United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS-87

April 2002

Development of Coarse-Scale

Spatial Data for Wildland Fire

and Fuel Management

Kirsten M. Schmidt

James P. Menakis

Colin C. Hardy

Wendel J. Hann

David L. Bunnell
Abstract

Schmidt, Kirsten M.; Menakis, James P.; Hardy, Colin C.; Hann, Wendel J.; Bunnell, David L. 2002.

Development of coarse-scale spatial data for wildland fire and fuel management. Gen. Tech. Rep.

RMRS-GTR-87. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain

Research Station. 41 p. + CD.

We produced seven coarse-scale, 1-km2

 resolution, spatial data layers for the conterminous United

States to support national-level fire planning and risk assessments. Four of these layers were developed

to evaluate ecological conditions and risk to ecosystem components: Potential Natural Vegetation

Groups, a layer of climax vegetation types representing site characteristics such as soils, climate, and

topography; Current Cover Type, a layer of current vegetation types; Historical Natural Fire Regimes,

a layer of fire frequency and severity; and Fire Regime Current Condition Class, a layer depicting the

degree of departure from historical fire regimes, possibly resulting in alterations of key ecosystem

components.

The remaining three layers were developed to support assessments of potential hazards and risks to

public health and safety: National Fire Occurrence, 1986 to 1996, a layer and database of Federal and

non-Federal fire occurrences; Potential Fire Characteristics, a layer of the number of days of high or

extreme fire danger calculated from 8 years of historical National Fire Danger Rating System (NFDRS) data;

and Wildland Fire Risk to Flammable Structures, a layer of the potential risk of wildland fire burning

flammable structures based on an integration of population density, fuel, and weather spatial data.

This paper documents the methodology we used to develop these spatial data layers. In a Geographic

Information System (GIS), we integrated biophysical and remote sensing data with disturbance and

succession information by assigning characteristics to combinations of biophysical, current vegetation, and

historical fire regime spatial datasets. Regional ecologists and fire managers reviewed and refined the data

layers, developed succession diagrams, and assigned fire regime current condition classes. “Fire Regime

Current Conditions” are qualitative measures describing the degree of departure from historical fire

regimes, possibly resulting in alterations of key ecosystem components such as species composition,

structural stage, stand age, canopy closure, and fuel loadings. For all Federal and non-Federal lands,

excluding agricultural, barren, and urban/developed lands, 48 percent (2.4 million km2) of the land area of

the conterminous United States is within the historical range (Condition Class 1) in terms of vegetation

composition, structure, and fuel loadings; 38 percent (1.9 million km2

) is moderately altered from the

historical range (Condition Class 2); and 15 percent (736,000 km2) is significantly altered from the historical

range (Condition Class 3). Managers can use these spatial data to describe regional trends in current

conditions and to support fire and fuel management program development and resource allocation.

Keywords: current conditions, fire regimes, fuel management, fire occurrence, potential natural

vegetation, cover type, GIS, wildland-urban interface

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 Fort Collins Service Center

Telephone (970) 498-1392

FAX (970) 498-1396

E-mail rschneider@fs.fed.us

Web site http://www.fs.fed.us/rm

Mailing Address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526
Authors

Kirsten M. Schmidt is a Resource Information Specialist with the USDA Forest Service at the Rocky Mountain Research

Station, Fire Sciences Laboratory, P.O. Box 8089, Missoula, MT 59807; Phone 406-329-4957; FAX 406-329-4877; e-mail:

kschmidt@fs.fed.us. She has worked on several research projects for the Fire Effects Research Unit involving GIS analysis and

field sampling for ecosystem management, gradient modeling, and fire behavior and effects modeling. She received her B.A.

degree in biology from the University of Montana, Missoula, and is pursuing her Ph.D. degree in remote sensing from the

University of Montana.

James P. Menakis is a GIS Specialist with the USDA Forest Service at the Rocky Mountain Research Station, Fire Sciences

Laboratory, P.O. Box 8089, Missoula, MT 59807; Phone 406-329-4958; FAX 406-329-4877; e-mail: jmenakis@fs.fed.us. Since

1990, he has worked on various research projects relating to fire ecology at a community and landscape level for the Fire Effects

Research Unit. He was the GIS Coordinator for the Landscape Ecology Team for the Interior Columbia River Basin Scientific

Assessment Project, and was involved with mapping FARSITE layers for the Gila Wilderness and the Selway-Bitterroot

Wilderness. He received his B.S. degree in forestry and his M.S. degree in environmental studies from the University of Montana,

Missoula.

Colin C. Hardy is a Supervisory Research Forester in the Fire Effects Research Work Unit, Rocky Mountain Research Station,

Fire Sciences Laboratory, Missoula, MT 59807. He is Team Leader for Landscape Analysis and Assessment, with emphasis

on remote sensing applications. His earlier work involved the characterization of smoke from wildland fires. He holds a B.S.

degree in resource conservation from the University of Montana, School of Forestry, and an M.S. degree in forest management

from the University of Washington, College of Forest Resources. He is currently pursuing a Ph.D. degree in remote sensing at

the University of Montana, School of Forestry.

Wendel J. Hann is a Fire/Landscape Ecologist for the USDA Forest Service, Washington Office, Fire and Aviation Management,

Pike-San Isabel National Forests, Leadville, CO 80461; Phone 719-486-3214; FAX 719-486-0928; e-mail: hann@amigo.net.

Since 1998, his primary responsibilities have been in national ecosystem and fire risk assessment, technology development and

transfer, and land management planning and implementation. He was a member of the Interior Columbia Basin Science Team

and Lead for Landscape Assessment at the Pacific Northwest Research Station. He worked for the Northern Region of the Forest

Service in the Ecosystem Management Group, developing and implementing ecological and fire management applications. He

taught ecology at the University of Idaho and served in the U.S. Navy for 4 years. He received a B.S. degree in range and wildlife

management, and an M.S. degree in forest and watershed science from Washington State University, Pullman, and a Ph.D.

degree in forest, wildlife, and range ecology from the University of Idaho, Moscow.

David L. Bunnell is the National Fire Use Program Manager with the USDA Forest Service at the National Interagency Fire

Center (NIFC), 3833 S. Development Ave., Boise, ID 83705; Phone 208-387-5218; FAX 208-387-5398; e-mail: dbunnell@fs.fed.us.

He started his career in the Forest Service as a seasonal Fire Guard, Biological Technician, Forestry Technician, and Research

Technician in Alaska and Montana. From 1972 to 1978, he worked in wilderness fire planning, fire effects, and physical fuel

properties. He was a Forest Fuel Specialist at the Lolo National Forest where he assisted in the early development of aerial

ignition devices, prescribed fire planning, and economic risk considerations of prescribed fire applications. He was Fire Staff,

Wildlife and Fisheries Staff, and Fire and Ecology Staff Officer on the Flathead National Forest, working in interagency

centralized dispatch and on implementation of prescribed natural fire policy in wilderness areas. As National Fuel Specialist at

NIFC, his responsibilities included prescribed fire applications and fire policy implementation. In 1999, he became the National

Fire Use Program Manager with responsibilities in prescribed fire applications and wildland fire use. He received a B.S. degree

in forestry from the University of Montana.

Development of Coarse-Scale Spatial Data for Wildland

Fire and Fuel Management

Kirsten M. Schmidt

James P. Menakis

Colin C. Hardy

Wendel J. Hann

David L. Bunnell

Rocky Mountain Research Station

USDA Forest Service

Fire Sciences Laboratory

P.O. Box 8089

Missoula, MT 59807

Phone: (406) 329-4957, FAX: (406) 329-4877

USDA Forest Service

General Technical Report RMRS-GTR-87. April 2002

iii

Contents

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

Scale and Use of Data............................................................................................................................................ 2

METHODS ................................................................................................................................................................ 2

Data Layer Development....................................................................................................................................... 2

Vegetation and Biophysical Data Layer Development ...................................................................................... 2

1. Integrate multiple data layers ................................................................................................................ 2

ECOHUC Sections ................................................................................................................................ 3

ECORegions .......................................................................................................................................... 3

Küchler Potential Natural Vegetation Groups ....................................................................................... 3

Historical Natural Fire Regimes ............................................................................................................ 4

Current Cover Types .............................................................................................................................. 6

Forest Density Classes........................................................................................................................... 6

2. Develop succession diagrams.................................................................................................................. 6

3. Map spatial data layers from succession diagrams.............................................................................. 7

4. Review and refine final maps ................................................................................................................. 7

Version 2000 .......................................................................................................................................... 8

Supplementary Data Layer Development .......................................................................................................... 8

National fire occurrence, 1986 to 1996 ...................................................................................................... 8

Federal Fire Occurrence Database ........................................................................................................ 8

Non-Federal Fire Database .................................................................................................................... 9

Potential fire characteristics..................................................................................................................... 10

Wildland fire risk to flammable structures............................................................................................. 12

RESULTS ................................................................................................................................................................ 12

Vegetation and Biophysical Data Layers............................................................................................................. 12

Supplementary Data Layers ................................................................................................................................ 15

National Fire Occurrence, 1986 to 1996......................................................................................................... 15

Potential Fire Characteristics......................................................................................................................... 15

Wildland Fire Risk to Flammable Structures .................................................................................................. 15

DISCUSSION .......................................................................................................................................................... 16

Vegetation and Biophysical Data Layers............................................................................................................. 16

Supplementary Data Layers ................................................................................................................................ 16

National Fire Occurrence, 1986 to 1996......................................................................................................... 16

Potential Fire Characteristics......................................................................................................................... 17

