 1986 through 2015. Disturbance 

intensity was estimated from random forest models using 

Landsat time series observations as inputs and FIA plot data 

for model calibration and validation. Models relied on data 

from FIA plots that had been measured both before and 

after a disturbance, thus capitalizing on the fact that FIA 

establishes permanent plots that provide ground truth data 

for assessing change over time.

Outcome: This map series represents the first annual 

forest disturbance intensity collection for the conterminous 

United States, modeled from field remeasurement of 

individual trees. It allows characterization of disturbance 

severity, in terms of percentage basal area removal, for 

the entire country or specific areas of interest, at 30-m 

resolution. Investigation of trends within this time series 

shows that disturbance severity has differed considerably 

among States and U.S. Environmental Protection Agency 

(EPA) ecoregions and through time. The highest average 

disturbance intensities by State and EPA ecoregion were 

observed in the Southeastern United States and along 

the west coast. The time series also indicates that of all 

disturbed areas, only about half experienced stand-clearing 

disturbances, which highlights the importance of considering 

severity when interpreting forest area disturbance and rates 

of disturbance.

Contact: Karen Schleeweis, karen.schleeweis@usda.gov

Links: 

Lu, J.; Huang, C.; Tao, X.; Gong, W.; Schleeweis, 

K. 2022. Annual forest disturbance intensity mapped

using Landsat time series and field inventory data for

the conterminous United States (1986–2015). Remote

Sensing of Environment. 275: 113003.

https://doi.org/10.1016/j.rse.2022.113003.

FIA Program Accomplishments Highlights
Fiscal Year 2022 Business Report 27

Lu, J.; Huang, C.; Tao, X.; Schleeweis, K. 2023. NACP 

NAFD project: forest disturbance intensity for CONUS 

from Landsat, 1986–2015. Oak Ridge, TN: Oak Ridge 

National Laboratory, Distributed Active Archive Center 

for Biogeochemical Dynamics. 

https://doi.org/10.3334/ORNLDAAC/2059. 

Aridity Controls Streamflow Response 

to Forest Disturbance

Impact: Forest disturbance is generally expected to increase 

runoff and streamflow, but recent studies have shown that 

this is not always the case. It is important to understand the 

relationship between disturbance and streamflow because 

changes in water availability can affect both aquatic 

ecosystems and downstream users. A combination of FIA 

data and hydroclimatic data from the National Center for 

Atmospheric Research allowed quantitative linkage between 

forest disturbance and streamflow changes in 159 Western 

U.S. watersheds. While this work found that streamflow 

often increased following forest disturbance, postdisturbance streamflow decreased in arid watersheds. 

Outcome: This work identified exceptions to the expectation 

that forest cover loss, whether through disturbance or 

treatment, will lead to increased streamflow. Very dry 

watersheds are more likely to produce less runoff following 

forest disturbance—and are also more likely to experience 

forest disturbance in the first place. Thus, the direction 

of streamflow response to forest disturbance (increase 

versus decrease) depends on aridity, defined as potential 

evapotranspiration relative to precipitation. These findings 

can inform forest management that seeks to implement 

silvicultural treatments. Specifically, forest thinning 

treatments in arid watersheds may not produce increases in 

water yield.

Contact: Sara Goeking, sara.goeking@usda.gov

Links: 

Goeking, S.A.; Tarboton, D.G. 2022. Variable streamflow 

response to forest disturbance in the western US: a largesample hydrology approach. Water Resources Research. 58: 

e2021WR031575. https://doi.org/10.1029/2021WR031575.

The ‘Hole’ Story About Wood Duck 

Nest Cavities: Forest Inventory Data 

Reveal Increased Potential Habitat in 

Northern Minnesota

Impact: Informing wildlife habitat conservation just became 

a little easier, thanks to new methods for combining local 

research data with FIA data. Results indicate that potential 

wood duck habitat in northern Minnesota has increased in 

recent decades, and the methodology developed here can be 

used to assess trends across the range of wood ducks and 

other cavity nesting species.

Outcome: Tree cavities provide nesting habitat for wood 

ducks, a species prized by both waterfowl hunters and 

wildlife watchers. But nesting duck hens do not settle for 

any tree hole; cavity size, height, and condition need to be 

just right. Artificial nest boxes provide such conditions at 

some local sites, but natural cavities in forest trees support a 

large majority of the wood duck population. Forest managers 

need to know how many suitable nesting cavities are 

available, and how those numbers are changing over time. 

But counting cavities over millions of acres is an impossible 

task. Wildlife researchers from the Minnesota Department 

of Natural Resources recently reported that probability 

of suitable nest cavity occurrence is based on three tree 

characteristics: species, size, and health status. These same 

tree attributes are measured on every FIA sample plot. 

Researchers from NRS FIA and Minnesota Department of 

Natural Resources (James B. Berdeen, Edmund J. Zlonis, 

and John H. Giudice) teamed up to develop new statistical 

methods for extrapolating local research findings to strategic 

scales. Abundance of potentially suitable wood duck 

nesting cavities increased during recent decades in northern 

Minnesota, exceeding prior published projections. That is 

good news for both wood ducks and the forest owners who 

manage their habitats. 

Contact: Mark Nelson, mark.d.nelson@usda.gov

Links: 

Berdeen, J.B.; Nelson, M.D.; Zlonis, E.J.; Giudice, 

J.H. 2022. Temporal change in abundance of potential 

nesting cavities for wood ducks (Aix sponsa) in Northern 

Minnesota, United States. Frontiers in Forests and Global 

Change. 5: 967060. 

https://doi.org/10.3389/ffgc.2022.967060.

Shifting Forests and Carbon

Impact: Forest communities change over time and so does 

the amount of carbon captured, stored, and/or emitted from 

those forests. Linking forest communities to carbon cycling 

can improve knowledge about the feedbacks between forest 

dynamics and climate change.

Outcome: Forest communities—tree species that commonly 

co-occur—are constantly changing as trees die and new 

trees replace them. At the same time, carbon moves from 

the live to the dead carbon pool. A challenge is to determine 

the amount of carbon being sequestered and stored by these 

forest communities as they change over time. In this project, 

NRS scientists and collaborators borrowed an approach from 

text mining research—an artificial intelligence (AI)-based 

discipline focused on extracting information from written 

data—to identify forest communities. Their text mining 

FIA Program Accomplishments Highlights
28 Forest Inventory and Analysis

algorithm mimics how commonly co-occurring words 

(species) in sentences (forest inventory plots) form topics 

(communities). Scientists used over 20,000 remeasurements 

of around 5,600 FIA plots in the Great Lakes region to 

evaluate how forest communities change over time. The 

findings quantified how much carbon was stored in each 

of six unique forest communities identified by the text 

mining algorithm. For example, the sugar maple-basswood 

community had the most live carbon, but the fir-cedarbirch community had the most standing dead carbon. The 

findings also showed that a combination of both the forest 

community and the forest structure—the number of different 

sized trees in the FIA plots—best predicted changes to the 

carbon pools. These improved knowledge areas can inform 

forest managers how shifts in their forests’ community 

composition and structure resulting from climate change, 

human intervention, and other forest stressors may impact 

their forests’ ability to capture and store carbon to further 

combat climate change.

Contacts:

Jonathan Knott, jonathan.knott@usda.gov;

Grant Domke, grant.m.domke@usda.gov;

Christopher Woodall, christopher.w.woodall@usda.gov; 

Brian Walters, brian.f.walters@usda.gov

Links: 

Knott, J.; Domke, G.; Woodall, C.; Walters, B.; Jenkins, 

M.; Fei, S. 2022. Shifting forests and carbon: linking 

community composition and aboveground carbon 

attributes. Ecosystems. 26: 412–427. 

https://doi.org/10.1007/s10021-022-00765-6.

Interactive Web Tool Provides 

Information About the Spread and 

Potential Impacts of Nonnative Forest 

Insects and Diseases

Impact: Invasions by nonnative insects and diseases have 

substantial negative impacts on the structure, composition, 

and function of forest resources. Understanding how host 

resources at risk respond in the presence of these forest 

pests has important implications for the management of 

native plant communities, invasive plants, and carbon 

sequestration. Scientists from NRS are providing sciencebased interactive data visualization tools that allow users 

to track the ranges of invasive forest pests, quantify trends 

in host tree species abundance, and compute increases in 

mortality caused by insect and disease invasions across the 

United States.

Outcome: Providing science-based interactive data 

visualizations aids in communicating where and how 

nonnative forest insects and diseases are contributing 

to changes in forest resources. To date, the Alien Forest 

Pest Explorer (AFPE) database includes the geographic 

distributions of 74 species of forest insects and 15 species of 

forest pathogens. In addition, the AFPE web tool integrates 

pest distribution data for 16 of the most damaging pests with 

forest inventory data from the FIA Program to highlight the 

status and trends in the health of host resources. This online 

tool allows users to customize host data retrievals across 

multiple scales to aid in addressing forest health management 

and research goals.

Partners: Songlin Fei, Purdue University and USDA Forest 

Service, Forest Health Protection, FHAAST

Contacts:

Susan Crocker, susan.j.crocker@usda.gov; 

Andrew Liebhold, andrew.liebhold@usda.gov; 

Randall Morin, randall.s.morin@usda.gov

Links: 

Alien Forest Pest Explorer: 

https://mapsweb.lib.purdue.edu/AFPE

Managing the FIA Program Nationally

FIA National Office

The National Office for the FIA Program provides leadership, 

guidance, coordination, and oversight to FIA field units 

in strategy and implementing the FIA Program; seeks 

opportunities to advance the program mission and resources; 

fosters relationships, transparency, and accountability; 

coordinates with other Forest Service programs and Federal 

agencies; seeks input from clients’ data needs; and represents 

FIA in national and international efforts. In collaboration 

with the field units’ leadership, the National Office provides 

strategic program direction and resource allocation to deliver 

the program in an efficient and effective way. 

Through meetings, presentations, policy papers, briefing 

papers, budget justifications, and other ways to provide input 

and engage in national and international efforts, the National 

Office provides liaison and strategic planning, showcases the 

value and impact of the program, and guides the allocation 

of the human and financial resources needed for the 

implementation of the program. Some of the accomplishments 

in FY 2022 include:

• Continued leading oversight and implementation of policy 

changes that provide additional, legally binding protection 

for confidential information. Since FY 2020,the FIA 

Program continues to adopt changes to strengthen

protections for plot locations, landowners’ personally

identifiable information, nonpublic business data, and 

unpublished information. In 2022, FIA entered into 32 new

MTAs and 1 new national interagency MOA to protect

confidential information when sharing data with partners.

• Worked with agency leadership to allocate and track 

FIA Program Accomplishments Highlights
Fiscal Year 2022 Business Report 29

additional funding from the Coronavirus Aid, Relief, and 

Economic Security (CARES) Act, Forest Service R&D 

funds to support plot backlog resulting from the COVID-19 

pandemic and catastrophic wildfires, and targeted FIA 

funding to universities to work on operationalizing small 

area estimation techniques, develop national vegetation 

classification, support national user group and focus group 

meetings, and support retirees to help on business reports 

and archiving historical plot measurement data. 

• Supported developmental details for six FIA or NFS

employees within National Office FIA to provide learning

opportunities and experience at national headquarters and to

strengthen the FIA workforce.

• Collaborated with NFS Ecosystem Management 

Coordination Staff to develop a framework for using FIA 

data to assess old growth and mature forest to respond to

Executive Order 14072 of April 22, 2022 (Strengthening

the Nation’s Forests, Communities, and Local Economies). 

Supported various data requests related to reforestation,

forest disturbances, climate change research, information

technology modernization, and artificial intelligence 

exploration.

• Collaborated with the Society of American Foresters and

the National Council for Air and Stream Improvement

(NCASI) in organizing two virtual meetings: a national 

user group focus meeting on carbon in March 2022 and 

the FIA national user group meeting in April 2022. Both

meetings served as a mechanism for FIA partners, users,

and research collaborators to present emerging information

needs, track the program accomplishments, and provide

feedback on performance. The national user group

meeting, with 156 virtual registrants, had 3 focus areas: 

(1) program accomplishments and priorities; (2) forest 

carbon estimation; and (3) emerging priorities and the FIA 

Program’s contributions. The virtual carbon meeting, with

about 140 attendees, also had 3 primary areas of focus: (1) 

identifying the grand challenges of forest carbon estimation; 

(2) new and emerging technologies and solutions to address 

these grand challenges; and (3) the ways in which the 

diverse range of people interested in forest carbon decision

support can form new working relationships to generate

associated solutions.

• Provided technical expertise on forest carbon inventories

and accounting by reviewing drafted legislation, producing 

communication products, contributing to an emerging

carbon investment program for NFS, estimating the 

investments needed to support carbon in the FIA Program

including greenhouse gas inventories, and collaborating

with a temporary Forest Service R&D-funded FIA policy

position to (1) provide science leadership to address urgent

carbon-related requests and (2) develop a strategy and 

operational plan to provide field leadership and research 

capacity to address national needs in coordination with the 

National Office.

• Demonstrated the transparency and accountability of 

the program by leading the development of this report, 

coordinating national reporting teams, soliciting input from

partners and data users, and working with the Forest Service

Budget Office and unit budget officers to ensure accuracy 

in the FIA charges and transparency in the financial 

information reported. Additionally, reported program

research and scientific accomplishments to the USDA 

Technology Transfer Annual Report.

• Provided liaison, technical expertise, and data to the Global 

Forest Resources Assessment conducted by the Food and 

Agriculture Organization of the United Nations (FAO) and

FAO North American Forest Commission; collaboratively

developed an online interactive tool for viewing national

data related to multiple resource areas; improved global 

reporting methods of primary forest through participation 

in workshops and pilot projects in the boreal region; and 

provided support to Forest Service International Programs

on activities related to the FAO Committee on Forestry and

other international issues.

Contact: Renate Bush, renate.bush@usda.gov

FIA National Operations Team

FIA has a national operations team that provides operational 

coordination and support across FIA’s core mission. 

Their major responsibilities include project management, 

operational planning, IT budget management, liaison to the 

Forest Service Chief Information Officer (CIO), and oversight 

of operations QA processes to increase national consistency

Major accomplishments in 2022 include:

• Identified issues related to implementing a nationally 

consistent program and moved through the change

management process to ensure effective and efficient rollout 

of solutions. Some of these issues included: 

◦ Bug fixes to the version 9.2 field guide to ensure 

consistent implementation

◦ Addition of growth, removals, and mortality tree status 

code for better tracking of removals

• Managed FIA software releases, security improvements,

and continuous improvements

• Worked toward improved database systems that connect 

different components of the inventory (e.g., urban, rural, 

special studies)

• Established a training program for all FIA staff on

compliance with Section 508 of the Rehabilitation ACT

(i.e., 508 compliance) to ensure electronic and information 

technology is accessible to people with disabilities

• Worked with collaborators to improve tools, estimates, and 

management of FIA data 

FIA Program Accomplishments Highlights
30 Forest Inventory and Analysis

• Worked directly with CIO staff on migrating the national 

FIA website as it moves to the new Drupal platform

• Continued to implement an annualized, national, urban field 

data collection certification

• Continued to develop systematic edit checks of data before 

public release, including MIDAS logic checks in the data

collection phase and Universal Information Management

System load error checks

• Developed a national system that performs checks 

and generates individual check-plot results to assist in 

comparing quality standards nationally

• Worked across FIA regions to identify inconsistencies, find 

a national resolution, and implement changes in prefield and 

field manual versions 9.3

• Developed and implemented national data collection staff 

training standards to ensure consistency

• Assisted with the new national-scale volume and biomass 

equations to ensure data quality

Contact: Donavon Nigg, donavon.nigg@usda.gov

The Director’s Awards for FIA Excellence

In FY 2022, the following individuals and groups were 

recognized for:

• Providing and promoting outstanding customer service as

part of the FIA Program: Paul Sowers (NRS)

• Advancing the core national FIA Program or expanding the

FIA Program to the areas as outlined in the 2014/2018 Farm

Bill and the FIA strategic plan: Interior Alaska Reporting

Team (Sean Cahoon, Kathryn Baer, and Hans Andersen

(PNW))

• Upholding the FIA program’s high standards in research,

quality assurance and control, and operational efficiency:

Brytten Steed (NFS Regions 1 and 4 Forest Health

Protection); NRS Archive Team (James Blehm, Mitchell

Pennabaker, Brian Gasper, Cassandra Olson, Melissa

Powers, Lucretia Stewart, Brian Wall, Jeffrey Wazenegger,

Rebecca Christopherson, Scott Hopton, Joseph Kernan,

Todd Renninger, and Paul Castillo (NRS))

• Applying FIA research on the ground to improve land

stewardship: National Woodland Owner Survey Team (Brett

Butler and Jesse Caputo (NRS), and Amanda L. Robillard,

Enna N. Sass, and Christopher Sutherland (University of

Massachusetts))

• Making a significant research contribution in the inventory

and monitoring sciences: Big Data

• Mapping and Analytics Platform (BIGMAP) Team

(Christopher Oswalt (SRS); Charles Perry, Barry Wilson,

and James Garner (NRS); Chuck Werstak (RMRS); David

Bell (PNW); and Eric Aiello, Michael Rich, and Joshua

Bixby (CIO))

• The Davita Colker Bryant Award for Outstanding Field

Service: Seth Ayotte (PNW) and Benjamin Nurre (NRS)

FIA Program Accomplishments Highlights
Fiscal Year 2022 Business Report 31

FIA Program Area Updates for FY 2022

Interior Alaska Inventory

The purpose of the Interior Alaska survey is to establish a 

baseline of forest conditions and monitor the status of boreal 

and arctic forests potentially experiencing rapid change. This 

work will help complete the base inventory of all forest land 

within the United States. Given current resources, all field 

plots across the Interior Alaska units (figure 12) are expected 

to be surveyed by 2043 (figure 13). Broadly, goals are to:

1. Determine the extent and rates of change in forests at

high latitudes.

2. Understand the present and potential future carbon

stores and flux of Alaskan forests.

3. Assess the potential for forest products and their role in

sustaining rural communities.

4. Leverage partnerships and remote sensing information

to develop efficient and cost-effective monitoring

strategies.

Objectives

1. Complete a ground measurement of FIA plots across

Interior Alaska at one-fifth intensity; 1,491 of an

estimated 4,677 forested plots are complete to date.

2. Leverage ground measurements using the NASA 

G-LiHT imaging platform.

3. Publish data to PNW FIADB website on a unit-by-unit

basis; Tanana and Susitna-Copper units are currently

available in Microsoft Access databases.

4. Report on data regularly.

5. Continue to explore more efficient, safer, and costeffective methods of inventorying Interior Alaska.

FY 2022 Accomplishments and Milestones

• The Southwest unit, started in 2020, is the first that is 

completely off the road system, posing substantial logistical 

challenges. Despite these challenges, field crews have 

measured tree, forest, and site information on a total of 412 

ground plots (approximately 45 percent of the unit), including 

149 during the 2022 field season (figure 14). Field crews also 

measured 24 plots in the Lower Yukon unit in 2022. Field 

plot collection for the Tanana and Susitna-Copper units has 

been complete since 2019 and 2020, respectively.

• In 2022, NASA completed G-LiHT data acquisition along 

strips covering FIA plots over approximately 19 percent of 

plots in the Southwest unit, for about 42 percent coverage in 

the unit to date.

Figure 12. FIA units in Interior Alaska.

FIA = Forest Inventory and Analysis.

Figure 13. Ongoing field plot progress for Interior Alaska 

inventory. The Tanana and Susitna-Copper units are field 

completed, and data are available in FIADB. Flyover plots 

were visited via helicopter and deemed nonforest (not 

requiring a field visit).

FIADB = Forest Inventory and Analysis Database.
32 Forest Inventory and Analysis

• The Tanana Data Report, which summarizes the forest

resources of the Tanana unit, was published.

