United States Department of Agriculture

DEPAR TMENT OF AGRICULT URE

Forest 

Service

Pacific Northwest 

Research Station

General Technical Report

PNW-GTR-972

April

2019

Fuel Characteristic Classification 

System (FCCS) Field Sampling 

and Fuelbed Development Guide

Susan J. Prichard, Anne G. Andreu, Roger D. Ottmar, and Ellen Eberhardt
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Authors

Susan J. Prichard and Anne G. Andreu are research scientists, University of 

Washington, College of the Environment, School of Environmental and Forest 

Sciences, Box 352100, Seattle, WA 98195-2100; Roger D. Ottmar is a research forester, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station, Pacific Wildland Fire Sciences Laboratory, 400 N 34th Street, Suite 201, 

Seattle, WA 98103; and Ellen Eberhardt is a technical information specialist, U.S. 

Department of Agriculture, Forest Service, Pacific Northwest Research Station, 

Forestry Sciences Laboratory, 3200 SW Jefferson Way, Corvallis, OR 97331.

Cover photos by Roger Ottmar
Abstract

Prichard, Susan J.; Andreu, Anne G.; Ottmar, Roger D.; Eberhardt, Ellen. 

2019. Fuel Characteristic Classification System (FCCS) field sampling and 

fuelbed development guide. Gen. Tech. Rep. PNW-GTR-972. Portland, OR: 

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station. 77 p. 

The Fuel Characteristic Classification System (FCCS) was designed to store and 

archive wildland fuel characteristics within fuelbeds, defined as the inherent physical characteristics of fuels that contribute to fire behavior and effects. The FCCS 

represents fuel characteristics in six strata including canopy, shrubs, herbaceous 

fuels, downed wood, litter-lichen-moss, and ground fuels. Each stratum is further 

divided into one or more categories and subcategories to represent the complexity 

of wildland and managed fuels. A variety of techniques to measure and summarize fuelbed data are detailed in this guide. This guide is organized by strata and 

categories to facilitate data input into FCCS fuelbeds and provides field sampling 

forms by stratum. The first section provides an overview of how FCCS reference 

fuelbeds were constructed from databases, literature sources, and expert opinion. 

The guide next describes how regional pathway fuelbeds can provide a systematic 

set of management fuelbeds that track vegetation and fuel succession over time as 

well as management activities such as prescribed burning and mechanical thinning. 

The final section details common field sampling methodologies for users who wish 

to use field measurements to construct FCCS fuelbeds. 

Keywords: Biomass, fuel characteristics, fuel treatments, field methods, 

wildland fire.
Contents

1 Introduction

3 FCCS Reference Fuelbed Development

3 Background

4 Fuelbed Inputs

4 Descriptive Data

10 Regional Fuelbed Pathway Development

13 Field Protocols for Customizing FCCS Fuelbeds

13 FCCS and the FIREMON-FEAT Integration Tool

15 Fuelbed Description

17 Canopy

17 Trees

24 Snags

25 Ladder Fuels

27 Shrubs

28 Sampling Design

29 Needle Drape

30 Percentage Cover

32 Height

32 Percentage Live

33 Loading 

37 Herbs

38 Downed Wood 

40 Fine Downed and Dead Wood

42 Sound Wood

43 Rotten Wood

43 Stumps

45 Piles

48 Litter-Lichen-Moss

49 Depth 

50 Percentage Cover

50 Moss Type

50 Litter Arrangement

50 Litter Type

51 Ground Fuels

51 Duff

52 Basal Accumulations

55 Squirrel Middens
Table 

number

Page 

number Description

1 6 User-input Fuel Characteristic Classification System fuelbed 

variables used in calculating physical characteristics and 

properties of wildland fuels

2 16 Fuel Characteristic Classification System fuelbed search variables 

and options

3 18 Input variables for tree and class 1 snag-with-foliage categories

4 19 Plot size recommendations based on median tree diameter and 

height

5 24 Snag input variables

6 26 Ladder fuel input variables

7 27 Shrub stratum input variables by primary and secondary layer

8 31 Fire effects and monitoring system cover class codes

9 33 Sample calculation of loading of manzanita (Arctostaphylos 

columbiana Piper)

10 37 Crosswalk from the natural fuels photo series to Fuel Characteristic 

Classification System catagories

11 38 Herb stratum input variables

12 39 Downed wood input variables 

13 39 Transect length by size class

14 44 Stump input variables applicable to sound, rotten, and lighteredpitchy categories

15 45 Machine and hand-pile inputs

16 48 Litter-lichen-moss stratum inputs

17 51 Upper and lower duff layer input variables

18 52 Inferred bulk density values by duff type and derivation

19 53 Basal accumulation input variables 

20 55 Interfered bulk density values by basal accumulation type

21 55 Squirrel midden input variables 

56 Conclusions

57 Acknowledgments

57 U.S. Equivalents

58 Literature Cited

61 Appendix 1: Fuel Characteristic Classification System Field 

Sampling Forms 

75 Appendix 2: Slope Correction Table

76 Appendix 3: Random Number Table

77 Appendix 4: Percentages of Cover of Vegetation

1

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Introduction

The Fuel Characteristic Classification System (FCCS) is a comprehensive software 

system that records wildland fuel characteristics and predicts potential fire hazard 

and surface fire behavior (Ottmar et al. 2007). With its large fuels dataset and ability to represent a wide variety of fuel conditions, FCCS has many applications, from 

small-scale fuel reduction projects to large-scale emissions and carbon assessments. 

Characterizing fuels and assessing their fire hazard has always been important to 

fire and fuel managers and are becoming increasingly pertinent to other specialists, 

including ecologists, air quality and smoke managers, land use planners, global 

change scientists, and carbon modelers (Ottmar et al. 2007).

The FCCS defines a fuelbed as the “inherent physical characteristics of fuels 

that contribute to fire behavior and effects” (Riccardi et al. 2007). A fuelbed can 

represent any scale considered to be fairly uniform. For example, a 5000-ha western sagebrush system may be adequately represented by a single fuelbed, whereas 

a 5-ha tropical rainforest may require several fuelbeds to represent the variability 

in fuel structure and composition. The FCCS represents wildland fuel characteristics in six strata, including canopy, shrubs, herbaceous fuels, downed wood, 

litter-lichen-moss, and ground fuels (fig. 1). Each stratum is further divided into 

one or more categories and subcategories to represent the complexity of wildland 

and managed fuels. 

A variety of techniques to measure and summarize fuelbed data are detailed in 

this guide. Fuelbeds are the common currency in FCCS and Consume (JFSP 2009), 

which have recently been integrated into a single user interface called Fuel and Fire 

Tools (FFT). This guide is organized by strata and categories to simplify data input 

into FCCS fuelbeds and provides field sampling forms by stratum. Before using the 

guide, we recommend exploring the fuelbed editor within FFT to become familiar 

with the fuelbed organization and required inputs. The FCCS calculator, documentation, and tutorials are located online.1

This guide is organized into three sections. The first section gives an overview 

of how FCCS reference fuelbeds were constructed from databases, literature 

sources, and expert opinion. Users may wish to create generic fuelbeds for their 

specific purposes and can use this same approach to create customized fuelbeds.

1 Source information about equations that use FCCS input variables to calculate vegetation 

biomass, fuel loading, and predicted fire behavior can be found in the FCCS technical 

documentation (Prichard et al. 2013).
2

GENERAL TECHNICAL REPORT PNW-GTR-972

The next section, “Regional Fuelbed Pathway Development,” briefly 

describes how regional pathway fuelbeds can provide a systematic set of management fuelbeds that track forest and fuel succession over time, and also the results 

of management activities such as prescribed burning and mechanical thinning. 

Users from land management agencies may wish to construct similar pathways 

specific to their vegetation types and management activities.

The final section, “Field Protocols for Customizing FCCS Fuelbeds,” details 

common field sampling methodologies for users who wish to use field measurements 

to construct FCCS fuelbeds to represent wildland fuels.

Stratum Catagory

Canopy Trees, snags, and ladder fuels

Shrubs

Ground fuels

Litter-lichen-moss

Downed wood

Herbaceous

Duff, basal accumulations, and 

squirrel middens

Litter, lichen, and moss layers

Sound wood, rotten wood, 

and stumps

Primary and secondary layers

Trees, snags, and ladder fuels

Figure 1—Fuel Characteristic Classification System fuelbed strata and categories (Prichard et al. 2013).
3

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

FCCS Reference Fuelbed Development

Background

In 1999, the Fire and Environmental Research Applications (FERA) team, part 

of the U.S. Forest Service (USFS), Pacific Northwest (PNW) Research Station, 

received funding from the Joint Fire Science Program to develop a national system 

of classifying fuel characteristics (JFSP 2007). Researchers began developing 

FCCS fuelbeds through a series of regional workshops attended by fire and fuel 

scientists representing the boreal, tropical and semitropical, dry, western temperate, and eastern temperate regions of the United States. Workshop participants 

wrote detailed descriptions of vegetation types and fuelbed categories they considered important in their regions. Often, participants also provided fuelbed data 

based on expert opinion or published literature. These data were incorporated into 

fuelbeds, and data gaps were filled using images from photo series, literature, and 

expert opinion (Ottmar et al. 2007, Riccardi et al. 2007). 

Members of the FERA team continued to develop fuelbeds that represent the 

major vegetation types for the United States. Most of these fuelbeds were created 

from a compilation of data sources including peer-reviewed literature, natural fuels 

photo series (e.g., logging residue photo series [Ottmar and Hardy 1989, Ottmar 

et al. 1990]), and government databases and reports (e.g., Forest Service research 

papers, general technical reports, and research notes). Some Western U.S. fuelbeds 

were based on datasets from National Park Service (NPS) fire monitoring data. 

Datasets generally came from sites within narrow geographic areas (usually one 

park) and did not reflect the complete geographic distribution of the vegetation 

types. Therefore, these fuelbeds were broadened with available data from pertinent 

literature or databases to better represent their full geographic range.

Forested fuelbeds were constructed with data derived from the USFS Forest 

Inventory and Analysis (FIA) national database and natural fuels photo series, 

where applicable.2 3 In many parts of the country, FIA data are limited to canopy 

and snag data; additional fuelbed data were obtained from relevant scientific literature and reports. In the USFS Pacific Northwest and Pacific Southwest Regions 

(Washington, Oregon, and California), FIA data included downed wood and 

understory vegetation information for many plots.

In total, 216 fuelbeds were constructed for use in FCCS version 1.0. Each 

fuelbed was reviewed for accuracy and consistency by a team of research scientists 

at the PNW Research Station Pacific Wildland Fire Sciences Laboratory, and by 

2 https://www.fia.fs.fed.us.

3 https://www.fs.fed.us/pnw/fera/fccs/fuelbed_references.shtml.
4

GENERAL TECHNICAL REPORT PNW-GTR-972

regional fire and fuels specialists throughout the United States. A data quality confidence rating was assigned to each fuelbed based on the availability of data sources.4

Fuelbeds have been mapped at 30- and 1-km scales across the conterminous 

United States and Alaska. The 30-m map is available in LANDFIRE (USDI GS 

2010), and fuelbed lists developed in LANDFIRE can be used to specify fuelbed 

lists within the FFT.5 In advance of the LANDFIRE 2008 refresh (LANDFIRE, 

n.d.), an additional 93 fuelbeds were constructed to address gaps in national fuels 

mapping for the conterminous United States and Alaska.

Fuelbed Inputs

Each reference fuelbed was created to broadly represent that fuelbed throughout its 

geographic distribution. When regional data sources were used for a single fuelbed, 

the most common (modal) value was used from those sources. The upper and lower 

limits of the averages, omitting clear outliers, were used for the minimum and maximum entries. Where specific data sources were available, a specific value was used 

and the range was estimated from general ecological descriptions. The fuelbed editor allows users to view multiple fuelbeds but is not able to accommodate minimum 

and maximum input values in the user interface. Minimum and maximum values 

are stored in each reference fuelbed file but are not visible in the fuelbed editor.6

Descriptive Data

Fuelbed name—

In general, the name of each FCCS reference fuelbed begins with a list of the most 

important or diagnostic species in the vegetation type that the fuelbed defines. Species in the same stratum are separated by a hyphen (e.g., red spruce [Picea rubens

Sargent]–balsam fir [Abies balsamea (L.) Mill.] forest), and those in different strata 

are separated by a slash (e.g., Douglas-fir [Pseudotsuga spp.]/oceanspray [Holodiscus sp.] forest). Vegetation type (forest, shrubland, grassland, etc.) is listed after the 

species names.

Fuelbed description—

Fuelbed descriptions typically contain the geographic extent of a fuelbed, species 

commonly associated with the fuelbed, a description of applicable change agents, 

and any other information important to distinguishing that fuelbed from others.

4 A list of source references by fuelbed, broken out by strata, is online. 

5 Fuelbed lists developed in LANDFIRE can be used to specify fuelbed lists within the FFT.

6 Fuelbed files are saved as extensible markup language (.xml) files within the program.
5

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Selection criteria—

Fuelbeds may be selected within the FCCS by any of a set of four criteria: 

• Bailey’s (1995) ecoregion7

• Vegetation form (conifer forest, broadleaf forest, mixed forest, shrubland, 

or grassland)

• Society of American Foresters cover type (Eyre 1980) or Society for Range 

Management (SRM) cover type (Shiflet 1994)

• Change agent(s) (includes natural disturbances, silvicultural activities, and 

other human impacts such as fire exclusion and grazing)

Confidence rating—

The FCCS reference fuelbeds contain an overall rating for the quality of the data 

used for creating the fuelbed. 

• No data (no referenced numbers for any data value)—created from experience, taken from ecological literature, or both

• Partial data—less than 35 percent of data is from literature, photo series, or 

peer-reviewed data sources

• Partial data—35 to 85 percent of data is from literature, photo series, or 

peer-reviewed data sources

• Data driven—85 to 100 percent of data is from photo series or peerreviewed data sources

• Data driven—85 to 100 percent of data, including minimum and maximum 

values, is from photo series or peer-reviewed data sources

Canopy stratum—

The canopy stratum contains overstory, midstory, and understory tree data, as well 

as snag data arranged by decay classes (table 1). Canopy inputs represent values 

for the entire fuelbed as opposed to an individual tree. Most canopy data are from 

the FIA national database, the NPS database, photo series, literature, and vegetation classifications (Riccardi et al. 2007).8 9 Additional data sources for snags were 

wildlife studies, coarse down wood studies, and old-growth studies. 