Wildland Fire Risk to Flammable Structures .................................................................................................. 17

Accuracy and Verification ................................................................................................................................... 17

MANAGEMENT IMPLICATIONS ........................................................................................................................ 18

CONCLUSIONS ..................................................................................................................................................... 18

ACKNOWLEDGMENTS ....................................................................................................................................... 18

REFERENCES ........................................................................................................................................................ 19

APPENDIX A: Potential Natural Vegetation Groups (after Küchler 1975)........................................................... 22

APPENDIX B: Current Cover Types (from LCC database, 1990, and RPA Forest Cover Types, 1992). ............. 28

APPENDIX C: Example of a Succession Diagram Summary Report ................................................................... 29

APPENDIX D: Federal and Non-Federal Fire Occurrence Per State, 1986 to 1996 ............................................. 30

APPENDIX E: National Fire Occurrence GIS Database Fields ............................................................................ 31

APPENDIX F: Non-Federal Fire Data Completeness ........................................................................................... 32

APPENDIX G: All Maps........................................................................................................................................ 34

v

USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 1

INTRODUCTION

Over 90 years of fire exclusion, grazing by domestic livestock, logging, and widespread establishment of exotic species

have altered fire regimes, fuel loadings, and vegetation composition and structure (Barrett and others 1991; Brown and

others 1994; Ford and McPherson 1999; West 1994; Whisenant

1990). As a result, the number, size, and intensity of wildfires

have been altered (U.S. GAO 1999; Vail 1994). Fire managers

recognize the need to reduce excessive fuel accumulations to

decrease the threat of catastrophic wildfires (USDA Forest

Service 2000), but lack national-level spatial data to support

management plans to reduce fuels as well as to conserve and

restore ecosystems. To accomplish fire and fuel management

goals, managers need answers to the following questions:

• How do current vegetation and fuels differ from those that

existed historically?

• Where on the landscape do vegetation and fuels differ from

historical levels? In particular, where are high fuel accumulations?

• When considered at a coarse scale, which areas estimated

to have high fuel accumulations represent the highest priorities for treatment?

The objective of this study was to provide managers with

national-level data on current conditions of vegetation and fuels

developed from ecologically based methods to address these

questions.

This mapping effort was initiated as two associated projects

under the auspices of the Fire Modeling Institute at the Fire

Sciences Laboratory, Rocky Mountain Research Station,

Missoula, MT. The first project, Fire Regimes for Fuels Management and Fire Use, began in 1997 through an agreement

with the U.S. Department of Agriculture, Forest Service

(USFS), State and Private Forestry, and USFS Fire and Aviation Management. The second project, Ecosystems at Risk,

was undertaken to add a fire-related component to the USFS’s

Forests at Risk project. The Joint Fire Sciences Program subsequently funded these two projects to develop several

additional spatial data layers (in other words, coverages, a set

of thematic data, usually representing a single subject matter). In the context of these projects, risk was defined as “the

relative risk of losing key components that define an ecosystem.”

We mapped fire regime current condition classes and historical fire regimes using the methodology of assigning

ecosystem characteristics to combinations of biophysical and

vegetation spatial data layers. “Biophysical data” describes

physiographic and ecological characteristics of the landscape.

“Fire Regime Current Conditions” are qualitative measures

describing the degree of departure from historical fire regimes,

possibly resulting in alterations of key ecosystem components

such as species composition, structural stage, stand age, canopy

closure, and fuel loadings. One or more activities may have

caused this departure: fire exclusion, timber harvesting, livestock grazing, introduction and establishment of exotic plant

species, introduced insects and disease, or other management

activities. The advantages of the methodology of assigning

ecosystem characteristics to combinations of biophysical and

vegetation spatial data layers include the familiarity that many

land managers have with biophysical and vegetation classifications, the large body of research that utilizes this

methodology, and the applicability of this methodology to

multiple spatial scales. Quigley and others (1996) used a biophysical layer, potential vegetation, and two vegetation layers,

cover type and structural stage, to describe ecosystem characteristics such as fuel characteristics, wildlife habitat, fire

potential, and hydrology. Keane and others (1998, 2000) used

a similar suite of biophysical and vegetation layers to assign

fuel characteristics to the Selway-Bitterroot Wilderness, Montana, and the Gila Wilderness, New Mexico.

To assess fire regime current conditions, we needed a

baseline of conditions from which to compare. A critical data

layer developed to assess current conditions and departure from

historical conditions was the “Historical Natural Fire Regimes”

layer. Fire regimes describe historical fire conditions under

which vegetation communities have evolved and have been

maintained (Hardy and others 1998). Historical natural fire

regime data are not exact reconstructions of historical conditions, defined here as conditions existing before extensive

Development of Coarse-Scale Spatial Data for

Wildland Fire and Fuel Management

Kirsten M. Schmidt

James P. Menakis

Colin C. Hardy

Wendel J. Hann

David L. Bunnell
2 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

pre-Euro-American settlement (pre-1900), but rather reflect

typical fire frequencies and effects that evolved in the absence

of fire suppression (Hardy and others 1998). We used fire frequency and severity measures to determine departure from

historical conditions, a context necessary to construct succession diagrams and assign fire regime current condition classes.

Regional ecologists and fire managers assigned current condition classes to succession diagrams for combinations of

potential vegetation type, current cover type, forest density,

and historical fire regime spatial data. Managers will use the

spatial data from this project to allocate resources to maintain

or restore areas to historical conditions.

Scale and Use of Data

The objectives of this mapping project were to provide

national-level data on the current condition of fuel and vegetation. Therefore, the data are most useful at that scale. The

end products were not intended to be used at scales other than

a coarse scale. While aggregating spatial data from fine scales

to coarse scales is a well-documented practice, converting

coarse scale data to finer scales is not recommended (Bian

1997; Bian and Butler 1999; Turner and others 1989; Weins

1989). The large cell size (1-km2) combined with the coarse

map scale (approximately 1:2,000,000) of these data products provide appropriate detail when viewed in their entirety

or at a regional scale, but details expected at finer scales will

be lacking. Zhu and Evans (1992) explicitly stated that the

“end products are not intended to be absolute or precise in

terms of accuracy in minute detail. It is the regional perspective and analysis that are most important in using the maps.”

This statement addresses the appropriate use of the Resource

Planning Act’s Forest Type Groups and Forest Density layers,

two of the primary data layers used to develop our products.

Our data products carry the same qualification.

METHODS

Data Layer Development

This section describes the methods used to develop the

seven fuel management spatial data layers. Five of these seven

layers were the result of integrating and modifying several

pre-existing vegetation and biophysical spatial data layers:

• Potential Natural Vegetation Groups, a spatial layer of

climax vegetation types representing site characteristics

such as soils, climate, and topography.

• Current Cover Type, a spatial layer of current vegetation

types.

• Historical Natural Fire Regimes, a spatial layer of fire

frequency and severity.

• Fire Regime Current Condition Class, a spatial layer

depicting the degree of departure from historical fire

regimes, possibly resulting in alterations of key ecosystem

components.

• Wildland Fire Risk to Flammable Structures, a spatial

layer of the potential risk of wildland fire burning flammable structures based on an integration of population

density, fuel, and weather spatial data.

In addition to the five vegetation and biophysical layers,

two additional layers were developed to support assessments

of potential hazards and risks to public health and safety:

• National Fire Occurrence, 1986 to 1996, a spatial layer

and database of Federal and non-Federal fire occurrences.

• Potential Fire Characteristics, a spatial layer of the number of days of high or extreme fire danger calculated from 8

years of historical National Fire Danger Rating System

(NFDRS) data.

Four steps were used to develop the five vegetation and

biophysical layers (Potential Natural Vegetation Groups, Current Cover Types, Historical Natural Fire Regimes, and Fire

Regime Current Condition Classes):

1. Integrate multiple spatial data layers.

2. Regional experts develop succession diagrams.

Transfer spatial data to succession diagrams.

Assign relative departure index.

Assign current condition classes.

3. Map spatial data layers from succession diagrams.

4. Review and refine final maps.

Vegetation and Biophysical Data Layer

Development

1. Integrate multiple data layers—We integrated and

modified several pre-existing spatial data layers, Bailey’s

Ecoregion Sections (Bailey and others 1994), Fourth Code

Hydrologic Units (HUC) (Seaber and others 1987), USFS regional boundaries, a Digital Elevation Model (DEM) (USGS

1994), Küchler’s Potential Natural Vegetation map (1975), earlier versions of fire regime maps, Forest and Range Resource

Planning Act’s (RPA) layer of U.S. Forest Types Groups (Zhu

and Evans 1992,1994; Powell and others 1992) for forest cover

types, the Land Cover Characteristics Database (Loveland and

others 1991) layer for nonforest cover types, and the RPA Forest Density layer, to derive final vegetation and biophysical

layers (fig. 1). We developed six intermediate layers, two

(ECOHUC and ECORegion) of which were not final products but were used to partition the landscape into coarse

biophysical units (fig. 1). Three of the intermediate layers (Potential Natural Vegetation Groups, Current Cover Types, and

Historical Natural Fire Regimes) were modified in the succession diagram process detailed below to become the final

layers (fig. 1). The last intermediate layer (Forest Density Classes)

was used in the succession diagram process, but was not a final

layer (fig. 1). All working and final spatial data layers were converted to 1-km2

 pixel raster layers and projected to the Lambert
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 3

Azimuthal Equal Area projection. Selection of pre-existing

spatial data layers was based on immediate availability and

continuity of data for the lower 48 States.