• Three publications related to Interior Alaska resource

inventory techniques development and improvements were

released.

• The Forest Service Interior Alaska data collection

coordinator and quality assurance positions were filled.

• The FIA national operations team helped PNW FIA 

complete an exhaustive, multiyear review of feasible

options for redesigning the approach to Interior Alaska

data collection to address logistical, safety, and budgetary

realities of sampling in remote locations. Based on the

preferred option from this review, PNW FIA began a

project to assess the feasibility of an annualized study

design across the Interior Alaska unit. The feasibility

assessment will take 2–3 years and begins with hiring an

annualized feasibility project coordinator.

Financial Status and Partners

Current funding: $1.8 million (Forest Service) and 

$261,000 (external sources). Funding was higher in FY 

2021, but progress in the more remote roadless areas was 

slower than expected due to ongoing COVID-19 mitigations 

and lack of staffing. As a result, some funds carried over and 

less needed to be added in FY 2022.

FTEs: 4.2 (Forest Service) and 10.3 (external cooperators)

Farm Bill request: $3.7 million per year

Partnerships: Alaska Department of Natural Resources, 

Division of Forestry; NASA Goddard Space Flight Center; 

University of Alaska; Alaska Native Science and Engineering 

Program; Tanana Chiefs Conference; DOI Bureau of Land 

Management, Alaska Fire Service

Figure 14. Field-completed (black) and unvisited, anticipated 

forested (white) FIA field locations in the Southwest and Lower 

Yukon units of southwestern Alaska. Green is mapped forested area.

FIA = Forest Inventory and Analysis.

FY 2022 Publications and Deliverables

Interior Alaska Database (including data from both the 

Tanana and Susitna-Copper units): 

https://www.fs.usda.gov/research/pnw/products/

dataandtools/tools/pnw-fiadb-forest-inventory-andanalysis-databases

Cahoon, S.M.P.; Baer, K.C., tech. eds. 2022. Forest 

resources of the Tanana unit, Alaska: 2018. Gen. Tech. 

Rep. PNW-1005. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station. 92 p. https://doi.org/10.2737/PNW-GTR-1005. 

The Susitna-Copper unit, which represents an estimated 9 

percent of the field plots in Interior Alaska and was field 

completed in 2019, will be grouped with all or part of the 

adjacent Southwest unit for reporting purposes.

Other publications:

Andersen, H-K.; Strunk, J; McGaughey, R.J. 2022. 

Using high-performance global navigation satellite 

system technology to improve Forest Inventory and 

Analysis plot coordinates in the Pacific region. Gen. 

Tech. Rep. PNW-1000. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station. 38 p. https://doi.org/10.2737/PNW-GTR-1000. 

Cahoon, S.M.P.; Baer, K.C., eds. 2022. Forest resources 

of the Tanana unit, Alaska: 2018. Gen. Tech. Rep. PNW1005. Portland, OR: U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station. 92 p. 

https://doi.org/10.2737/PNW-GTR-1005. 

Cahoon, S.M.P.; Sullivan, P.F.; Gray, A.N. 2022. 

Interactions among wildfire, forest type and landscape 

position are key determinants of boreal forest carbon. 

Journal of Ecology. 110: 2475–2492. 

https://doi.org/10.1111/1365-2745.13963. 

Shoot, C.; Andersen, H.-E.; Moskal, L.M.; Babcock, 

C.; Cook, B.D.; Morton, D.C. 2021. Classifying forest 

type in the national forest inventory context with airborne 

hyperspectral and lidar data. Remote Sensing. 13(10): 

1863. https://doi.org/10.3390/rs13101863.

Tóth, S.F.; Oken, K.L.; Stawitz, C.C.; Andersen, H.-E. 

2022. Optimal survey design for forest carbon monitoring 

in remote regions using multi-objective mathematical 

programming. Forests. 13(7): 972. 

http://dx.doi.org/10.3390/f13070972.

Program Area Updates for FY22
Fiscal Year 2022 Business Report 33

Small Area Estimation

The purpose of the small area estimation (SAE) research 

portfolio is to modernize FIA’s methods for estimation of 

forest parameters within spatiotemporal domains spanning 

sub-State geographies and short time intervals. Early-phase 

research results are anticipated to support operational 

estimators and tools for (1) a nationwide, experimental series 

of annual, county-level forest area and biomass estimates by 

2025 and (2) area and biomass change by 2027. 

Objectives

1. Define user needs: Target attributes and domains,

precision and/or accuracy standards, and delivery

mechanisms.

2. Conduct techniques research: Evaluate new sources of

auxiliary information, explore new forms for supporting

models, and compare competing estimators and

estimates of their precision and/or accuracy.

3. Develop tools: Recommend best statistical practices and

deliver associated tools to the user community.

4. National project: Now called the Partnership for Small

Area Estimation (PSAE), we’ve formed user, science,

and development panels composed of FIA scientists

as well as representatives from industry, agencies,

academia, and other stakeholder groups. PSAE is a

strategic, nationally coordinated effort to synthesize

historic SAE R&D efforts and to prioritize tasks to

achieve objectives 1–3 above.

In FY 2022, a 3-year, $1.36 million cooperative agreement 

was executed with NCASI Foundation to refine user needs, 

conduct national SAE research, and develop tools via 

solicitation of proposals and distribution of research and 

development subawards. The execution of new and existing 

agreements and distribution of subawards will enable 

national coordination on R&D activities. Success of the FIANCASI Foundation cooperative agreement will be measured 

in part by the extent of national coordination achieved, 

numbers of peer-reviewed journal articles published, and 

estimation capacity delivery (FIESTA, BIGMAP, r-FIA, 

RegRake, and other tools).

FY 2022 Accomplishments and Milestones

• User needs: To undergo further refinement and

synthetization by the user panel at in-person executive

meeting

• Techniques research:

◦ Application of area-level model-based estimation

strategies for stand-level inventory

◦ Investigating indirect SAE of forest regeneration

following fire

◦ Evaluating impacts of data transformation on modelassisted estimation

◦ Developing a national ownership map and NWOS

county-level estimates

◦ Application of nearest neighbor techniques in a modelbased SAE context

◦ Developing county-level volume estimates for

Southeastern States and carbon estimates for the United

States

◦ Eight alternative SAEs for six FIA attributes for the

United States

• Delivery tools:

◦ FIESTA’s model-assisted and SAE modules were

expanded; demonstration dashboards were developed

nationally for ecosubsections, counties, and watersheds;

and advances were made in FIESTA-BIGMAP and

FIESTA-desktop delivery.

◦ Esri accelerated its support of BIGMAP with

supplemental access to Amazon Web Services, and

the BIGMAP team demonstrated the integration of

published SAE methods related to kNN estimation using

the R-ArcGIS Bridge.

◦ RegRake methodology was demonstrated via a

dashboard in South Carolina.

Financial Status and Partners

Historically, SAE-related projects were funded primarily 

by FIA units and collaborators. Upcoming research will be 

funded via direct or competitive grants through the NCASI 

Foundation agreement. Participants include:

• Forest Service: NRS, RMRS, SRS, PNW, GTAC, and

NFS Regions 1–4. FIA representatives from the four

research stations and GTAC are helping to set research and

platform development trajectories and conducting R&D

activities collaboratively with funding recipients (but are

not receiving funding themselves). NFS representatives

are providing insights into NFS-specific FIA information

needs and associated feedback on R&D proposals.

• Universities: Virginia Tech, University of Montana,

Harvard University, Missouri State University, Oregon

State University, University of Missouri, University

of Tennessee, Swarthmore College, Michigan State

University, Colby College

• Industry/other: RedCastle Resources, Esri, NCASI

Program Area Updates for FY22
34 Forest Inventory and Analysis

FY 2022 Publications and Deliverables

Special journal issue:

Wilson, B.; Coulston, J.; Prisley, S.; Radtke, P., eds.

2023. Small area estimation in forest inventories: new 

needs, methods, and tools. Frontiers in Forests and 

Global Change. Lausanne: Frontiers Media SA. 196 p. 

https://doi.org/10.3389/978-2-83251-647-8. 

Articles included in the special issue:

Bell, D.M.; Wilson, B.T.; Werstek, C.E.; Oswalt, 

C.M. 2022. Examining k-nearest neighbor small area

estimation across scales using national forest inventory

data. Frontiers in Forests and Global Change. 5: 763422.

https://doi.org/10.3389/ffgc.2022.763422.

Cao, Q.; Dettmann, G.T.; Radtke, P.J.; Coulston, J.W.; 

Derwin, J.; Thomas, V.A.; Burkhart, H.E.; Wynne, 

R.H. 2022. Increased precision in county-level volume 

estimates in the United States national forest inventory 

with area-level small area estimation. Frontiers in Forests 

and Global Change. 5: 769917. 

https://doi.org/10.3389/ffgc.2022.769917.

Dettmann, G.T.; Radtke, P.J.; Coulston, J.W.; Green, 

P.C.; Wilson, B.T.; Moisen, G.G. 2022. Review and

synthesis of estimation strategies to meet small area

needs in forest inventory. Frontiers in Forests and Global

Change. 5: 813569.

https://doi.org/10.3389/ffgc.2022.813569.

Ekström, M.; Nilsson, M. 2021. A comparison of modelassisted estimators, with and without data-driven 

transformations of auxiliary variables, with application to 

forest inventory. Frontiers in Forests and Global Change. 

4: 764495. https://doi.org/10.3389/ffgc.2021.764495.

Frescino, T.S.; White, G.W.; Toney, J.C.; Moisen, G.G.

2022. Small area estimates for national applications: a 

database to dashboard strategy using FIESTA. Frontiers 

in Forests and Global Change. 5: 779446. 

https://doi.org/10.3389/ffgc.2022.779446.

Gaines, G.C., III; Affleck, D.L.R. 2021. Small area 

estimation of postfire tree density using continuous forest 

inventory data. Frontiers in Forests and Global Change. 

4: 761509. https://doi.org/10.3389/ffgc.2021.761509.

Harris, V.; Caputo, J.; Finley, A.; Butler, B.J.; Bowlick, 

F.; Catanzaro, P. 2021. Small-area estimation 

for the USDA Forest Service, National Woodland 

Owner Survey: creating a fine-scale land cover and 

ownership layer to support county-level population 

estimates. Frontiers in Forests and Global Change. 4: 

745840. https://doi.org/10.3389/ffgc.2021.745840.

Prisley, S.; Bradley, J.; Clutter, M.; Friedman, S.; 

Kempka, D.; Rakestraw, J.; Sonne Hall, E. 2021. 

Needs for small area estimation: perspectives from the 

US private forest sector. Frontiers in Forests and Global 

Change. 4: 746739. 

https://doi.org/10.3389/ffgc.2021.746439.

Schroeder, T.A.; Nagle, N.N.; McCollum, J. 2022. 

RegRake: a web-based application for custom small 

area estimation and mapping of forest survey data with 

regularized raking. Frontiers in Forests and Global 

Change. 5: 769268. 

https://doi.org/10.3389/ffgc.2022.769268.

Stanke, H.; Finley, A.O.; Domke, G.M. 2022. Simplifying 

small area estimation with rFIA: a demonstration of tools 

and techniques. Frontiers in Forests and Global Change. 

5: 745874. https://doi.org/10.3389/ffgc.2022.745874.

Temesgen, H.; Mauro, F.; Hudak, A.T.; Frank, B.; 

Monleon, V.; Fekety, P.; Palmer, M.; Bryant, T.

2021. Using Fay–Herriot models and variable radius 

plot data to develop a stand-level inventory and update 

a prior inventory in the Western Cascades, OR, United 

States. Frontiers in Forests and Global Change. 4: 

745916. https://doi.org/10.3389/ffgc.2021.745916.

White, G.W.; McConville, K.S.; Moisen, G.G.; 

Frescino, T.S. 2021. Hierarchical Bayesian small 

area estimation using weakly informative priors in 

ecologically homogeneous areas of the Interior Western 

forests. Frontiers in Forests and Global Change. 4: 

752911. https://doi.org/10.3389/ffgc.2021.752911.

Wiener, S.S.; Bush, R.; Nathanson, A.; Pelz, K.; Palmer, 

M.; Alexander, M.L.; Anderson, D.; Treasure, E.; 

Baggs, J.; Sheffield, R. 2021. United States Forest 

Service use of forest inventory data: examples and needs 

for small area estimation. Frontiers in Forests and Global 

Change. 4: 763487. 

https://doi.org/10.3389/ffgc.2021.763487.

Wojcik, O.C.; Olson, S.D.; Nguyen, P.-H.V.; McConville, 

K.S.; Moisen, G.G.; Frescino, T.S. 2022. GREGORY:

a modified generalized regression estimator approach

to estimating forest attributes in the Interior Western

US. Frontiers in Forests and Global Change. 4: 763414.

https://doi.org/10.3389/ffgc.2021.763414.

Program Area Updates for FY22
Fiscal Year 2022 Business Report 35

Dashboards:

• Precision standards for small area estimators: watersheds

(https://mjdvl.shinyapps.io/watersheds/)

• Small area estimates for CONUS: counties (figure 15)

(https://fia-dash.shinyapps.io/fiesta-counties/)

• Small area estimates for CONUS: ecosubsections

(https://fia-dash.shinyapps.io/fiesta-subsections/)

• Small area estimates for CONUS: watersheds

(https://fia-dash.shinyapps.io/fiesta-watersheds/)

Carbon

The carbon portfolio’s mission is to advance the science, 

monitoring, and reporting of greenhouse gas emissions 

and removals on land with trees in the United States. This 

portfolio includes:

• Estimation and accounting compilation systems and tools

• Carbon pool science (including harvested wood products)

• Leveraging FIA remeasurements and auxiliary information

for change estimation and attribution across spatial and

temporal scales (figure 16)

• Informing carbon management, mitigation, and adaptation

activities

Objectives

1. Increase FIA contributions to the EPA National

Inventory Report (NIR) and other reporting instruments

and efforts.

2. Develop more spatially and temporally resolved

estimates to inform entity, State, and national

assessments as well as management, mitigation, and

adaption activities.

3. Employ new RPA Assessment projection modeling

framework.

Figure 15. Small area estimation dashboard: proportion of forest 

land by county.

4. Be more entrepreneurial—expand partners.

5. Improve collaboration and cooperation between FIA 

regions, bands, and portfolios to facilitate reporting

consistency, reduce redundancies, and ensure regional

applicability.

FY 2022 Accomplishments and Milestones

• Contributed the forest land, woodlands, harvested wood

products, and urban tree components of the 2022 NIR of

greenhouse gas emissions and sinks

• State-level disaggregation included in the 2022 Resource

Update (currently in Forest Service review) on FIA 

contributions to NIR with research datasets

• Contributed to State-level greenhouse gas inventories

(California, Oregon, Washington, West Virginia, Vermont,

South Carolina, New Hampshire, New York, Maine,

Minnesota, and Colorado—and the list is growing)

• Continuing to lead and contribute to U.S. Global Change

Research Program reports and reviews (Intergovernmental

Panel on Climate Change (IPCC) Assessment Report

6, Working Group III review, Fifth National Climate

Assessment (NCA5), Decadal Survey) and Committee

on Earth Observation Satellites activities (e.g., global

stocktake)

• Leading the land representation of the United States as

part of the 2022 NIR in cooperation with the land use and

land cover change portfolio

• Leading and contributing to research and applications on

nature-based climate solutions

• Disaggregating harvested wood products estimates for

States and regions with expected release in 2025

• Produced many refereed publications (10+), invited

presentations (10+), and organized sessions in FY 2022

documenting advances (e.g., pool science, estimation,

modeling, tool development, and applications of FIA data

in carbon science and management)

• Delivered a report on alternative methods, models, and

technologies used to estimate forest attributes (e.g., carbon

in aboveground biomass) to the California Air Resources

Board (CARB)

• Continuing to respond to unprecedented demand for

information from the National Office and stakeholders,

including work on Executives Orders on reforestation and

mature/old growth forest

Program Area Updates for FY22
36 Forest Inventory and Analysis

Figure 16. Carbon stock changes for forest land remaining forest land for the conterminous United States and Coastal Alaska by FIA region 

and ownership (MMT CO2 Eq.). (Ownership information was not available for forest land in Interior Alaska, so those lands were excluded 

from these estimates.)

MMT CO2 Eq. = million metric tons of carbon dioxide equivalent.

Financial Status and Partners

Current funding and capacity for FIA Program carbon 

activities: Internal: $1.2+ million (includes Forest Service 

salaries); external: $2 million+ (NASA, EPA, CARB, States, 

WO); FTEs: 9 (Forest Service) and 10+ (cooperators)

Stakeholders and partners: University of Minnesota, 

Colorado State University, Purdue University, Michigan 

State University, University of Vermont, University of 

Florida, United Nations Framework Convention on Climate 

Change, EPA, Council on Environmental Quality, IPCC, 

U.S. Department of State, NASA, U.S. States, NCASI, 

NFS, CARB, voluntary carbon registries, and American 

Forests, among many other nongovernmental organizations, 

scientists, policymakers, and land managers

FY 2022 Publications and Deliverables

Doraisami, M.; Kish, R.; Paroshy, N.J.; Domke, G.M.; 

Thomas, S.C.; Martin, A.R. 2022. A global database of 

woody tissue carbon concentrations. Scientific Data. 9: 

284. https://doi.org/10.1038/s41597-022-01396-1.

Fitts, L.A.; Domke, G.M.; Russell, M.B. 2022. 

Comparing methods that quantify forest disturbances 

in the United States’ national forest inventory. 

Environmental Monitoring and Assessment. 194: 304. 

https://doi.org/10.1007/s10661-022-09948-z.

Giebink, C.L.; Domke, G.M.; Fisher, R.A.; Heilman, 

K.A.; Moore, D.J.P.; DeRose, R.J.; Evans, M.E.K.

2022. The policy and ecology of forest-based climate

mitigation: challenges, needs, and opportunities. Plant

and Soil. 479: 25–52.

https://doi.org/10.1007/s11104-022-05315-6.

Hayes, D.J.; Butman, D.E.; Domke, G.M.; Fisher, J.B.; 

Neigh, C.S.R.; Welp, L.R. 2022. Boreal forests. In: 

Poulter, B.; Canadell, G.G.; Hayes, D.J.; Thompson, 

R.L., eds., Balancing greenhouse gas budgets.

Amsterdam: Elsevier: 203–236. Chapter 6.

https://doi.org/10.1016/B978-0-12-814952-2.00025-3.

Knott, J.; Domke, G.; Woodall, C.; Walters, B.; Jenkins, 

M.; Fei, S. 2023. Shifting forests and carbon: linking 

community composition and aboveground carbon 

attributes. Ecosystems. 26: 412–427. 

https://doi.org/10.1007/s10021-022-00765-6.

Nave, L.E.; DeLyser, K.; Domke, G.M.; Holub, S.M.; 

Janowiak, M.K.; Kittler, B.; Ontl, T.A.; Sprague, 

E.; Sucre, E.B.; Walters, B.F.; Swanston, C.W. 

2022. Disturbance and management effects on forest 

soil organic carbon stocks in the Pacific Northwest. 

Ecological Applications. 32(6): e2611. 

https://doi.org/10.1002/eap.2611.

Program Area Updates for FY22
Fiscal Year 2022 Business Report 37

Nave, L.E.; DeLyser, K.; Domke, G.M.; Holub, S.M.; 

Janowiak, M.K.; Ontl, T.A.; Sprague, E.; Viau, N.R.; 

Walters, B.F.; Swanston, C.W. 2022. Soil carbon in 

the South Atlantic United States: land use change, forest 

management, and physiographic context. Forest Ecology 

and Management. 520: 120410. 

https://doi.org/10.1016/j.foreco.2022.120410.