Ladder fuels data are based on the structure of each particular forest type. For 

example, if vines, shrubs, or saplings were present in amounts sufficient to create vertical continuity between the canopy layers and lower vegetation strata, an 

estimate of the maximum and base height is included. 

7 https://www.fs.fed.us/land/ecosysmgmt/ecoreg1_home.html.

8 https://www.fia.fs.fed.us/tools-data/.

9 https://science.nature.nps.gov/im/inventory/veg/.
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GENERAL TECHNICAL REPORT PNW-GTR-972

Table 1—User-input Fuel Characteristic Classification System fuelbed variables used in calculating physical 

characteristics and properties of wildland fuels (continued)

Strata, category, and subcategory Variable Field data form

Canopy:

Total canopy Percentage covera 2, 3, 4, 5

Trees— Percentage covera c

Overstory, midstory, understory Height (m) 2

Height to live crown (m)a

Density (number of stems/ha)a

Diameter at breast height (cm)

Species and relative cover (%)a

Snags—

Class 1 snags with foliage Cover (%)a 2

Height (m)a c

Height to snag crown base (m)a

Density (number of stems/ha)a c

Diameter at breast height (cm)c

Species and relative percentage cover (%)a c

Class 1 (no foliage), class 2, 

class 3

Height (m)c 2

Diameter (cm)c

Density (number of stems/ha)c

Species and relative percentage cover (%)c

Ladder fuels— 2

Type: arboreal lichens and 

mosses, climbing ferns 

and other epiphytes, dead 

branches, leaning snags, 

stringy or fuzzy bark, tree 

regeneration, vines-liana

Minimum height (m)

Maximum height (m)

Is there vertical continuity sufficient to carry fire between 

the canopy and lower strata?a

Shrubs: 5, 6, 7

Primary layer, secondary layer Percentage cover (%)a b

Height (m)a b c

Percentage live (%)a b

Loading (Mg ha-1)

a b c—optional 8

Species and relative cover (%)a b c

Needle drape— Is needle drape on shrubs sufficient to affect fire behavior?a
7

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Table 1—User-input Fuel Characteristic Classification System fuelbed variables used in calculating physical 

characteristics and properties of wildland fuels (continued)

Strata, category, and subcategory Variable Field data form

Herbs:

Primary layer, secondary layer Percentage cover (%)a b 5, 6, 7

Height (m)a b

Percentage livea

Loading (Mg ha-1)

a b c 8

Species and relative cover (%)a b

Woody fuels:

All woody Total coverage by fine wood and 1-, 10-, and 100-hr downed 

wood (percentage)a b

Depth (m)a b

Sound wood— Species and relative cover (%)a b

1-hr Loading (Mg ha-1)

a b c 9

10-hr Loading (Mg ha-1)

a b c 9

100-hr Loading (Mg ha-1)

a b c 9

1,000-hr Loading (Mg ha-1)

a b c 9

10,000-hr Loading (Mg ha-1)

a b c 9

>10,000-hr Loading (Mg ha-1)

a b c 9

Rotten wood— Species and relative cover (%)a b

1,000-hr Loading (Mg ha-1)

a b c 9

10,000-hr Loading (Mg ha-1)

a b c 9

>10,000-hr Loading (Mg ha-1)

a b c 9

Stumps— Species and relative cover (%)c 2

Sound, rotten, lightered/pitchy Height (m)c 2

Diameter (cm)c 2

Density (number per hectare)c 2

Piles— Type (hand or machine)c 10

Number of piles Piles per hectarec

Pile shape Half-sphere, paraboloid, half-cylinder, half-frustum of cone, 

half-cone with rounded ends, half-ellipsoid, and irregular 

solidc

Pile dimensions Width, height, and length by pile shape (m)c

Composition (hand piles only) Conifer or shrub/hardwoodc

Soil (machine piles only) Pile volume that is soil (%)c

Species composition (machine 

piles only)

Primary and secondary species to assign wood densitiesd

Litter-lichen-moss: 9

Litter— Arrangement (fluffy, normal, or perched)a b c
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GENERAL TECHNICAL REPORT PNW-GTR-972

Table 1—User-input Fuel Characteristic Classification System fuelbed variables used in calculating physical 

characteristics and properties of wildland fuels (continued)

Strata, category, and subcategory Variable Field data form

Type: Short needle pine, long needle 

pine, other conifer, broadleaf 

deciduous, broadleaf evergreen, 

palm frond, grass

Depth (cm)a b c

Cover (%)a b c 6

Loading (Mg ha-1)

a b c —optional

Lichen— Depth (cm)a b c

Cover (%)a b c

Loading (Mg ha-1)

a b c —optional

Moss— Depth (cm)a b c

Cover (%)a b c 6

Loading (Mg ha-1)

a b c—optional

Type (sphagnum or other moss)a b c

Ground fuels:

Upper duff— Depth (cm)c 9

Total cover (%)a b c

Derivation Cover of partially decomposed moss and litter (%)

Cover of partially decomposed sphagnum moss or peat (%)

Cover (%)c

Lower duff— Depth (cm)c 9

Total coverage (%)c

Derivation Cover of fully decomposed moss and litter (%)

Cover of partially decomposed sphagnum moss or peat (%)

Basal accumulations— 11

Derivation Bark slough, branches, broadleaf deciduous, broadleaf 

evergreen, grass, needle litter, palm fronds 

Depth (cm)c

Radius (m)c

Density (number per ha)c

Loading (Mg ha-1)

c

—optional

Squirrel middens— Depth (cm)c 11

Radius (m)c

Density (number per ha)c

Loading (Mg ha-1)

c

—optional

a

 Important to crown fire potentials.

b

 Important to surface fire potentials.

c

 Important for biomass and carbon calculations.

d

 If a species is not listed, a proxy species with similar wood density may be used.
9

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Shrub and herbaceous strata—

Shrub and herbaceous strata inputs may be divided into primary and secondary layers. Shrub layers are generally differentiated by height classes. If most shrubs have 

a similar height, the secondary layer is not populated. In the herbaceous stratum, 

if both grasses and forbs are present, both primary and secondary layers are populated. Herbaceous stratum fuel loadings were obtained from photo series whenever 

possible. Other data sources include ecological studies, biomass data and equations, 

and expert opinion.

Source data for shrub and herbaceous inputs included NPS and FIA databases, 

vegetation classifications, photo series, and ecological literature. Examples of 

classifications consulted include the NPS Inventory and Monitoring Program10 state 

natural heritage programs such as the Florida Natural Areas Inventory,11 and the 

NatureServe vegetation classification.12 

Reference sources used for determining potential shrub and herbaceous vegetation 

heights when plot data were not available include the Fire Effects Information System 

database13 or PLANTS database14 and individual plant taxonomic descriptions.

Downed wood stratum—

Total percentage cover and the depth of fine downed wood are not available in most 

data sources. These were generally estimated from a photo series or with expert 

opinion (Riccardi et al. 2007). Sound and rotten downed wood loadings were typically derived from photo series. Additional data were available through the FIA and 

NPS databases and other local studies. 

Data on stumps and accumulations of downed wood in natural fuelbeds were 

generally unavailable. Most data was estimated based on photo series plots, the 

expert opinions of fuelbed creators or reviewers, or both. 

Litter-lichen-moss stratum—

Sources of moss and lichen data were scarce, but it was usually possible to find 

information about litter depth. Data from databases (e.g., USDI NPS 2016) were 

used when available. Many vegetation classifications also discuss soils and moss/

lichen. Where data were not available, experts assigned values. Litter type and relative percentage cover were estimated from overstory and understory composition. 

10 https://science.nature.nps.gov/im/networks.cfm.

11 http://www.fnai.org.

12 https://www.natureserve.org/biodiversity-science/species-ecosystems/ecosystems.

13 https://www.feis-crs.org/feis/.

14 https://plants.usda.gov/java/.
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GENERAL TECHNICAL REPORT PNW-GTR-972

Ground fuels stratum—

Upper and lower duff depths were obtained from literature, soil series descriptions, 

and fuels and wildlife studies.15 If only one duff value was available, it was split 

equally between upper and lower layers. Squirrel midden and basal accumulation 

inputs were typically based on expert opinion.

Regional Fuelbed Pathway Development

The Fire and Environmental Research Applications Team collaborated with several 

national forests and with the U.S. Bureau of Land Management (BLM) to create a 

set of regional fuelbeds that represents major vegetation types, management activities, and fuel succession over time.16 To date, regional fuelbeds and maps have been 

developed for:

• Okanogan-Wenatchee National Forest (north-central Washington state)

• Central Oregon (USFS)

• Northeastern Oregon (USFS and BLM)

• Lake Tahoe Basin Management Unit (USFS)

• Southeastern U.S. Army installations

In each case, we worked closely with local land and fire managers to develop 

fuelbed management pathways. Fuelbeds were customized to represent (1) major 

vegetation types (mostly forests), (2) common management activities and natural 

disturbances, and (3) forest and fuel succession over time. Forests that are not 

actively managed have relatively simple pathways (fig. 2), whereas forests that are 

actively managed (e.g., precommercial thinning, commercial thinning, and prescribed burning) have complex pathways (fig. 3). Information was synthesized from 

plant association guides, research studies, vegetation plot data, and expert opinion 

to develop the pathway fuelbeds. Within similar ecosystems, pathway fuelbeds 

can be used as templates and customized to represent actual sites. Land managers 

may also wish to use existing fuelbed pathway handbooks to help design similar 

pathway fuelbeds that represent major vegetation types and management activities 

on their management units.

15 https://www.fs.fed.us/pnw/fera/fft/maps.shtml.

16 https://www.frames.gov/partner-sites/ffi/ffi-home/.
11

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Forest age

(years)— 0–10

Wildfire

CO073 CO074 CO075 CO076

CO077

High density

CO078

Medium density

None None Insects and disease

10–40 40–90 90–120 >120

Change

agent—

FCCS

fuelbed

number—

Figure 2—Sample subalpine fir (Abies lasiocarpa [Hook.] Nutt.) pathway (central Oregon [CO]), representing forest development over 

stand ages and insects and diseases. Each box represents a fuelbed, starting with stand initiation following a wildfire (CO073), young 

subalpine forests (CO074 and CO075), a 90- to 120-year-old subalpine forest with insect and disease (CO076), and two old subalpine forests with either medium- or high-density stocking (CO077 and CO078, respectively). FCCS = Fuel Characteristic Classification System.
12

GENERAL TECHNICAL REPORT PNW-GTR-972

Age (years)

0–10

Stand-replacement

wildfire treat shrub

10–25 25–50 50–80 80–120 >120

None LT021 LT022 LT023 LT024 LT027

LT086

LT031

LT026 LT030

LT028 LT033

LT035

LT034

LT089

LT032

LT033

LT036

LT034

LT028

LT029

LT031

LT025

None None None

None

None

None

None

None

None

None

None

Wf underburn 

select cut and 

pile and burn

Wf underburn 

select cut and 

pile and burn

Wf underburn 

select cut and 

Wf underburn 

pile and burn

select cut and 

pile and burn

Wf underburn 

 select cut and 

 pile and burn

Wf underburn 

select cut and 

pile and burn

Select cut and pile

Select cut

and pile

Select cut

and pile

Select cut and pile

Select cut and pile

Select cut and pile

Thin from below pile and no burn

Thin from below pile and no burn

Select cut and

mastication

Figure 3—Red fir (Abies magnifica [A. Murray bis]) pathway (Lake Tahoe Basin Management Unit [LT]), representing management 

actions and fuelbed succession over a range of stand ages. Each box represents a fuelbed, beginning with stand initiation following a 

stand-replacing wildfire, and dividing into many fuelbeds to represent common forest management and fuel reduction treatment activities in young (25 to 30 years) to old (>120 years) red fir forests. Wf = wildfire. 
13

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Field Protocols for Customizing FCCS Fuelbeds

The FCCS was designed to represent the geographic and structural complexity of 

wildland and managed fuels throughout North America. A custom fuelbed may 

contain only a fraction of the inputs accommodated by FCCS. It is generally most 

efficient to modify an FCCS fuelbed that closely matches to a specific site and use 

default data as necessary. For example, a reference fuelbed may have tree and snag 

data that approximate conditions on the site, but surface fuels (e.g., shrubs, herbs, 

fine wood, and litter) may need to be adjusted with site-specific data to better 

inform surface fire behavior predictions, fuel consumption modeling, or both. In 

addition, some reference fuelbed data may not be needed for a particular fuelbed 

and can simply be deleted (e.g., secondary shrub and herb layers).

Fuelbeds can be developed for different purposes, and the required inputs differ 

by application. For surface fire behavior, FCCS needs inputs only in the shrub, 

herb, wood, and litter-lichen-moss strata (table 1). For crown fire potentials, canopy 

inputs are also required. Complete fuel loading and carbon assessments can use the 

full range of fuelbed inputs from canopy to ground fuels.

FCCS and the FIREMON-FEAT Integration Tool

Field sampling methods in this guide closely follow Fire Effects and Monitoring 

Inventory System (FIREMON) sampling protocols (Lutes et al. 2006), which were 

developed for use in fire monitoring applications with an emphasis on repeating plot 

measurements. FIREMON was integrated with the Fire Ecology Assessment Tool 

(FEAT) (Sexton 2003) to create an online database (FEAT-FIREMON Integrated 

[FFI]) that can support fire effects monitoring (Lutes et al 2009) (see footnote 15). 

Where applicable, FIREMON sampling protocols are either duplicated or adapted 

for use in FCCS. 

Before beginning fieldwork, locate a sampling area with relatively uniform 

fuels. If possible, avoid sampling within a mosaic of different vegetation or fuel 

types. There are many possible approaches to sampling fuel characteristics, 

including fixed-area plots, belt transects, prism plots, line transects, and point 

sampling. In this guide, we recommend that you use fixed, circular plot sampling 

along a grid with a random start point (fig. 4). This design is consistent with the 

FIREMON sampling techniques (Lutes et al. 2006) and enables a variety of fuel 

characteristics to be sampled from each plot location. For further information on 

sampling design, including determining appropriate plot dimensions and sampling intensity, refer to the FIREMON integrated sampling strategy guide (Lutes 

et al. 2006).
14

GENERAL TECHNICAL REPORT PNW-GTR-972

FCCS predicts surface fire behavior and crown fire potentials based on input 

fuel characteristics (table 1) and environmental variables, including mid-flame 

windspeed, slope gradient, and fuel moisture scenario (Prichard et al. 2013). 