ECOHUC Sections—The first intermediate spatial data layer

(fig. 1), ECOHUC Sections, partitioned the conterminous

United States data layer into 165 relatively homogenous physiographic units of climate, vegetation, landform, and soils,

following watershed, or Fourth Code HUC, boundaries. Because original Bailey’s Ecoregion Sections (Bailey and others

1994) did not conform to any mapable features on the landscape such as watershed boundaries, we modified the Bailey’s

Ecoregion Section vector layer with the Fourth Code HUC

vector layer (Seaber and others 1987), replacing Section lines

with HUC lines (fig. 2). Bailey’s Sections are the fourth level

in Bailey’s Ecoregion system, a hierarchical biophysical system based on climate, vegetation, landform, and soils.

Ecoregions are widely used to describe ecological units in geographic analysis and planning (McNab and Avers 1994).

Hydrologic units are a hierarchical system developed by the

U.S. Geological Survey that divides the United States into

multiple levels: regions, subregions, accounting units, and

cataloging units (Seaber and others 1987). Cataloging units,

also called watersheds, are equivalent to HUCs and delineate

river basins with drainage areas usually greater than 1,800 km2

.

ECORegions—The next intermediate spatial data layer

(fig. 1), Ecological Regional Boundaries (ECORegions), divided the national-scale data into partitions containing each

of the eight USFS regions for the development workshops

that were structured around each region. Original USFS regional boundaries primarily followed State borders. To

register the regional boundary layer with our first stratification layer, ECOHUC Sections, we delineated ECORegions

by merging adjacent ECOHUC Sections within each USFS

region to roughly the same area as the original region (fig. 3).

Küchler Potential Natural Vegetation Groups—The third

intermediate layer (fig. 1) was the Küchler Potential Natural

Vegetation Groups biophysical layer. We used Küchler’s

(1975) Potential Natural Vegetation (PNV) map of climax

vegetation types that represent site characteristics such as

soils, climate, and topography. Küchler (1964) defined

a Küchler 1975.

b Hardy and others 1998.

c

 Zhu and Evans 1992, 1994.

d Loveland and Ohlen 1993.

e Zhu 1994.

Figure 1—Flow diagram of spatial data layer development. ECOHUC Sections are Bailey’s Ecoregion

Sections (Bailey and others 1994) adjusted to Fourth Code Hydrologic Unit Codes (Seaber and

others 1987). ECORegions are Forest Service regions merged with ECOHUC Sections.

Forest Service Regions

Fire Regimes v1

Non-Forest Cover

Types

Resource Planning Act

Resource Planning Act

Land Cover Characterizationd

Fire Regimes v2b

Forest Type Groupsc

Forest Densitye

Bailey’s Ecoregion

Sections

Fourth Code

Hydrologic Unit Codes

Digital Elevation

Model

Küchler Potential

Natural Vegetationa

ECOHUC Sections

ECORegions

Küchler Potential

Natural Vegetation

Groups

Potential Natural

Vegetation Groups

v2000

Historical Natural

Fire Regimes v2000

Current Cover Types

v2000

Fire Regime Current

Condition Classes

v2000

Forest Density

Classes

Fire Regimes v1, v2

Current Cover Types

S

U

C

C

E

S

S

I

O

N

D

I

A

G

R

A

M

S

Original Intermediate Final
4 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

potential natural vegetation as (1) vegetation that would exist

without human interference and (2) vegetation that would exist if the resulting plantsuccession were projected to its climax

condition while allowing for natural disturbance processessuch

as fire.

We digitized the 1:3,168,000 scale, Kuchler PNV map

(1975), for the conterminous United States and then converted

it to a 1-km2 raster map.To make the Kuchler PNV map useful in

a spatial and modeling context, we adjusted the coarse Kuchler

PNV polygons to match topographic features and watershed

delineations. We made these adjustments by using DEM and

Fourth Code HUC spatial data.

We first created topographic classes of elevation and slope

based on a 500-m DEM (USGS 1994). The continuous DEM

data were reclassified into 50-m-elevation classesfor the Western States (USFS Regions 1 through 6) and 10-m-elevation

classes for eastern USFS Regions 8 and 9. Various elevation

class breaks were tested for the Eastern and Western United

States to best fit the original continuous elevation data. Fiftymeter-elevation classes best represented the high-relief

topographic gradients of the Western United Staes. Ten-meter

classes best represented the low-relief topographic gradients

of the East. We increased the pixel size of the DEM data from

500 m2 to 1 km2 to match the pixel size of the other layers.

Slope classes were divided into two classes: (1) less than

or equal to 5 percentslope to differentiate flat areas and (2) greater

than 5 percent slope. These two slope classes were used to

differentiate grassland and agricultural areas from forested or

wooded areas. The elevation and slope class layers were then

combined with the Fourth Code HUC watershed delineation

layer to create a “HUC Terrain” grid. To build the terrainmatched Kuchler PNV layer, we assigned the modal PNV to

each of these HUC Terrain combinations.

Next, we aggregated the original 118 Kuchler PNVs into

63 Kuchler PNV Groups classes based on similar vegetation

types to reduce the number of combinations in the succession

diagram mapping process (appendix A). We reclassified grass

and shrub lifeformsinto the Forest-Range Environmental Study

ecosystem classification (Garrison and others 1977) by using

assignments in the Fire Effects Information System (Fischer

and others 1996). For example, we grouped several of the forested PNVs based on similar forest types, grouping Kuchler

PNVs Western ponderosa pine forest, Eastern ponderosa forest, and Black Hills pine forest into one PNV, Pine Forest (see

appendix A for a complete list of groupings by USFS region).

Historical Natural Fire Regimes —The fourth intermediate layer (fig. 1) was a combination of two earlier versions of

fire regime spatial data. Fire regime data provided reference

conditions against which current conditions can be compared.

We modified Heinselman’s (1981) seven fire regimes, which

are defined by return interval and fire intensity, into five fire

regimes defined by fire frequency and severity.

Fire frequency isthe average number of years between fires.

Severity is the effect of the fire on the dominant overstory

vegetation, which can be forest, shrub, or herbaceous vegetation. Low-severity fires are firesin which more than 70 percent

of the basal area and more than 90 percent of the canopy cover

of the overstory vegetation survives(Morgan and others 1996).

Figure 2 – ECOHUC Sections were developed by modifying Bailey’s Ecoregion sections (Bailey and others 1994)

with Fourth Code Hydrologic Unit Codes (Seaber and others 1987).

Fourth Code Hydrologic Unit Code

Bailey’s Ecoregion Sections

ECOHUC Sections

 ̈

 ̈

 ̈

 ̈

 ̈

 ̈

 ̈
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 5

Mixed-severity fires are fires that result in moderate effects

on the overstory, cause mixed mortality, and produce irregularspatial mosaicsresulting from different fire severities(Smith

and Fischer 1997). Stand-replacement fires consume or kill

more than 80 percent of the basal area or more than 90 percent of the overstory canopy cover (Morgan and others 1996).

Our classification system includes five historical fire regimes (table 1). Fire Regime I (0- to 35-year frequency, low

severity) isfound primarily in foreststhat experience frequent,

low-severity, nonlethal surface fires. Fire Regime II (0- to

35-year frequency, stand-replacement severity) is found primarily in grass and shrublands. Because fire consumes the

dominant aboveground vegetation in the form of grasses or

shrubs, fire severity is considered to be stand replacing regardless of the plants’ response to fire (Brown 1994). Fire

Regimes III (35- to 100+ year frequency, mixed-severity), IV

(35- to 100+ year frequency, stand-replacement severity), and

V (200+ year frequency, stand-replacement severity) can occur in any vegetation type.

The first version of the Historical Natural Fire Regimes

data layer was a prototype developed for the conterminous

United States, using expert knowledge to assign fire regimes

to General Land Cover Classes (Loveland and Ohlen 1993).

For the second version, we integrated expert knowledge, remote sensing, and biophysical data to map fire regimes(Hardy

and others 1998) for the 11 conterminousWestern States, from

Washington south to California, east to New Mexico, and north

to Montana. For the first two versions, we used a methodology similar to that used by Brown and others (1994), who

integrated site characteristics, habitat types, topographic attributes, and vegetation to map fire regimes for the

Selway-Bitterroot Wilderness of Montana.

A database of historical fire regimes by Kuchler PNV

groups was developed to assist expert panels in mapping Historical Natural Fire Regimes and to resolve mapping conflicts

that occurred among adjacent USFS regions. The database was

built by querying the Fire EffectsInformation System (Fischer

and others 1996). All literature citations used to assign historical fire regimes were included in the database.

Table 1—Historical natural fire regimes.

Code Description

I 0–35-year frequencya

, low severityb

II 0–35-year frequency, stand-replacement severity

III 35–100+ year frequency, mixed severity

IV 35–100+ year frequency, stand-replacement

severity

V 200+ year frequency, stand-replacement severity

a Fire frequency is the average number of years between fires. b Severity is the effect of the fire on the dominant overstory vegetation.

Figure 3—Ecological Regional Boundaries (ECORegions) were developes by modifying U.S. Forest Service

regional boundaries with ECOHUC Sections (Bailey’s Ecoregion sections and Fourth Code Hydrologic Unit

Codes).

USDA Forest Service Regions

ECOHUC Sections

ECORegions

 ̈
6 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Current Cover Types—The fifth intermediate layer (fig. 1)

was the Current Cover Type layer (appendix B). We used two

existing remote sensing vegetation data layers to develop an

integrated Current Cover Type layer: (1) the Forest and Range

Resource Planning Act’s layer of U.S. Forest Type Groups

(Powell and others 1992; Zhu and Evans 1992, 1994) for

forest cover types and (2) the Land Cover Characteristics Database (Loveland and others 1991; conterminous U.S. land

cover characteristics dataset 1990) for nonforest cover types.