Quirion, B.R.; Domke, G.M.; Walters, B.F.; Lovett, 

G.M.; Fargione, J.E.; Greenwood, L.; Serbesoff-King,

K.; Randall, J.M.; Fei, S. 2021. Insect and disease

disturbances correlate with reduced carbon sequestration

in forests of the contiguous United States. Frontiers in

Forests and Global Change. 4: 716582.

https://doi.org/10.3389/ffgc.2021.716582.

Smith, J.E.; Domke, G.M.; Woodall, C.W. 2022. 

Predicting downed woody material carbon stocks in 

forests of the conterminous United States. Science of The 

Total Environment. 803: 150061. 

https://doi.org/10.1016/j.scitotenv.2021.150061.

U.S. Department of Agriculture, Office of the Chief 

Economist. 2022. U.S. Agriculture and Forestry 

Greenhouse Gas Inventory: 1990–2018. Tech. Bull. No. 

1957. Washington, DC. 181 p. 

https://www.usda.gov/sites/default/files/documents/

USDA-GHG-Inventory-1990-2018.pdf.

U.S. Environmental Protection Agency. 2022. Land 

use, land-use change, and forestry. In: Inventory of U.S. 

Greenhouse Gas Emissions and Sinks. EPA 430-R-22-

003. Washington, DC: 6-1–6-148. Chapter 6.

https://www.epa.gov/system/files/documents/2022-04/usghg-inventory-2022-chapter-6-land-use-land-use-changeand-forestry.pdf.

Walters, B.F.; Domke, G.M.; Greenfield, E.J.; Smith, 

J.E.; Nowak, D.J.; Ogle, S.M. 2022. Greenhouse gas

emissions and removals from forest land, woodlands, and

urban trees in the United States, 1990–2020: estimates

and quantitative uncertainty for individual states, regional

ownership groups, and National Forest System regions.

Fort Collins, CO: Forest Service Research Data Archive.

https://doi.org/10.2737/RDS-2022-0052.

Yu, Y.; Saatchi, S.; Domke, G.M.; Walters, B.; Woodall, 

C.; Ganguly, S.; Li, S.; Kalia, S.; Park, T.; Nemani, R.

2022. Making the US national forest inventory spatially 

contiguous and temporally consistent. Environmental 

Research Letters. 17: 065002. 

https://doi.org/10.1088/1748-9326/ac6b47. 

Land Use and Land Cover Change 

The 2014 Farm Bill charged FIA to understand and 

report changes in land use and land cover (LULC). FIA 

continuously monitors 326,000 plots across all land types, 

providing the most complete set of ground-based LULC 

observations in the world. FIA analysis of LULC focuses on 

three goals:

1. Help FIA leverage its unique dataset to lead national

LULC monitoring.

2. Create a forum for FIA LULC experts to coordinate

research within and outside of the program.

3. Maintain communication between LULC researchers

and FIA leadership.

Objectives

1. Draw lessons from the now-complete image-based

change estimation (ICE) pilot project. A determination

has been made that parallel LULC observations on the

FIA network at a slightly accelerated schedule do not

provide benefits commensurate with involved costs.

A paper is in progress that frames lessons learned in

the context of international image-based estimation

campaigns.

2. Refine a new LULC dashboard that currently delivers

plot-based land use estimates at State, county, and

survey unit scales. Land cover will be added soon, and

development is in progress for change estimation in

States where the database supports it.

3. Build a business case for national LULC monitoring.

Forthcoming documentation will focus on FIA’s

incomparable plot information and recent investments in

LULC data continuity and display.

FY 2022 Accomplishments and Milestones

• Updated and maintained the FIA Land Resources Explorer

dashboard (figure 17)

• Contributed data, funding, and relevant research studies

to the Landscape Change Monitoring System (https://

data.fs.usda.gov/geodata/rastergateway/LCMS/index.php)

and National Land Cover Database Tree Canopy Cover

Product (https://data.fs.usda.gov/geodata/rastergateway/

treecanopycover/#docref)

Financial Status and Partners

The portfolio currently tracks numerous LULC-related 

projects funded primarily by their home units and 

collaborators. Participating organizations:

• Forest Service: NRS, RMRS, SRS, PNW, GTAC, NFS

• Universities: Oregon State University, University of

Maryland

• Industry/other: Google, Planet Labs, NASA, NCASI

Program Area Updates for FY22
38 Forest Inventory and Analysis

Figure 17. Landing page for the interactive Land Resources Explorer dashboard.

FY 2022 Publications and Deliverables

Bullock, E.L.; Healey, S.P.; Yang, Z.; Houborg, R.; 

Gorelick, N.; Tang, X.; Andrianirina, C. 2022. 

Timeliness in forest change monitoring: a new 

assessment framework demonstrated using Sentinel-1 

and a continuous change detection algorithm. Remote 

Sensing of Environment. 276: 113043. 

https://doi.org/10.1016/j.rse.2022.113043.

Davis, R.J.; Bell, D.M.; Gregory, M.J.; Yang, Z.; Gray, 

A.N.; Healey, S.P.; Stratton, A.E. 2022. Northwest

Forest Plan—the first 25 years (1994–2018): status and

trends of late-successional and old-growth forests. Gen.

Tech. Rep. PNW-1004. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research

Station. 82 p. https://doi.org/10.2737/PNW-GTR-1004.

Dubayah, R.; Armston, J.; Healey, S.P.; Bruening, J.M.; 

Patterson, P.L.; Kellner, J.R.; Duncanson, L.; Saarela, 

S.; Ståhl, G.; Yang, Z.; Tang, H.; Blair, B.; Fatoyinbo, 

L.; Goetz, S.; Hancock, S.; Hansen, M.; Hofton, M.; 

Hurtt, G.; Luthcke, S. 2022. GEDI launches a new 

era of biomass inference from space. Environmental 

Research Letters. 17(9): 095001. 

https://doi.org/10.1088/1748-9326/ac8694. 

Lu, J.; Huang, C.; Tao, X.; Gong, W.; Schleeweis, 

K. 2022. Annual forest disturbance intensity mapped

using Landsat time series and field inventory data for

the conterminous United States (1986–2015). Remote

Sensing of Environment. 275: 113003.

https://doi.org/10.1016/j.rse.2022.113003.

Rishmawi, K.; Huang, C.; Schleeweis, K.; Zhan, X. 

2022. Integration of VIIRS observations with GEDILidar measurements to monitor forest structure dynamics 

from 2013 to 2020 across the conterminous United 

States. Remote Sensing. 14: 2320. 

https://doi.org/10.3390/rs14102320.

Shang, R.; Zhu, Z.; Zhang, J.; Qiu, S.; Yang, Z.; Li, 

T.; Yang, X. 2022. Near-real-time monitoring of land 

disturbance with harmonized Landsats 7-8 and Sentinel-2 

data. Remote Sensing of Environment. 278: 113073. 

https://doi.org/10.1016/j.rse.2022.113073.

Strunk, J.L.; Bell, D.M.; Gregory, M.J. 2022. Pushbroom 

photogrammetric heights enhance state-level forest 

attribute mapping with Landsat and environmental 

gradients. Remote Sensing. 14(14): 3433. 

https://doi.org/10.3390/rs14143433.

Wulder, M.A.; Roy, D.P.; Radeloff, V.C.; Loveland, T.R.; 

Anderson, M.C.; Johnson, D.M.; Healey, S.; Zhu, Z.; 

Scambos, T.A.; Pahlevan, N.; Hansen, M.; Gorelick, 

N.; Crawford, C.J.; Masek, J.G.; Hermosilla, T.; 

White, J.C.; Belward, A.S.; Schaaf, C.; Woodcock, 

C.E.; Huntington, J.L.; Cook, B.D. 2022. Fifty years

of Landsat science and impacts. Remote Sensing of

Environment. 280: 113195.

https://doi.org/10.1016/j.rse.2022.113195.

Program Area Updates for FY22
Fiscal Year 2022 Business Report 39

Forest Ecosystem Health Indicators 

The purpose of collecting a suite of forest health indicators 

in FIA inventory is to quantify complex forest ecosystem 

processes. These indicators include crown condition, tree 

damage, tree mortality, DWM, vegetation profile, soil 

quality, lichen communities, nonnative invasive plants, 

regeneration and browse impacts, and fragmentation. At 

a minimum, each indicator is assessed on approximately 

7 percent of the standard plot grid with a set of national 

protocols that are “core” to the indicator program. The 

intensity of implementation varies by FIA region due to 

budget fluctuation and stakeholder interest.

Objectives 

1. Collect and publish health indicator data to FIADB

annually from each State and contribute indicator

analyses to FIA reports.

2. Provide research, technical assistance, and tool support

for health indicator data access and analyses conducted

by partners and users.

3. Develop health indicator data with BIGMAP and other

online digital tools to help facilitate better access and

utility and access for users.

4. Integrate FIA health indicator data with forest health

data from State and Federal programs.

FY 2022 Accomplishments and Milestones

• Caught up on a subset of pandemic-related delays in data

collection. Published around 25 percent of health indicator

data collected in 2021 to FIADB.

• Continued to conduct meaningful science, engage with

important partners such as the NFS and universities,

publish data and reports related to forest ecosystem health,

and assist users with data access and analysis.

• Deployed and maintained a variety of online tools that

provide interactive data visualizations focused on health

indicators; many other tools are in development (figure

18).

• Supported an integration team with broad membership

to increase communication between FIA and the Forest

Health Monitoring Program, improve data alignment and

dissemination, and develop integrated services for the

public.

Financial Status and Partners

Current funding: The collection of forest health indicators 

is part of the core function of the national FIA Program; 

no additional funds are allocated to this task. Some of the 

publications on this topic resulted from individually funded 

studies.

Figure 18. Development status of forest health indicator 

objectives.

Partnerships: State, local, and regional forestry agencies, 

universities, and many other Forest Service deputy areas, 

programs, and teams, including NFS, Forest Health 

Protection, Forest Health Monitoring, and FHAAST

FY 2022 Publications and Deliverables

Barker, J.S.; Gray, A.N.; Fried, J.S. 2022. The effects of 

crown scorch on post-fire delayed mortality are modified 

by drought exposure in California (USA). Fire. 5(1): 21. 

https://doi.org/10.3390/fire5010021.

Berdeen, J.B.; Nelson, M.D.; Zlonis, E.J.; Giudice, 

J.H. 2022. Temporal change in abundance of potential 

nesting cavities for wood ducks (Aix sponsa) in Northern 

Minnesota, United States. Frontiers in Forests and Global 

Change. 5: 967060. 17 p. 

https://doi.org/10.3389/ffgc.2022.967060.

Brandeis, T.; Turner, J.; Baeza-Castro, A.-A.; Brown, 

M.; Lambert, S. 2022. Assessing forest resource damage 

following natural disasters using national forest inventory 

plots: a case study of Hurricane Michael. Res. Pap. 

SRS-65. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southern Research Station. 30 p. 

https://doi.org/10.2737/SRS-RP-65. 

Cahoon, S.M.P.; Sullivan, P.F.; Gray, A.N. 2022. 

Interactions among wildfire, forest type and landscape 

position are key determinants of boreal forest carbon 

stocks. Journal of Ecology. 110(10): 2475–2492. 

https://doi.org/10.1111/1365-2745.13963.

Program Area Updates for FY22
40 Forest Inventory and Analysis

Edgar, C.B.; Westfall, J.A. 2022. Timing and extent 

of forest disturbance in the Laurentian Mixed Forest. 

Frontiers in Forests and Global Change. 5: 963796. 

https://doi.org/10.3389/ffgc.2022.963796.

Evans, M.E.K.; DeRose, R.J.; Klesse, S.; Girardin, M.P.; 

Heilman, K.A.; Alexander, M.R.; Arsenault, A.; Babst, 

F.; Bouchard, M.; Cahoon, S.M.P.; Campbell, E.M.; 

Dietze, M.; Duchesne, L.; Frank, D.C.; Giebink, C.L.; 

Gómez-Guerrero, A.; Gutiérrez García, G.; Hogg, 

E.H.; Metsaranta, J.; Ols, C.; Rayback, S.A.; Reid, A.;

Ricker, M.; Schaberg, P.G.; Shaw, J.D.; Sullivan, P.F.;

Villela GaytÁn, S.A. 2022. Adding tree rings to North

America’s national forest inventories: an essential tool to

guide drawdown of atmospheric CO2. BioScience. 72(3):

233–246. https://doi.org/10.1093/biosci/biab119.

Harris, L.B.; Woodall, C.W.; D’Amato, A.W. 2022. 

Increasing the utility of tree regeneration inventories: 

linking seedling abundance to sapling recruitment. 

Ecological Indicators. 145: 109654. 

https://doi.org/10.1016/j.ecolind.2022.109654.

Hessburg, P.F.; Charnley, S.; Gray, A.N.; Spies, T.A.; 

Peterson, D.W.; Flitcroft, R.L.; Wendel, K.L.; 

Halofsky, J.E.; White, E.M.; Marshall, J. 2021. 

Climate and wildfire adaptation of inland Northwest US 

forests. Frontiers in Ecology and the Environment. 20(1): 

40–48. https://doi.org/10.1002/fee.2408.

Jovan, S.; Haldeman, M.; Will-Wolf, S.; Dillman, K.; 

Geiser, L.; Thompson, J.; Stone, D.; Hollinger, J.

2021. National atlas of epiphytic lichens in forested 

habitats of the United States. Gen. Tech. Rep. PNW-986. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 96 p. 

https://www.fs.usda.gov/research/treesearch/63620.

Kondo, M.C.; Zuidema, C.; Moran, H.A.; Jovan, S.; 

Derrien, M.; Brinkley, W.; De Roos, A.J,; Philip Tabb, 

L. 2022. Spatial predictors of heavy metal concentrations

in epiphytic moss samples in Seattle, WA. Science of The

Total Environment. 825: 153801.

https://doi.org/10.1016/j.scitotenv.2022.153801.

Kralicek, K.; Barrett, T.M.; Ver Hoef, J.M.; Temesgen, 

H. 2022. Forests at the fringe: comparing observed

change to projected climate change impacts for five tree

species in the Pacific Northwest, United States. Frontiers

in Forests and Global Change. 5: 966953.

https://doi.org/10.3389/ffgc.2022.966953.

Lugo, A.E.; Smith, J.E.; Potter, K.M.; Marcano-Vega, 

H.; Kurtz, C.M. 2022. The contribution of nonnative 

tree species to the structure and composition of forests 

in the conterminous United States in comparison with 

tropical islands in the Pacific and Caribbean. Gen. Tech. 

Rep. IITF-54. Río Piedras, PR: U.S. Department of 

Agriculture, Forest Service, International Institute of 

Tropical Forestry. 81 p. 

https://doi.org/10.2737/IITF-GTR-54. 

McCune, B.; Yang, S.; Jovan, S.; Root, H.T. 2022. 

Climate and epiphytic macrolichen communities in 

the Four Corners region of the U.S.A. The Bryologist. 

125(1): 70–90. 

https://doi.org/10.1639/0007-2745-125.1.070.

Potter, K.M.; Riitters, K.H.; Guo, Q. 2022. Non-native 

tree regeneration indicates regional and national risks 

from current invasions. Frontiers in Forests and Global 

Change. 5: 966407. 

https://doi.org/10.3389/ffgc.2022.966407.

Smith, J.E.; Domke, G.M.; Woodall, C.W. 2022. 

Predicting downed woody material carbon stocks in 

forests of the conterminous United States. Science of the 

Total Environment. 803: 150061. 

https://doi.org/10.1016/j.scitotenv.2021.150061.

Woodall, C.W.; Fraver, S.; Oswalt, S.N.; Goeking, 

S.A.; Domke, G.M.; Russell, M.B. 2021. Decadal dead

wood biomass dynamics of coterminous US forests.

Environmental Research Letters. 16(10): 104034.

https://doi.org/10.1088/1748-9326/ac29e8.

Woodall, C.W.; Weiskittel, A.R. 2021. Relative density 

of United States forests has shifted to higher levels over 

last two decades with important implications for future 

dynamics. Science Report. 11: 18848. 

https://doi.org/10.1038/s41598-021-98244-w.

Woodbridge, M.; Keyser, T.; Oswalt, C. 2022. Stand 

and environmental conditions drive functional shifts 

associated with mesophication in eastern US forests. 

Frontiers in Forests and Global Change. 5: 991934. 

https://doi.org/10.3389/ffgc.2022.991934.

Online tools:

• National FIA Land Resources Explorer

• Northern Research Station Oak Mortality Dashboard

• Northern Research Station Wildland Urban Interface

Dashboard

• Alien Forest Pest Explorer

Program Area Updates for FY22
Fiscal Year 2022 Business Report 41

Urban Inventory

The purpose of urban FIA is to implement an annualized 

inventory of trees in urban settings that provides key data 

to assess the status and trends of urban trees and forests, 

including the services they provide, their health, and future 

risk from insects and disease. The goal is to survey 105 

iconic cities, and all Census-defined Urban Areas and Urban 

Cluster lands outside of cities and not currently in the FIA 

Nationwide Forest Inventory survey.

Links: 

• Urban FIA Program website and implementation map

• My City’s Trees app

• FIA Urban DataMart

Objectives

See figure 19.

FY 2022 Accomplishments and Milestones

Data collection: 

• Upgraded to Field Guide 9.2

• Developed and conducted virtual and face-to-face national

certification training

• Completed all remaining FY 2020/FY 2021 plots that were

postponed due to the COVID-19 pandemic

• Began data collection in five new cities and five new

States (figure 19)

Information management and data processing:

• Improved workflows with release of Universal Information

Management System (UNIMS) database 1.6.0

• Began data processing on all 2022 urban plot projects

(figure 20)

• Completed initial exploratory work on urban growth,

removal, and mortality (GRM) estimates

• Set up five new city and five new State urban plot projects

• Updated national city-level reporting template tables and

figures

• Set up 68 urban sample projects

• Started the approval process for population estimates in

Urban EVALIDator

Analysis:

• Continued work on six city-level reports

• Designed standard tables for annual reports

Financial Status and Partners

Current funding: Currently funded: $2,961,168; shortfall: 

$6,663,184; cooperator/added value: $390,913

FTEs: Estimated need for about 78 FTEs spread across 

multiple business models in each FIA region at full 

implementation

Farm Bill request: Total estimated cost: $9,624,352 

Partnerships: Texas A&M Forest Service; Maine Forest 

Service; New Jersey Forest Service; Wisconsin Department 

of Natural Resources; Minnesota Department of Natural 

Resources; University of New Hampshire; City of Portland, 

OR; Davey Tree Expert Company; Washington, DC, Urban 

Forestry Division; Missouri Department of Conservation

Figure 19. Status of implementing urban inventories.

FY = fiscal year.

Figure 20. Status and availability of urban inventory data and 

reports urban inventories.

Program Area Updates for FY22
42 Forest Inventory and Analysis

FY 2022 Publications and Deliverables

• Completed a full cycle of data collection for seven

cities (Des Moines, IA; Madison and Milwaukee, WI;

Baltimore, MD; Minneapolis, MN; Portland, OR; and

Providence, RI). Data are currently being processed.

• Added Washington, DC, to the My City’s Trees app.

• Added Portland, OR, and Springfield, St. Louis, and

Kansas City, MO, to the Urban DataMart.

i-Tree 

The mission of i-Tree is to provide a state-of-the-art, 

peer-reviewed software suite that provides urban and rural 

forestry analysis and benefits assessment tools. These tools 

allow people from around the world the ability to assess 

and quantify the values provided by their local trees and 

forests, as well as risks to forest health. Since 2006, there 

have been almost 420,000 users in 149 countries (figure 21). 

These tools form the foundation for conversations about tree 

equity and environmental justice. The primary focus of the 

program is to provide user-supported tools promoting the 

latest science in support of managing urban forests and the 

communities that depend on the benefits that these forests 

provide.

i-Tree software suite: https://www.itreetools.org/

Objectives

1. Lead in the delivery of tools supported by the latest

science that will continue to drive, promote, and support

the tree equity and environmental justice conversation

and associated programs while serving as the

international urban forest management standard.