Surface fire behavior predictions include reaction intensity (kJ m-2), rate of 

spread (m min-1), and flame length (m). Because of a limited understanding of 

crown fire behavior, FCCS calculates crown fire potentials as indexed ranking 

between 0 and 9. 

Figure 4—Sample plot layout in a recently thinned unit.
15

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Fuelbed Description

Each fuelbed is associated with several descriptive fields, including search variables that can be used in FCCS search screen (table 2) and contact information on 

the fuelbed author or source. Fuelbeds are also associated with a written fuelbed 

description that generally describes the vegetation type, disturbance history, and 

geographic extent of each fuelbed. 

Field sampling forms are provided in appendix 1. There are variables listed in 

the fuelbed description form (app. 1, form 1) that you may wish to include in your 

written fuelbed description (table 2). These options include:

• Fuelbed name—User-defined name of fuelbed. The FCCS does not require 

unique names or any particular naming protocol for custom fuelbeds. 

• Description—User-defined description of the fuelbed. Fuelbed descriptions 

generally include age, geographic representation, vegetation and disturbance, management history, or a combination of these descriptors.

• Ecoregion—Fuelbeds are organized geographically into 13 Bailey ecoregion divisions. Fuelbeds often span multiple ecoregions. A map of these 

divisions is provided in the fuelbed selection screen. 

• Vegetation form—Select one of six vegetation forms. Mixed forests are 

defined as forests in which evergreen and deciduous species each contribute 25 to 75 percent of total tree cover in both overstory and midstory 

strata.

• Cover type—Society of American Foresters and Society for Rangeland 

Management cover types. More than one cover type may apply to an individual fuelbed. 

• Stand structural class—Applicable to forested fuelbeds only. Select a 

structural class that best describes the number of canopy layers, relative 

size of trees, stage of understory development, and relative degree of stand 

closure (O’Hara et al. 1996). 

• Change agent(s)—Select from a list of natural or management activities 

that have altered your fuelbed. More than one change agent may apply. 

• Plot ID—Plot identifier (if applicable).

• Plot dimensions—Radius (m).

• Field crew—Names of field personnel.

• Description—Written description of the site.

• Date—Sampling date.
16

GENERAL TECHNICAL REPORT PNW-GTR-972

Table 2—Fuel Characteristic Classification System fuelbed search variables and optionsa

Search variable Options

Ecoregion 120 - Tundra

130 - Subarctic

210 - Warm continental

220 - Hot continental

230 - Subtropical

240 - Marine

250 - Prairie 

260 - Mediterranean 

310 - Tropical/subtropical desert

320 - Tropical/subtropical steppe desert

330 - Temperate steppe

340 - Temperate desert

410 - Savanna

420 - Rainforest

Vegetation form Broadleaf forest

Conifer forest

Grassland

Mixed forest

Savanna

Shrubland

Slash

Cover type Eyre (1980), Shiflet (1994)

Structural class Old-forest multistory

Old-forest single story

Stand initiation

Stem-exclusion closed canopy

Stem exclusion open canopy

Understory reinitiation

Young forest–multistory

Change agent(s) Avalanche

Chipping

Clearcut

Ditching/draining

Fire exclusion

Grazing

Ice storm

Insects and disease

Introduction of exotic species

Landslide

Logging methods/equipment damage

Lop and scatter

Mastication

None

Paving

Pile burn

Prescribed fire

Pruning

Residual fertilizer

Restoration work

Salvage logging

Stumpwooding

Thinning (thin from below)

Turpentining

Unknown

Wildfire

Wildfire (crown)

Wildfire (ground)

Windthrow

Natural fire regime 0- to 35-year frequency and low severity 

0- to 35-year frequency and high severity 

35 to 200+ year frequency and mixed severity 

35 to 200+ year frequency and high severity

200+ year frequency and high severity

Fire regime 

condition class 

Class 1: Fire regimes are within the natural (historical) range, and the risk of losing key ecosystem 

components is low 

Class 2: Fire regimes have been moderately altered from their natural (historical) range

Class 3: Fire regimes have been substantially altered from their natural (historical) range

Data quality 

ranking

No data—No data (no hard numbers for any data value)—created from experience or ecological 

literature. 

Partial data—Less than 35 percent of mode inputs from literature, photo series, or peer-reviewed data 

source. 

Partial data—35 to 85 percent of mode inputs from literature, photo series, or peer-reviewed data source. 

Data driven—85 to 100 percent of mode inputs from photo series or peer-reviewed data source. 
17

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

• Elevation (m)—Recorded from a topographic map, calibrated altimeter, or 

global positioning system (GPS) unit.

• Slope gradient (percent)—Recorded from a laser or clinometer.17

• Aspect (°)—Plot aspect.

• GPS location—Coordinate system, latitude, longitude, position error.18 

The following sections are organized to assist with custom fuelbed creation 

within the Fuel and Fire Tools (FFT) application. The fuelbed editor within FFT is 

organized in tabs, starting with fuelbed description. Additional tabs organize inputs 

by fuel stratum, including the canopy, shrub, herb, wood, litter-lichen-moss, and 

ground fuels stratum. Many inputs, including vegetation cover, can be sampled by 

multiple methods, and this guide includes details and suggested forms to support 

common methodologies. In most cases, field data would need to be collected and 

summarized prior to creating custom fuelbeds.

Canopy

The canopy stratum is made up of live and dead canopy fuels including live trees 

(tree category), standing dead trees (snag category), and ladder fuels. Required data 

and recommended methodologies are detailed by category.

Trees

FCCS divides the tree category into three subcategories. Recently dead trees 

(termed class 1 snags with foliage) share the same inputs and can be sampled as an 

additional tree category.

• Overstory trees: dominant trees

• Midstory trees: codominant or intermediate trees

• Understory trees: understory trees, including seedlings and saplings19

Trees are defined as tall, perennial woody plants with a central trunk and 

branches forming distinct elevated crowns. There is no clear distinction between tall 

shrubs and small trees, and FCCS allows you to define them as either. If you enter a 

species as a tree in FCCS, it will not contribute to surface fire behavior predictions.

17 See Lutes et al. (2006) on how to measure a slope.

18 See Lutes et al. (2006) on how to record a GPS location.

19 Surface fire behavior equations in FCCS do not consider understory trees.
18

GENERAL TECHNICAL REPORT PNW-GTR-972

With the exception of total percentage cover, the following inputs are required 

for each tree layer category, and recommended sampling methods are suggested by 

input variable (table 3). Some forested fuelbeds only have a single layer whereas 

more structurally complex fuelbeds may have all three layers. 

• Percentage cover (m)

• Height (m)

• Height to live crown/height to crown base (m)

• Density (number per hectare)

• Diameter at breast height (cm)

• Species and relative cover (percentage)

Sampling design—

Sampling design and plot size will differ greatly depending on forest type. 

FIREMON recommends a default 0.1-m2

 circular plot (table 4) and, on average, a 

minimum of 20 trees per plot. Plot radius may need to be expanded in areas with 

low tree density but should remain consistent throughout your sampling inventory. 

Table 3—Input variables for tree and class 1 snag-with-foliage categories

Variable Definition Sampling method

Units 

(hard limits)

Total percentage 

cover

Total percentage cover, by crown projection, 

of all trees including overstory, midstory, and 

understory canopy layers

Moosehorn

Spherical densiometer

Aerial photography

Satellite imagery

Percentage

(0–100)

Percentage cover Percentage cover, by crown projection, of each 

canopy layer

Plot estimation

Line intercept method

Percentage

(0–100)

Height Height of each canopy layer Laser clinometer Meters

(0–122)

Height to live 

crown

Height from ground to bottom of live canopy for 

each canopy layer

Laser clinometer Meters

(0–76.2)

Height to crown 

basea

Height to base of crown for recently dead trees 

(class 1 snags with foliage)

Laser clinometer Meters

(0–76.2)

Density Number of trees per unit area for each canopy 

layer

Fixed plot

Prism plot

Number per hectare

(0–123 500 ha-1)

Diameter at breast 

height

Diameter at breast height for each canopy layer Caliper or tape Centimeters

(0–508)

Scientific name Scientific name of species in each canopy class 

(overstory, midstory, understory, snag class)

— —

Relative cover Relative percentage of each species in each tree 

canopy class. Must sum to 100 percent.

Plot estimate

Inference from tree density

Percentage

(0–100)

— = not applicable

a

 Applicable to class 1 snags with foliage.
19

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Subplots may be required to sample seedlings, saplings, and pole-sized trees in 

dense stands. Field reconnaissance and preliminary sampling is advisable to determine consistent plot and subplot dimensions and the number of plots to be sampled. 

The most efficient strategy for collecting tree data for FCCS is to sample each 

tree in a given plot, categorize it as a living tree or snag, and record either canopy 

layer for living trees or snag class for dead trees. Once sampling is complete, you 

can calculate tree density and relative cover by overstory, midstory, and understory 

trees. Class 1 snags with foliage may simply be tallied by a live/dead designation of 

dead trees with foliage.

Total coverage—

Total percentage cover (percent) is the percentage of the plot covered by crown projection of all live trees, including overstory, midstory, and understory tree canopy 

layers, and class 1 snags with foliage. Trees are considered to be alive if they have 

any green foliage in their crowns. For example, deciduous trees generally have no 

canopy cover when they are dormant (i.e., “leaf off”). When sampling a forest with 

deciduous tree species, there will likely be a dramatic difference in canopy cover 

and other fuelbed characteristics between growing and dormant seasons. If you 

are interested in capturing seasonal differences in fuelbeds, we suggest that you 

construct at least two different fuelbeds to represent leaf-on and leaf-off conditions. 

There are several approaches to estimating total percentage of canopy cover, 

including: 

• Ground estimates using a moosehorn

• Hemispherical camera

• Line-intercept coverage estimate

• Natural fuels photo series

• Remote sensing techniques, including aerial photos and satellite imagery

Table 4—Plot size recommendations based on median tree diameter and heighta

Median tree diameter Median tree height Plot radius Plot size

Centimeters - - - - - - - - - -Meters - - - - - - - - - Hectares

<50 <3 11.28 0.04

<100 30–90 12.6 0.05 

<200 >90 17.84 0.1

a

 Source: Keane 2006.
20

GENERAL TECHNICAL REPORT PNW-GTR-972

Ground-based estimates of canopy cover—Sampling time and intensity will depend on the technique you choose. For rapid measurements of total canopy cover, a 

self-leveling moosehorn is your best option (Fiala et al. 2006). Estimating tree cover 

along line intercepts is the most time-consuming technique, but where possible, 

allows for systematic estimates of tree cover by layer (i.e., overstory, midstory, and 

understory) and by species. Each method is detailed below.

Moosehorn—To adequately measure percentage cover, you will need 30 to 100 

samples per forested stand. We recommend that you conduct a preliminary analysis 

to determine required sample size. A potential option is to establish three slopecorrected transects radiating from each plot center and take self-leveling moosehorn measurements at regular intervals along each transect (after Fiala et al. 2006).

A moosehorn consists of a right-angled PVC tube with a mirror sight. At each 

measurement site, hold the moosehorn level using the leveling bubble. Using the grid 

in the sight, at each intersection, determine whether the grid or crosshair crosses tree 

canopy or sky. These determinations are tallied, and percentage canopy cover is calculated as the percentage of all observations that were recorded as tree (app. 1, form 3).

Line-intercept method—The line-intercept method is time intensive but provides 

estimates of percentage cover by tree canopy layer and by tree species. A minimum 

of 51 m of transect is recommended per 0.04-ha plot. Fiala et al. (2006) established 

three slope-corrected 17-m transects radiating from each 0.25-ha plot center and 

sampled intersection lengths of canopy cover along each transect. 

Canopy cover is recorded for each individual tree and includes the entire length 

of the vertically projected crown cover along the transect tape (interstitial spaces 

are included in this estimate) (app. 1, form 4). Tree canopy position (overstory, 

midstory, and understory) and species are recorded for all trees >1.4 m tall (fig. 5). 

Shrub and herb cover also can be recorded along transect lines (see next section). 

Total percentage cover, including class 1 snags with foliage, is calculated as the 

percentage of total transect length covered by tree crowns, capped at 100 percent. 

Percentage cover by tree layer and species can be calculated in a similar fashion.

Natural fuels photo series—Depending on the vegetation type and location, 

your site may be reasonably represented by a photo series. You can access all of 

the available natural fuel photo series from the digital photo series (University of 

Washington 2016a). Older photo series on logging residues are sometimes available 

for locations but have not yet been incorporated in the digital photo series.

Although canopy data differ somewhat by series, they generally contain tree 

density, diameter at breast height, height, height to live crown, and height to crown 

base of live and dead trees. Canopy cover is not provided and would need to be 

estimated separately.
21

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Remote sensing techniques and other data sources—

Several LANDFIRE data layers are available that could be used to provide a 

coarse-scale characterization of forest canopies.20 The existing vegetation cover 

layer provides an estimate of the vertically projected, live canopy layer. Similarly, the existing vegetation height layer provides the average height of dominant 

vegetation cover, interpreted from 30-m Landsat Thematic Mapper images. 

Given that LANDFIRE is intended for broader scale analyses, we recommend 

that you visit the site and refine canopy values by visual stand inspection or 

photo series assessments.

Interpreted LiDAR images can provide highly accurate estimates of canopy 

cover and other canopy characteristics (Andersen et al. 2005). Aerial photointerpretation is also a good technique for estimating canopy cover and other canopy 

characteristics (e.g., Hessburg et al. 1999).

If you have stand exam data already entered in the Forest Vegetation Simulator 

(FVS), you may use the FVS to provide stand summary data (tree density, diameter, 

height, crown base height, and crown radii) that could be used to populate FCCS 

canopy characteristics (Fiala et al. 2006). 