Both data layers were derived from 1-km2 resolution Advanced

Very High Resolution Radiometry (AVHRR) satellite imagery. The Forest Type Groups layer was selected for forest cover

types because it was based on intensive field data. Also, descriptions of the Forest Type Groups could be found in Forest

Resources of the United States (Powell and others 1992). Forest types were also cross-referenced with the Society of

American Foresters’ Forest Cover Types of the United States

and Canada (Eyre 1980).

In 1992, the USFS Southern Forest Experiment Station,

Forest Inventory and Analysis Unit, developed a layer of forest types of the United States under the Forest and Rangeland

Renewable Resources Planning Act (RPA) (Powell and others

1992; Zhu and Evans 1992, 1994). Because the Forest Type

Groups layer represented only forested areas, we used the

nonforest cover types of the Land Cover Characterization

Database (Loveland and others 1991), to fill in the remaining

nonforested areas.

In the development of the Western States fire regime layer

described above, Hardy and others (1998) used the 26 General Land Cover Types (GLCTs) (Loveland and Ohlen 1993)

aggregated from the 159 Land Cover Characterization Classes,

expanding one of the classes, Western Coniferous Forest, into

three subclasses: short-needle conifer, long needle conifer, and

mixed short- and long-needle conifer. We combined the Hardy

and others (1998) GLCT layer with the Forest Type Groups

layer to produce an intermediate cover type layer. All nonforest

areas of the Forest Type Groups layer were replaced with forest GLCTs.

Forest Density Classes—The last intermediate layer (fig. 1)

was a classification of forest density developed for the 1992

RPA assessment. We used this forest density data as a surrogate for forest structure because no spatial layer of forest

structure for the conterminous United States existed and it was

beyond the scope of this project to develop such a product.

The layer was developed from several regression analyses

between coregistered 1991 AVHRR data and classified

LANDSAT Thematic Mapper data (Zhu 1994). Forest density

was defined as the proportion of 28.5-m2 LANDSAT Thematic

Mapper cells per 1-km2 AVHRR cell that was forested (Zhu

1994). We classified the continuous forest density values,

which ranged from 0 to 100 percent, into four density classes:

0 = nonforest, 1 = 0 to 32 percent, 2 = 33 to 66 percent, and

3 = 67 to 100 percent. All nonforest cover types were assigned

the nonforest density class.

2. Develop succession diagrams—Succession diagrams (fig. 4) were used to map fire regime current conditions

as well as to refine all the input spatial data layers. Regional

experts, during workshops held in 1999 and 2000 at the Fire

Laboratory in Missoula, MT, developed succession diagrams

for each combination of ECOHUC, Küchler PNV groups, and

Historical Natural Fire Regimes, which we call STRATA,

within their ECORegion boundary. The succession diagram

consists of a series of boxes ordered from early seral through

climax. Regional experts filled in these succession boxes with

data provided in summary reports generated in a Geographic Information System (GIS) by combining the following layers:

ECOHUCs, Fire Regime, Küchler PNV groups, Current Cover

Type, and Forest Density within an ECORegion boundary (appendix C). The succession diagram is a very simplified version

of the successional pathway diagrams described by Keane and

others (1996); they differ in that they lack the multiple pathways, real-time intervals, and probability links among

vegetation types.

Regional experts completed the succession diagrams in

three steps:

1. The ECOHUC, Küchler PNV group, cover type, and

forest density information was transferred from the summary report generated by combining all input layers in the

GIS to the STRATA section of the succession diagram. The

experts assigned historical fire regimes at this time. If they

wanted to map combinations that did not occur in the report or remap a specific area, they filled in the succession

diagrams with classes other than those provided by the reports. For example, all Pine PNV groups within a given

ECOHUC could be combined into a single Pine-Douglasfir PNV group.

2. The experts assigned a relative departure index (RDI) to

each succession box in the succession diagram based on

the STRATA, cover type, and forest density data. The relative departure index reflects either vegetation composition

(cover type and density) and fuel loadings within historical ranges or it reflects changes in these attributes due to

the cumulative effects of fire exclusion, livestock grazing,

logging, establishment of exotic plant species, introduced

insects or diseases, or combinations of these disturbances.

Relative departure index values range from 0 to 3, with a

value of 0 indicating that the cover type and density class

combination for that specific succession diagram’s STRATA

are within the historical range. A value of 3 indicates that

the cover type and density class combination for that specific succession diagram’s STRATA is cumulatively three

fire return interval increments from its historical conditions.

For example, in figure 4, the first three succession boxes

were assigned an RDI of 0, indicating that the current cover

types and forest density classes assigned in each succession box could occur in a Pine-Douglas-fir PNV group and

a Fire Regime I (0- to 35-year frequency, low severity).

Succession box 4 was assigned an RDI of 1 because the

cover types and forest density combination was one increment removed from the vegetation composition of the third

succession box. The combination of a ponderosa pine current cover type and a forest density class 2 (33 to 66 percent)
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 7

could not have occurred unless at least one fire return interval was missed. Succession box 5 was assigned an RDI

of 2 because the combination of a ponderosa pine current

cover type and a forest density class 3 (67 to 100 percent)

was one increment from succession box 4, which was assigned an RDI of 1.

3. Once the relative departure index was assigned, the regional experts completed the succession diagram by

assigning a fire regime current condition class (table 2),

which was based on the STRATA, species composition,

forest density, and RDI found in each succession box. For

example, succession box 4 (fig. 4) was assigned Current

Condition class 2, indicating that the ecosystem components have been moderately altered from historical

conditions due to the disturbances mentioned above.

3. Map spatial data layers from succession diagrams—All succession diagram assignments and changes

were loaded into a database containing all STRATA, current

cover types, and forest density combinations within the

ECORegion boundaries and linked to a master spatial layer.

This database also contained changes made to the cover type,

potential natural vegetation groups, and fire regime layers

completed during the succession diagram development. We

generated new spatial data layers of historical natural fire

regime, Küchler PNV groups, current cover types, and current condition classes for each ECORegion from the master

spatial layer and database, then merged all ECORegions to

create the conterminous United States layers of Potential

Natural Vegetation Groups, Current Cover Types, Historical Natural Fire Regimes, and Current Condition Classes

(appendix G).

4. Review and refine final maps—The final steps in

the development of the vegetation-based data layers involved

sending the maps produced from the workshops to the regional

experts for review and refinement. Maps included their

ECORegion boundary and the surrounding regions, allowing

the experts to review how their assignments compared to other

regions.

The final step in the editing process was to resolve edge

effects among ECORegion boundaries. Edge effects resulted

from different groups of experts making layer assignments,

causing disagreement between adjacent region boundaries.

Edge effects were resolved by one or more of the following

steps: (1) literature review of the Fire Effects Information

System, (2) expert knowledge of a specific area, or (3) majority opinion of regional experts from two or more ECORegions.

Figure 4—Succession diagram example. Fields filled out in italics indicate information provided by summary reports (appendix C). Fields filled out in bold indicate information filled in by regional experts.

Grassland

Douglas-fir Douglas-fir

Other shrub Ponderosa

Pine

Ponderosa

Pine

Ponderosa

Pine

Douglas-fir

0:Non-forest

2.33%-66% 3.67%-100%

Successional Box

STRATA:

ECOHUC:

Fuel Management Succession Diagram

Küchler PNV Groups: 3: Pine Douglas-fir

Historical Fire Regime: 1: 0-35 year, low severity

All

Cover Type:

Forest Density:

Relative Departure

Index:

Condition Class:

Condition Class:

Relative Departure

Index:

Succession Box

Directions

1.

2.

4.

3.

Fill in STRATA from worksheet.

Fill in Cover Type and Forest Density from worksheet.

Assign Condition Class to STRATA, Cover Type, Forest Density,

and Relative Departure Index combinations for each Succession Box.

Assign Relative Departure Index to STRATA, Cover Type, and

Forest Density combinations for each Succession Box.

Cover Type:

Forest Density:

0

0 1

0 0 1 20

1

1 2

112 3 1

0:Non-forest 1: 0%-32% 2:33%-66% 3:67%-100% 1:0%-32%

Can Agriculture Occur

Yes No

in this Strata?

1

7

2

8

34 56
8 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Version 2000—After the release of all the data products in

November 1999, some inconsistencies were found across

ECORegional boundaries because the data were compiled

separately for each ECORegion. To eliminate these inconsistencies, we conducted another series of workshops in the

summer of 2000 with participants from adjacent ECORegions

who repeated the steps described above. For Version 2000

products, succession diagram assignments were made to

ECOHUC sections (average size 2,400 km2) instead of to

ECORegions (average size 970,000 km2) as was done for the

first versions. Once all refinements were incorporated into the

master database and GIS, final Version 2000 spatial data layers (appendix G) were completed.

Supplementary Data Layer Development

Three additional spatial data layers were developed that

were not directly associated with the biophysical and vegetation-based layers. Development of these supplementary layers

was in response to risk assessment needs identified both in

the Joint Fire Sciences Program funding agreement and in the

USFS’s Forests at Risk project charter. In contrast to the focus

on ecological conditions and risks to ecosystem components

inherent in the biophysical and vegetation-based layers, the

three supplementary layers were developed specifically to support assessments of potential hazards and risks to public health

and safety. These include an 11-year National Fire Occurrence

database, a Potential Fire Characteristics layer, and a layer

expressing Wildland Fire Risk to Flammable Structures. The

layers are based on syntheses of historical fire and weather

data and their associated fire-related indices. These layers provide the probability component of a formal risk assessment,

and can be used as such by agencies or administrative units.