2. Enhance customer service by expanding the existing

user base at the local level, enabling potential users to

advocate for their local urban forests from where they

are regardless of their level of familiarity of urban forest

science. Tool design, delivery, and output will meet the

needs of both new and experienced users.

3. Provide free user support and develop free training

to enhance tool usability for all users regardless of

background and experience.

FY 2022 Accomplishments and Milestones

Accomplishments:

• Planned and delivered three International i-Tree Town Hall

listening sessions

• Developed and signed a new 5-year memorandum of

understanding with the Davey Tree Expert Company,

including a signing ceremony with Forest Service Chief

Randy Moore

• Released the OurTrees Tool—a quick “go to your phone

and get answers about your community” tool for tree

canopy assessment

• Consolidated tools to six core Individual Tree and Canopy

Assessment tools, ranked from easy to advanced

• Made major performance improvements in i-Tree Eco

with the changeover to SQLite, including faster, better

installation behavior and the ability to handle much bigger

tree inventory datasets (several hundred thousand trees

now)

• Made large amounts of back-end improvements on all the

web tools for increased performance and stability

Figure 21. Growth in i-Tree tool users over time.

Program Area Updates for FY22
Fiscal Year 2022 Business Report 43

• Helped design and implement a data science camp

field day for Washington, DC, high school students in

collaboration with local nonprofit organizations

Current projects and next steps:

• Addition of Global Precipitation Model rainfall data to

i-Tree Eco to make up for poor weather data at various

locations around the globe (with forthcoming release)

• Addition of hydrological tree benefits to i-Tree Eco’s

Forecast module (with forthcoming release)

• Long-awaited i-Tree Eco Plot Importer (with forthcoming

release)

• Landscape performance improvements (with forthcoming

release)

• Continued development of a Stormwater Calculator Tool

• Continued development of a National Urban FIA reporting

template

• Continued implementation of suggestions from the 2022

i-Tree Town Hall listening sessions

• Expansion of the membership and role of the i-Tree

Executive Committee and further development of user

feedback loops

Financial Status and Partners

FY 2022 funding: $703,500 (FIA S&E)

Annual operational funds required: $850,000, plus the 

cost of application science and technical updates. Actual 

2022 funding received was $1,524,000 from Forest Service 

R&D and $100,000 for training from Forest Service State, 

Private, and Tribal Forestry, Urban and Community Forestry.

Farm Bill request: None

Partnerships: Davey Tree Expert Company, The Arbor Day 

Foundation, Society of Municipal Arborists, International 

Society of Arboriculture, Casey Trees, and State University 

of New York College of Environmental Science and 

Forestry. In FY 2022, funding support was also provided 

by the Great Lakes Restoration Initiative and the Korean 

National Institute of Forest Science. 

FY 2022 Publications and Deliverables

Cavender-Bares, J.M.; Nelson, E.; Meireles, J.E.; Lasky, 

J.R.; MitevaI, D.A.; Nowak, D.J.; Pearse, W.D.;

Helmus, M.R.; Zanne, A.E.; Fagan, W.F.; Mihiar,

C.; Muller, N.Z.; Kraft, N.J.B.; Polasky, S. 2022.

The hidden value of trees: quantifying the ecosystem

services of tree lineages and their major threats across the

continental US. PLOS Sustainability and Transformation.

1(4): e0000010.

https://doi.org/10.1371/journal.pstr.0000010.

Nowak, D., contributing author. 2022. Urban systems 

and other settlements. In: Lwasa, S.; Seto, K.C.; Bai, 

X.; Blanco, H.; Gurney, K.R.; Kılkış, Ş.; Lucon, O.; 

Murakami, J.; Pan, J.; Sharifi, A.; Yamagata, Y. 

IPCC, 2022: Climate change 2022: mitigation of climate 

change. Contribution of Working Group III to the Sixth 

Assessment Report of the Intergovernmental Panel on 

Climate Change [P.R. Shukla et al., eds.]. Cambridge, 

UK, and New York: Cambridge University Press: 

861–952. https://doi.org/10.1017/9781009157926.010. 

Lagrosa, J.J.; Zipperer, W.C.; Andreu, M.G. 2022. 

An ecosystem services-centric land use and land cover 

classification for a subbasin of the Tampa Bay Watershed. 

Forests. 13(5): 745. https://doi.org/10.3390/f13050745.

Meléndez-Ackerman, E.J.; Pérez, M.E.; Pou, A.B.; 

Caballero, E.C.; Cortés, L.; Bonilla-Duarte, S.; Bauer, 

G.; Martínez Guridy, J.M.; Arendt, W.J.; Nowak, D.J. 

2022. A social-ecological approach to studying variation 

in urban trees and ecosystem services in the National 

Municipal District of Santo Domingo, Dominican 

Republic. Frontiers in Sustainable Cities. 3: 764073. 

https://doi.org/10.3389/frsc.2021.764073.

Nowak, D.J.; Ellis, A.; Greenfield, E.J. 2022. The 

disparity in tree cover and ecosystem service values 

among redlining classes in the United States. Landscape 

and Urban Planning. 221: 104370. 

https://doi.org/10.1016/j.landurbplan.2022.104370. 

Nowak, D.J.; Greenfield, E.J.; Ellis, A. 2022. Projecting 

urban forest threats across the conterminous United 

States. Journal of Forestry. 120(6): 676–692. 

https://doi.org/10.1093/jofore/fvac019.

Ramon, M.; Ribeiro, A.P.; Theophilo, C.Y.S.; Moreira, 

E.G.; Barbosa de Camargo, P.; Pereira, C.A.B.;

Saraiva, E.F.; Tavares, A.R.; Dias, A.G.; Nowak, D.;

Ferreira, M.L. 2022. Assessment of four urban forest

as environmental indicator of air quality: a study in a

Brazilian megacity. Urban Ecosystems. 26: 197–207.

https://doi.org/10.1007/s11252-022-01296-7.

Program Area Updates for FY22
44 Forest Inventory and Analysis

National Resource Use Monitoring

The mission of the national resource use monitoring program 

(formerly known as the timber products monitoring portfolio) 

is to deliver a nationally consistent program that collects, 

processes, and reports timber products output (TPO) and harvest 

utilization (HU) data. The effort includes data related to harvests 

for industrial products, logging and mill residue, residential 

fuelwood, and other removals.

The TPO surveys gather information from primary woodprocessing facilities to quantify the use of roundwood and mill 

residue by geographic location, tree species, and timber product 

type. 

The HU studies collect data at active logging sites to identify 

the tree species, tree size, and primary product destination of 

the volume removed, as well as the felled volume left onsite 

(logging residue).

Objectives

1. Annual TPO:

a. Implement an annual sample design across all

participating States (figure 22).

b. Enhance the national compilation system to adapt to 

the sample design.

c. Develop a strategy to improve residential fuelwood 

estimates.

2. Data accessibility:

a. Develop TPO data and analysis tools to replace the 

legacy TPO data retrieval system.

b. Develop a national factsheet series.

FY 2022 Accomplishments and Milestones

• All FIA regions are collecting mill data on an annual basis

using national sample design.

• A tool replacing the legacy TPO data retrieval system is 

functional and available at TPO Data Reporting Tool.

• A proposal was submitted requesting language indicating

confidentiality of FIA’s mill survey data in the next Farm Bill.

• Analysis of survey item nonresponse was submitted for 

publication.

Financial Status and Partners

FTEs: 11.45 (8 SRS, 3 NRS, and 0.45 PNW and RMRS) and 

9.5 (external cooperators)

Partnerships: University of Montana, Bureau of Business and 

Economic Research (joint venture agreement for PNW and 

RMRS program); University of Massachusetts Amherst (NRS 

mill data collection); and multiple State forestry agencies across 

southern and northern regions (assisting with data collection)

Figure 22. Development status of timber products monitoring 

objectives.

TPO = timber products output.

FY 2022 Publications and Deliverables

Hayes, S.W.; Townsend, L.; Dillon, T.; Morgan, T.A.; 

Shaw, J.D. 2021. Montana’s forest products industry 

and timber harvest, 2018. Resour. Bull. RMRS-35. Fort 

Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station. 54 p. 

https://doi.org/10.2737/RMRS-RB-35. 

Marcille, K.C.; Berg, E.C.; Morgan, T.A.; Christensen, 

G.A. 2021. Alaska’s forest products industry and 

timber harvest, 2015: part 1–4. Resour. Bull. PNW-271. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 45 p. 

https://www.fs.usda.gov/research/treesearch/63556.

Simmons, E.A.; Marcille, K.C.; Lettman, G.J.; Morgan, 

T.A.; Smith, D.C.; Rymniak, L.A.; Christensen, G.A.

2021. Oregon’s forest products industry and timber

harvest 2017 with trends through 2018. Gen. Tech.

Rep. PNW- 997. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research

Station. 63 p.

https://www.fs.usda.gov/research/treesearch/63436.

Simmons, E.A.; Berg, E.C.; Morgan, T.A.; Hayes, S.W.; 

Christensen, G.A. 2022. Logging utilization in Alaska, 

2016–2019. Resour. Bull. PNW-272. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 21 p. 

https://doi.org/10.2737/PNW-RB-272. 

Winn, M.F.; Gray, J.A.; Cooper, J.A.; Bentley, J.W. 

2022. Southern pulpwood production, 2020. Resour. Bull. 

SRS-234. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southern Research Station. 13 p. 

https://doi.org/10.2737/SRS-RB-234. 

Program Area Updates for FY22
Fiscal Year 2022 Business Report 45

“Timber Product Output and Use” factsheets: 

Alabama, 2020 (Resource Update FS-346;

https://doi.org/10.2737/FS-RU-346)

Arkansas, 2020 (Resource Update FS-347; 

https://doi.org/10.2737/FS-RU-347) 

Florida, 2020 (Resource Update FS-348;

https://doi.org/10.2737/FS-RU-348) 

Georgia, 2020 (Resource Update FS-349; 

https://doi.org/10.2737/FS-RU-349) 

Kentucky, 2020 (Resource Update FS-350; 

https://doi.org/10.2737/FS-RU-350) 

Louisiana, 2020 (Resource Update FS-351; 

https://doi.org/10.2737/FS-RU-351) 

Mississippi, 2020 (Resource Update FS-352; 

https://doi.org/10.2737/FS-RU-352)

North Carolina, 2020 (Resource Update FS-353; 

https://doi.org/10.2737/FS-RU-353) 

Oklahoma, 2020 (Resource Update FS-354; 

https://doi.org/10.2737/FS-RU-354) 

South Carolina, 2020 (Resource Update FS-355; 

https://doi.org/10.2737/FS-RU-355) 

Tennessee, 2020 (Resource Update FS-356; 

https://doi.org/10.2737/FS-RU-356) 

Virginia, 2020 (Resource Update FS-357; 

https://doi.org/10.2737/FS-RU-357) 

Data Delivery: TPO toolkit 

(https://www.fs.usda.gov/research/programs/nrum) 

updated with southern 2020 data.

National Woodland Owner Survey

The purpose of the NWOS is to advance the science, 

monitoring, and reporting of private forest ownerships across 

the United States by quantifying:

• Who owns the forests of the United States

• Why they own them

• How they have used them in the past

• What they intend to do with them in the future

The NWOS conducts separate surveys or modules for 

family forest ownerships, corporate forest ownerships, urban 

landowners, and forest ownerships on U.S. protectorates and 

territories.

National, regional, and State summaries of family forest 

(10+ acres) ownership characteristics: 

https://www.fia.fs.usda.gov/nwos/results

NWOS Dashboard: 

https://www.fs.usda.gov/research/programs/fianwos#pubs

Objectives

1. Plan and develop the NWOS based on stakeholder input.

2. Implement all NWOS modules in an effective and

efficient manner.

a. Base: 10,000 contacts per year across the United

States.

b. Corporate: Census of large corporate forest owners

once every 5 years.

3. Distribute the results of the NWOS through

presentations, publications, online tools, and responses to

individual stakeholders.

FY 2022 Accomplishments and Milestones

1. Planning and development:

a. Convened national user group meeting

b. Submitted Office of Management and Budget

review package for next iteration

2. Implementation:

a. No landowners contacted due to review process

and printing delays; missed landowners will be

contacted in FY 2023

b. Processed data for landowners contacted in FY

2021

3. Distribution:

a. Published reports and online tool for last full

iteration of base module

b. Initial reports from current iterations of the base,

urban, and islands modules underway

c. Wrote numerous journal articles, delivered

presentations, and fulfilled stakeholder requests

Financial Status and Partners

Current funding: $650,000 (Forest Service)

FTEs: Two Forest Service and three external cooperators

Farm Bill request: $3.1 million per year (includes full 

implementation of modules listed above plus urban, islands, 

Tribal, and public modules)

Selected partnerships: American Forest Foundation, 

Harvard Forest, NCASI, Society of American Foresters, 

State forestry agencies, University of Massachusetts Amherst

Program Area Updates for FY22
46 Forest Inventory and Analysis

FY 2022 Publications and Deliverables

Butler, B.J.; Butler, S.M.; Floress, K. 2023. Studies of 

family forest owners in the USA: a systematic review of 

literature from 2000 through 2019. Small-scale Forestry. 

22: 1–35. https://doi.org/10.1007/s11842-022-09529-5.

Butler, B.J.; Caputo, J.; Henderson, J.D.; Pugh, S.A.; 

Riitters, K.; Sass, E.M. 2022. An assessment of the 

sustainability of family forests in the U.S.A. Forest 

Policy and Economics. 142: 102783. 

https://doi.org/10.1016/j.forpol.2022.102783.

Butler, B.J.; Caputo, J.; Henderson, J.D.; Pugh, 

S.; Riitters, K.; Sass, E.M. 2022. Cross-boundary 

sustainability: assessment across forest ownership 

categories in the conterminous USA using the Montréal 

Process Criteria and Indicators framework. Forests. 

13(7): 992. https://doi.org/10.3390/f13070992.

Hollins, K.; Chawla, P.; Butler, S.M. 2023. Social 

marketing works: results from ten years of tools for 

engaging landowners effectively trainings. Journal of 

Forestry. 121(1): 84–94. 

https://doi.org/10.1093/jofore/fvac029. 

Sass, E.M.; Caputo, J.; Butler, B.J. 2022. United States 

family forest owners’ awareness of and participation in 

carbon sequestration programs: initial findings from the 

USDA Forest Service National Woodland Owner Survey. 

Forest Science. 68(5–6): 447–451. 

https://doi.org/10.1093/forsci/fxac026.

Shanafelt, D.W.; Caputo, J.; Abildtrup, J.; Brett, B.J. 

2022. If a tree falls in a forest, why do people care? An 

analysis of private family forest owners’ reasons for 

owning forest in the United States National Woodland 

Owner Survey. Small-scale Forestry. 22: 303–321. 

https://doi.org/10.1007/s11842-022-09530-y.

National Inventory and Monitoring 

Applications Center

The National Inventory and Monitoring Applications Center 

(NIMAC) is responsible for providing technical assistance 

on all aspects of forest inventory for FIA, as well as NFS, 

Federal agencies, State governments, and other countries. 

Inventory and monitoring goals are accomplished through 

development of leading-edge forest ecosystem monitoring 

methods and tools designed for use by land managers across 

ownerships at landscape to national scales.

Objectives

1. Continue maintenance of DATIM.

2. Provide technical assistance, annual data processing, and

analytical tool support for forest inventories conducted

by State and Federal agencies.

3. Conduct research and technology transfer that benefits

forest inventory and monitoring efforts around the

globe across various spatial scales and diverse ranges of

objectives.

FY 2022 Accomplishments and Milestones

• Design and Analysis Toolkit for Inventory and

Monitoring (DATIM): The National Forest System was

unable to continue funding DATIM in FY 2022. FIA 

continued to fund NIMAC for the ongoing maintenance

and further development of DATIM in FY 2022 (figure

23). DATIM allows users to create custom, static analyses

that can then be tailored by adding spatial attributes using

geographic information system (GIS) software. Those

spatial attributes can then be incorporated into analytical

queries. In FY 2022, version 17.0 was the most recent

release, with subsequent versions already planned for

release early in FY 2023. DATIM is publicly available at:

www.fs.usda.gov/emc/rig/DATIM/index.shtml.

• State and Federal agency forest inventory technical

assistance: NIMAC assisted three State-sponsored annual

forest inventories (Indiana, Wisconsin, and Missouri)

and forest inventory projects on 22 DOI U.S. Fish and

Wildlife Service refuges. NIMAC also had representation

on the Pennsylvania State forest land Continuous Forest

Inventory review/redesign committee.

• Research: NIMAC completed a number of forest

inventory and monitoring research projects during FY

2022 (see publications below).

Figure 23. Development status of NIMAC objectives.

DATIM = Design and Analysis Toolkit for Inventory and Monitoring; NIMAC = 

National Inventory and Monitoring Applications Center. 

Program Area Updates for FY22
Fiscal Year 2022 Business Report 47

Financial Status and Partners

Current funding: $56,000 (external sources)

Partnerships: NFS; U.S. Fish and Wildlife Service; 

Wisconsin Department of Natural Resources; Indiana 

Department of Natural Resources; Missouri Department of 

Conservation; SilvaCarbon; Forest Service International 

Programs; University of Nevada, Las Vegas; Southern Utah 

University

FY 2022 Publications and Deliverables

DATIM versions 15.1, 16.0, 16.1, and 17.0 were released 

during FY 2022.

Dettmann, G.T.; MacFarlane, D.W.; Radtke, P.J.; 

Weiskittel, A.R.; Affleck, D.L.R.; Poudel, K.P.; 

Westfall, J. 2022. Testing a generalized leaf mass 

estimation method for diverse tree species and climates 

of the continental United States. Ecological Applications. 

32(7): e2646. https://doi.org/10.1002/eap.2646.

Edgar, C.B.; Westfall, J.A. 2022. Timing and extent 

of forest disturbance in the Laurentian Mixed Forest. 

Frontiers in Forests and Global Change. 5: 963796. 

https://doi.org/10.3389/ffgc.2022.963796.

Lamb, R.; Hurtt, G.C.; Boudreau, T.J.; Campbell, E.; 

Sepúlveda Carlo, E.A.; Chu, H.-H.; de Mooy, J.; 

Dubayah, R.O.; Gonsalves, D.; Guy, M.; Hultman, 

N.E.; Lehman, S.; Leon, B.; Lister, A.J.; Lynch, C.;

Ma, L.; Martin, C.; Robbins, N.; Rudee, A.; Silva,

C.E.; Skoglund, C.; Tang, H. 2021. Context and future

directions for integrating forest carbon into sub-national

climate mitigation planning in the RGGI region of the

U.S. Environmental Research Letters. 16: 063001.

https://doi.org/10.1088/1748-9326/abe6c2.

Ma, L.; Hurtt, G.; Tang, H.; Lamb, R.; Campbell, E.; 

Dubayah, R.; Guy, M.; Huang, W.; Lister, A.; Lu, 

J.; O’Neil-Dunne, J.; Rudee, A.; Shen, Q.; Silva, 

C. 2021. High-resolution forest carbon modeling for

climate mitigation planning over the RGGI region, USA.

Environmental Research Letters. 16(4): 045014.

https://doi.org/10.1088/1748-9326/abe4f4.

Ma, L.; Hurtt, G.C.; Tang, H.; Lamb, R.; Campbell, E.; 

Dubayah, R.O.; Guy, M.; Huang, W.; Lu, J.; Rudee, 

A.; Shen, Q.; Silva, C.E.; Lister, A.J. 2022. Forest 

aboveground biomass and carbon sequestration potential, 

northeastern USA. Oak Ridge, TN: Oak Ridge National 

Laboratory, Distributed Active Archive Center for 

Biogeochemical Dynamics. 

https://doi.org/10.3334/ORNLDAAC/1922.