Figure 5—Individual tree crown cover vertically projected on a sampling transect.

20 http://www.landfire.gov.
22

GENERAL TECHNICAL REPORT PNW-GTR-972

Percentage cover of each tree layer—

FCCS requires estimates of percentage cover by live tree layer (overstory, midstory, 

and understory) and class 1 snags with foliage. Because the tree canopy layers may 

overlap, percentage cover of overstory, midstory, and understory tree layers may 

sum to greater than 100 percent. However, the total canopy cover input value may 

not exceed 100 percent. You may want to visually estimate this value for an entire 

plot. A more empirical approach is to use the line-intercept method and record 

tree species and tree canopy layer (i.e., overstory, midstory, understory, and class 1 

snags with foliage) (app. 1, form 4). 

Tree layer definitions—

• Overstory layer—Dominant tree crowns

• Midstory layer—Codominant or intermediate tree crowns

• Understory layer—Understory tree crowns, including seedlings and and 

saplings that are less than 1.4 m tall 

• Class 1 snags with foliage—Recently dead trees (in the overstory, midstory, 

or understory) that still have foliage

Tree height—

Tree height is summarized by layer in FCCS. For quick estimates of layer height, 

you can take a single estimate of layer height. A more accurate and repeatable 

method is to sample height of each tree in your plot and assign each tree to a layer 

(overstory, midstory, understory, snags). Layer height is calculated as the average 

height of all trees within each layer.

Tree height is measured from the ground to tree top. For smaller trees such as 

seedlings and saplings, a height pole should be sufficient. For larger trees, use a 

clinometer or laser to estimate tree height. If the tree is leaning but with an angle 

greater than 45° from the ground, measure the length instead of the height of the 

tree. If you are using a clinometer, record the planar distance to the tree, your 

height, and angles of elevation (percent) to tree height to live crown, tree height, 

and tree base (fig. 6). If any angle of elevation exceeds 100 percent, increase your 

distance from the tree. 

Tree height is calculated as:

y = θ1 (x / 100) – θ2 (x / 100) , (1)

where

y = tree height or height to live crown (m),

x = distance to tree (m),

θ1 = angle of elevation to tree top (percent), and

θ2 = angle of elevation to tree base (often a negative number) (percent).
23

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Height to live crown—

Tree height to live crown (and height to crown base for class 1 snags with foliage) 

is measured as the distance from the ground to crown base (app. 1, form 2). Some 

trees may have a few live branches below the crown base, which should not be 

counted in this measure. For smaller trees such as seedlings and saplings, a height 

pole should be sufficient. For larger trees, use a clinometer or laser to estimate 

height to live crown (fig. 6). 

Density—

Density is measured as the number of trees in each layer. This variable can be summarized once all individual trees in a fixed plot have been sampled and categorized 

as overstory, midstory, understory, and class 1, 2, and 3 snags. 

Tree diameter at breast height is summarized by layer in FCCS. The most 

repeatable and accurate method for measurement is to survey each tree in each 

overstory, midstory, and understory layer (app. 1, form 2). Measurements are 

made to the nearest 0.25 cm at 1.37 m above ground. If the tree is on a slope, 

remove any basal accumulations and measure on the uphill side of the tree. If the 

tree is forked below diameter at breast height, record the diameter of each stem. 

If the tree is forked above diameter at breast height, measure the stem as if it 

were one tree.

Distance to tree (x)

Tree height

Height to live crown

θ1

θ2

Figure 6—Tree height and height-to-live-crown can be sampled with a laser or a clinometer. Clinometer measurements should be taken 

as a percentage. Refer to equation 1.
24

GENERAL TECHNICAL REPORT PNW-GTR-972

Species and relative cover—

Species and relative cover (the percentage of each species cover in overstory, midstory, 

and understory tree layers) can be visually estimated over an entire plot or surveyed. 

Measuring the relative cover of each species for each layer may be difficult and time 

consuming. In stands where each species has a similar crown shape and projection, 

you may be able to calculate the relative density of each species and use that value to 

represent relative cover. However, for more accurate estimates and in more diverse 

forest types (i.e., mixed conifer–hardwood forests), we recommend that you use the 

line-intercept method (see “Total Canopy Cover” above) and calculate relative cover as:

where

Relative cover = the percentage of total canopy cover comprised by each tree species,

i = tree species, and

%Cover = percentage of canopy cover by ground projection by tree species.

Snags

The snag category represents standing dead trees in the following four categories. 

• Class 1 snags with foliage: recently dead trees that still have dead foliage intact.

• Class 1 snags without foliage: recently dead trees that have lost their foliage. Bark and branches are intact and wood is sound.

• Class 2 snags: older dead trees. Coarse branches and bark are present. 

Wood is partially decayed.

• Class 3 snags: older dead trees. Branches and bark not present.

Input variables are defined in table 5. Field sampling techniques are the same as 

trees (detailed above). It will be most efficient to sample snags within tree plots and 

simply note if each tree is alive or dead. Dead trees would then be classified into 

one of the four FCCS snag categories. 

100 ( ) %Coveri

∑i%Coveri

(2)

Table 5—Snag input variables

Variable Definition Sampling protocol Units (hard limits)

Density Number of snags per hectare for each class Fixed plot Area 

(0–24 700 ha)

Diameter Diameter at breast height, or highest point if broken below 

breast height, of snags for each class

Measuring tape Diameter

(0–508 cm)

Height Height of snags for each class Laser clinometer Height

(0–122 m)

Scientific name Scientific name of species in each snag class — —

Relative cover Relative percentage of each species in each snag class. 

Must sum to 100 percent.

Percentage of total 

snag density

Percentage

(0–100)

— = not applicable
25

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Ladder Fuels

Ladder fuels have the potential to spread a surface fire into tree canopies (fig. 7). 

Currently, the variables minimum and maximum height are placeholders in FCCS 

and are not used in fire behavior calculations. Vertical continuity and ladder fuel 

type are used in the calculation of crown fire potential.

Minimum height—

Minimum height is the base height of ladder fuels. This variable can be measured 

directly by a height pole, clinometer, or laser (see “Tree” section).

Maximum height—

Maximum height from ground to top of ladder fuels. This variable can be measured 

directly by a height pole, clinometer, laser, or a combination of those tools (see 

“Tree” section).

Figure 7—Dead branches acting as ladder fuels.

Nichole Noyer
26

GENERAL TECHNICAL REPORT PNW-GTR-972

Is vertically contiguous?—

If ladder fuels are sufficiently abundant and continuous to provide vertical continuity between surface and canopy fuels, crown fire initiation potential increases. This 

answer is subjectively determined from field observations. 

Type—

Although multiple ladder fuels may exist for your fuelbed, select the most dominant 

ladder fuel type for inclusion in FCCS. Input variables are listed in table 6. Ladder 

types include:

• Arboreal lichen and moss (e.g., bearded lichen [Usnea spp.)

• Climbing ferns and other epiphytes (e.g., climbing fern or Spanish moss 

(Tillandsia usneoides)

• Dead branches (retained on trees)

• Leaning snags

• Profuse epicormic sprouting (e.g., side branching in recently thinned 

Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco])

• Stringy or fuzzy bark (e.g., eucalyptus bark)

• Tree regeneration 

• Vines/lianas (e.g., kudzu (Pueraria lobate [Wild.] Ohwi) or clematis)

Table 6—Ladder fuel input variables

Variable Definition Sampling protocol Units (hard limits)

Minimum height Height from ground to base of ladder fuels Laser clinometer Meters (0–23)

Maximum height Height from ground to top of ladder fuels Laser clinometer Meters (0–91)

Is vertically 

contiguous

Do surface and canopy provide vertical continuity 

between tree crowns and lower strata?

Field observation —

Type Type of ladder fuela Field observation —

— = not applicable.

a

 Arboreal lichen and moss (e.g., beard lichen [Usnea spp.]), climbing ferns, and other epiphytes (e.g., climbing fern or Spanish moss), dead branches 

(retained on tree), leaning snags, profuse epicormics sprouting (e.g., side branching in recently thinned Douglas-fir), stringy or fuzzy bark (e.g., 

eucalyptus bark [Eucalyptus spp.]), tree regeneration, or vines/lianas (e.g., kudzu [Pueraria spp.] or clematis [Clematis spp.]).
27

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Shrubs

Shrubs are low woody plants, generally with multiple stems. There is no clear distinction between tall shrubs and short broadleaf deciduous or evergreen trees, and FCCS 

allows you to define them as either. If you enter a species as a shrub in FCCS, it will 

contribute to surface fire behavior predictions. In contrast, if you enter the same species as a tree in FCCS, it will not contribute to predicted surface fire behavior.

The primary shrub layer is the main layer of shrubs. Primary and secondary 

layer shrubs can be delineated by height, shrub species groupings, or any other 

classification you choose (app. 1, form 5). 

The secondary shrub layer is an optional layer with a different species composition, height, biomass, or other distinguishing factor from the primary shrub layer. 

Surface fire behavior calculations treat the shrub stratum as a single layer and 

combine primary and secondary shrub layers (Prichard et al. 2013).

Shrub input variables in FCCS (table 7) include:

• Is needle drape sufficient to affect fire behavior?

• Percentage cover (percent) of primary and secondary shrub layers 

(if present), and of relative cover by shrub species

• Height (m)

• Percentage live (percent)

• Loading (Mg ha-1)

Table 7—Shrub stratum input variables by primary and secondary layer

Variable Definition Sampling protocol Units (hard limits)

Percentage cover Percentage cover by crown projection Line intercept, quadrant plots, 

photo series

Percentage

(0–100)

Height Average height from ground to top of shrub 

layer

Meter stick, clinometer, 

photo series

Meters

(0–22.9)

Percentage live Percentage of shrub biomass that is livinga Clip plots, field observation Percentage

(0–100)

Needle drape Is the needle drape sufficient to affect surface 

fire behavior?

Field observation Yes or no

Loading (optional) Loading of the shrub layerb Clip plots, allometric 

equations, photo series

Megagrams per 

hectare

(0–336)

Scientific name Scientific name of shrub species — Centimeters

(0–508)

Relative cover Relative percentage of each species. Must sum 

to 100 pecent.

Clip plots, field observation Percentage

(0–100)

— = not applicable 

a

 This input can differ markedly between growing and dormant seasons.

b

 Fuels Characteristic Classification System will calculate shrub loading if this value is left as zero in the fuelbed editor.
28

GENERAL TECHNICAL REPORT PNW-GTR-972

Sampling Design

Sampling strategy and plot size will vary widely depending on vegetation type. If 

you are sampling a shrub stratum under a forest canopy, use the same sample plot 

for canopy sampling to sample shrubs. To estimate shrub percentage cover and 

height, the FIREMON sampling guide recommends a default 0.04-ha circular plot 

with a minimum of five transects containing five sample point quadrats (fig. 8). If 

you are working in a shrub-dominated vegetation type, consult appendix C of the 

FIREMON sampling guide for specific sampling recommendations. 

15

12

9

6

3

0

Belt transect (m)

Figure 8—Sample layout of quadrats. In this example, a 15.25-m baseline is established in the bottom left corner of the macroplot. Transects are positioned at 3.05-m intervals along the baseline and 

run perpendicular to the baseline.
29

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Needle Drape

Suspended needles on a shrub understory can substantially increase fire hazard in 

some fuelbeds. For example, pine forests in the Southeastern United States with a 

shrub understory often have needle drape that is sufficient to affect fire behavior 

(fig. 9).21 This variable is recorded as either present or absent in FCCS.

Figure 9—Needle drape/suspended long needles on shrubs, Southeastern United States.

Susan Prichard

21 This variable is not used in the FCCS crown fire potential algorithms.
30

GENERAL TECHNICAL REPORT PNW-GTR-972

Percentage Cover

Percentage cover is input in primary and optional secondary shrub layers in FCCS 

and is the vertical projection of each layer over the ground surface. In deciduous 

shrub types, percentage cover estimates will vary markedly between leaf-on growing 

season conditions and leaf-off dormant season conditions; it may be useful to create separate fuelbeds to represent both vegetation states. Because shrub layers may 

overlap, percentage cover of the two layers may sum to greater than 100 percent. 

There are a variety of techniques to estimate percentage cover. This guide covers three main techniques: 

• Estimation of percentage cover in quadrats

• Line-intercept method

• Photo series guides 

Visual estimation of percentage cover by quadrat—

Estimating percentage cover in quadrats along lines is a more accurate method than 

estimating cover over entire plots or subplots (Lutes et al. 2006). For most vegetation types, FIREMON recommends sampling five quadrats along five transects 

per macroplot. A baseline is established, and transects are run perpendicular to the 

baseline at regular intervals. If the plot is on a slope gradient, the slope-corrected 

baseline runs upslope, and transects run across slope. 

Standard quadrat size is 0.5 by 0.5 m but will depend on your vegetation type. 

You may wish to mark the quadrat frame to delineate subplots with known percentages. You can then mentally group plant species within subplots (fig. 10). For larger 

shrubs, and if you are working in a shrub-dominated ecosystem, consult appendix 

C of the FIREMON sampling guide (Lutes et al. 2006).

Depending on the complexity of the shrub stratum, visual estimations of percentage cover can be difficult, and estimates can differ between observers. Cover 

guides (app. 4) can be helpful to calibrate your eye, and careful calibration between 

field observers is strongly recommended. Using cover classes may also provide 

more consistency between observers (table 8). Plants are still counted if they are not 

rooted within the quadrat frame but have measureable cover.

If a fuelbed has two distinct shrub layers composed of different species, you can 

record percentage cover and height by species and summarize inputs by primary 

and secondary species groupings. However, if the shrub stratum is divided into a 

primary and secondary layer based on height alone, it will probably be necessary to 

estimate percentage cover by species for each individual layer. Grouping all shrubs 

into a single layer or dividing them into two layers is completely optional and has no 

consequence on surface fire behavior calculations or total shrub stratum fuel loading.
31

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

5 cm 7.5 cm

12.5% 12.5%

25%

100%

50%

12.5 cm 25 cm

5 cm 1%

20 cm

25 cm

Figure 10—Sample quadrat with sample subplots and corresponding percentages (Lutes et al. 2006).