National fire occurrence, 1986 to 1996—The National

Fire Occurrence database and GIS coverage (appendix G) is a

GIS database of natural and human-caused fire occurrences

for the years 1986 to 1996. It includes Federal data from the

USDA Forest Service and four Department of the Interior

(DOI) agencies: Bureau of Land Management (BLM), Bureau of Indian Affairs (BIA), National Park Service (NPS),

and U.S. Fish and Wildlife Service (FWS). It also includes

non-Federal data from all conterminous States except Nevada

(appendix D).

Federal Fire Occurrence Database—The USDA Forest Service administrative units submitted fire occurrence data to the

national database, which is called the National Interagency

Fire Management Integrated Database (NIFMID) (USDA

Table 2—Fire Regime Current Condition Classa descriptions.

Condition class Fire regime Example management options

Condition Class 1 Fire regimes are within an historical range, Where appropriate, these areas

and the risk of losing key ecosystem compo- can be maintained within

nents is low. Vegetation attributes (species the historical fire regime by

composition and structure) are intact and treatments such as fire use.

functioning within an historical range.

Condition Class 2 Fire regimes have been moderately altered Where appropriate, these areas

from their historical range. The risk of losing may need moderate levels of

key ecosystem components is moderate. restoration treatments, such as

Fire frequencies have departed from histor- fire use and hand or mechanical

ical frequencies by one or more return inter- treatments, to be restored to the

vals (either increased or decreased). This historical fire regime.

results in moderate changes to one or more

of the following: fire size, intensity and severity, and landscape patterns. Vegetation attributes have been moderately altered from

their historical range.

Condition Class 3 Fire regimes have been significantly altered Where appropriate, these areas

from their historical range. The risk of losing may need high levels of restoration

key ecosystem components is high. Fire fre- treatments, such as hand or

quencies have departed from historical fre- mechanical treatments, before

quencies by multiple return intervals. This fire can be used to restore the

results in dramatic changes to one or more historical fire regime.

of the following: fire size, intensity, severity,

and landscape patterns. Vegetation attributes

have been significantly altered from their historical range.

a Fire Regime Current Condition Classes are a qualitative measure describing the degree of departure from historical fire regimes, possibly

resulting in alterations of key ecosystem components such as species composition, structural stage, stand age, canopy closure, and fuel

loadings. One or more of the following activities may have caused this departure: fire suppression, timber harvesting, livestock grazing,

introduction and establishment of exotic plant species, introduced insects or disease, or other management activities.
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 9

Forest Service 1993), located at the USDA National Information Technology Center in Kansas City, MO. USDA Forest

Service data were extracted from NIFMID for USFS Regions

covering the conterminous United States (USFS Regions 1

through 6, 8 and 9) for the years 1986 to 1996. A GIS coverage was generated from the latitude-longitude coordinates, and

database attributes were adjusted to conform to database items

chosen for this project (appendix E).

Department of the Interior Agencies submitted fire occurrence data to the common Shared Applications Computer

System, located at the National Interagency Fire Center in

Boise, ID. We obtained new data directly from the DOI

central database in October 1999 and worked closely with the

FWS to summarize appropriate fire types and acreages. These

new data were used in the final product. A GIS coverage was

generated from the database’s latitude-longitude coordinates,

recorded in the database to the nearest second.

We performed several processing steps on both the USFS

and DOI layers. We removed incorrectly recorded latitude or

longitude coordinates from the USFS and DOI databases.

Records from these databases were removed that contained

data not needed for this analysis, such as pre-1986 data and

records of false alarms. In addition, a GIS layer of State boundaries was overlaid with the point layers to identify those points

that did not occur within the recorded State. If the point occurred further than 10 km from the nearest State boundary to

which it was assigned, or if the point occurred within 10 km

of the State boundary but was not recorded as being in the

adjacent State, it was removed from the GIS database.

Non-Federal Fire Database—Non-Federal fire records were

received from all lower 48 States except Nevada, which was

composed primarily of Federal land. The quality and completeness of the data received varied by State (appendix F).

Many States did not have complete fire records for each of the

11 years from 1986 through 1996 (fig. 5). In this case, we

used only the years with complete data. For nine States that

lacked digital fire data, data were obtained from the National

Fire Incident Reporting System (NFIRS) database.

We received non-Federal fire locations in a variety of formats. Fire records that were provided in a GIS format or with

latitude-longitude or Universal Transverse Mercator (UTM)

coordinates were imported directly into the GIS. Fire locations recorded as legal descriptions (township, range, section)

were converted to section centers. State records that had county

as the most precise fire location were assigned the center of

the county as the fire location.

Data for two States, Colorado and Missouri, were processed

differently than the other States. We received fire records from

Colorado in a GIS format, which contained both State and

Federal fires. Because it was not possible to trace the records

to their original agency source, the layer was overlaid with an

ownership layer and only those records falling on non-Federal lands were kept as the non-Federal GIS coverage. Missouri

provided fire records with both legal descriptions and county

as the best location. Those records with legal descriptions were

converted to the center of the section and appended to the

State point coverage. Those with county as the best location

were included in the county GIS database.

Figure 5—Number of years missing from non-Federal fire data for the 11-year period, 1986 to 1966.

0

0

0

0

0

0

1

1

0

0

0

0

0

0

7

0

2

4 3

8

6

6

5

5 5

6

2

0

0

0

2

4

3

2

1 2

7

2

2

5

2

2

1

0

3

3

11
10 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Records from the NFIRS database were used for States from

which we were unable to obtain data directly. Because participation in NFIRS is voluntary, the database does not

represent all wildland fires within the State within a given time

period. After attempting to contact State Foresters from each

of the nine States for which only NFIRS data were available,

State Foresters from Kentucky, Louisiana, Alabama, and West

Virginia responded with reviews. The NFIRS data were determined to be an inadequate representation of State fire

occurrence (table 3). All States with NFIRS data were given a

status of unsatisfactory, but were included in the database as

the only available data (appendix F).

Potential fire characteristics—The Potential Fire Characteristics layer, Version 1999 (appendix G), is a spatial

representation of the number of days of high or extreme fire

danger calculated from 8 years of historical National Fire

Danger Rating System (NFDRS) data. The basis for the Potential Fire Characteristics layer is the Burning Index (BI),

which was developed to assess containment problems at a fire’s

flaming front. Burning Index describes the magnitude of the

fire containment problem in the context of coarse-scale, nonspecific fire potential (Andrews and Rothermel 1981). The

fire potential interpretations shown in table 4 can be applied

to corresponding BI values. These flame length classes and

interpretations are familiar to fire managers and are widely

accepted as an intuitive communications tool. Fires with flame

lengths exceeding 8 feet present serious control problems such

as torching, crowning, and spotting. Control efforts at the head

of such fires are mostly ineffective, and major runs can occur

in more extreme cases. Therefore, the 8-foot flame length

threshold was selected for this project to indicate high or extreme fire potential.

National Fire Danger Rating System data characterize the

near worst-case scenario of fire danger or potential for fires

that could occur during a specific time period, and are intended

for mid- to large-scale applications. Deeming and others (1977)

note that “fire-danger rating areas are typically greater than

100,000 acres. Weather is observed and predicted for one specific time during the day at one specific location.” The 1978

NFDRS indices are used throughout the lower 48 States to

guide fire management planning activities (Deeming and others 1977). The primary NFDRS indices include Spread

Component, Energy Release Component, and Burning Index

(Bradshaw and others 1983).

The flame length inputs to the Potential Fire Characteristics map layer were derived from 180 days of interpolated BI

data (April to September) for each of 8 years (1989 to 1996).

Each daily map layer was individually processed in two steps:

1. Area-weighted mean BI values were calculated and summarized to Fourth Code HUC polygons (fig. 6).

2. Area-weighted mean BI values for each Fourth Code

HUC were categorized into three potential flame length

categories: less than or equal to 4.0 ft, 4.1 to 8.0 ft, and

greater than 8.0 ft. Figure 7a shows the weighted-average

data layer and the three flame length categories (fig. 7b)

for April 1, 1991.

Table 4—Fire potential interpretations for four flame length

classes. Potential flame length is calculated as BI/10.

Flame length Fire potential

Burning index feet interpretation

<40 <4.0 Fires can generally be

attacked at the head or

flank by persons using

handtools. Handline

should hold the fire.

41–80 4.1–8.0 Fires are too intense

for direct attack on the

head by persons using

handtools. Handline

cannot be relied on to

hold fire. Equipment

such as plows, dozers,

pumps, and retardant

aircraft can be effective.

81–110 8.1–11.0 Fire behavior may

present serious control

problems such as

torching out, crowning,

and spotting. Control

efforts at the head of

the fire will probably be

ineffective.

>110 >11.0 Crowning, spotting,

and major runs are

probable. Control

efforts at the head of

the fire are ineffective.

Table 3—National Fire Incident Reporting System (NFIRS) fire data and State

Foresters’ review data, 1987 to 1996 summaries.

State NFIRS State reviews

Total number Total km2 Total number Total km2

 of fires (acres) of fires (acres)

Alabama 168 Not reported 51,973 2,372 (586,208)

Kentucky 1,191 Not reported 16,903 2,707 (668,813)

Louisiana 3,206 Not reported 43,362 2,168 (535,631)

West Virginia 6,294 Not reported 12,720 3,932 (971,664)
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 11

Figure 6—Area-weighted mean Burning Index values were calculated for each Fourth Code HUC, as shown in

this example for April 1, 1991. In this procedure, each daily raster layer is converted to weighted-average

polygon data.