Westfall, J.A.; Coulston, J.W.; Gray, A.N.; Shaw, 

J.D. 2022. Biomass increases in U.S. forests as FIA 

implements new tree volume, biomass, and carbon

models. Forestry Source. 27(8): 14.

Westfall, J.A. 2022. An estimation method to reduce 

complete and partial nonresponse bias in forest inventory. 

European Journal of Forest Research. 141: 901–907. 

https://doi.org/10.1007/s10342-022-01480-6.

Westfall, J.A.; Coulston, J.W. 2022. Estimating change in 

annual timber products output using a stratified sampling 

with certainty design. Environmental and Ecological 

Statistics. 29(2): 415–431. 

https://doi.org/10.1007/s10651-022-00533-8.

Westfall, J.A.; Edgar, C.B. 2022. Addressing nonresponse 

bias in urban forest inventories: an estimation approach. 

Frontiers in Forests and Global Change. 5: 895969. 

https://doi.org/10.3389/ffgc.2022.895969.

Westfall, J.A.; Schroeder, T.A.; McCollum J.M.; 

Patterson, P.L. 2022. A spatial and temporal assessment 

of nonresponse in the national forest inventory of the 

U.S. Environmental Monitoring and Assessment. 194: 

530. https://doi.org/10.1007/s10661-022-10219-0.

Westfall, J.A.; Wilson, B.T. 2022. Nonresponse bias in 

change estimation: a national forest inventory example. 

Forestry 95(3): 301–311. 

https://doi.org/10.1093/forestry/cpab056.

Zhao, D.; Lynch, T.; Westfall, J.A.; Coulston, J.W. 2022. 

Additional biomass estimation alternatives: nonlinear 

two- and three-stage least squares and full information 

maximum likelihood for slash pine. Canadian Journal of 

Forest Research. 52(5): 780–793. 

https://doi.org/10.1139/cjfr-2021-0335.

Digital Engagement

The mission of the digital engagement portfolio is to 

radically reorient analysis, reporting, and delivery through:

• Deep collaboration with agency and external partners

and stakeholders to develop and publish relevant and

authoritative data supporting their identified needs

• Analytical and reporting application development

relying upon commercial off-the-shelf (COTS) solutions

that leverage agency and partner competencies and

investments, reduce development times, and increase the

potential for collaboration

• Deployment of a secure cloud computing environment

providing scalable resources necessary to store, process,

and share analyses conducted at national scales

Program Area Updates for FY22
48 Forest Inventory and Analysis

Objectives

1. Place the Analytics and Decision Support (ADS) on a

permanent CIO funding line.

2. Continue push for flexible computing, decision-support,

and reporting technologies.

3. Leverage cooperating research and development

agreement (CRADA) with Esri for content and

application production.

4. Set direction and deploy diverse national reporting

applications.

5. Develop the next version of the national One-Click

reporting application.

6. Drive innovation in national tabling tools.

7. Continue collaboration across portfolios.

8. Update 2018 BIGMAP raster data products.

9. Identify new partners for continued build-out of issuefocused applications.

10. Finalize new blanket purchasing agreement with Esri to

support ongoing digital engagement priorities.

FY 2022 Accomplishments and Milestones

• Moved BIGMAP (pilot project) to full production in an

FIA- and CIO-managed cloud environment (analytical

decision support or ADS) (figure 24)

• Received Director’s Award for “Making a Significant

Research Contribution in the Inventory and Monitoring

Sciences”

• Formally established digital engagement science team in

NRS FIA within the Information Management section

• Formally established digital engagement science team in

SRS FIA within the Analysis Resources section

• Delivered multiple contributed and invited presentations at

the Esri International User Conference

• Delivered high-quality raster products to the Esri Living Atlas

of the World—the premiere repository for geospatial data

• Completed multiple digital 5-year State reports

• Aided in identifying and resolving 30+ software bugs in

Esri core and Esri Raster Analytics software

• Developed TPO BIGMAP Wood Flow dashboard

• Funded and hired a post-doctoral researcher to work

across SRS research work units on BIGMAP and REGEN

modeling work

• Developed Small Area Estimation GeoSpatial Toolbox

Note: Some links currently require login credentials, so 

demonstrations are available upon request.

Figure 24. Status of digital engagement portfolio milestones.

Financial Status and Partners

Current funding: Over $1 million, including $500,000 

invested in the BIGMAP environment, $443,000 in 

universities, and $125,000 in GTAC. These investments 

continue to support partners and stakeholders, including:

• FIA analysts, who improve the technical capacity for

raster data processing and reporting

• Agency stakeholders, who access the authoritative

geospatial raster data for forest planning

• External partners, who use high-profile tools supporting

sustainability assessments by multinational brands (e.g.,

Mars, McDonald’s) and their forest products supply chains

Additional resources would expand capacity to implement 

these promising products and the rate of delivery. 

FTEs: A total of 11 Forest Service employees, including 5 

scientists and 6 technical experts

Partners: Esri, Purdue University, Virginia Tech, The 

Wilderness Society, Harvard Forest, Locana, Xentity 

Corporation, Forest Service FHAAST, GTAC, Forest Service 

Center for Forest Restoration and Management 

FY 2022 Publications and Deliverables

Perry, C.H.; Finco, M.V.; Wilson, B.T., eds. 2022. Forest 

atlas of the United States. FS-1172. Washington, DC: 

U.S. Department of Agriculture, Forest Service. 54 p. 

https://www.fs.usda.gov/research/treesearch/64468. 

One-Click factsheets:

• 36 annual State factsheets published in SRS and NRS

• 36 sets of annual tables published in SRS and NRS

• 12 annual TPO State factsheets published in SRS and NRS

• 12 sets of TPO annual tables published in SRS and NRS

• Bourbon Barrel Oak Availability tool

Program Area Updates for FY22
Fiscal Year 2022 Business Report 49

• The Mysteries of Bourbon: How Forestry, Mapping

Support a Changing Industry (Esri blog post on Bourbon

Barrel Oak Availability tool)

• Discover White Oak Suitability with the Bourbon Barrel

Oak Availability Tool (ArcGIS blog post on tool use)

Community Engagement

The purpose of the community engagement team is to 

facilitate efficiency through increased communication, 

product sharing, and collaboration between units, and 

to maintain relevancy by showcasing FIA products both 

internally and externally. Additionally, the team makes 

concerted efforts to outreach to and recruit diverse 

candidates for open positions. 

Objectives

• Increase internal communication by facilitating

information sharing between team members and via

newsletters and Microsoft Teams channel.

• Increase external communication by updating the national

website, increasing social media presence, and other

means.

• Showcase FIA products through social media posts and

informational videos.

Ongoing efforts include:

• Continue updates to the FIA Resource Center Microsoft

Teams channel to ensure its relevance and usefulness.

• Update content for the national FIA website.

• Continue outreach efforts to underserved communities for

diversity recruits.

• Continue to provide and increase social media content

reflecting FIA accomplishments (#USDA_FIA).

• Maintain and facilitate contact with station communication

shops.

• Update FIA staff and partners on the FIA Program through

a newsletter shared internally and on the national website.

FY 2022 Accomplishments and Milestones

• Communicated necessary information regarding updates

on the status of upcoming web modernization activities.

• Created an urgent notifications and bulletins alert on the

national FIA website to keep users updated on critical

changes and upcoming releases.

• Updated several factsheets (using new 508-compliant

factsheet template) to provide more timely and relevant

information within all factsheets available on the national

FIA website.

• Grew and increased use of the FIA Resource Center

Microsoft Teams channel.

• Updated the FIA outreach plan (i.e., communication plan)

by identifying issues and making suggestions to address

those issues.

• Reported on FIA engagement with the public and

opportunities for student engagement in the program.

• Provided necessary information internally regarding

national issues moving through the change management

process.

• Began development of a national glossary of terms for the

national FIA website to improve user comprehension.

• Produced a monthly newsletter featuring FIA national

portfolios, program news, change management, and

community engagement events.

Financial Status and Partners

Current funding and capacity for FIA Program 

community engagement activities: No program funding is 

invested in this area or work other than the S&E of the team. 

FTEs: The time invested by the eight FIA members of this 

team is equivalent to one FTE. 

Spanning Cultures

FIA engagement with communities is a critical component 

to program success. FIA crews are based in rural, local, 

and/or Indigenous communities for months at a time. This 

requires the program to build critical relationships and draw 

a connection between data collected and community needs 

and priorities. The FIA Program has an ongoing citizen 

science component to help cultivate relationships between 

Indigenous communities and FIA crews, including FIA, 

State, and contracted personnel. FIA staff also coordinate 

with an array of partners to complete fieldwork and host a 

wide variety of community presentations at events, schools, 

and community centers, and via webinars.

Objectives

1. Outreach: Provide written materials (posters, brochures,

flyers) to community members to provide information

about FIA and updates on local project work.

2. Collaborate: Work closely with Tribal coalitions,

Tribes, and Alaska Native Corporations to understand

needs, share data, and access lands for field data

collection.

3. Engage: Increase engagement and communication with

Tribes and other Indigenous communities through the

activities of a national team consisting of Tribal liaisons

from each FIA region.

Program Area Updates for FY22
50 Forest Inventory and Analysis

FY 2022 Accomplishments and Milestones

• National FIA Tribal team continued to collaborate and

share across regions including welcoming new Tribal

liaisons to NRS and PNW and inviting them to team

meetings.

• Developed a plan for updated outreach materials

specifically for Indigenous communities and other Tribal

entities.

• Developed two sessions of Tribal-related topics for the

2022 FIA Science Stakeholder Meeting, including seven

talks that touched on using FIA data to support Tribal

management goals, sustainability of culturally important

forest products, and timber allotment assessment.

• Continued participating in the NFS Region 9 Tribal

Homelands Working Group.

• National Tribal team consisting of Tribal liaisons

from each FIA region continued to plan for increased

engagement and communication with Tribes and

other Indigenous communities. This team also began

coordinating with research station Tribal liaisons.

• Delivered summaries of the data collected from plots on

Tribal lands to numerous Tribes.

• Led conversations with the RMRS Tribal liaison to discuss

opportunities for future recruitment of Tribal members and

the development of analysis and reporting products that

meet the needs of Tribal foresters.

• Continued partnering with Pacific Islands local

governments in six culturally unique jurisdictions,

working with diverse staff that speak over nine different

languages.

• Continued ongoing partnership with the Tanana Chiefs

Conference to implement forest inventory in Interior

Alaska.

• Enhanced opportunities for interns and staff throughout

the Pacific Islands to build on their knowledge of forest

monitoring through a newly implemented joint venture

agreement with the Micronesia Conservation Trust.

• Successfully partnered with Tribes across the Nation to

grant access to FIA plots on Tribal lands. This included 6

entities in the Pacific Northwest, 20 in the North, 10 in the

South, and 23 in the Rocky Mountains.

Financial Status and Partners

Current funding: Core function of national FIA Program, 

so there is no separate funding. Deliverables listed below 

may have resulted from individually funded projects. 

Partnerships: Tanana Chiefs Conference, Pacific Islands 

local governments, Northern Tribal Homelands Working 

Group, Ojibwe Tribes of the Great Lakes, Bad River Tribe, 

Great Lakes Indian Fish & Wildlife Commission, Micronesia 

Conservation Trust, and DOI Bureau of Indian Affairs

Program Area Updates for FY22
Fiscal Year 2022 Business Report 51

FY 2023 Anticipated FIA Program Direction

An increase in Federal funding has allowed the FIA Program 

to make investments in increasing support for the TPO 

survey and small area estimation techniques and application 

development, as well as technological investments such as 

high-precision GPS and increased software development 

support. Since Forest Service R&D S&E allocations 

remained unchanged from 2022, much of the funding is 

being invested into existing and new agreements with States, 

universities, and other FIA stakeholders.

The FIA Program will continue inventory operations in all 

50 States as well as U.S. territories and affiliated islands with 

focus on continuing efforts to catch up on plot data collection 

due to delays incurred from the COVID-19 pandemic, 

natural disasters, hiring of employees, and contracting of 

plot measurement. FIA will take every advantage it can to 

use hiring authorities, participate in hiring events, and hire 

multiple positions (sometimes across more than one FIA 

unit) through single advertisements. FIA is standardizing 

position descriptions across FIA units to create efficiencies 

in hiring and ensure equitable pay across FIA units. It 

is expanding its outreach to contractors and developing 

factsheets for becoming a contractor for field data collection. 

Additionally, FIA field crews, both Federal and State, 

are traveling between units to complete priority plot 

measurements. By the end of 2023, all 2020 and 2021 plots 

and most 2022 field plots are anticipated to be completed. 

Other major activities planned for 2023 and beyond include: 

• Releasing FIA Tableau Dashboard which provides

semiannual reporting of many tables found in the annual

FIA Business Report

• Responding to the President’s Executive Order 14072

on Strengthening the Nation’s Forests, Communities,

and Local Economies with data, expertise, and analytics,

especially in collaboration with NFS to provide estimates

of old growth and mature forest on Federal land

• Continuing to modernize the program’s TPO data

management, operations, and reporting

• Continuing to develop user-friendly applications with

small area estimation techniques that will leverage access

to new computing libraries, including nationwide runs at

improved speed, automated reporting, and landscape-scale

biomass and carbon estimates

• Continuing to populate FIA Urban DataMart and My

City’s Trees applications as urban data become available

• Modernizing websites

• Increasing accessibility by ensuring FIA products are

508-compliant

Accomplishment of these goals will depend on the continued 

strong support from partners and their commitment to an 

efficient and productive FIA, and adequate funding for full 

program implementation.
52 Forest Inventory and Analysis

Long-Term Strategic Direction 

The FIA Program initially intended to implement the 

“Strategic Plan for Forest Inventory and Analysis” by 

achieving a base Federal program of sampling 10 percent 

of forested base plots per year in the West and 15 percent 

per year in the East by FY 2003. In late 2013, FIA drafted 

a new strategic plan to update the 2007 plan, in response 

to the 2014 Farm Bill and its requirements for FIA. This 

strategic plan was delivered to the agency and USDA in 

mid-2014, with a final submission delivered to Congress 

in March 2015. The FIA strategic plan was developed in 

cooperation with partners and stakeholders and identifies the 

base program, potential enhancements to the base, priorities 

for new programs, and areas for increased flexibility in the 

future. Since the plan is now a decade old, FIA anticipates 

revising it soon.

Passage of the 2014 Farm Bill and FIA Requirements

On February 7, 2014, Congress passed the Agricultural Act 

of 2014 (Public Law 113–79), also referred to as the 2014 

Farm Bill. Section 8301 of this legislation required the FIA 

Program to revise its previous strategic plan, approved by 

Congress in 1999, and submit the new plan to the Committee 

on Agriculture of the House of Representatives and the 

Committee on Agriculture, Nutrition, and Forestry of the 

Senate within 180 days of the passage of the law.

Farm Bill provisions that were addressed in the revised 

(current) strategic plan:

1. Complete the transition to a fully annualized forest

inventory program and include inventory and analysis of

Interior Alaska.

2. Implement an annualized inventory of trees in urban

settings, including the status and trends of trees and

forests, and assessments of their ecosystem services,

values, health, and risk from pests and diseases.

3. Report information on renewable biomass supplies and

carbon stocks at the local, State, regional, and national

levels, including by ownership type.

4. Engage State foresters and other users of FIA 

information in reevaluating the list of core data

variables collected on FIA plots, with an emphasis on

demonstrated need.

5. Improve the timeliness of the TPO program and

accessibility of the annualized information on that

database.

6. Foster greater cooperation among the FIA Program,

research station leaders, State foresters, and other users

of FIA information.

7. Promote availability of and access to non-Federal

resources to improve information analysis and

information management.

8. Collaborate with the USDA Natural Resources

Conservation Service; NASA; U.S. Department

of Commerce, National Oceanic and Atmospheric

Administration; and DOI U.S. Geological Survey to

integrate remote sensing, spatial analysis techniques, and

other new technologies in the FIA Program.

9. Understand and report on changes in land cover and use.

10. Expand existing programs to promote sustainable

forest stewardship through increased understanding, in

partnership with other Federal agencies, of the more than

10 million private forest owners, their demographics,

and the barriers to forest stewardship.

11. Implement procedures to improve the statistical

precision of estimates at the sub-State level.

Passage of the 2018 Farm Bill, FIA Requirements, and 

Ongoing Implementation 

On December 11, 2018, Congress passed the 2018 Farm Bill. 

Section 8632 directed the FIA Program to find efficiencies 

through the improved use and integration of remote sensing 

technologies and to partner with States and interested 

stakeholders.

To comply with congressional direction, FIA scientists 

continue to investigate and develop promising techniques 

and applications of remote sensing for improving estimations 

of forest resources and collaborate with other researchers in 

the geospatial and remote sensing community. A long-term 

project called BIGMAP (Big Data, Mapping, and Analytics 

Platform), entered the full production phase, developed 

six major digital products, and will deliver FIA PlotMap, a 

single-plot imputation product that aids users to downscale 

the FIADB to a 30-m resolution in FY 2024. BIGMAP 

incorporates the capabilities of Esri Raster Analytics and 

ArcGIS Enterprise to support the integration of plot data and 

satellite data in order to add value to the FIA Program.

As the Federal nationwide lidar acquisition program (3D 

Elevation Program (3DEP), led by U.S. Geological Survey) 

continues to make progress toward a complete coverage for 
Fiscal Year 2022 Business Report 53

all land in the conterminous United States, FIA is supporting 

lidar collection and exploring how to best incorporate lidar 

data to improve estimation that has the potential to yield 

substantial benefits, especially in small area estimation of 

biomass and carbon. Additionally, the FIA Program seeks to 

capitalize on these resources along with photogrammetrically 

derived point clouds including NAIP-3D by extracting lidar 

point clouds over fuzzed FIA plots to facilitate new and 

ongoing research to develop tree canopy height products and 

to meet additional needs for characterizing forest structure, 

including recovery from disturbance and assessment of treesout-of-forest conditions.

Since 2016, FIA has supported and advanced a methodology 

designed to efficiently inventory the boreal forests of Interior 

Alaska, a region that occupies about 114 million acres. 

To increase the precision and efficiency of the inventory 

estimates, as mandated by Congress, the relatively sparse 

field plot sample (one plot every 30,000 acres rather than 

one plot every 6,000 acres as in the rest of the FIA base grid) 

was augmented with strip samples (covering 5 percent of 

the land area) of remotely sensed data collected from the 

G-LiHT integrated system. The airborne imaging system

comprises several sensors that combine lidar, hyperspectral

imaging spectroscopy, thermal imagery, and high-resolution 

multispectral imagery. G-LiHT allows for the mapping 

of composition, structure, and function of terrestrial 

ecosystems at high resolution. This is a significant step 

toward improving the use and integration of remote sensing 

technologies in the FIA Program. 

FIA continues to prioritize and enhance the collaboration 

with States, Tribes, Federal agencies, and universities to 

improve and efficiently provide assessment and analysis of 

fundamental information for the Nation’s forest resources 

and investments. The Government Performance and Results 

Act (GPRA) of 1993 directs Federal entities to develop longterm goals and performance measures to monitor progress 

toward those goals. Although intended for application at 

the agency level, the GPRA framework also provides an 

excellent tool for guiding progress for FIA. Table 6 shows 

key goals, performance measures, and benchmarks for the 

FIA Program for FYs 2013 through 2022 and targets for 

a fully implemented program. As discussed above, data 

collection, publishing of data, and subsequent analysis are 

behind due to data collection lags during the COVID-19 

pandemic.

Table 6. National performance measures of the FIA Program, FYs 2013–2022.