Table 8—Fire effects and monitoring system cover class codes 

Code Cover class Code Cover class

Percentage Percentage

0 No cover 50 45–55

0.5 0–1 60 55–65

3 1–5 70 65–75

10 5–15 80 75–80

20 15–25 90 85–95

30 25–35 98 95–100

40 35–45 — —

— = not applicable. 

Source: Adapted from Lutes et al. 2006.
32

GENERAL TECHNICAL REPORT PNW-GTR-972

Estimating percentage cover by line intercept—

Percentage cover of shrubs (and other understory plants) also can be measured along 

line intercept transects (app. 1, form 6). Each line defines the imaginary vertical plane 

to be measured. For each line, the total length of shrub cover that crosses the plane is 

counted and summed. Overlap of plant cover is common, and any given line can total 

more than 100 percent cover. The total number and length of transect lines will depend 

on the variability of shrub layers. If you are planning to estimate tree cover using the 

line-intercept method, it may be most efficient to sample shrubs and herbs along the 

same transect lines (see “Canopy: Total coverage” section above under “Canopy”).

Using a photo series guide to estimate percentage cover—

For rapid assessments of shrub stratum characteristics, a photo series guide may 

be used. Some photo series guides provide data on shrub cover (app. 1, form 7). 

Because photographs offer an oblique view of fuel properties rather than a vertical 

view, cover may be difficult to discern from photographs. For instructions on using 

the Natural Fuels Photo Series, refer to the shrub “Loading” section below.

Height

Average shrub height is recorded for each shrub layer. Shrub height may be 

measured along with percentage cover and percentage live estimates in quadrats 

(app. 1, form 5) or the line-intercept method (app.1, form 6). A tree pole or measuring rod or tape will be sufficient for most shrub heights. For taller shrub layers, you 

may need to use a laser or clinometer (see “Canopy: Tree height” section above 

under “Canopy”). 

Primary and secondary shrub layer heights may be calculated as the mean 

height of individual shrubs in each layer. For fairly uniform shrub layers, height 

may be estimated for the entire layer rather than by individual shrubs. Shrub layer 

height should be recorded as the average height of that layer rather than the maximum height of any specific shrubs within that layer.

Percentage Live

Percentage live is a measure of live biomass in each shrub layer. This variable takes 

into account that for most living plants, a portion of the biomass is dead. Percentage 

live can vary markedly by season. For example, for deciduous plants that retain their 

dead leaves, it may be necessary to construct different fuelbeds that represent standing live and dead shrub biomass during dormant and growing seasons. The most 

accurate method for estimating percentage live is through direct biomass sampling 

in clip plots and sorting live and dead vegetation. A less accurate but more expedient approach is to visually estimate this input while estimating percentage cover 

using either quadrats (app. 1, form 5) or the line-intercept method (app. 1, form 6). 
33

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Loading 

Shrub loading is an optional input in FCCS fuelbeds. The FCCS supports 29 allometric 

equations assigned by shrub species to estimate shrub biomass by input percentage 

cover. Using sampled fuel loading or estimates using local biomass equations will likely 

offer better estimates of shrub loading and will override FCCS calculations (table 9). 

There are a number of techniques for which to estimate shrub loading (or “biomass”): 

• Direct biomass sampling the most accurate technique

• Allometric equations can be used to estimate biomass from measured shrub 

height, percentage cover, or basal diameter

• The natural fuels photo series may be used to visually estimate shrub biomass

Direct biomass sampling—

Clip plots are the most accurate way to determine the loading of vegetation on a specific 

site (app. 1, form 8). However, they require considerable field time and a drying oven. The 

number of plots and sampling locations depends on the heterogeneity of the shrub stratum 

you are measuring. Clip plot locations should be evenly spaced along a grid across the 

vegetation type to be assessed (fig. 4). Lay the plot frame on the ground at each grid 

intersection (fig. 11). Place the same corner of the biomass square at each intersect. (e.g., 

top left hand corner in the southeast quadrat of the intersect). 

Sparse vegetation should be measured in 1- by 1-m plots. More consistent vegetation should be measured in 0.5- by 0.5-m plots. A minimum of 10 plots per sampling 

location is recommended. At ground level, clip all rooted vegetation within the plot 

frame. Dead shrubs that are no longer rooted in the soil are counted as downed wood. 

Separate vegetation into the following live and dead categories: grasses, forbs/herbs, 

and shrubs; and collect into labeled bags. 

Table 9—Sample calculation of loading of manzanita 

(Arctostaphylos columbiana Piper)a

Cover Loadinga b Cover Loadinga b

Percent Grams m-2 Percent Grams m-2

0 0.07 30 71.46

1 1.77 40 96.07

2 3.96 50 120.76

5 10.87 60 145.51

10 22.75 80 195.14

20 46.98 100 244.89

a

 Loading values in g m-2 are converted to either tons ac-1 or Mg ha-1 for entry into the Fuel 

Characteristics Classification System.

b

 Loading (g m-2) = 0.0681 + (2.5312COV) – (0.8305COV0.5).

Source: Martin et al. 1981.
34

GENERAL TECHNICAL REPORT PNW-GTR-972

When clip plots yield large quantities of vegetation, it may be more efficient 

to record the gross weight of each sample in the field and collect subsamples to 

estimate moisture content. Place each sample into a pre-weighed drying tin and dry 

in a drying oven at 21 °C for at least 48 hours. Record the dry weight. Calculate the 

percentage fuel moisture (eqs. 3 and 4) and use this to estimate the dry weight of 

your field sample, such that

Fuel moisture (percent) = (gross weight – dry weight) ∕ gross weight (3)

Dry weight (kg) = gross weight − (gross weight × fuel moisture) (4)

Allometric equations—

Allometric equations can be used to estimate shrub loading from commonly collected field measurements. Allometric equations are regression models developed 

from sampled biomass and its correlation with other measured variables such as 

percentage cover, height, and basal diameter. Regression models are appropriate 

only for data that fall within the variable ranges for which they were developed. For 

example, if an equation is based on sampled shrub heights of 1.5 to 3.0 m, it will 

not necessarily be reliable for shrubs shorter or taller than this. Allometric equations are also more generally reliable in the bioregion they represent. An equation 

for sagebrush created in central Arizona, for instance, may not correctly estimate 

biomass of sagebrush in eastern Oregon.

Figure 11—Clip plot biomass sampling.

Susan Prichard
35

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

The FCCS contains 31 standard biomass equations that can be used to estimate shrub loading based on input shrub percentage cover and height (table 9). 

Depending on available time and resources, you may opt to simply collect shrub 

percentage cover and height and rely on the general shrub equations that FCCS 

provides. If local allometric equations are available to you, they will likely be 

more reliable. Methods to estimate shrub percentage cover and height are detailed 

in previous sections. The FCCS shrub loading equations only require percentage 

cover and height, but many regional shrub biomass equations require basal diameter as well. Basal diameter is the stem diameter of an individual shrub, measured 

at ground level. 

Natural fuels photo series—

Shrub biomass can also be estimated using a photo series.22 All photo series volumes include shrub loadings, where present (app. 1, form 7). Photo series are land 

management tools that can be used to assess fuels through appraisal of living and 

dead woody material, vegetation, and stand characteristics. 

The natural fuels photo series, created by the FERA team, is a collection of 

volumes for quantifying unmanaged fuels, each representing a region of the United 

States. Photo series are also available for central Brazil and montane ecosystems of 

Mexico. A list of available photo series, ordering information, and a tutorial on how 

to use the photo series are available (FERA 2016).

The Digital Photo Series is a Web-based application to the Natural Fuels Photo 

Series 23 (also see footnote 22). It takes advantage of data collected for the published 

photo series, and the technology to create a software application that includes a 

fuels database—allowing users to search, browse, compare, and format output 

for other fire science software. However, because it does not support stereoscopic 

viewing of fuelbeds, it complements but does not replace the printed versions. The 

following sections detail how to use the photo series and are applicable to other 

sections in this guide (see footnote 23).

Getting started. Select an area in the landscape that is representative of the site 

you are interested in categorizing. To best match the conditions of your site, consider using more than one site and possibly more than one photo series to estimate 

various fuel characteristics. 

22 https://depts.washington.edu/nwfire/dps/.

23 Before you begin to use the photo series, read the “Note to users” section of each photo 

series. In this section, you will find important information for that specific photo series 

(e.g., calculations, loading specifics, and series limitations). 
36

GENERAL TECHNICAL REPORT PNW-GTR-972

Framing fuels. Frame your site into fuel categories. You may need to use multiple 

sites within a photo series or sites from other photo series to estimate the values you 

require for the various fuels within your site.

Making a visual inventory—Make a visual inventory by observing fuel and stand conditions within your site and compare them to the photographs. Observe the following:

• Characteristics of each fuel category. 

• Select a photo series, or multiple photo series, that closely matches or 

encompasses observed characteristics. 

• Using the data summary tables, look up the value(s) for the characteristics being estimated or interpolate a value between multiple photo series. 

Repeat steps for each characteristic inventoried. For more complex sites or 

larger areas, you may need to take multiple inventories. 

Using stereo photos—You may get an additional perspective on fuel arrangement by 

viewing the stereo photos with a stereoscope. The three-dimensional view can aid in 

the separation of fuel components and more accurately estimate characteristics.

Limitations—The photo series alone may not be sufficient for estimating a reliable 

estimate. In these cases, you will need to take actual field measurements. The following examples highlight some limitations of the photo series:

• Some fuel characteristics may not be distinguishable in a photograph. If 

you need these values for your inventory, you should measure or estimate 

them using a different tool or reference. 

• Fuels or vegetation may not be visible from a single vantage point at your 

field site or be obscured by other fuels. Make sure you make a thorough 

reconnaissance of the site before making your estimations. 

• If your site has seasonal variation in fuel conditions (e.g., a deciduous forest in leaf-on or leaf-off condition), be aware of what the photo series data 

actually represent relative to the current condition of your site. 

• The Natural Fuels Photo Series was developed over many years, and earlier 

volumes do not contain all of the variables collected in later volumes. In 

addition, data collected in an individual photo series are somewhat dependent on the ecosystem type. 

Scientific names—Scientific names are used throughout the photo series. You 

will find the species list with common names in the introductory section of each 

photo series. 
37

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Fuel categories crosswalk to FCCS—A crosswalk was created to help users enter 

photo series data into FCCS. Table 10 provides translation between FCCS inputs 

and data available in the Natural Fuels Photo Series. Not all categories will pertain 

to your fuelbed.

Herbs

The herbaceous (herb) stratum includes grasses, sedges, and other herbaceous fuels.

The primary herb layer is the main layer of vegetation within the herb stratum. 

Users can determine the primary layer based on a number of selection criteria 

including species, height, mass, etc. The secondary herb layer is an optional herb 

layer with a different species composition or height than the primary herb layer.

FCCS input variables for herbs (table 11) are very similar to those required for 

the shrub stratum and include: 

• Percentage cover (percent) of primary and secondary herbaceous layers (if 

present) and relative percentage cover (percent) by species 

• Height (m) 

• Percentage live (percent)

• Loading (Mg ha-1)

With the exception of shrub needle drape, all methods detailed in the shrub 

stratum section are applicable to the herbaceous stratum (app. 1, forms 5 and 6).

Table 10—Crosswalk from the natural fuels photo series to Fuel Characteristic Classification categories

Natural fuels photo series fuel category

Fuel Characteristic Classification System

Stratum Category

Saplings and trees ↔ Canopy Trees, snags

Shrubs (understory vegetation) ↔ Shrub Primary and secondary layers

Graminoids and forbs (understory vegetation) ↔ Herbaceous vegetation Primary and secondary layers

Woody materials ↔ Woody fuels Sound and rotten wood

Forest floor—litter or surface material ↔ Litter-lichen-moss Litter

Forest floor—lichen ↔ Litter-lichen-moss Lichen

Forest floor—cryptogams ↔ Litter-lichen-moss Moss

Forest floor—duff ↔ Ground fuels Duff
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GENERAL TECHNICAL REPORT PNW-GTR-972

Downed Wood 

Downed wood represents all downed and dead woody material in a fuelbed. Dead 

trees that are still standing are input in the snags category of the canopy stratum. 

Similarly, dead shrubs that are still rooted are input in the shrub stratum. 

The downed wood stratum is divided into four categories: 

• Sound wood: downed and dead sound wood

• Rotten wood: downed and dead rotten wood (coarse wood only)

• Stumps: remaining sawn or broken stems up to 1.4 m

• Piles: naturally occurring or human-made piles or accumulate downed wood

Brown’s planar intersect method (Brown 1974) is a standard approach for 

sampling downed wood. This technique involves counting intersections of wood 

particles with a vertical sampling plane (app. 1, form 9). All material less than 7.6 

cm in diameter is considered sound. Downed wood greater than 7.6 cm in diameter 

are separated into sound and rotten wood categories by time-lag class (table 12).

To survey downed wood using Brown’s method, locate a plot center within a 

designated fuelbed and mark the sampling point with a chaining pin or center stake, 

avoiding disturbance of the plot. To avoid sampling bias, it is recommended that you 

run planar intercept transects at randomly selected angles from plot center. The length 

and number of lines run can vary depending on the density of downed wood. Suggested length of transect lines is 20.1 m, and three to five lines are typically surveyed 

from each plot center. Fuel loadings can be underrepresented if the planar intersect 

lines have little to no intersects with downed wood. It is important to achieve an 

accurate loading; multiple lines and lengths can be run to achieve this goal (table 13). 

Table 11—Herb stratum input variables

Variable Definition Sampling protocols Units

Input limits

Percentage cover Percentage cover by crown projection of the herb layer 

(primary or secondary)

Line intercept, 

quadrant plots, 

photo series

Percentage 

(0–100)

Height Average height from ground to top of herb layer (primary 

and secondary

Meter stick, 

clinometer, photo 

series

Meters

(0–22.9)

Loading Loading of herb layer (primary or secondary) Clip plot, photo series Percentage 

(0–100)

Scientific name Scientific name of species in the primary or secondary 

herb layer

— —

Relative cover Relative percentage of each species in the primary or 

secondary herb layer. Must sum to 100 percent.