Burning Index

Weighted Mean to Fourth Code HUC

Figure 7—Area-weighted mean Burning Index data layer (a) and the three flame length classes (b) for April 1, 1991.

a) Area-weighted Burning Index b) Flame length classes (ft)

< 4.0

4.1 - 8.0

> 8.0
12 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

After each daily map layer was processed for a given year,

the annual number of days that potential flame length exceeded

8 feet was counted for each sub-basin. Finally, the maximum

annual number of days when 8-foot flame lengths were exceeded was determined for each sub-basin from the 8 years of

data. The resulting map is Potential Fire Characteristics,

Version 1999 (appendix G).

Wildland fire risk to flammable structures—The

threat of wildland fire to homes is a significant concern for

Federal, State, and local land management agencies (Cohen

2000). Wildland fires have destroyed 8,925 homes from

1985 to 1994 (USDA 2000). The growing human population along with shifting demographics from urban to rural

areas is increasing the concentration of houses adjacent to

or embedded in wildlands, resulting in escalated risk of

human life and private property loss from catastrophic wildfire (USDA 2000). To identify these problem areas, we

created a map of the potential risk of wildland fire burning

flammable structures based on an integration of population density, fuels, and weather spatial data for the

conterminous United States (appendix G). For this product, we defined risk as the potential of wildland fire burning

numerous houses in a single event. In physical terms, a wildland-urban interface fire occurs when a wildfire is close

enough for its flames and/or firebrands to contact the flammable parts of a structure. Although recent research shows

that the potential for residential ignition is usually determined

by a home’s exterior materials, design, and immediate surrounding conditions rather than by wildland fire behavior in

surrounding lands (Cohen 2000), our analysis assumes that

all homes are highly ignitable and flammable. Our national

map portrays areas at risk of wildland fire burning flammable

structures and will provide land managers with a tool for evaluating this increasing problem.

We integrated several spatial database layers in the GIS to

map the potential risk of wildland fire burning flammable structures. The Potential Fire Exposure layer was created by first

combining Potential Natural Vegetation Groups and Current

Cover Types data layers and then assigning these combinations to severe fire behavior classes that produced similar

fire or heat intensity. We created an Extreme Fire Weather

Potential data layer by calculating the average number of

days per year when historical weather conditions had exceeded thresholds and wildfires had burned structures.

Weather conditions included temperature, relative humidity,

and wind. To create the Housing Density layer, we reclassified the LandScan Global Population 1998 database,

developed by Oak Ridge National Laboratory (Dobson and

others 2000), into classes of housing density per hectare

(assuming the average household contained three people

per house) and assigned a risk rating to each class (table 5).

By combining these data layers, we produced a matrix used

to assign classes of potential risk of wildland fire burning

flammable structures. A complete description of the methods

used to develop Wildland Risk to Flammable Structures can

be found in Menakis and others (in preparation).

RESULTS

Vegetation and Biophysical Data Layers

For all Federal and non-Federal lands, excluding agricultural, barren, and urban/developed lands, 48 percent of the

land area of the conterminous United States is within the

historical range (Condition Class 1) in terms of fuel loadings and vegetation composition and structure; 38 percent

is moderately altered from the historical range (Condition

Class 2); and 15 percent is significantly altered from the

historical range (Condition Class 3) (table 6). Sixty-one

percent of the conterminous United States historically experienced frequent fires (every 0 to 35 years) (table 6). Fire

Regime I (0- to 35-year frequency, low severity) is primarily composed of forested lands, while Fire Regime II (0- to

35-year frequency, stand replacement) is primarily grass

and shrublands. The moderately frequent Fire Regimes III

and IV (35- to 100-year frequency) comprise 34 percent of

the conterminous United States; these fire regimes are composed of both forest and shrublands. The highest proportion

of area for all ownerships occurs in Fire Regimes I (34 percent) and II (27 percent) (fig. 8).

Fire Regimes I and II occupy nearly all the lower elevations across the United States and have been most affected

by human intervention (Barbour and Billings 1988; Hann

and Bunnell, in press; Wright and Bailey 1982). Forty-one

percent of the area in Fire Regime I is within its historical

range, while 59 percent is altered from the historical range.

Fifty-seven percent of the area in Fire Regime II is within

its historical range, while 43 percent is altered from the

historical range (table 6). Typical types represented in these

two fire regimes are pine, oak, and pinyon-juniper forests

in Fire Regime I and grass and shrublands in Fire Regime

II. Fire exclusion, housing and agricultural development,

livestock grazing, logging, and invasion of exotic species

are primary causes of departures. The areas in Condition

Classes 2 and 3 within Fire Regimes I and II are often at

the greatest cumulative risk to loss of native plant and animal habitats, reduction in air quality due to wildfire smoke,

Table 5—Risk rating of wildland fire burning flammable structures by houses per hectare and houses per acre.

Houses per Houses per

Risk rating hectare acre

None No houses No houses

Very low 0.01–0.49 0.01–0.20

Low 0.50–2.48 0.21–1.0

Moderate 2.49–4.94 1.01–2.0

High 4.95–12.36 2.01–5.0

High/city 12.37–24.71 5.01–10.0

City 24.72+ 10.01+
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 13

Table 6—All ownership land summary of historical fire regimes by condition classes of all cover types except agriculture,

barren, water, and urban/development/agriculture.

Condition class

Class 1 Class 2 Class 3

km2 (acres) Row % km2 (acres) Row % km2 (acres) Row %

I. 0–35 years; 712,901 41 708,325 41 313,60 18 1,734,828 34

low severity (175,031,010) (176,161,740) (77,492,543) (428,685,293)

II. 0–35 years; 779,198 57 538,965 40 41,869 3 1,360,033 27

stand replacement (192,544,136) (133,181,268) (10,346,175) (336,071,579)

III. 35–100+ years; 516,553 43 454,292 38 218,542 18 1,189,387 24

mixed severity (127,642,957) (112,258,095) (54,002,982) (293,904,034)

IV. 35–100+ years; 214,737 43 142,990 29 141,755 28 499,483 10

stand replacement (53,062,756) (35,333,666) (35,028,486) (123,424,908)

V. 200+ years; 196,509 72 55,469 20 19,853 7 271,831 5

stand replacement (48,558,333) (13,706,766) (4,905,719) (67,170,818)

2,419,898 Col % 1,900,043 Col % 735,621 Col % 5,055,562

Total (597,969,922) 48 (469,510,805) 38 (181,775,905) 15 (1,249,256,632)

Historical fire

regime

 Total km2 Total

(Total acres) %

degraded water quality and risk of wildfire degradation to

watersheds, reduced commodity outputs, and risks to human health and safety as a result of the combination of

ecosystem departure and risk of catastrophic wildland fire

(Flather and others 1994; Frost 1998; Hann and Bunnell, in

press; Hann and others 1997, 1998, 2001; Hunter 1993;

Quigley and others 1996; Raphael and others 2000; Reiman

and others 1999; Rockwell 1998; Wisdom and others 2000).

Figure 8—Area distribution of fire regime by

condition class for all ownerships.

1,000,000

aSee table 2 for condition class definition.

Class 1a

Class 2

Class 3

Fire Regime

I

II

III

IV V

Fire Regime

Condition Classes

750,000

500,000

km2

250,000

0

0 35 year frequency,

low severity

0 35 year frequency,

stand replacement

35 100+ year frequency,

mixed severity

35 100+ year frequency,

stand replacement

200+ year frequency,

stand replacement
14 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

The highest percentage of Condition Class 3 (28 percent)

is found in Fire Regime IV (35- to 100-year frequency, stand

replacement), while 18 percent of Condition Class 3 is found

in Fire Regime III (35- to 100-year frequency, mixed severity). Typical types represented in these two fire regimes are

shrublands, lodgepole pine forests, mixed deciduous-conifer

forests of the upper Midwest and Northeast, and Douglas-fir

forests of the Pacific Northwest and Intermountain West. Fire

Regimes III and IV have been less dramatically affected by

human intervention as compared to Fire Regimes I and II, but

the more subtle effects of homogenization and increased woody

density have substantial risks to ecosystems (Barbour and

Billings 1988; Hann and Bunnell, in press; Wright and Bailey

1982). Fire exclusion, establishment of exotic species, livestock grazing, and logging are primary causes of departure

for Fire Regimes III and IV.

Lands in Fire Regime V (200-year frequency, stand replacement) are closest to historical conditions with 72

percent in Condition Class 1; 28 percent of the area is beyond its historical range. These areas typically occur in

higher elevation and wetter forests of the United States.

The high elevation types, where human population is scarce,

have been least affected by human intervention, as compared to Fire Regimes I and II. High-elevation spruce/fir

types, whitebark pine, and moist coastal spruce and Douglas fir-hemlock associations represent these types. Some

high-elevation lodgepole pine and northeast conifer/hardwood forests are also included in this fire regime. In

contrast, timber harvest and road effects have extensively

affected the wet and productive forests of the coastal and

Northern Rocky Mountain areas and have increased the risk

of losing key ecosystem components.