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Target

Goal Performance measure Percent 

Include 100 percent 

of U.S. forest lands 

in the FIA sample 

population

Percentage of Nation’s 

forest land included in the 

target FIA sample population

100 100 100 100 100 100 100 100 100 100 100 

Keep fieldwork 

current

Percentage of States actively 

engaged in the annualized 

inventory program

100 100 100 100 100 100 100 100 100 100 100 

Make data accessible 

to national forest 

customers

Percentage of national 

forest land for which FIA 

data are loaded into NRIS

100 100 100 100 100 100 100 100 100 100 100 

Keep analysis 

current

Percentage of States with 

FIA State report less than 6 

years old

88 90 94 96 96 96 90 94 88 75 100 

Keep online data 

current

Percentage of States with 

FIA data available online less 

than 2 years old

92 96 96 96 96 96 88 90 88 45 100 

Partners’ 

participation

Partners’ financial 

contributions expressed as 

percentage of total program 

funds

10 10 10 12 16 16 13 14 16 13 20 

FIA = Forest Inventory and Analysis; FY = fiscal year; NRIS = Natural Resource Information System.
54 Forest Inventory and Analysis

Portage Lake, Chugach National Forest, AK. USDA Forest Service photo by Tyra Olstad.
Fiscal Year 2022 Business Report 55

Conclusions

The FIA Program continues to operate in an era of 

partnership and collaboration in which Federal and State 

agencies and other cooperators and stakeholders work 

together to plan, manage, implement, and continually 

improve the program. FIA is gathering and disseminating 

information on a wide array of ecological attributes, while 

continuing to serve its traditional customers who require 

timely information on forest resources. FIA is increasing 

the timeliness of surveys and reporting to provide a 

continually updated, publicly accessible information base 

that includes meaningful reports, analyses, and elemental 

data for others to use. FIA is exploring and leveraging the 

latest technologies, including remote sensing, to expand the 

scope of its products and to deliver them more efficiently. 

As these annual business reports demonstrate, FIA is 

also openly reporting on financial information, progress, 

accomplishments, successes, and challenges.

In summary, the FIA Program is committed to working 

collaboratively with all partners to deliver the best program 

possible with the available resources. This report is intended 

to provide a transparent view of the business practices of the 

FIA Program, to help FIA improve business practices, and to 

provide information to partners to help improve the program 

with feedback.
56 Forest Inventory and Analysis

Glossary of Terms Used in Appendixes

■ base Federal FIA Program. A level of FIA program delivery

that includes sampling 10 percent of base grid (Phase 2) plots

per year in the Western United States and 15 percent of base

grid plots per year in the Eastern United States, with data

compiled and made available annually and complete State

analyses done every 5 years. A subsample of these plots also

provides data on key ecosystem health indicators.

■ base grid plots sampled. The base grid consists of one

sample location per approximately 6,000 acres (Phase 2), and

one location per approximately 96,000 acres provides data

on key ecosystem health indicators. Some partners chose to

intensify beyond the base grid.

■ buy down. Plots installed at State expense to reach

20-percent implementation level of the base grid. These plots

are referred to as “temporal acceleration” plots.

■ core reports. A class of publications that summarizes forest

status and trends for a complete administrative unit, such as a

whole State or a national forest. Examples include survey unit

reports, State statistical and analytical reports, and national

forest reports. Congressionally required 5-year State reports

are part of the FIA’s core reporting.

■ direct operational expenses. All expenses directly

attributable to the FIA unit incurred as a part of doing FIA 

business. Excludes indirect business costs (such as rent,

telephones, and administrative overhead outside the FIA unit

staff) and salary and related expenses. Includes work done for

other units as a normal part of FIA business and the following

items:

□ equipment:

▪ imagery. Aerial photos and satellite imagery data

files.

▪ vehicles. All vehicle costs, including items such as

operating costs, depreciation, and leases.

▪ field equipment. Measurement tools and equipment,

such as data recorders, carried by field crews.

▪ information technology/communications.

Additional computer hardware, software, and

communications costs.

▪ other. Any cost that does not fit into one of the

previous equipment categories.

□ publications. Costs for laying out, editing, printing, and

distributing publications.

□ grants and agreements. Cost of cooperative grants,

agreements, and contracts that directly support the FIA 

mission.

□ office space and utilities. Charges for rent, lease, or

other real estate costs for FIA staff, plus utilities.

□ other direct expenses. Any cost that does not fit into

one of the previous categories, including office supplies, 

postage, moving expenses, and other expenses related to 

delivering the FIA Program.

■ ecosystem indicators. Data collected on a subset of Phase

2 sample locations measured for a more extended set of

ecosystem attributes, including tree crown dieback, soil data,

and down woody debris.

■ forest land. Unless noted, this report uses the FIA definition

of forest land. The FIA Program defines forest land as:

Land at least 10-percent canopy cover by trees of any size,

including land that formerly had such tree cover and that will

be naturally or artificially regenerated. Forest land includes

transition zones, such as areas between heavily forested and

nonforested lands that are at least 10-percent canopy cover

with trees and forest areas adjacent to urban and builtup lands. Also included are pinyon-juniper and chaparral

areas in the West and afforested areas. The minimum area

for classification of forest land is 1 acre and 120 feet wide

measured stem to stem from the outermost edge. Unimproved

roads and trails, streams, and clearings in forest areas are

classified as forest if less than 120 feet wide.

The Resources Planning Act (RPA) Assessment defines forest

land as: Land at least 10-percent canopy cover by trees at

least 16.4 m high, or trees able to reach these thresholds in

situ, including land that formerly had such tree cover and

that will be naturally or artificially regenerated. Forest land

includes transition zones, such as areas between heavily

forested and nonforested lands that are at least 10-percent

canopy cover with trees and forest areas adjacent to urban and

built-up lands. The minimum area for classification of forest

land is 1 acre and 120 feet wide measured stem to stem from

the outermost edge. Unimproved roads and trails, streams,

and clearings in forest areas are classified as forest if less than

120 feet wide. This is the definition used for international

reporting.

■ FY (end-of-the-year) balance. Funds reported in the

previous fiscal year business report as unspent at the end of

that fiscal year and presumably available for use in the current

fiscal year.

■ intensification. Plots installed at the expense of State,

National Forest System, or other partner to achieve higher

quality estimates for smaller areas or to buy the base Federal

sample down to a 5-year cycle.

■ management meetings held. Number of national or regional

management team meetings held by each FIA unit. Each

regional management team consists of partners who share

in funding and implementing the FIA Program. The team

typically consists of representatives from the FIA unit; NFS

regional offices; State, Private, and Tribal Forestry offices;

and State forestry agencies.
Fiscal Year 2022 Business Report 57

■ NGO (nongovernmental organization). A class of

customers with whom FIA staff members are asked to

consult. Includes environmental organizations, professional

societies, and other, generally nonprofit, organizations.

■ NIPF (nonindustrial private forest landowners). Private

individuals or organizations that own forest land for purposes

other than industrial operations.

■ percentage of forested base grid plots sampled. Total

number of base grid plots sampled divided by the total

number of plots in the base grid. Set by Congress, the current

target in the East is 15 percent and 10 percent in the West.

■ percentage of full funding. Total available funds divided

by the funding needed to fully implement the base Federal

program for a given year’s target funding.

■ percentage of region covered by annual FIA. Sum of

forested acres in States currently implementing annual FIA,

divided by the total number of forested acres in each FIA 

region; a measure of the degree to which the FIA region has

moved from periodic to annual inventory.

■ publications. Number of publications per unit, by type

of publication, as reported in official agency attainment

reports. Publications are among the major outputs of the FIA 

Program. Types of publications include:

□ core report. A report pertaining to reporting inventory

results for a complete geographic entity. Includes the

following:

▪ national forest report. A complete analysis for a

single national forest.

▪ national report. A report for the entire Nation, such

as the Resources Planning Act Assessment report.

▪ regional report. A report for a group of States or

other contiguous unit larger than a single State, such

as a regional assessment.

▪ State resource report. A complete statistical or

analytical summary of the forested resources within

a single State.

▪ State timber products output (TPO) report. A 

complete analysis of TPO data for a single State.

▪ other. Publication that does not fit into any of the

previous categories, such as an abstract, book, or

other government publication.

■ other station publication. A manuscript published by the

Forest Service, for example, a general technical report.

■ peer-reviewed journal article. An article appearing in a

refereed or peer-reviewed journal.

■ proceedings paper. An article appearing in the proceedings

from a meeting or symposium.

■ salary. Includes direct salary, benefits, and related expenses,

broken into the following categories:

□ administration. Program manager, project leader, and

administrative staff.

□ data collection/QA. Staff who interpret photos and

high-resolution images to determine forested areas and

increase the efficiency of field work; collect, coordinate,

or support the collection of field data; and conduct

quality assurance (QA) control at least 50 percent of

their time.

□ information management. Forestry data managers and

data compilers with support staff to build data views

and analytical data queries.

□ analysis and research. Staff who analyze satellite

imagery for statistical stratification, analyze collected

field data, write publications, and conduct FIA-related

research on methods and techniques.

■ significant consultations. Cases in which an FIA staff person

spent at least 1 hour in discussion, analysis, or research to

address a specific question or need raised by an external

FIA Program customer, and which is not part of the normal

course of business in collecting, analyzing, and reporting FIA 

information.

■ spatial intensification. Additional plot locations added to

increase the number of plots sampled per unit area.

■ temporal acceleration. Additional plots that are sampled

ahead of schedule to reduce the cycle length.

■ total available funds. Total funds available for delivering

the FIA Program, including funds appropriated by Congress

for the FIA Program, other funds made available by Forest

Service partners, and previous year carryover funds. These

funds are a measure of Federal funding for the base Federal

program.

■ travel. Broken into the following categories:

□ office travel. Travel costs for all staff except field and

QA crews.

□ field/quality assurance crew travel. Travel costs for

field and QA crews.

■ user group meetings held. Number of user group meetings

sponsored or attended by each FIA unit. A user group meeting

is an open meeting in which a complete regional cross section

of FIA partners and customers is invited to attend. User group

meetings differ from the usual smaller meetings with one

or two partners that all FIA units call as a normal course of

business.
58 Forest Inventory and Analysis

Appendix A: Contacts

For information about the status and trends of the Nation’s forests, please contact the appropriate office below.

Northern FIA Program

Program Manager, FIA

USDA Forest Service

Northern Research Station

1992 Folwell Avenue

☎ 651–649–5191

Rocky Mountain FIA Program

Program Manager, FIA

USDA Forest Service

Rocky Mountain Research Station

4919 S. 1500 W.

Riverdale, UT 84405

☎ 801–625–5464

Southern FIA Program

(includes Commonwealth of

Puerto Rico and the U.S. Virgin Islands)

Program Manager, FIA

USDA Forest Service

Southern Research Station

4700 Old Kingston Pike

Knoxville, TN 37919

☎ 865–862–2000

Pacific Northwest FIA Program

Program Manager, RMA (FIA)

USDA Forest Service

Pacific Northwest Research Station

1220 SW 3rd Avenue, Suite 1410

Portland, OR 97204

☎ 971–280–0858

National FIA Program Office

National Program Leader, FIA

USDA Forest Service

201 14th Street, SW

Washington, DC 20250

☎ 703–605–4177

All regional FIA websites and a wealth of statistical and 

other information are available through the national FIA 

website at www.fs.usda.gov/research/programs/fia. 

Figure A-1. FIA regional units and headquarters.

FIA = Forest Inventory and Analysis.

The Pacific Northwest FIA unit also includes American Samoa, Guam, Republic of Palau, Commonwealth of the Northern Mariana Islands, Federated States of 

Micronesia, and Republic of the Marshall Islands. The Southern FIA unit also includes the Commonwealth of Puerto Rico and the U.S. Virgin Islands.
Fiscal Year 2022 Business Report 59

Appendix B: Additional Data Tables

Table B-1. Performance measures for the FY 2022 FIA Program.

Table B-2a. Federal funds received by the FIA Program to pay for salary and expenses, FY 2022.

Table B-2b. Financial statement for FIA operational funds, FY 2022.

Table B-3a. Federal staffing, in full-time equivalent (FTE) hours, for the FY 2022 FIA Program.

Table B-3b. Estimate of cooperator staffing, in full-time equivalent (FTE) hours, funded by FIA grants and agreements 

for the FY 2022 FIA Program.

Table B-3c. Estimated total federally funded staffing, in full-time equivalent (FTE) hours, for the FY 2022 FIA Program.

Table B-4. Partner contributions toward implementing FIA in FY 2022.

Table B-5. Grants and agreements entered into by FIA units, FY 2022.

Table B-6. Number and hours of significant FIA staff consultations by customer group, FY 2022.

Table B-7. FIA data access by online tools and Spatial Data Services team requests, FYs 2013–2022.

Table B-8. Mill, fuelwood, and ownership surveys processed and utilization sites visited, FYs 2013–2022. 

Table B-9. Forest health indicator, year of initiation, and number of plots sampled, FYs 2013–2022. 

Table B-10. Status of FIA surveys in U.S. islands and territories, FY 2022.

Table B-11. State-level summary of land and forest area, years for the most recent available FIA data and 5-year State 

reports, and length of inventory cycle as of 2022.

Table B-12. FIA summary statistics and performance measures, FYs 2013–2022.
60 Forest Inventory and Analysis

Table B-1. Performance measures for the FY 2022 FIA Program.

Pacific

Northwest

Rocky

Mountain Southern Northern NationalOffice Total

Total Federal funds directly invested in FIA salary 

and expenses $10,273,173 $10,719,111 $10,677,881 $12,001,768 $376,094 $44,048,027

Total Federal funds available for operations $11,093,964 $9,275,025 $15,022,730 $8,810,248 $6,698,800 $50,900,767

Total FY 2022 appropriated operational funds $3,874,764 $3,124,062 $7,695,744 $5,295,516 $3,598,800 $23,588,886

Contributions from partners (operations):

 Supporting the 20% FIA Program $206,538 $259,564 $1,881,083 $763,669 $0 $3,110,854

 Value-added contributions $2,182,173 $378,224 $275,665 $7,258,705 $1,097,591 $11,192,358

 Total partner contributions $2,388,711 $637,788 $2,156,748 $8,022,374 $1,097,591 $14,303,212

Total available operational funds $13,482,675 $9,912,813 $16,816,878 $16,722,622 $7,796,391 $64,731,379

Base grid (forested and possibly foresteda

)

Total forested base grid plots 23,012 29,318 52,846 37,636 - 142,812

Field-sampled 1,425 2,958 4,945 4,516 - 13,844

Nonsampled hazard 98 37 55 17 - 207

Nonsampled denied accessb 100 406 500 1,000 - 2,006

 % forested base grid completedc 8% 12% 10% 15% - 11%

Base forest quality assurance plots 65 202 429 289 - 985

 % field-sampled base grid with QA 5% 7% 9% 6% - 7%

Forest plots with one or more health indicatorsd 1,425 2,958 4,945 583 - 9,911

Additional plots sampled (forested and nonforest)

Spatial intensification 994 0 280 1,519 - 2,793

Temporal acceleration 281 0 1,480 369 - 2,130

Urban plots 46 85 175 1,508 - 1,814

Special Study plotse 23 0 0 0 - 23

Number of publications:

 State/island resource reports 0 0 14 14 - 28 

 State Timber Product Output reports 3 1 13 0 - 17 

 Regional reports 0 0 0 2 - 2 

 National reports 0 0 0 3 - 3 

 5-Year State reports 1 1 2 1 - 5 

 Subtotal – core reports 4 2 29 20 - 55 

 Peer-reviewed journal articles 13 19 5 35 - 72 

 Proceedings articles 0 0 0 1 - 1 

 Other publications 4 5 4 2 - 15 

 Subtotal – nonreport publications 17 24 9 38 - 88

Total publications 21 26 38 58 - 143

Publications per analyst and researcher 1.4 1.6 2.5 2.0 - 1.9 

Consulting activities:

 Number of significant consultations 152 591 72 438 23 1,276 

 Total hours of significant consultations 1,362 1,315 316 2,820 585 6,398 

Meetings:

 User group meetings held 0 5 2 5 0 12 

 Management meetings held 5 0 1 1 2 9 

FIA = Forest Inventory and Analysis; FY = fiscal year; QA = quality assurance.

a

 Plots that appear forested based on a prior field visit or remote sensing data but could not be sampled due to hazardous conditions or denied access are 

classified as "nonsampled (possibility of forest)."

b Landowner permission is required to sample plots on private land; some plots could not be sampled because the landowner denied access.

c

 Plots that could not be sampled due to hazardous conditions or denied access are included as completed when calculating this performance metric. 

Percent of forested base grid plots completed = (field sampled plots + nonsampled hazard + nonsampled denied access) / total forested base grid plots. 

For the Pacific Northwest, the percentage was calculated excluding plots in Hawaii and Interior Alaska because those areas have periodic inventories and 

are not part of the annual sampling target of 10 percent.

d Health indicators measured include crown dieback, vegetation diversity and structure, down woody materials, forest soils, and invasive plant species.

e

 Special study plots are typically post-disturbance measurements. 

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 61

Table B-2a. Federal funds received by the FIA Program to pay for salary and expenses, FY 2022.

Pacific 

Northwest

Rocky 

Mountain Southern Northern National 

Office Total

FIA Salary and Expenses (S&E)a Dollars

 Salary 8,994,221 10,183,132 8,347,832 11,706,895 362,100 39,594,180 

 Administration 630,411 803,837 731,201 783,643 362,100 3,311,192 

 Data collection/QA 4,725,471 6,196,634 4,185,422 5,207,947 0 20,315,474 

 Information management 1,206,158 970,889 1,102,230 1,234,640 0 4,513,917 

 Analysis & Research 2,432,181 2,211,772 2,328,979 4,480,665 0 11,453,597 

 Travel 749,505 535,979 1,806,434 176,099 11,994 3,280,011 

 Office travel 41,879 49,510 762,730 29,009 11,994 895,122 

 Field/quality assurance crew travel 707,626 486,469 1,043,704 147,090 0 2,384,889 

 Otherb 529,447 0 523,615 118,774 2,000 1,173,836 

Total FIA S&E 10,273,173 10,719,111 10,677,881 12,001,768 376,094 44,048,027 

FIA = Forest Inventory and Analysis; FY = fiscal year; QA = quality assurance.

a Funds made available to pay for S&E charges from FIA staff.

b

 All other expenditures using funds available for S&E, including awards, training, overtime, and boot replacements.

Appendix B: Additional Data Tables
62 Forest Inventory and Analysis

Table B-2b. Financial statement for FIA operational funds, FY 2022.