Clip plot, visual 

estimate

Percentage 

(0–100)

— = not applicable.
39

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Table 12—Downed wood input variables

Variable Definition Units

Input limits

Percentage cover Percentage cover of fine downed wood (1-hr, 10-hr, and 100-hr time-lag 

classes)

Percentage

(0–100)

Depth Average depth of fine wood (1-hr, 10-hr, and 100-hr time-lag classes) Centimeters

(0–304.8)

Sound 1-hr 1-hr time-lag class sound downed wood (≤0.6 cm diameter) Megagrams per hectare 

(0–112)

Sound 10-hr 10-hr time-lag class sound downed wood (0.6–2.5 cm diameter) Megagrams per hectare 

(0–112)

Sound 100-hr 100-hr time-lag class sound downed wood (2.5–7.6 cm diameter) Megagrams per hectare 

(0–448)

Sound 1,000-hr 1,000-hr time-lag sound downed wood (7.6–22.9 cm diameter) Megagrams per hectare 

(0–1121)

Sound 10,000-hr 10,000-hr time-lag sound downed wood (22.9–50.8 cm diameter) Megagrams per hectare 

(0–2242)

Sound >10,000-hr >10,000-hr time-lag sound downed wood (>50.8 cm diameter) Megagrams per hectare 

(0–2242)

Rotten 1,000-hr 1,000-hr time-lag rotten downed wood (7.6–22.9 cm diameter) Megagrams per hectare 

(0–1121)

Rotten 10,000-hr 10,000-hr time-lag rotten downed wood (22.9–50.8 cm diameter) Megagrams per hectare 

(0–2242)

Rotten >10,000-hr >10,000-hr time-lag rotten downed wood (>50.8 cm diameter) Megagrams per hectare 

(0–2242)

Table 13—Transect length by size class

Time lag class Diameter Transect length

Centimeters Meters

1-hr 0–0.64 1.8

10-hr 0.064–2.54 3.0

100-hr 2.54–7.62 20.1

Source: Adapted from Brown 1974.
40

GENERAL TECHNICAL REPORT PNW-GTR-972

Starting from the outer edge of the transect line and working in toward plot 

center, tally the number of wood particles (generic term for sticks or logs) that 

intersect the sampling plane by each size class (fig. 12). The actual diameter of the 

particle at the point of intersection determines the size class. For example, if a wood 

particle lies across the transect line, the correct measure is the actual diameter, not 

the horizontal length it spans across the intersection. A go-no-go gauge is helpful to 

accurately measure fine fuel diameter classes (fig. 13). For 1,000-hr fuels, species, 

width, length, and decay class are also recorded.

Fine Downed and Dead Wood

This category records the overall depth and percentage cover of fine (<7.6 cm) 

downed wood and is an important variable in surface fire behavior modeling. 

Because large-diameter fuels (>7.6 cm diameter) do not contribute to surface fire 

behavior, they are not included in the depth or percentage cover measurements.

Depth—

Downed wood depth represents the average depth of small-diameter downed wood 

(<7.6 cm) and is analogous to “fuelbed depth” in surface fire behavior modeling 

(Rothermel 1972). The Brown (1974) line intercept method for sampling downed 

wood has a technique for estimating downed wood depth along planar transect 

lines, and it has been adapted for use in FCCS. Fine wood depth is estimated as the 

highest particle height within a vertical partition of the planar intercept (fig. 14). If 

there is more than a 0.9-m gap between particles (e.g., a dead branch hangs over 

the intercept but is more than 0.9 m higher than the other downed wood within the 

partition), it is tallied but not factored into the depth measurement at that point. 

Because depth can vary considerably between sampling points, we recommend 

sampling at regular intervals along transect lines. A suggested sampling intensity 

is to measure depth within 0.3-m segments every 1.5 m until reaching 15 m along 

your transect line.

Total percentage cover—

Total percentage cover of fine downed wood represents the portion of ground area 

covered by <7.6 cm diameter downed wood. Because downed wood coverage is 

heterogeneous and sometimes obscured by live vegetation and litter, it is not easy 

to visually estimate. However, there is no good alternative, and use of cover guides 

(app. 4) may be the best option. 
41

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Meters

1-hr tally

10-hr tally

100-hr tally

1.8 3.0 4.6 6.1 9.1 12.2 15.2 20.1

2.54 cm

0.63 cm

7.62 cm

Figure 13—A wildland fire fuel sizing 

gauge (i.e., go/no-go gauge) can be 

used to quickly and accurately determine the size class of fine downed 

wood (Brown et al. 1974). Wood 

diameters are sampled as the actual 

diameter of the downed wood.

Figure 12—Suggested sampling intervals for downed wood by size class. Starting from the outer edge of the transect and working back 

to plot center, 1-hr fuels are sampled to 1.82 m; 10-hr fuels to 3.05 m); and 100-hr fuels and greater are sampled along the entire transect. 
42

GENERAL TECHNICAL REPORT PNW-GTR-972

Sound Wood

Sound wood is downed wood that has minimal decay. The FCCS inputs for sound 

wood include loadings by size class of small downed wood (<7.6 cm diameter) and 

large downed wood (>7.6 cm diameter). The two most common species and relative 

covers are assigned to small and large downed wood groups separately. If you cannot identify downed wood to species, you might consider using the two dominant 

species in the forest or shrubland you are sampling.

The standard method for sampling downed wood is to use the Brown (1974) 

planar intercept method (see above). Photo series can provide a faster but less 

accurate estimate of downed wood biomass.

1-foot-wide verticle partitions

Fuel

Duff

Litter

Mineral soil

Sample

point

Figure 14—Fine downed wood depth is sampled at regular intervals along the transect lines (e.g., 1.5 

to 1.9 m, 3.0 to 3.4 m, 4.5 to 4.9 m). Downed wood depth is recorded as the highest particle height in 

each 30-cm vertical partition, excluding fuels that are suspended more than 0.91 m above the other 

downed wood in the 91-cm vertical partition (Brown 1974).
43

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Rotten Wood

The rotten wood category enters fuel loading for less than 7.6 cm downed wood size 

classes. Rotten wood is defined as partially decomposed wood debris with obvious 

signs of decay, such that the material falls apart when kicked. The three rotten wood 

time lag classes are 1,000-hr, 10,000-hr, and >10,000 hr. Smaller rotten wood is 

generally too decayed to accurately sample. Species designations and relative cover 

apply to all rotten wood size classes. 

Rotten wood loadings are estimated along with sound wood. The standard 

method is the Brown (1974) planar intercept sampling protocol. Photo series can 

provide a faster but less accurate estimate of downed wood biomass.

Stumps

Stumps are defined as the remaining portion of a tree stem after it has been sawn 

or broken (fig. 15). Broken-top, dead trees that are greater than breast height (1.4 m) 

are generally considered to be snags and are recorded in the canopy stratum. The 

three stump categories are:

Sound stumps—Bark intact; hard when kicked

Rotten stumps—Bark may or may not be intact; represents decay classes 3, 4, and 

5; feels soft or punky when kicked 

Lightered stumps—Rotten with resin-soaked heartwood; particularly common in 

Southeastern pine stands

Figure 15—Stumps can contribute to long-term smoldering emissions.

Susan Prichard
44

GENERAL TECHNICAL REPORT PNW-GTR-972

The most efficient way to sample stumps is to include them in tree measurement 

plots (app. 1, form 2). For each stump, collect the following information (table 14):

• Category (sound, rotten, or lightered)

• Diameter

• Height

• Species 

• Density

1. Density. Density refers to the number of stumps per hectare. Number of 

stumps can be sampled along with trees and snags (see “Canopy stratum” 

above). Stumps can be tallied by category to calculate sound, rotten, and 

lightered-stump densities. 

2. Diameter. For all stumps less than breast height, diameter should be measured at the top of each stump using a standard measuring tape or caliper. 

For sawn stumps greater than breast height, diameter should be measured at 

breast height using a diameter tape. 

3. Height. Height of each stump should be sampled from the ground to the top 

of each stump. Each stump should include a decay class category.

4. Species and relative cover. Species of each stump should be recorded. 

Once you have sampled all stumps, you can calculate the “relative cover” of 

each species for each stump category. For example, in the sound stump category, 70 percent of the stumps may have been loblolly pine [Pinus taeda L.] 

and 30 percent may have been slash pine [Pinus elliottii L.]. For consistency 

between canopy, shrub, herb fuel, and downed wood input screens, FCCS 

refers to the percentage each species by stump category as “relative cover.”

Table 14—Stump input variables applicable to sound, rotten, and lightered-pitchy categories

Variable Definition Sampling protocol

Units

(input limits)

Density Number of stumps per area Plot tally Number per hectare

(0–123,500)

Diameter Average depth of fine wood (1-hr, 10-hr and 

100-hr time-lag classes)

Measuring tape/stick Centimeters

(0–508)

Height Stump height, measured from the ground to 

top of the stump

Measuring tape/stick Meters

(0–1.5)

Scientific name Dominant woody plant species — —

Relative cover Relative percentage of each species. Must 

sum to 100 percent.

— Percentage

(0–100)

— = not applicable
45

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Piles

Piles are defined as accumulations of downed wood, including natural fuel accumulations (“jackpots”), hand piles, and machine piles. Pile inputs can be collected for use 

in the online pile calculator (University of Washington 2016b) or FFT fuelbed editor to 

calculate pile volume and biomass within an FCCS fuelbed. Piles of the same dimensions can be compiled into groups (app. 1, form 10). More than one pile group can be 

specified to represent the piles in a fuelbed (e.g., 100 hand piles and 2 machine piles).

Required measurements differ between hand piles (piles that were not created 

by machines), and machine piles (material was piled using equipment) (table 15).

Hand-pile variables—

• Number of piles or number of piles per unit area

• Pile shape

• Pile dimensions

• Pile composition (hardwood/shrub or conifer)

Table 15—Machine and hand-pile inputs

Variable Definition Sampling protocol Units

Pile type Hand or machine Number per pile group Number of piles per hectare

Number of piles Number of piles per unit areaa Field observations —

Pile shape Geometric shape of pileb Measuring tape, laserc Meters 

Pile dimensions Necessary dimensions vary by pile shaped Field observation —

Pile composition Conifer, or shrub/hardwoode Field estimate —

Percentage soil Percentage of soil by volumef g Field observation Percent 

Packing ratio Pile packing ratiog h Field observation —

Pile species 

composition

Primary and optional secondary species to 

specify a wood densityg

Field observation —

Pile quality Rating of pile cleanliness including clean 

(hand piles), dirty, and really dirtyi

Field observation —

— = not applicable.

a

 Data can be organized into pile groups (of similar type and dimensions).

b

 Half sphere, parabola, half cylinder, half frustum, half cone with rounded ends, half ellipsoid, or irregular solid.

c

 Groups can be formed by piles of similar size and shape.

d

 Width, height, and length.

e

 Applicable only to hand piles.

f

 This measure accounts for soil that may be mounded below a pile and should be subtracted by the actual pile volume.

g

 Applicable only to machine piles.

h

 Piles with a lot of air space (10 percent), densely packed piles (20 percent), or very densely packed piles with large logs (25 percent).

i

 Pile quality refers to how coated pile particles are with dirt, and can affect pile emission calculations.
46

GENERAL TECHNICAL REPORT PNW-GTR-972

Machine pile variables—

• Number of piles

• Pile shape

• Pile dimensions

• Pile composition

• Percentage soil

• Packing ratio

• Species composition

• Pile quality

Number of piles—

Count the number of piles per area or across a burn unit. 

Shape and dimensions—

Pile shape and dimensions (m) inform which geometric equation will be used to 

estimate pile volume (fig. 16). 

Composition—

Hand piles—Record whether the pile group is dominated by broadleaf hardwood 

and shrub or by conifers.

Machine piles—Select up to two dominant tree species and their relative composition. In cases where species are not listed, proxy species with similar wood densities can be used.

Percentage soil—Estimate the percentage of pile, by volume, which is soil. This 

generally pertains to landing piles that may have mounds of soil under them.

Packing ratio— For machine piles only, select one of three options to best represent how densely packed the fuel particles are in a pile group: 

1. Ten percent (10 percent)—Piles dominated by long-needled pines or 

broadleaf deciduous litter. Mean diameter of large downed wood is less 

than 25 cm.

2. Twenty percent (20 percent)—Pile dominated by short-needled conifers. 

Mean diameter of large downed wood is less than 25 cm.

3. Twenty-five percent (25 percent)—Very compacted and clean piles generally 

constructed by a crane or loader. Mean diameter of logs is greater than 25 cm.
47

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

h

w

h

w

(1) Half-sphere—height (2) Paraboliod—width and height

h

w

I

(3) Half cylinder—width, height, and length

h1

h2

w1

w2

I

(4) Half-frustrum of a cone—width1, 

 width2

, height1, height2, length

h1

h2

w1

w2

I

1

I

2

(7) Irregular solid—width1, width2, height1, 

 height2

, length1, length2, 

h1

h2

w1

w2

I

(5) Cone with round ends—width1, width2, 

 length, height1

, height2, 

h

I

w

(6) Half ellipsoid—width, height, and length 

Figure 16—Various pile shapes and their dimensions.
48

GENERAL TECHNICAL REPORT PNW-GTR-972

Pile quality—

Machine piles can either be clean or mixed with soil, depending on how they were 

constructed (e.g., crane or bulldozer). Clean piles burn more efficiently than dirty 

piles. Record three levels of pile cleanliness for each pile group:

• Clean (no soil)

• Dirty (up to 10 percent soil)

• Very dirty (more than 10 percent soil)

Litter-Lichen-Moss

Litter, ground lichen, and moss (LLM) are treated as a single stratum in FCCS. 

Litter is the top layer of the forest floor (also called the O1 or Oi organic soil 

horizon) and is composed of loose debris of dead sticks, branches, twigs, and 

recently fallen leaves or needles; little altered in structure by decomposition.

Lichen grows on forest, shrubland, and grassland floors. The FCCS does not inventory arboreal lichen; they are included as a type of ladder fuels in the canopy stratum.

Moss grows on forest, shrub, and grassland floors, particularly in moist habitats.

Inputs are similar between LLM layers (table 16) and include depth, percentage 

of cover, type (for moss and litter), and litter arrangement. The LLM measurements 

are most efficiently sampled along downed wood planar intercept transects (refer to 

downed wood stratum) (app. 1, form 9).