Over two-thirds of USFS lands are beyond the historical

range, with 26 percent significantly altered from the historical range (Condition Class 3) (table 7). Only the area in Fire

Regime IV has a high proportion of USFS land (86 percent)

within its historical range. Of particular concern is the high

proportion of USFS lands altered from the historical range in

Fire Regimes I, II, III, and IV; these fire-adapted ecosystems

are perhaps the most adversely affected by fire exclusion,

which causes excessive fuel loadings and ecosystem health

problems. In addition, human populations tend to concentrate in the lower elevations of these fire regimes, putting

people and structures at risk. With its cohesive strategy, the

USDA Forest Service targets these areas to reduce fuel loadings, protect people, and sustain resources (USDA Forest

Service 2000). On DOI lands, 56 percent of the land area is

within its historical range, while 44 percent is altered from

the historical range (table 8). Ten percent is in Condition

Class 3 (significantly altered from the historical range),

while 33 percent is in Condition Class 2 (moderately altered from the historical range). The highest proportion of

area is in Fire Regime III (43 percent); this area is composed primarily of shrublands. The biggest threat to the

loss of key ecosystem components in these shrublands,

particularly the desert shrublands in Condition Classes 2

and 3, is the presence of exotic species such as cheatgrass

(Bromus tectormum). In these shrublands, fire frequency

has increased beyond the historical range, endangering native plant communities.

Table 7—USDA Forest Service land summary of historical fire regimes by condition classes of all cover types except agriculture, barren, water, and urban/development/agriculture.

Condition class

Class 1 Class 2 Class 3

km2 (acres) Row % km2 (acres) Row % km2 (acres) Row %

I. 0–35 years; 80,422 24 141,484 42 116,683 34 338,589 43

low severity (19,872,707) (34,961,526) (28,832,900) (83,667,133)

II. 0–35 years; 18,044 33 35,033 64 1,45 3 54,533 7

stand replacement (4,458,712) (8,656,737) (360,028) (13,475,477)

III. 35–100+ years; 64,937 30 108,110 50 45,186 21 218,233 27

mixed severity (16,046,333) (26,714,487) (11,165,814) (53,926,634)

IV. 35–100+ years; 21,288 23 29,754 32 42,461 45 93,503 12

stand replacement (5,260,312) (7,352,286) (10,492,461) (23,105,059)

V. 200+ years; 78,150 86 11,173 12 1,10 1 90,430 11

stand replacement (19,311,301) (2,760,876) (273,542) (22,345,719)

262,841 Col % 325,553 Col % 206,894 Col % 795,288

Total (64,949,365) 33 (80,445,912) 41 (51,124,745) 26 (196,520,022)

Historical fire

regime

 Total km2 Total

(Total acres) %
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 15

Supplementary Data Layers

National Fire Occurrence, 1986 to 1996

A summary of Federal and non-Federal fire occurrence

per year is shown in table 9, with over 900,000 fires and

100,000 burning km2 from 1986 to 1996. Summaries of fires

per State are shown in appendix D.

Potential Fire Characteristics

The final map of Wildland Fire Risk to Flammable Structures shows a concentration of Fourth Code HUCs of maximum

annual days with potential flame length exceeding 8 feet from

1989 to 1996 in the Southwestern United States, particularly

Arizona (appendix G).

Wildland Fire Risk to Flammable Structures

The final map of Wildland Fire Risk to Flammable Structures is shown in appendix G. Total area of the classes that

have the highest risk of a wildland fire igniting flammable

structures is shown in table 10. Ninety-two percent of the total area in the three risk classes falls in non-Federal ownerships

(table 10). Of the 48 conterminous States, California had the

largest area in the high risk class, with 3,222 km2 (796,174

acres) or 42 percent of all area in the high risk class.

Table 9—Federal and non-Federal fire occurrence per year, 1986 to1996.

Number of Federal km2 Number of non- Non-Federal Total number Total km2

Year Federal fires burned Federal fires km2 burned of fires burned

1986 16,376 5,226 36,728 2,108 53,104 7,334

1987 19,988 7,087 64,110 3,094 84,098 10,181

1988 20,294 14,996 79,717 6,126 100,011 21,122

1989 18,563 4,514 66,056 6,369 84,619 10,883

1990 18,755 3,790 68,479 5,181 87,234 8,971

1991 17,625 1,785 77,998 5,123 95,623 6,908

1992 20,484 5,059 69,598 5,469 90,082 10,528

1993 15,511 2,626 63,381 4,036 78,892 6,662

1994 25,437 10,497 74,402 7,306 99,839 17,803

1995 18,268 4,395 77,646 4,593 95,914 8,988

1996 21,599 13,885 75,634 8,146 97,233 22,031

Total 212,900 73,860 753,749 57,551 966,649 131,411

Table 8—U.S. Department of the Interior (BLM, DOI, FWS, and NPS) land summary of historical fire regimes by condition

classes of all cover types except agriculture, barren, water, and urban/development/agriculture.

Condition class

Class 1 Class 2 Class 3

km2 (acres) Row % km2 (acres) Row % km2 (acres) Row %

I. 0–35 years; 75,679 38 96,448 49 26,151 13 198,277 22

low severity (18,700,695) (23,832,773) (6,461,972) (48,995,440)

II. 0–35 years; 78,788 46 92,539 54 148 1 172,808 19

stand replacement (19,468,939) (22,866,849) (365,960) (42,701,748)

III. 35–100+ years; 251,106 63 104,506 26 40,153 10 395,765 43

mixed severity (62,049,637) (25,823,917) (9,922,142) (97,795,696)

IV. 35–100+ years; 97,030 72 11,838 9 26,734 20 135,601 15

stand replacement (23,976,589) (2,925,197) (6,606,030) (33,507,816)

V. 200+ years; 17,106 89 153 8 475 2 19,118 2

stand replacement (4,226,934) (379,793) (117,371) (4,724,098)

519,709 Col % 306,867 Col % 94,994 Col % 921,569

Total (128,422,794) 56 (75,828,529) 33 (23,473,475) 10 (227,724,798)

Historical fire

regime

 Total km2 Total

(Total acres) %
16 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

DISCUSSION

Vegetation and Biophysical Data Layers

While our methodology of using existing data layers and

expert opinion provided a qualitative comparison of current

vegetation and fuel conditions with estimated historical

conditions, the methodology does have its limitations. Many

of the assignments made in the expert opinion development

process were subjective and potentially not repeatable. Some

assignments made to adjacent regions were initially incompatible. These problems were specifically addressed and

rectified in additional workshops, but revealed the potential

for incongruities across regional boundaries given that different experts made assignments.

Because the vegetation-based data layers were based on

pre-existing maps or spatial data, scale inconsistencies may

cause error in the data layers. Many edits were made to the

Küchler map because of scale differences between the coarse

polygon delineations of the Küchler PNV and the finer scale,

continuous data of the DEM used in terrain matching. We edited the PNV Groups and cover type layers by overlaying them

with the fire regime layer to adjust conflicting combinations,

but because neither the accuracy of the cover type layer or

PNV layer was known, we were uncertain if this step actually

improved the layers. We integrated two readily available,

national-scale current cover type layers to create the Current

Cover Type layer, but different methodologies used to develop these two layers caused spatial registration problems,

such as large water bodies not overlaying, forcing us to shift

the data up to two kilometers. Because the Historical Natural Fire Regimes layer was developed from these vegetation

maps, any spatial inconsistencies were carried through to

this layer.

Another weakness of our methodology was using forest

density as a surrogate for structural stage. Because forest density data were mapped as the amount of forest per unit area,

not as actual forest structure, the data were sometimes inadequate to reliably determine what condition class to assign to

the combination of potential natural vegetation group, cover

type, forest density, and fire regime. Mapping detailed and

accurate forest structure over large areas is complex, data intensive, and usually requires high-resolution data (in other

words, small cell size) (Cohen and Spies 1992). It was beyond the scope of this project to develop a National Forest

structure map. Therefore, we used one of the few available

spatial datasets covering the conterminous United States as a

proxy for structure. Using true forest structure data, developed from newer sensor technologies such as lidar (Light

Detection and Ranging), would likely improve classifications

of condition class. In general, the quality of products could be

improved by developing base layers in conjunction with one

another and in developing layers required by the methodology, specifically forest structure.

One of the most noteworthy aspects of this project was the

succession diagram. The methodology used to develop the

succession diagrams could be used to assign other ecosystem

components such as insect and disease infestation levels, smoke

production, and hydrologic and soil processes. This pathway

approach, as well as the integration of multiple data layers,

can be applied to multiple scales from a national level, as was

done for this project, down to a local level such as a National

Forest or district.

Supplementary Data Layers

National Fire Occurrence, 1986 to 1996

Although we invested 21/2 person-years to develop a complete, conterminous United States fire occurrence spatial

database, not all data were in a usable spatial format or were

not complete. While the Federal database has been verified

by each Federal agency as being representative of the 11-year

period, 1986 to1996, several States (non-Federal data) have

years missing from this time period (appendix F). Fires in the

spatial database are not represented as polygons but instead

Table 10—Area and percent of Risk Class by Federal and non-Federal ownership.

Federal lands Non-Federal lands

Total km2

Risk class km2 (acres) Percenta km2 (acres) Percent (acres)

Low 24,435 7 345,163 93 369,598

(6,038,021) (85,291,641) (91,329,662)

Moderate 4,656 23 15,716 77 20,372

(1,150,523) (3,883,508) (5,034,031)

High 1,717 23 5,904 77 7,621

(424,280) (1,458,910) (1,883,190)

Total 30,808 8 366,783 92 397,591

(7,612,824) (90,634,059) (98,246,883)

a Percent of total area for each risk class.
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 17

are represented as points. Therefore, summaries of area burned

are limited to nonspatial summaries, but even these nonspatial

summaries, if summarized for the entire conterminous United

States, are limited because some States did not report acres

burned (appendix F). Also missing from some non-Federal

records are fields such as fire name, date of control, and cause

(appendix F). Several States, such as Alabama, Oklahoma,

Texas, and Ohio, did not send spatially complete databases,

with some counties having few or no fire records.