Pacific 

Northwest

Rocky 

Mountain Southern Northern National 

Office Total

Available Federal operational FIA funds Dollars

Previous year end-of-year balance 22,226 33,082 274,836 55,348 0 385,492 

Post-year adjustmentsa (22,226) (33,082) (274,836) 151,684 0 (178,460)

 Subtotal pre-year adjustments 0 0 0 207,032 0 207,032 

FY 2022 appropriated FIA operational funds

 Initial FIA funds added to base 3,874,764 2,624,062 7,195,744 4,295,516 81,000 18,071,086 

 Secondary FIA funds added to baseb 0 0 0 0 953,000 953,000 

 Congressional directives 0 500,000 500,000 1,000,000 1,010,800 3,010,800 

 IT funds 0 0 0 0 1,554,000 1,554,000 

 Subtotal FY22 appropriated operational funds 3,874,764 3,124,062 7,695,744 5,295,516 3,598,800 23,588,886 

Other Forest Service R&D funds 0 96,200 80,000 0 0 176,200 

Other Forest Service R&D IT funds 0 0 0 0 1,500,000 1,500,000 

Other Federal fundsc 0 38,703 389,946 0 0 428,649 

Disaster supplemental (CR) 7,219,200 6,016,060 6,857,040 3,307,700 1,600,000 25,000,000 

 Subtotal additional Federal funds 7,219,200 6,150,963 7,326,986 3,307,700 3,100,000 27,104,849 

Total available Federal operational funds 11,093,964 9,275,025 15,022,730 8,810,248 6,698,800 50,900,767 

Direct operational expenses

Equipment 376,737 586,236 457,806 326,304 1,222,834 2,969,917 

 Imagery 0 0 71,146 0 25,000 96,146 

 Vehicles 230,860 445,723 231,488 213,582 0 1,121,653 

 Field equipment 145,877 106,670 154,720 90,937 192,703 690,907 

 Information technology/communications 0 8,822 0 9,861 1,005,131 1,023,814 

 Other 0 25,021 452 11,924 0 37,397 

Publications 0 23,932 0 66,219 8,634 98,785 

Grants and agreementsd 4,878,437 5,120,796 8,683,668 7,898,621 3,086,643 29,668,165 

 Field work/data 3,719,014 3,842,687 6,697,026 2,753,605 - 17,012,332 

 Information management 0 0 0 0 2,749,931 2,749,931 

 Research 1,159,423 1,278,109 1,584,946 5,145,016 230,000 9,397,494 

 Other 0 0 401,696 0 106,712 508,408 

Office space and utilities 2,842 12,206 4,191 54,400 0 73,639 

Other direct expenses 8,676 440,333 15,320 0 3,312 467,641 

 Total direct operational expenses 5,266,692 6,183,503 9,160,985 8,345,544 4,321,423 33,278,147 

EOY operations balancee 5,827,272 3,091,522 5,861,745 464,704 2,377,377 17,622,620 

Total FIA Federal operational expense 11,093,964 9,275,025 15,022,730 8,810,248 6,698,800 50,900,767 

CR = continuing resolution; EOY = end of year; FIA = Forest Inventory and Analysis; FY = fiscal year; IT = information technology; R&D = Research and 

Development.

a Some bookkeeping is not completed until after the new FY begins, which may affect beginning balances. These adjustments include items such as 

carryover, return of unused prior year grants, Station adjustments, etc.

b Additions to base funding from FIA National Office. This number does not include the congressional allocation for the Small Business Innovation 

Research (SBIR) program, as that money is not available for FIA operations.

c

 Includes funding from national forests and other Federal agencies.

d Grants and agreements include general allocation of grants to basic thematic categories.

e

 The EOY operations balance is higher than average for FY 2022 because some of the disaster supplemental funds will be spent in the following years. 

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 63

Table B-3a. Federal staffing, in full-time equivalent (FTE) hours, for the FY 2022 FIA Program.

Pacific 

Northwest

Rocky 

Mountain Southern Northern National Office Total

Administration 3.9 7.0 7.0 6.0 1.7 25.6

Field operations 55.2 62.1 41.2 47.2 0 205.7

Information management 9.4 15.1 9.1 10.0 0 43.6

Analysis and research 15.4 16.2 15.0 29.5 0 76.1

Indirect support1 0.3 0.0 0.0 0.0 0 0.3

Total 84.2 100.4 72.3 92.7 1.7 351.3

FIA = Forest Inventory and Analysis; FY = fiscal year.

1 Indirect support FTEs are research station salaries and expenses charged toward the tracking FIA salary budget code.

Table B-3b. Estimate of cooperator staffing, in full-time equivalent (FTE) hours, funded by FIA grants and agreements for the FY 2022 FIA 

Program.

Pacific 

Northwest

Rocky 

Mountain Southern Northern National Office Total

Administration 0.4 1.0 1.9 0.0 0.0 3.3

Field operations 38.0 21.6 120.5 26.0 0.0 206.1

Information management 0.4 0.0 4.3 3.0 0.0 7.7

Analysis and research 8.0 5.0 1.8 5.0 0.0 19.8

Total 46.8 27.6 128.5 34.0 0.0 236.9

FIA = Forest Inventory and Analysis; FY = fiscal year.

Table B-3c. Estimated total federally funded staffing, in full-time equivalent (FTE) hours, for the FY 2022 FIA Program.

FIA = Forest Inventory and Analysis, FY = fiscal year.

a

 Indirect support FTEs are research station salary and expenses charged toward the tracking FIA salary budget code.

Pacific 

Northwest

Rocky 

Mountain Southern Northern National Office Total

Administration 4.3 8.0 8.9 6.0 1.7 28.9

Field operations 93.2 83.7 161.7 73.2 0 411.8

Information management 9.8 15.1 13.4 13.0 0.0 51.3

Analysis and research 23.4 21.2 16.8 34.5 0.0 95.9

Indirect supporta 0.3 0.0 0.0 0.0 0.0 0.3

Total 131.0 128.0 200.8 126.7 1.7 588.2

Appendix B: Additional Data Tables
64 Forest Inventory and Analysis

Table B-4. Partner contributions toward implementing FIA in FY 2022.

Unit Partner Contributions toward 

the base program

Contributions 

that add value

Dollars

Rocky Mountain Forest Service Region 1 81,575 365,576

Forest Service Region 2, Forest Health Protection 15,945 - 

Forest Service Region 4 1,524 2,648

Harvard University - 10,000

New Mexico State Forestry Division 4,000 - 

University of Montana 153,820 - 

Utah Division of Forestry, Fire, and State Lands 2,700 - 

Rocky Mountain total 259,564 378,224

National Office Society of American Foresters - 21,236

Southern Utah University - 475,727

University of Nevada, Las Vegas - 600,628

National Office total - 1,097,591 

Northern Alabama A&M University - 30,284

California Air Resources Board - 150,000

Colorado State University - 662,552

Connecticut Department of Conservation 2,000 - 

Davey Tree Expert Company - 1,000,000

Delaware Department of Conservation 4,392 - 

Forest Service Region 9 - 100,000

Forest Service Research & Development - 650,000

Forest Service Resource Planning Act - 50,000

Forest Service Rocky Mountain Research Station - 40,194

Forest Service State, Private, and Tribal Forestry 67,423 200,000

Illinois Division of Forestry 19,039 - 

Indiana Department of Natural Resources 27,923 - 

Iowa Department of Natural Resources 15,203 - 

Kansas State Forest Service 16,938 - 

Maine Forest Service 253,847 717,598

Maryland Department of Natural Resources 20,730 - 

Massachusetts Department of Conservation and Recreation 7,700 - 

Michigan Division of Forest Management 40,200 - 

Michigan State University - 50,000

Minnesota Department of Natural Resources 56,279 568,116

Missouri Department of Conservation - 18,996

National Council for Air and Stream Improvement - 90,000

National Institute of Forest Science (South Korea) - 40,120

Nebraska Department of Forestry, Fish and Wildlife 3,174 - 

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 65

Table B-4. Partner contributions toward implementing FIA in FY 2022, continued.

Unit Partner Contributions toward 

the base program

Contributions 

that add value

 Dollars

Northern (continued) New Hampshire Department of Resources & Economic Development 19,600 - 

New Jersey Forest Service 20,599 117,234

New York Department of Environmental Conservation 18,195 - 

North Dakota Forest Service 4,590 - 

Ohio Department of Natural Resources 13,687 - 

Pennsylvania Department of Conservation & Natural Resources 43,083 6,123

Rhode Island Department of Environmental Management 6,471 6,471

South Dakota Dept. of Agriculture and Natural Resources 17,225 - 

State University of New York - 30,000

Texas A&M University - 213,610

University of Florida - 90,000

University of Maine - 253,848

University of Massachusetts-Amherst - 11,942

University of Minnesota - 82,957

University of Nevada, Las Vegas - 600,627

University of New Hampshire - 189,034

U.S. Environmental Protection Agency - 550,000

USDA Natural Resources Conservation Service - 260,000

Vermont Department of Conservation 8,500 4,000

West Virginia Division of Forestry 22,271 - 

Wisconsin Department of Natural Resources 54,600 475,000

Northern total 763,669 7,258,705

Pacific Northwest Alaska Department of Natural Resources 19,272 - 

CALFIRE - 986,596

DOI Bureau of Land Management - 165,000

Forest Service Region 6 - 750,000

Greening Youth Foundation 11,122 - 

Michigan State University 73,882 - 

Micronesia Conservation Trust 55,005 - 

Oregon Department of Forestry - 9,054

Oregon State University - 98,777

Portland State University - 60,290

Sitka Conservation Society - 3,850

University of Alaska Anchorage - 17,876

University of Hawaii 18,798 - 

University of Kentucky Research Foundation - 67,500

University of Montana 28,460 - 

University of Washington - 23,230

Pacific Northwest total 206,538 2,182,173

Appendix B: Additional Data Tables
66 Forest Inventory and Analysis

Table B-4. Partner contributions toward implementing FIA in FY 2022, continued.

Unit Partner Contributions toward 

the base program

Contributions 

that add value

Dollars

Southern Arkansas Forestry Commission 116,568 - 

Florida Forest Service 155,681 - 

Georgia Forestry Commission 183,444 - 

Kentucky Division of Forestry 200,418 - 

North Carolina Forest Service - 216,991

Oklahoma Forestry Services 117,556 - 

South Carolina Forestry Commission 122,862 - 

Texas A&M Forest Service 690,801 - 

University of North Carolina at Chapel Hill 66,182 22,674

University of Tennessee 58,000 36,000

Virginia Department of Forestry 169,571 - 

Southern total 1,881,083 275,665

Total, all FIA units $3,110,854 $11,192,358

Grand total (base program and added value) $14,303,212

 DOI = U.S. Department of the Interior; FIA = Forest Inventory and Analysis, FY = fiscal year; USDA = U.S. Department of Agriculture.

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 67

Table B-5. Grants and agreements entered into by FIA units, FY 2022.

Unit Recipient Purpose Amount 

(dollars)

Rocky Mountain American West Forestry LLC Field Data Collection 218,679

Colorado State University Fire Impacts 169,840

Colorado State University, Colorado State 

Forest Service Field Data Collection 1,839,105

Forest Service GTAC FIESTA Development 255,000

Forest Service R&D Forest and Woodland 

Ecosystem Program Soils Analyses 106,410

Harvard University Small Area Estimation (Congressionally Directed) 150,000

Integrated Resource Inventories Field Data Collection 310,772

Michigan State University FIESTA Development 75,003

National Council for Air and Stream 

Improvement Small Area Estimation (Congressionally Directed) 113,500

New Mexico State University Soils Analysis Enhancement 160,001

Oregon State University Land Use and Land Cover Rapid Assessment Dashboard 32,628

Paul Chisholm Field Data Collection 251,680

Skylight Forestry Field Data Collection 579,650

Synergy Staffing Contract Science Consultations 4,751

University of Arizona Increment Core Measurements 50,000

University of Montana Nonresponse Mill study 38,000

University of Montana Small Area Estimation (Congressionally Directed) 136,500

University of Montana, Bureau of Business 

and Economic Research Timber Products Output 308,000

University of Montana, Bureau of Business 

and Economic Research Wood Utilization Study 46,686

University of Vermont National Land Cover Database Tree Canopy Cover 96,200

Utah State University Increment Core measurements 50,000

Wesley Winslow Field Data Collection 128,391

Rocky Mountain total 5,120,796

National Office Chief Information Office Cloud services 419,931

Forest Service GTAC Land Use and Land Cover ICE analysis and programming 120,000

Forest Service GTAC FIESTA development 110,000

Forest Service GTAC FIA data viewer and dashboards 30,000

National Experienced Workforce Solutions ACES contract (FIA program support) 31,712

Society of American Foresters National User Group and Carbon meetings 75,000

Southern Utah University 508 compliance testing and DATIM support 300,000

University of Nevada Las Vegas Data management support 2,000,000

National Office total 2,666,712

Appendix B: Additional Data Tables
68 Forest Inventory and Analysis

Table B-5. Grants and agreements entered into by FIA units, FY 2022, continued.

Unit Recipient Purpose Amount 

(dollars)

Northern Bradley Angle Field Data Collection 4,149

Chandler Johnson Field Data Collection 191,425

Colorado State University Forest Service Urban Forest Inventory, Analysis Assistance 662,553

Daniel Huberty Field Data Collection 79,720

Davey Tree Expert Company i-Tree: Development, Dissemination and Support 921,895

Digital Map Products, Inc. Digital Map Products 2,000

DJM Ecological Services, Inc. Field Data Collection 283,920

DOI National Park Service Forest Service Lease of National Park Service Office Space 10,000

Grand Rapids Forestry Science Laboratory Soil Analysis 74,176

Hispanic Access Foundation Resource Assistants Program Cohorts 31,967

Indiana Department of Natural Resources Indiana’s Statewide Data Collection 92,975

Joel Fyock Field Data Collection 8,050

Lightbox Parent, L.P. Parcel Data 125,500

Maine Department of Agriculture, 

Conservation & Forestry

Maine’s Statewide Resource Annualized Forest Resource 

Inventory 717,599

Mark Webb Field Data Collection 161,025

Michigan State University Investigating New National Tree Biomass Models for Urban 

FIA 50,000

Minnesota Department of Natural 

Resources Data Collection and Analytical Reporting 375,258

National Council for Air and Stream 

Improvement

Biometrical Research in Support of Entity-Scale Greenhouse 

Gas Guidelines 90,000

National Council for Air and Stream 

Improvement Small Area Estimation and Assistance Assessment 896,500

Native Resource Preservation, LLC Field Data Collection 104,758

Oak Ridge Associated Universities ORAU Digital Engagement Products 110,000

Oak Ridge Associated Universities ORAU Information Management 300,000

Oak Ridge Associated Universities ORAU Carbon Postdoctoral Research Associates 270,000

Regents of the University of Minnesota Forest Biometrics Research and Program Support 82,957

Regents of the University of Minnesota Marcell Experimental Forest 70,000

Research Foundation for the State 

University of New York Assessing Forests and Their Benefits 30,000

Reyco Forest Management, LLC Field Data Collection 96,026

Ryan Nowak Field Data Collection 213,643

South Dakota Department of Agriculture 

and Natural Resources

South Dakota Statewide Annualized Forest Resource 

Inventory 31,990

Strohman Enterprise, Inc. Continuation of inReach Air Plan 20,500

Texas A&M University System FIA Analytical Support 213,610

Thomas Bergstrom Field Data Collection 170,891

University of Florida Quantifying Changes in Dynamics of U.S. Forests Using FIA 

Data and Novel Modeling Approaches 350,000

University of Massachusetts Family Forest Research Center 571,500

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 69

Table B-5. Grants and agreements entered into by FIA units, FY 2022, continued.

Unit Recipient Purpose Amount 

(dollars)

Northern University of Massachusetts Small Area Estimation and Assistance Assessment 220,000

(continued) University of Massachusetts National Woodland Owner Survey 65,000

University System of New Hampshire Urban Forest Inventory and Analysis (Analytical Assistance) 189,034

USDA National Agricultural Statistics 

Service National Woodland Owner Survey Nonresponse Phone Calls 10,000

Northern total 7,898,621

Pacific 

Northwest Alaska Department of Natural Resources Field data collection in Interior Alaska 1,983,369

Alaska Transportation Contractors Helicopter Transportation in Alaska 1,232,604

Department of Interior Acquisition 

Services Alaska FIA Aviation Services Agreement 50,000

FIA Data Collection Plot Contractors Field Data Collection 270,939

Greening Youth Foundation, Inc. Resource Assistants Program Cohorts 43,193

Michigan State University Small Area Estimation Methods and Tool Development 

(Congressionally Directed) 100,000

Micronesia Conservation Trust Forest Inventory and Monitoring Network Within Micronesian 

Communities 120,000

NASA Optimizing Inventory Methods and Sampling Design for 

Carbon Monitoring in Interior Alaska 50,000

Oregon State University Collaborative Species and Change Modeling Investigation 50,000

Oregon State University Point Cloud-Based Augmentation of Forest Inventory 

Parameters and Solar Insolation Assessment in Riparian Areas 135,999

Paul Chisholm Pacific Northwest Tree Demography Database Development 50,000

Portland State University Design and Validation of a Spatially Aware Variant of the 

BioSum Modeling Framework 159,000

Sitka Conservation Society

Assessing Forest Conditions Supporting Berry Harvesting, 

Mushroom Gathering, and Cultural Tree Use in Southeast 

Alaska

18,909

University of Alaska Anchorage Using Tree Rings to Understand Changes in Tree Growth in 

Interior Alaska 62,289

University of Hawaii Sustaining the Capacity for Forest Inventory and Analysis in 

Hawaii and the Western Pacific Islands 65,000

University of Kentucky Research 

Foundation

Techniques for Analysis of Epiphytic Mosses for Source 

Apportionment of Airborne Pollutants 150,000

University of Montana CALFIRE California Logging Utilization 17,000

University of Montana Pacific West TPO and Forest Industry Analysis 2021 85,300

University of Washington Pilot Study Developing Moss Bioindicators for Mapping Diesel 

Exhaust 50,000

University of Washington Evaluation of Ground-Based Laser Scanning to Support Forest 

Inventory in Interior Alaska 80,462

U.S. Department of Energy Forest Inventory and Analysis Dendroecology Fellowship 104,373

Pacific Northwest total 4,878,437

Appendix B: Additional Data Tables
70 Forest Inventory and Analysis

Table B-5. Grants and agreements entered into by FIA units, FY 2022, continued.

Unit Recipient Purpose Amount 

(dollars)

Southern Alabama Forestry Commission Alabama Forest Inventory and Analysis 536,112

Arkansas Forestry Commission Arkansas Forest Inventory and Analysis 447,207

Clemson University Invasive Plant Fire Behavior Study 39,946

Florida Department of Agriculture Florida Forest Inventory and Analysis 467,044

Forest Service International Institute of 

Tropical Forestry Direct Support to FIA Activities 80,000

Forest Service Region 8 Collection of Annual Tree Seedling Data 30,000

Georgia Forestry Commission Georgia Forest Inventory and Analysis 644,584

Greening Youth Foundation Resource Assistants Program Cohorts 46,542

Kentucky Division of Forestry Kentucky Forest Inventory and Analysis 366,282

Lurleen B. Wallace Community College Lurleen B. Wallace Outreach and Education Partnership 401,696

Mississippi Forestry Commission Mississippi Forest Inventory and Analysis 557,425

National Council for Air and Stream 

Improvement Small Area Estimation (Congressionally Directed) 350,000

North Carolina Department of Agriculture 

and Consumer Services North Carolina Forest Inventory and Analysis 508,016

North Carolina State University Methodology for Rapid Assessment of Hurricane Damage on 

Primary Forest Industry 80,000

North Carolina State University Forest Health Monitoring, Analysis, and Assessment 250,000

Oak Ridge Institute for Science and 

Education ORISE Research Participation Program 240,000

Oklahoma Department of Agriculture, 

Food & Forestry Oklahoma Forest Inventory and Analysis 352,669

South Carolina Forestry Commission South Carolina Forest Inventory and Analysis 346,283

Tennessee Division of Forestry Tennessee Forest Inventory and Analysis 423,804

Texas A&M Forest Service Texas Forest Inventory and Analysis 1,431,684

University of North Carolina at Chapel Hill Mapping Forest Aboveground Biomass Loss from Hurricanes 160,000

University of Tennessee Improving Small Area Estimation Methods and Tools for 

Forest Inventories 150,000

University of Tennessee Assessing U.S. Roundwood Equivalent Factors 135,000

University of Tennessee Rapid Assessment of Hurricane Damage on Primary Forest 

Industry 20,000

University of Tennessee Allometric Functions for Assessing Mangrove Forest Structure 

Loss After Hurricanes 160,000

Virginia Department of Forestry Virginia Forest Inventory and Analysis 459,374

Southern total 8,683,668

Grand total 29,248,234

ACES = Agriculture Conservation Experienced Services; DATIM = Design and Analysis Toolkit for Inventory and Monitoring; DOI = U.S. Department of the 

Interior; FIA = Forest Inventory and Analysis; FY = fiscal year; GTAC = Geospatial Technology and Applications Center; ICE = image-based change estimation; 

NASA = National Aeronautics and Space Administration; NWOS = National Woodland Owner Survey; ORAU = Oak Ridge Associated Universities; ORISE = 

Oak Ridge Institute for Science and Education; R&D = Research and Development; TPO = timber products output.