Table 16—Litter-lichen-moss stratum inputs

Variable Definition Sampling protocol

Units

(input limits)

Depth Total depth of litter, lichen, or moss layer Ruler Centimeters

(0−76)

Percentage cover Percentage cover of litter, lichen, or moss layer based on 

linear or subplot coverage

— Percentage

(0−100)

Litter arrangement Dominant of three arrangements: normal, fluffy, or perched 

(on grass or forb)

Field observation —

Litter type Composition of litter type including short needle pine, long 

needle pine, other conifer, broadleaf deciduous, broadleaf 

evergreen, palm fronds, and grass

Clip plots, field 

observation

—

Relative percentage 

cover

Relative cover of each litter type. Must sum to 100 percent Clip plots, field 

observations

Percentage

(0−100)

Moss type Dominant of two types including sphagnum moss or other 

moss (e.g., feathermoss)

Clip plots, field 

observations

—

— = not applicable.
49

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Depth 

Depth refers to the thickness of each LLM layer. LLM depth is most efficiently 

sampled at regular intervals along downed wood transect lines (e.g., 1.5 to 1.8 m, 3.1 

to 3.4 m, 4.6 to 4.9 m) and is recorded as the vertical distance between the bottom 

and top of each layer (app. 1, form 9). For example, litter depth is measured as the 

top of the litter layer to the bottom, defined as the boundary between distinguishable 

litter and decomposed material (duff) (fig. 17). Depth of LLM is generally measured 

along an exposed vertical profile of the upper soil. Forest soils are variable, and 

frequent depth measurements will be required to obtain a reliable fuelbed estimate.

Roger Ottmar

Litter layer

Duff layer

Mineral soil

Figure 17—Litter and duff layers above mineral soil.
50

GENERAL TECHNICAL REPORT PNW-GTR-972

Percentage Cover

Percentage cover refers to the percentage of the ground covered by each LLM layer. 

The most efficient way to estimate percentage litter, moss, and ground lichen is 

to add these as categories in your shrub and herb surveys. If you use the quadrat 

method (app. 1, form 5) or the line-intercept method (app. 1, form 6) to estimate 

plant cover, simply record percentage cover of each litter type, each moss type, and 

ground lichen as additional plant species. 

Additional descriptors are required for moss and litter:

Moss Type

Record the dominant moss type for your fuelbed. 

• Sphagnum moss

• Other moss 

Litter Arrangement

Record the dominant litter arrangement for your fuelbed. The selected litter 

arrangement determines which inferred bulk density value FCCS uses in its loading calculations.

• Fluffy (freshly fallen). The most common occurrence of a “fluffy” litter 

arrangement is broadleaf deciduous litter in the autumn. Long-needled pine 

litter may also be considered fluffy. Other needle litter may also be relatively uncompact after a windstorm or other disturbance. 

• Normal. A normal litter arrangement includes most conifer-dominated litter 

types and broadleaf deciduous litter after compaction by rain and snow.

• Perched (on grass or forb). In fuelbeds with abundant herbaceous or 

downed wood, recently fallen litter may be perched on surface fuels.

Litter Type

Many fuelbeds will contain a mix of litter types. Assign a relative cover for each 

litter type that applies to your fuelbed.

• Short needle pine (i.e., lodgepole pine [Pinus contorta Dougl.])

• Long needle pine (i.e., ponderosa pine [P. ponderosa Dougl. ex Laws], 

loblolly pine, longleaf pine [P. palustris Mill.])

• Other conifer (i.e., Douglas-fir, larch [Larix spp.], hemlock, cedar)

• Broadleaf deciduous (i.e., maple [Acer spp.])

• Broadleaf evergreen (i.e., madrone [Arbutus spp.])

• Palm fronds 

• Grass
51

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Ground Fuels

The ground fuels stratum has three categories:

• Duff is organic soil between the LLM stratum and mineral soil. Duff is 

recorded in two layers: an upper layer representing the Oe soil horizon 

and a lower layer representing the Oa soil horizon. These layers are also 

called fermentation and humic layers, respectively. Many fuelbeds have 

only a single, upper duff layer, but boreal and high-elevation forests often 

have two duff layers. The upper duff layer contains partially decomposed 

organic matter in which tree needles, leaves, and other material are identifiable. The lower duff layer, where it exists, contains mostly decomposed 

organic matter and is much denser than the upper duff layer.

• Basal accumulations are accumulations of bark, downed wood, and forest 

floor surrounding tree trunks.

• Squirrel middens are mounds of litter, tree cones, and other plant material 

accumulated by squirrels; these are generally limited to boreal-spruce-dominated forest fuelbeds in Alaska.

Duff

Depth—

Depth refers to the thickness of each duff layer (table 17). Upper duff depth is the 

average depth from the base of the litter layer to the top of the lower duff layer. 

Lower duff depth is the average depth from the base of the upper duff layer to the 

start of mineral soil. Forest soils are generally variable, and multiple depth measurements will be necessary to obtain a reliable estimate (see LLM “Depth” section on 

page 49).

Table 17—Upper and lower duff layer input variables

Variable Definition Sampling protocol

Units

(input limits)

Depth Total depth of upper of lower duff layer Ruler Centimeters

(0–508)

Percentage cover Percentage cover of the upper or lower duff layers based on 

linear or subplot coverage

Ocular Percentage

(0–100)

Derivation Derivation of upper duff layer or lower duff layers (2 options 

each)

Clip plots, field 

observation

—

Loading Optional loading by layera Clip plot Megagrams per 

hectare (0–448)

— = not applicable.

a

 If left at zero, Fuels Characteristic Classification System will calculate loading.
52

GENERAL TECHNICAL REPORT PNW-GTR-972

Percentage cover—

Percentage cover is estimated as the percentage of the ground area covered by each 

duff layer (see LLM “Depth” section). 

Derivation—

Derivation is recorded for each duff layer. There are two derivation types per layer:

Upper duff—

• Partially decomposed moss and litter.

• Partially decomposed sphagnum moss or sedge, generally found in bogs 

and boreal tussocks.

Lower duff—

• Fully decomposed moss and litter.

• Fully decomposed sphagnum moss or sedge, generally found in bogs and 

boreal tussocks.

Loading—

Upper and lower duff loading values are optional inputs and can be estimated by 

multiplying measured depth by measured bulk density and proportional cover 

(percentage divided by 100). Inferred bulk density values within FCCS are listed in 

table 18.

Basal Accumulations

Basal accumulations are twigs, bark pieces, litter, and duff that accumulate and 

form a deep organic layer surrounding the base of trees (fig. 18). Inputs are defined 

in table 19.

Table 18—Inferred bulk density values by duff type and derivation

Duff type Bulk density

Mg ha-1 cm-1

Partially decomposed moss and litter 1

Partially decomposed sphagnum moss or peat 1

Fully decomposed moss and litter 7

Fully decomposed sphagnum moss or peat 16
53

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Depth

Radius

Figure 18—Diagram of a basal accumulation. 

Table 19—Basal accumulation input variables

Variable Definition

Sampling 

protocol Units (input limits)

Depth Depth of basal accumulation of ground fuels around tree trunks Ruler Centimeters (0–127)

Radius Radius of basal accumulation of ground fuels around tree trunks Ruler, laser Meters (0–6)

Density Density of trees with basal accumulations Tally Number per hectare 

(0–127,000)

Type Type of basal accumulationa — —

Loading Optional loadingb Clip plot Megagrams per hectare 

(0–336)

— = not applicable.

a

 Bark slough, branches, broadleaf deciduous litter, broadleaf evergreen litter, grass, palm fronds, needle litter. 

b

 If left at zero, Fuels Characteristic Classification System will calculate loading.
54

GENERAL TECHNICAL REPORT PNW-GTR-972

Depth—

Depth is generally measured in several median locations within the sloped ring of 

tree basal accumulations and averaged for a single depth (app. 1, form 11).

Radius—

Radius is measured from the outer edge of the tree trunk to the outer edge of the 

basal accumulation. Because basal accumulations may be irregular in shape and 

differ between trees, you may wish to take multiple depth and radius measurements 

and report modal (i.e., the most commonly occurring) values.

Density—

Density is the number of trees with basal accumulation per unit area. 

Type—

Note the dominant basal accumulation type of your fuelbed. Options include:

• Bark slough: accumulated pieces of old bark

• Branches: dead tree and shrub branches

• Broadleaf evergreen: dead leaves of broadleaf evergreen trees and shrubs

• Broadleaf deciduous: dead leaves of broadleaf deciduous trees and shrubs

• Grass: grass litter

• Needle litter: dead conifer needles

• Palm fronds: dead palm fronds

Loading—

Basal accumulation loading is an optional input and can be estimated by first 

calculating the volume of a representative basal accumulation and then calculating 

loading based on measured bulk density. Because basal accumulations form around 

tree stems, the volume of the trees stems in the center of the basal accumulation 

must be subtracted from an estimated gross volume. Table 19 lists inferred bulk 

densities by derivation type.

Where

volume (m3

) = gross volume – tree stem volume,

density (ha-1) = number of basal accumulations per hectare,

bulk density (kg m-3) = bulk density of basal accumulation type (table 20), and 

conversion kilograms to megagrams (Mg kg-1) = 0.001,

and where

gross volume (m3) = π × depth (m) × radius (m2), and

tree stem volume (m3

) = π × depth (m) × overstory tree radius (m2) / 8.

Loading (Mg ha-1) = volume (m3) × density (number per ha-1) 

× bulk density (kg m-3) × 0.001 (Mg kg-1) (5)
55

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Squirrel Middens

Squirrel middens are mounds of cone scales and other cone debris accumulated 

over time from generations of squirrels extracting seeds from cones. The mounds 

are composed exclusively of organic matter that can burn for extended periods of 

time. They are generally found in boreal forests and are uncommon in the contiguous United States. 

Depth—

Depth is generally measured in several median locations within squirrel middens 

(app. 1, form 12) and averaged for a single depth input (table 21).

Radius—

Radius is measured from the center of the squirrel midden to the outer edge of the 

accumulation (fig. 19). Because squirrel middens may be irregular in shape and 

differ between trees, you may wish to take multiple depth and radius measurements 

and report modal (i.e., the most commonly occurring) values.

Table 20—Inferred bulk density values by basal 

accumulation type 

Type Bulk density

Mg m-3

Bark slough 98.67

Branches 98.67

Broadleaf deciduous 61.36

Broadleaf evergreen 61.36

Grass 45.57

Needle litter 59.20

Palm fronds 45.57

Table 21—Squirrel midden input variables

Variable Definition Sampling protocol Units (input limits)

Depth Average depth of squirrel middens Ruler Centimeters (0–508)

Radius Average radius of squirrel middens Ruler, laser Meters (0–15.2)

Density Number per unit area of squirrel middens Tally Number per hectare (0–101)

Loading Optional loadinga Clip plot Megagrams per hectare (0–560)

a

 If left at zero, Fuels Characteristic Classification System will calculate duff loading.
56

GENERAL TECHNICAL REPORT PNW-GTR-972

Loading—

Squirrel midden loading is an optional FCCS input that can be estimated by first 

calculating the volume of the midden and then calculating loading based on measured bulk density (g m-3) of the squirrel midden material. The FCCS inferred bulk 

density value for squirrel middens is 97.12 g m-3.

Volume (m3

) = [π Depth (m) × Radius (m)2] / 8

Loading (tons m-2) = Volume (m3) × Density (# m-2) × 

Bulk density (kg m-3) × 410.95 kg kg-1

Density—

Density is the number per unit area of squirrel middens.

Conclusions

Methods presented in this guide are intended to provide guidelines for measurement 

of input variables and development of FCCS fuelbeds. The FCCS was designed to 

represent the spatial and temporal variability of wildland fuels. Fuelbeds can be 

constructed to characterize fuels in six strata including canopy, shrubs, herbaceous 

fuels, downed wood, litter–lichen–moss, and ground fuels. Each stratum is further 

divided into one or more categories and subcategories. A fuelbed can represent 

any scale that is relatively uniform on the landscape that represents a distinct fire 

Depth

Radius

Figure 19—Diagram of a squirrel midden.
57

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

environment. A planned prescribed burn unit, for example, may contain many stand 

types that can be represented by individual fuelbeds. Alternatively, fuelbeds can be 

constructed to represent growing season versus dormant season conditions to reflect 

temporal changes in available fuels throughout the year.

Although there are over 300 possible fuelbed inputs, constructing fuelbeds to 

represent a specific site does not have to be an exhaustive process. Because FCCS 

was designed to accommodate wildland fuel characteristics across a range of 

geographic locations and ecosystems, many fuelbed inputs may not apply to regionally- or site-specific fuelbeds.

The amount of field sampling required for fuelbed customization depends on 

the intended application. For prescribed burning with a low probability of affecting 

tree crowns, customizing the fuelbed could focus on surface and ground fuel characteristics, including shrubs, grasses, downed wood, litter, and duff. In contrast, 

fuelbeds may also be constructed to represent total carbon stores of a particular site. 

In that case, careful accounting of fuel characteristics from ground to canopy fuels 

may be required.

Acknowledgments

We thank the many fire and fuels managers who have participated in FCCS workshops over the years and provided feedback on FCCS fuelbed development. We also 

thank present and past members of the Fire and Environmental Applications team 

for contributing to fuelbed design and development including Paige Eagle, Jennifer 

Long, David L. Peterson, Joseph Restaino, Cynthia Riccardi, David Sandberg, Kjell 

Swedin, Clint Wright, and Bob Vihnanek. We acknowledge funding from the Joint 

Fire Science Program (JFSP) for their initial support of development of the FCCS 

under JFSP projects #98-1-1-06, #04-4-1-02, #04-2-1-49, and #11-2-1-11. 

U.S. Equivalents

When you know: Multiply by: To find:

Inches 2.54 Centimeters

Feet .305 Meters

Acres .405 Hectares

Square feet .0929 Square meters

Cubic feet .0283 Cubic meters

Pounds .454 Kilograms

Pounds per square foot 4.88 Kilograms per square meter

Pounds per cubic foot 16.0185 Kilograms per hectare

Number per acre 2.471 Number per hectare

Degrees Celsius (°C) 1.8 °C +32 Degrees Fahrenheit 
58

GENERAL TECHNICAL REPORT PNW-GTR-972

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Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

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Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Appendix 1: Fuel Characteristic Classification System 

Field Sampling Forms 

Page number

Form 1—Fuelbed description and search variables 62

Form 2—Total canopy cover sampling form (general) 63

Form 3—Total canopy cover sampling form (moosehorn method) 64

Form 4—Total canopy cover sampling form (intercept method) 65

Form 5—Shrub and herb sampling form (quadrat method) 66

Form 6—Shrub and herb sampling form (intercept method) 67

Form 7—Shrub and herb characteristics (photo series method) 69

Form 8—Clip plot sampling form 70

Form 9—Downed wood, litter-lichen-moss, and duff sampling form 71

Form 10—Pile group sampling form 72

Form 11—Forest floor sampling form 73

Form 12—Basal accumulation and squirrel midden sampling form 74
62

GENERAL TECHNICAL REPORT PNW-GTR-972

SAF or SRM cover type (list all that apply)c d

a Latitude and longitude, Universal Transverse Mercator (UTM), or Albers equal area conic projection (Albers). b For example, geographic location, major vegetation, disturbance, and management history.c Eyre 1980.d

Ecoregion (select all that apply)

□

 Shiflet 1994.

 120: Tundra 

□ 130: Subarctic □ 210: Warrn continental □ 220: Hot continental □ 230: Subtropical □ 240: Marine □ 250: Prairie□ 310: Tropical/subtropical desert □ 320: Tropical/subtropical steppe 

Desert

□ 340: Temperate desert □ 410: Savanna □ 420: Rainforest

Vegetation form (select one)

□ Broadleaf forest □ Conifer forest □ Grassland mixed forest □ Savanna □ Shrubland □ Slash

Stand structural class (select one)

□ Old-forest multistory □ Old-forest single story □ Stand initiation □ Stem-exclusion closed canopy □ Stem-exclusion open canopy □ Understory reinitiation □ Young forest-multistory 

Change agent (select all that apply) Change over time

□ Fire exclusion □ Introduction of exotic spp. □ Stand development

Fuel treatments

□ Chipping □ Lop and scatter□ Mastication □ Pile and burn □ Prescribed fire 

Timber harvest 

□ Pruning □ Clearcut □ Logging methods/equipment □ Salvage logging□ Stumpwooding□ Thinning (thin from below)

Land use change

□ Ditching/draining□ Paving

Natural event 

□ Avalanche □ Flood □ Ice damage □ Insects and disease □ Landslide □ Windthrow 

Vegetation

□ Grazing □ Residual fertilization□ Tree planting □ Restoration work □ Tree planting□ Turpentining

Wildfire 

□ Wildfire□ Wildfire (ground)□ Wildfire (crown)

Descriptionb

Fuelbed name

Plot ID

Plot dimensions 

Field crew

Date

Elevation 

Slope gradient (%)

Aspect (°)

Coordinate systema

Latitude

Longitude

GPS location

GPS error

Form 1—Fuelbed description and search variables
63

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Canopy

Percentage cover

Total canopy

Overstory

Midstory

Understory

Live tree ID number

Species 

code Layer

Alive or 

dead

Snag decay 

class

Stump decay 

class DBHa Height

Height to live 

crown

Basal 

accum? Notes

O, M, Ub L, Dc 1F, 1, 2, 3d S, R, Le Centimeters Meters Yes/No

1234567891011121314151617181920

a Diameter at breast height.b O = overstory, M = midstory, U = understory.c L = alive, D = dead.d 1F = class 1 snag with foliage, 1 = class 1 snag, 2 = class 2 snag, 3 = class 3 snag.e S = sound, R = rotten, L = lightered.

Ladder fuels

Characteristics

Minimum height (m)

Maximium height (m)

Vertical continuity?

Ladder fuels—select one type

□ Arboral lichens and moss□ Climbing ferns and other epiphytes□ Dead branches□ Leaning snags

□ Profuse epicormic sprouting□ Stringy or fuzzy bark□ Tree regeneration□ Vines/lianas

Form 2—Total canopy cover sampling form (general)
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GENERAL TECHNICAL REPORT PNW-GTR-972

Form 3—Total canopy cover sampling form (moosehorn method)

Fuelbed name

Plot ID

Date

Field crew

Description

 

 

 

Point No. Transect 1a Transect 2a Transect 3a Point No. Transect 1a Transect 2a Transect 3a
65

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Form 4—Total canopy cover sampling form (intercept method)

Fuelbed name

Plot ID

Date

Field crew

Description

 

 

 

Transect 

ID

Tree 

number Species Status Tree layer Start Stop Distance

L/Da (O, M, U)b - - - - - Meters - - - - - 

a

 L = alive, D = dead.

b

 O = overstory, M = midstory, U = understory.
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GENERAL TECHNICAL REPORT PNW-GTR-972

Form 5—Shrub and herb sampling form (quadrant method)

Fuelbed name

Plot ID

Date

Field crew

Description

 

 

 

Transect Quadrant Species Percentage live Layer Cover codea height

ID Number — Percent Primary or secondary — Meters

a

 Cover code:

0 = no cover 0.5 = >0–1% 3 = >1–5% 10 = >5-15% 20 = >15–25% 30 = >25–35% 40 = >35–45%

50 = >45–55% 60 = >55–65% 70 = >65–75% 80 = >75–85% 90 = >85–95% 98 = >95–100%
67

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Form 6a—Shrub and herb sampling form (intercept method)

Fuelbed name

Plot ID

Date

Field crew

Transect length

Sampling notes

 

 

Shrub and herb cover by line intercept method—

Transect ID Species Layer Percentage live Height Start Stop Distance

Number — 1, 2a Percent - - - - - - - Meters - - - - - - -

a

 1 = primary layer, 2 = secondary layer.

Transect summary by primary or secondary shrub/herb vegetation layer—

Transect ID Total Distance Transect length Percentage cover

Number - - - - - - - - - - - - - - - Meters - - - - - - - - - - - - - - - Percent

1

2

3

4

5

6

7

8

9

10

Plot cover (%)
68

GENERAL TECHNICAL REPORT PNW-GTR-972 Form 6b— Transect Point Litter Lichen Moss Duff Upper Lower Cover Depth Arrangement Type1 Cover Depth Cover Depth Type Cover Depth Cover Depth

Percent cm F, N, P2 Percent cm Percent cm S, O3 Percent cm Percent cm

1 11 21 31 41 52 12 22 32 42 53 13 23 33 43 54 14 24 34 44 5
69

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Form 7—Shrub and herb characteristics (photo series method)

Fuelbed name

Plot ID

Plot dimensions

Primary shrub layer—

Photo series volume and ID

Percentage cover (%)

Layer height (m)

Loading (Mg ha-1)

Species list—

Secondary shrub layer—

Photo series volume and ID

Percentage cover (%)

Layer height (m)

Loading (Mg ha-1)

Species list—

Primary herb layer—

Photo series volume and ID

Percentage cover (%)

Layer height (m)

Loading (Mg ha-1)

Species list—

Secondary herb layer—

Photo series volume and ID

Percentage cover (%)

Layer height (m)

Loading (Mg ha-1)

Species list—

Is needle drape sufficient to affect fire behavior? Yes No

Date

Field crew

Subplot dimensions

Plot notes

 

 

 
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GENERAL TECHNICAL REPORT PNW-GTR-972

Form 8—Clip plot sampling form

Fuelbed name

Plot ID

Date

Field crew

Clip plot dimensions

Notes

 

 

Plot ID Material type Bags per sample Bag weight Net dry weight Notes

Shrub, shrub, LLMa

, or 

ground fuel Number Grams Grams

a

 Litter, lichen, and moss
71

Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Fuelbed name

Plot ID

Plot dimensions

Date

Field crew

Duff derivation

Plot description

Form 9—Downed wood, litter-lichen-moss, and duff sampling form

Transect direction Fine wood tally Course wood measurements

Transect

Diameter

Transect Azimuth <0.64 cm 0.64–2.54 cm 2.54–7.62 cm Transect Diameter Species Decay class

Degrees Number of pieces of wood centimeters — 1, 2, or 3a

1 1 12 2 23 3 34 4 45 5 56 6 67 7 78 8 89 9 9

10 10 10

11 11 11

12 12 12

13 13 13

14 14 14

15 15 15

16 16 16

17 17 17

18 18 18

19 19 19

20 20 20

21 21 21

22 22 22

23 23 23

24 24 24

25 25 25

26 26 26

27 27 27

28 28 28
72

GENERAL TECHNICAL REPORT PNW-GTR-972 Pile group Typea All piles Hand piles only Machine piles only Relative cover Soil Packing ratio Pile quality Shapeb W1c W2 H1 H2 L1 L2 Compositiond Species 1 Species 2 ID number — — - - - - - - - - - Meters - - - - - - - - - — - - - - - - Percentage - - - - - - 10, 20, or 25% Clean, dirty, really dirty

a M = machine, H = hand.b 0 = half sphere, 1 = paraboloid, 2 = half cylinder, 3 = half fulstrum of cone, 4 = half fulstrum of cone with rounded ends, 5 = half ellipsoid, 6 = irregular solid.c W = width, H = height, L = length.d c = conifer, h = hardwood.

Fuelbed name

Sampling area (ha)

Date

Field crew

Form 10—Pile group sampling form

Site notes
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Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Form 11—Forest floor sampling form

Transect Point

Litter Lichen Moss Upper duff Lower duff

Cover Depth Arrangementa Typeb Cover Depth Cover Depth Typec Cover Depth Cover Depth

Percent cm F, N, P — Percent cm Percent cm S, O Percent cm Percent cm

1 51 101 151 201 251 301 351 401 451 502 52 102 152 202 252 352 402 452 503 53 103 153 203 253 303 353 403 453 50

a Litter arrangement (F = fluffy; N = normal, P = perched).b Litter type (SP = short-needled pine, LP = long-needled pine, OC = other conifer, BD = broadleaf deciduous, BE = broadleaf evergreen, PF = palm frond, GR = grass).c Moss type (S = sphagnum, O = other).
74

GENERAL TECHNICAL REPORT PNW-GTR-972 Form 12—Basal accumulation and squirrel midden sampling form Fuelbed name Plot ID Date Site notes

Basal accumulation measurements— Squirrel midden measeurements—Group Depth Radius Density Typea Group Depth Radius Density Typea

Centimeters Meters No. per hectare Centimeters Meters No. per hectare

1 12 23 34 45 56 67 78 89 910 10

a BD (broadleaf deciduous); BE (broadleaf evergreen [e.g., madrone (Arbutus spp.)]); BR (branches); BS bark slough); G (grass); NL (needle litter); P (palm fronds).
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Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Appendix 2: Slope Correction Table

Plot size in hectares

0.05 0.1 0.5 1.0 2.5 5.0 10.0

Slope

Correction 

factora Plot radiusb

Percent - - - - - - - - - - - - - - - - - - - Meters - - - - - - - - - - - - - - - - - - - 

5 1.000 12.6 17.8 39.9 56.4 89.2 126.2 178.4

10 1.005 12.7 17.9 40.1 56.7 89.7 126.8 179.3

15 1.010 12.7 18.0 40.3 57.0 90.1 127.4 180.2

20 1.020 12.9 18.2 40.7 57.5 91.0 128.7 182.0

25 1.031 13.0 18.4 41.1 58.2 92.0 130.1 183.9

30 1.044 13.2 18.6 41.6 58.9 93.1 131.7 186.3

35 1.060 13.4 18.9 42.3 59.8 94.6 133.7 189.1

40 1.077 13.6 19.2 43.0 60.8 96.1 135.9 192.2

45 1.097 13.8 19.6 43.8 61.9 97.9 138.4 195.7

50 1.118 14.1 19.9 44.6 63.1 99.7 141.0 199.5

55 1.141 14.4 20.4 45.5 64.4 101.8 143.9 203.6

60 1.166 14.7 20.8 46.5 65.8 104.0 147.1 208.0

65 1.194 15.1 21.3 47.6 67.4 106.5 150.6 213.0

70 1.221 15.4 21.8 48.7 68.9 108.9 154.0 217.8

a

 Corrections are provided for circular plots. 

b

 For each incremental step in slope gradient, plot radius (m) is listed.
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GENERAL TECHNICAL REPORT PNW-GTR-972

Appendix 3: Random Number Table

86 85 19 85 71 95 31 6 2 4 60

17 48 32 58 98 12 58 85 89 72 82

55 69 44 46 76 64 23 93 38 37 39

60 31 66 11 80 80 62 74 9 96 79

84 56 99 1 25 46 32 24 35 85 18

72 74 51 78 66 61 17 17 84 72 16

46 78 47 93 82 35 8 52 39 17 100

90 68 38 99 56 89 93 85 5 2 88

68 59 38 82 87 20 62 93 95 35 69

8 29 79 45 8 19 95 49 53 97 80

95 8 27 28 51 83 72 66 47 50 23

95 13 13 93 26 22 1 97 99 24 51

7 82 21 40 16 53 22 74 75 61 74

1 17 6 13 0 23 72 83 12 31 40

30 82 41 55 92 35 28 83 39 57 2

66 17 13 25 36 69 96 41 44 74 87

6 55 22 67 89 89 15 33 38 69 96

84 63 100 100 21 95 79 75 8 83 42

59 85 69 14 92 69 24 72 71 89 57

5 33 22 38 55 47 57 24 39 5 14

50 39 11 88 79 47 26 49 68 27 42

78 95 54 86 16 89 57 93 68 9 49

62 20 75 58 16 18 5 16 52 79 1

8 32 82 77 37 60 76 49 90 52 9

59 27 38 39 72 58 96 25 93 45 22

64 58 14 67 61 79 18 55 98 7 43

6 3 55 96 37 92 8 85 73 43 81

89 95 89 7 10 4 93 98 44 66 30

90 52 29 99 39 11 29 38 16 31 20

54 47 69 15 4 60 17 31 14 10 27
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Fuel Characteristic Classification System (FCCS) Field Sampling and Fuelbed Development Guide

Appendix 4: Percentages of Cover of Vegetation

Figure A4-1—Percentage cover of live vegetation (illustration from Lutes et al. 2006).
Figure A4-2—Percentage cover of live vegetation on a 6-cm diameter sampling area (Lutes et al. 2006).
Pacific Northwest Research Station

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