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 71

Table B-6. Number and hours of significant FIA staff consultations by customer group, FY 2022.

Customer 

group

Pacific

Northwest

Rocky

Mountain Southern Northern National Office Total

Number Hours Number Hours Number Hours Number Hours Number Hours Number Percent Hours Percent

Academic 28 317 24 59 16 139 109 605 6 135 183 14% 1,255 20%

Government 103 952 38 1,069 21 2 180 1,011 6 135 348 27% 3,169 50%

Industry 6 30 4 6 23 117 73 218 5 80 111 9% 451 7%

NGO 11 55 60 7 2 12 68 416 1 110 142 11% 600 9%

NIPF - - 450 160 1 2 3 25 - - 454 36% 187 3%

Media 3 7 7 12 - - 2 67 - - 12 1% 86 1%

Other 1 1 8 1 9 44 3 480 5 125 26 2% 651 10%

Total 152 1,362 591 1,315 72 316 438 2,820 23 585 1,276 100% 6,398 100%

FIA = Forest Inventory and Analysis; FY = fiscal year; NGO = nongovernmental organization; NIPF = nonindustrial private forest landowner.

Appendix B: Additional Data Tables
72 Forest Inventory and Analysis

Table B-7. FIA data access by online tools and Spatial Data Services team requests, FYs 2013–2022.

Number of annual accesses

Indicator 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total 

2013–2022

Online tools

DATA downloads 7,383 19,768 66,000 69,025 53,315 195,836 436,119 275,444 331,366 117,252 1,571,508 

DATIM - - - - 37,000 1,605 5,129 4,755 3,768 3,818 56,075 

EVALIDator 33,759 35,839 36,532 34,082 38,597 42,625 46,349 46,011 47,120 26,943 387,857 

EVALIDator API - - - 75,449 38,313 63,162 3,963,560 1,041,049 515,406 472,014 6,168,953 

FIDO 57,567 57,974 47,263 33,293 11,898 4,500 - - - - 212,495 

TPO Toolkit - 69,600 18,544 37,000 1,092 2,652 2,771 2,400 1,400 8,363 143,822 

NWOS 4,502 2,994 2,068 1,710 2,517 3,000 2,194 2,431 995 984 23,395 

Online accesses total 103,211 186,175 170,407 250,559 182,732 313,380 4,456,122 1,372,090 900,055 629,374 8,564,105 

Spatial data requests

Academia 143 155 160 162 163 158 82 103 82 62 1,270 

State 29 55 91 56 43 61 37 44 30 23 469 

NFS 31 32 29 40 37 26 21 24 26 5 271 

Other Federal 175 131 136 130 134 105 37 70 41 25 984 

NGO 35 31 38 35 38 44 15 22 25 14 297 

Industry 41 94 84 54 65 78 30 40 31 36 553 

Other 67 88 66 55 59 31 20 21 22 16 445 

Spatial data requests total 521 586 604 532 539 503 242 324 257 181 4,289 

API = application programming interface; DATIM = Design and Analysis Toolkit for Inventory and Monitoring; FIA = Forest Inventory and Analysis; 

FIDO = Forest Inventory Database Online; FY = fiscal year; NFS = National Forest System; NGO = nongovernmental organization; NWOS = National 

Woodland Owner Survey; TPO = timber products output.

FIDO support was discontinued in FY 2019.

Online data accesses jumped in FY 2019 due to FIA access to data through EVALIDator API for tool development.

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 73

Table B-8. Mill, fuelwood, and ownership surveys processed and utilization sites visited, FYs 2013–2022.

Number of annual survey questionnaires or sites

Survey or site Year 

initiated 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Total

2013-2022

Timber products 1947 1,529 2,503 1,411 2,421 831 2,719 2,682 2,563 2,713 2,858 22,230

Fuelwooda 1947 2,360 0 0 0 0 0 0 0 0 0 2,360

Ownership surveysb 1978 5,262 0 0 0 5,254 6,407 1,713 3,135 3,105 0 24,876

Utilization sites 1947 189 105 216 162 39 219 132 118 97 140 1,417

FY = fiscal year.

a

 FIA no longer conducts surveys to estimate fuelwood consumption. Industrial fuelwood estimates are part of the timber products output mill surveys. 

Residential fuelwood estimates are calculated from the U.S. Department of Energy Residential Energy Consumption Survey and the U.S. Census Bureau 

American Community Survey.

b

 No ownership questionnaires were mailed in 2022 due to review process and supply delays.

Timber products survey numbers from prior years were updated to correct an error in previous reports.

Appendix B: Additional Data Tables
74 Forest Inventory and Analysis

Table B-9. Forest health indicator, year of initiation, and number of plots sampled, FYs 2013–2022.

Number of annual samples

Total

2013–2022 Indicator Year 

initiated 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Crown diebacka 1991 2,183 1,341 1,880 2,771 2,976 3,843 2,156 2,736 2,334 1,714 23,934 

Lichensb 1998 0 98 61 193 197 351 257 - - - 1,157 

Soils 1999 565 439 487 456 716 426 791 394 836 724 5,834 

Vegetation profile 2001 6,703 7,098 6,666 6,757 6,294 7,025 7,000 5,497 6,168 6,661 65,869 

DWM 2001 8,271 8,635 8,186 8,459 9,234 9,277 8,188 7,203 7,280 7,360 82,093 

Invasive species 2013 8,389 10,402 10,276 10,753 12,045 11,898 11,116 10,256 11,399 11,443 107,977 

Mortalityc 2001 13,859 17,308 16,825 14,606 17,083 16,825 16,116 16,942 16,810 17,523 163,897 

FY = fiscal year; DWM = down woody materials. 

a

 Lichen data are no longer collected. 

b Crown dieback numbers from all prior years were updated to correct an error in previous reports.

c

 Number of remeasured annual inventory plots from which tree mortality can be estimated.

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 75

Table B-10. Status of FIA surveys in U.S. islands and territories, FY 2022.

Region 

and area

 Land 

area in 

inventory 

(acres) 

 Forest 

Area 

(acres)

 Percent 

forest 

Number 

of major 

islands

Fiscal year 

of current 

inventory 

cycle end

Fiscal year 

of inventory 

available in 

databasea

Fiscal 

year of 

published 

report

Number of 

base field 

plots

Number 

of forest 

health 

plots

Number of 

intensified 

plots

Available 

online 

data

Pacific (PNW)

American Samoa 48,434 43,631 90% 4 2023 2012 2020 76 0 0 Yes

Guam 135,660 63,833 47% 1 2023 2013 2020 66 0 70 Yes

Palau 110,028 90,685 82% 10 2024 2014 2007 56 0 0 Yes

Commonwealth 

of the Northern 

Mariana Islands

75,546 51,009 68% 3 2025 2015 2012 37 0 0 Yes

Federated States 

of Micronesia 161,917 143,466 89% 4 2026 2016 2012 78 0 78 Yes

Marshall Islands 33,182 23,230 70% 10 2028 2018 2012 50 0 20 Yes

Hawaii 4,141,469 1,990,000 48% 8 2022 2022 2023 429 0 82 Yes

Atlantic (SRS)

Commonwealth 

of Puerto Rico 2,192,073 1,154,763 53% 4 2024 2019 2019 478 149 0 Yes

U.S. Virgin Islandsb 82,164 46,967 57% 3 2024 2014 2020 116 59 0 Yes

Total 6,980,473 3,607,584 52% 47 1,386 250

FIA = Forest Inventory and Analysis; PNW = Pacific Northwest Research Station; SRS = Southern Research Station.

a

 Periodic inventories do not enter data in the FIA database until full cycle is completed. For Hawaii data, check: 

https://www.fs.usda.gov/research/pnw/products/dataandtools/tools/pnw-fia-hawaii-inventory-database. 

b The 2019 inventory year for the U.S. Virgin Islands, scheduled to start collecting field data in FY 2020, was delayed due to the COVID-19 pandemic.

Appendix B: Additional Data Tables
76 Forest Inventory and Analysis

Table B-11. State-level summary of land and forest area, years for the most recent available FIA data and 5-year State reports, 

and length of inventory cycle as of 2022.

Region and State

 U.S. Census 

Bureau land 

area 

 Forest land area 

defined by RPA 

Assessment 

 Forest land area 

defined by FIA 

Latest year of 

data available 

online

Inventory year of 

FIA 5-year State 

report

Publication year 

of FIA 5-year 

State report

Cycle 

Lengtha

 Thousand acres Year Years 

Northern 606,841 182,587 182,603 

 Connecticut 3,099 1,808 1,808 2020 2012 2016 7

 Delaware 1,247 361 361 2020 2013 2018 7

 Illinois 35,532 4,980 4,980 2019 2015 2018 7

 Indiana 22,929 4,876 4,876 2020 2013 2017 7

 Iowa 35,749 2,923 2,923 2021 2013 2016 7

 Kansas 52,326 2,527 2,527 2020 2015 2018 7

 Maine 19,739 17,579 17,579 2021 2018 2022 5

 Maryland 6,252 2,463 2,463 2019 2008 2012 7

 Massachusetts 4,992 3,025 3,025 2019 2012 2016 7

 Michigan 36,185 20,311 20,311 2019 2014 2017 7

 Minnesota 50,961 17,413 17,413 2019 2018 2022 5

 Missouri 43,995 15,409 15,409 2021 2018 2021 7

 Nebraska 49,167 1,532 1,532 2020 2015 2018 7

 New Hampshire 5,730 4,758 4,758 2020 2017 2020 7

 New Jersey 4,707 1,990 1,990 2019 2013 2017 5

 New York 30,161 18,887 18,887 2019 2017 2020 7

 North Dakota 44,161 789 805 2021 2015 2018 7

 Ohio 26,151 8,077 8,077 2019 2016 2019 7

 Pennsylvania 28,635 16,898 16,898 2020 2014 2017 7

 Rhode Island 662 370 370 2020 2012 2016 7

 South Dakota 48,519 1,949 1,949 2020 2015 2018 7

 Vermont 5,899 4,511 4,511 2020 2017 2020 7

 West Virginia 15,384 12,077 12,077 2020 2013 2016 7

 Wisconsin 34,661 17,074 17,074 2020 2014 2017 7

Southern 533,031 245,513 268,034 

 Alabama 32,413 23,127 23,127 2021 2015 2018 7

 Arkansas 33,303 19,040 19,040 2021 2010 2015 5

 Florida 34,447 17,253 17,253 2019 2013 2017 7

 Georgia 36,809 24,635 24,635 2020 2014 2016 5

 Kentucky 25,271 12,442 12,442 2018 2014 2022 7

 Louisiana 27,650 14,984 14,984 2018 2013 2016 7

 Mississippi 30,031 19,380 19,380 2020 2017 2020 5

 North Carolina 31,115 18,829 18,829 2021 2013 2015 7

 Oklahomab 43,901 11,911 12,274 2019 2014 2017 7

 South Carolina 19,239 12,931 12,931 2020 2016 2018 5

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 77

Table B-11. State-level summary of land and forest area, years for the most recent available FIA data and 5-year State reports, 

and length of inventory cycle as of 2022, continued.

Region and State

 U.S. Census 

Bureau land 

area 

 Forest land area 

defined by RPA 

Assessment 

 Forest land area 

defined by FIA 

Latest year of 

data available 

online

Inventory year of 

FIA 5-year State 

report

Publication year 

of FIA 5-year 

State report

Cycle 

Lengtha

 Thousand acres Year Years 

Southern (continued)

 Tennessee 26,390 13,967 13,967 2018 2014 2022 7

 Texasc

 167,188 40,970 63,128 2019 2013 2020 5

 Virginia 25,274 16,043 16,043 2020 2016 2018 5

Rocky Mountain 547,691 123,844 152,848 

 Arizona 72,700 10,934 18,617 2019 2014 2018 10

 Colorado 66,331 20,063 22,804 2019 2013 2017 10

 Idaho 52,892 21,386 21,589 2019 2015 2019 10

 Montana 93,149 25,517 25,884 2019 2015 2019 10

 Nevada 70,260 7,487 10,564 2019 2016 2022 10

 New Mexico 77,631 16,619 24,601 2019 2014 2017 10

 Utah 52,589 12,087 18,296 2019 2012 2016 10

 Wyoming 62,140 9,751 10,493 2019 2015 2018 10

Pacific Northwest 573,389 213,391 218,882 

 Alaska, Coast 39,041 14,426 14,426 2019 2013 2020 10

 Alaska, Interiord 326,575 114,151 114,151 2019 2018 2022 10

 California 99,699 31,515 36,768 2019 2015 2020 10

 Hawaiid 4,110 1,471 1,471 2019 2015 2023 10

 Oregon 61,432 29,653 29,726 2019 2015 2019 10

 Washington 42,532 22,174 22,339 2019 2016 2019 10

 TOTAL 2,260,953 765,334 822,366

FIA = Forest Inventory and Analysis; RPA = Resources Planning Act. 

Note: The RPA and FIA definitions of forest differ. Because the FIA definition includes woodlands, estimates of forest area from the FIA database will be higher in 

the arid to semiarid regions of the Interior Western United States.

a

 Cycle length is the number of years that it takes to sample all base grid plots in the State. Some States provide supplemental funding to reduce the cycle length 

to fewer than 10 years in the West and 7 years in the East.

b

 Eastern Oklahoma has a cycle length of 7 years; western Oklahoma has a cycle length of 10 years.

c

 For western Texas, data are available from 2019; for eastern Texas, data are available from 2021. Western Texas has a cycle length of 10 years; eastern Texas has 

a cycle length of 5 years.

d

 Interior Alaska and Hawaii have periodic inventories; all other States have annualized inventories.

Appendix B: Additional Data Tables
78 Forest Inventory and Analysis

Table B-12. FIA summary statistics and performance measures, FYs 2013–2022.

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Available funds directly invested (in thousand dollars)

 S&E funds directly invested in FIA 39,317 44,048

 Operational funds 17,621 22,035

 IT operational funds 1,500 1,554

 Total apropriated funds 

directly invested in FIA 65,567 66,805 70,000 75,000 77,000 77,000 77,000 77,000 58,438 67,637

 Other Federal operational 

fundsa 2,668 3,077 1,119 910 85 2,666 4,617 3,223 8,035 27,312

 Total Federal funds 68,235 69,882 71,119 75,910 77,085 79,666 81,617 80,223 66,473 94,949

 Partner fundsb 7,772 7,833 8,972 10,176 10,906 10,883 11,735 12,860 11,426 14,303

 Total available funds 76,007 77,715 80,091 86,086 87,991 90,549 93,352 93,083 77,899 109,252 

 % Full Federal 

appropriated fundingc 76% 74% 78% 82% 83% 81% 80% 78% 68% 61%

Program expenses and balances (in thousand dollars)

 Administration 2,854 3,036 2,703 2,759 3,632 3,532 3,714 3,090 3,098 4,206

 Image processing 589 597 635 761 680 833 981 - - - 

 Field support 4,151 4,082 3,782 4,029 3,797 3,770 3,776 - - - 

 Data collection 22,559 23,590 22,807 26,888 28,404 26,952 28,610 - - - 

 Combined field operationsd 27,299 28,269 27,225 31,678 32,881 31,555 33,366 31,678 35,665 41,621

 Information managementd 5,933 6,737 7,680 7,962 8,743 8,807 7,920 7,872 7,457 8,288

 Analysis 6,695 7,058 6,907 6,800 6,534 6,575 6,453 - - - 

 Researchc 6,690 7,072 6,111 7,084 7,054 7,050 6,680 - - - 

 Combined analysis and 

researchd 13,385 14,131 13,017 13,884 13,588 13,625 13,133 14,254 17,002 20,851

 Miscellaneous/other 3,652 3,864 5,025 4,342 2,909 2,933 2,717 2,998 2,865 2,360

 Total direct expense 53,124 56,037 55,651 60,625 61,752 60,452 60,850 59,894 66,087 77,326

 Total indirect expensese 14,704 13,461 14,708 14,652 15,333 19,076 19,024 19,437 - - 

 Indirect rate 22% 20% 21% 20% 20% 24% 23% 24% - - 

Fire transfer 0 0 449 181 0 0 0 - - - 

Total EOY balancef 407 384 312 452 0 137 1,742 892 385 17,623

 Total Federal expense 68,235 69,882 71,119 75,910 77,085 79,666 81,617 80,223 66,473 94,949

Other measures

 % States with annual activity 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

 % Annualized States with 

FIADB 1–2 yrs old 94% 96% 96% 96% 96% 94% 86% 88% 88% 47%

 Federal employees 366 366 338 352 341 339 382 379 332 351

 Other employees 184 204 185 213 209 220 237 224 232 237

 Total employees 550 570 523 565 550 559 618 602 564 588 

 Base forest plots 21,263 19,789 18,346 14,308 15,543 14,598 14,848 13,502 13,309 142,812

 Base QA plots 5,465 2,312 3,083 1,529 2,199 2,171 1,839 1,730 1,233 985

 Percent QA plots 11% 5% 7% 11% 11% 15% 12% 13% 9% 1%

 All publications 238 234 236 371 206 211 204 239 248 143

 Journal publications 90 87 122 122 92 122 112 101 97 72

 Percent journal publications 38% 37% 52% 33% 45% 58% 55% 42% 39% 50%

 Consultations, number 824 945 1,350 1,289 1,341 1,648 950 1,434 696 1,276

 Consultations, hours 8,124 7,987 13,806 7,547 8,781 8,000 7,764 16,735 8,285 6,398

 User/management meetings 12 14 13 12 9 14 19 16 10 21

 Spatial data requests filled 605 586 604 532 586 503 242 324 257 181

 Online accesses 103,211 186,175 170,407 250,559 182,732 310,758 4,456,122 1,372,090 900,055 629,374

Appendix B: Additional Data Tables
Fiscal Year 2022 Business Report 79

Table B-12. FIA summary statistics and performance measures, FYs 2013–2022, continued.

EOY = end of year; FIA = Forest Inventory and Analysis; FIADB = Forest Inventory and Analysis database; FY = fiscal year; IT = information technology; QA = 

quality assurance; S&E = salary and expense.

a

 Includes return of previous year carryover, return of fire transfers, COVID-19 economic relief, supplemental disaster funding, National Forest System funds, additional Research and Development commitments (including IT contributions managed by FIA in FY 2021 and FY 2022), and funds from other Federal agencies.

b

 Includes partner contributions towards the base program and partner contributions that add value. Cash contributions from the National Forest System and 

other Federal programs are included under other Federal operational funds rather than under partner funds.

c

 Considering full program implementation funding to achieve 2007 strategic plan for FYs 2007 through 2013 and 2014 (current) strategic plan options A through 

C for FY 2014 through present. Full funding needed was adjusted for inflation. For FY 2022, appropriated funding received was calculated as the sum of appropriated operational funds and funds invested in S&E. This value is not comparable to prior years.

d

 Includes Federal grants and agreements.

e

 Starting in FY 2021, indirect S&E and rate related to S&E of non-FIA employees tracked with FIA budget code.

f

 Starting in FY 2021, EOY balance is for the appropriated operational funds. It does not include unspent S&E budgeted by the research stations. 

Indirect expenses rate jumped in FY 2018 because of the Forest Service approach, adopted that year, to charge costs pools, which are considered an indirect 

expense rather than a direct expense in this report. Starting in FY 2021, indirect expenses cannot be tracked because, under the new budget structure, indirect 

costs are no longer charged to the programs.

Online data accesses jumped in FY 2018 due to FIA access to data through EVALIDator API for tool development. 

Some Federal partner contributions are included in both the partner funds and total Federal funds categories. Total available funds category is adjusted to avoid 

duplication.

Some historic numbers have been updated to correct errors discovered during a data review.

Appendix B: Additional Data Tables
80 Forest Inventory and Analysis
Fiscal Year 2022 Business Report 81