Duplicate non-Federal and Federal records for the same

fire may exist in the databases. Fires on Federal land may also

be recorded by State (Bunton 1999). Because fire locations

are generally imprecise (to the nearest section) and not all

database fields that could aid in tracking duplicates are fully

populated, we were unable to track fires duplicated between

Federal and non-Federal databases.

While problems like different cause codes or absence of

key data fields can be documented, it is not known to what

extent wildland fires from States’ urban and rural jurisdictions

go unreported. Fires from volunteer rural firefighting organizations may not be reported to a centralized agency such as

State Fire Marshals or State Foresters (Stuever and others

1995). For instance, the Forestry Division of Montana’s Department of Natural Resources and Conservation in western

Montana rarely receives fire reports from central or eastern

Montana rural fire departments.

Despite the time invested in acquiring and synthesizing data,

inconsistencies in the database still exist, primarily because

most fire data are managed as databases, not as GIS spatial

databases. While the fire occurrence data in its present state

may illustrate trends, the usefulness of this type of product

will be limited until fire reporting is standardized and consistently collected across all jurisdictions with spatial information

such as fire perimeter as a requirement.

Potential Fire Characteristics

The Potential Fire Characteristics data have limited application at any level other than national planning. Although the

concept and application of NFDRS indices has been widely

accepted since the late 1970s, continuous spatial layers of these

data clearly bring out “the worst” in the data. Perhaps the most

limiting factor is the low spatial and temporal density of

weather observations. Spatial density is defined by the number and distribution of acceptable NFDRS reporting stations;

only about 2,000 are used for the entire conterminous United

States. Values between stations are estimated with an inverse

distance-squared technique on a 10-km grid. Burgan and others (1997) have noted that this works reasonably well in areas

of relatively high station density, such as in the Western United

States, but has obvious shortcomings in other areas, particularly for the Central and Eastern States. These shortcomings

are also noted on the Web site for the Wildland Fire Assessment System: http://www.fs.fed.us/land/wfas (USDA Forest

Service 1998). The NFDRS weather observation protocol is

reported once a day at 2:00 p.m., the theoretical worst-case

fire-weather period. This limits the temporal resolution of the

dynamic fire-related weather observations.

Wildland Fire Risk to Flammable Structures

The classes used to assign risk to flammable structures from

wildland fire were designed to target areas where a single fire

event could destroy many homes. These single events are

driven by a combination of extreme fire weather occurrence

and high fire intensity. Areas with moderate to high populations but with low to very low hazard to flammable structures

were missing one or both of these combinations. Though these

areas were classified as low risk, it does not mean a single fire

event could not occur and be a risk to structures. In 2000,

wildland fires burned over 70 structures in western Montana.

These areas were classified as low or very low risk because

western Montana averages less than 10 days per year of

extreme fire weather, compared to parts of New Mexico, which

averages 27 to 90 days per year. The classification provides a

relative comparison of areas from high to low risk across the

conterminous United States.

Each of the input data layers used to develop the Wildland

Fire Hazard to Flammable Structures layer has irregularities

associated with them that may be compounded when combined (Menakis and others, in preparation). By classifying risk

into general classes of low, moderate, and high, we smoothed

some of these irregularities and presented information in a

relative fashion (Menakis and others, in preparation). Our wildland fire risk analysis assumes that all homes are highly

ignitable. This analysis does not consider home exterior materials, design, or ignition zone characteristics, but assesses

the potential and degree of ignitable structure exposure to wildland fire (Menakis and others, in preparation).

Accuracy and Verification

No accuracy assessment or field verification of the spatial

data layers developed for this project was conducted. Kloditz

and others (1998) stated that classification accuracies for 1-km2

resolution or coarser data are not feasible because obtaining

ground truth data would not only be difficult and expensive

but would represent only a very small portion of the image.

Loveland and others (1991) stated that because developed

classes are based on heterogeneous rather than homogeneous

regions and because there is a lack of consistent ground-truth

data, there are limitations to verifying coarse-resolution data.

One potential method to verify coarse-scale data is to use highresolution images in place of ground-truth data (Kloditz and

others 1998), but it was beyond the scope of this project to

acquire and classify high-resolution images as ground-truth

data. Because condition classes are qualitative rather than quantitative attributes and because no similar fine-scale data exists,

no such comparison could be made. Moreover, not all input

data layers have quantitative accuracies associated with them.

For one of the input data layers, the LCC nonforest cover types,

Loveland and others (1991) verified the dataset by comparing

it to other datasets such as Omernik’s (1987) ecoregions, Major Land Resource Areas, and Land Use and Land Cover, but

no quantitative assessment was attempted. Accuracy tests were

performed on the Forest Type Groups and Forest Density data

layers, but the tests were either performed in small areas
18 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

relative to the entire study area or accuracies were reported

for very broad classes (for example, forest and nonforest) (Zhu

and Evans 1994).

MANAGEMENT IMPLICATIONS

Land management agencies need to initiate proactive measures to address combinations of natural resource, political,

and social concerns. Obviously, not all lands can be treated

during any given timeframe. Local criteria have been used in

the past to select areas for treatment. This study provides the

first national-level comparison of current vegetation and fuel

conditions with estimated historical conditions. These data

provide management with an ecological basis for identifying,

then selecting, priority treatment areas based on both the opportunity and need to alter vegetation and fuel conditions.

The dynamic nature of vegetation and dead fuel conditions

of forests and grasslands predisposes large areas of the country to increasing threats to loss of key components that define

ecosystems, increased severity of wildland fires, and continued risk to human lives and property. Recently completed

management plans, such as the Review and Update of the 1995

Federal Wildland Fire Management Policy (U.S. 2001) and

Cohesive Strategy (USDA Forest Service 2000), highlight the

need for proactive management to modify existing vegetation

and fuel conditions to provide long-term relief from escalating risk to both societal and natural resource values (USDA

Forest Service 2000).

Fire Regimes I and II and the Pacific coastal shrub communities included in Fire Regime III will be the focus of the

majority of Federal land management actions. The greatest

departure from historical conditions has occurred in these regimes. The areas in these fire regimes occur primarily in the

highest population centers in the wildland urban interface, as

well as in the most productive growing sites on forest and

rangelands. Addressing social and political objectives of increased protection in wildland urban interface areas will be a

continuing challenge in all fire regimes. The use of fire to

alter vegetation and fuel conditions will be a secondary management option in most of these areas, due primarily to social

sensitivity to smoke production and potential loss from escaped

fires. Primary treatments of mechanical fuel manipulation should

precede fire use applications to reduce the potential damage

from fire restoration or maintenance management actions.

Where natural resource objectives are the primary management focus, aggressive use of fire can be highlighted as a

priority to maintain existing Condition Class 1 areas in fireadapted systems. Treatment with fire in these areas provides

the greatest return for the investment, minimizes long-term

risk to the environment, minimizes social impacts, and offers

the greatest management flexibility for the future.

Depending on each situation, restorative management actions to reverse the vegetative trend in Condition Class 2

environments may require a combination of both fire use and

mechanical treatments to effectively and safely restore

conditions to the maintenance level. Multiple treatments for

areas in Fire Regimes I and II in Condition Class 2 may be

required over one or more historical fire intervals before a

maintenance level, Condition Class 1, is achieved.

Area of fire regimes III, IV, and V in Condition Classes 2

and 3 will receive some focus from wildland management

agencies. Risks in these systems also occur primarily in association with departure of vegetation and fuel composition,

structure, and landscape patterns, but changes are often not as

dramatic as in Fire Regimes I and II. However, fire regimes

do not exist as unlinked entities to the other fire regimes in a

wildfire risk, landscape, watershed, or airshed context. To avoid

landscape scale fragmentation of ecosystem processes, hydrologic regimes, or native species habitats, it is important to

prioritize and design restoration projects from an integrated

ecological and human perspective and to restore whole landscapes using a watershed approach (Hann and Bunnell, in

press; Hann and others 1997, 1998, 2001; Haynes and others

1996; Reiman and others 1999).

Future land management goals should include reducing the

rate of change from lower risk levels of losing key ecosystem

components (Condition Classes 1 and 2) to those with increased risk and loss of management flexibility (Condition

Classes 2 and 3). This study and these data strongly suggest

that continued protection from the natural disturbance element of periodic wildland fire provides only short-term

societal benefits, and delays inevitable changes to vegetation and fuel conditions, producing more severe consequences to all values.

CONCLUSIONS

The coarse-scale mapping project described in this paper

successfully provided land managers with national-level data

on current conditions of vegetation and fuels developed from

ecologically based methods to accomplish fire management

goals and to maintain and restore ecosystems. Key to the

project was the integration of biophysical and remote sensing

data with disturbance and succession information. Data products produced from this project can also be used as input into

risk assessments and other national-level analyses. The methodology used in this project could be applied to finer scales,

using finer input data.

ACKNOWLEDGMENTS

This project was a success because of the assistance of many

individuals. We thank all those who helped with the completion of this project, including Janice Garner, Dalice McIntyre,

Roberta Bartlette, Don Long, Cameron Johnston, Denny

Simmerman, Bob Burgan, Larry Bradshaw, Jane Kapler-Smith,

Janet Howard, and Jack Cohen of the U.S. Department of

Agriculture, Forest Service, Rocky Mountain Research
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 19

Station, Fire Sciences Laboratory; Jim Brown and Duncan

Lutes, Systems for Environmental Management; Susan

Goodman, Bureau of Land Management; and Delvin Bunton,

John Skeels, and Lowell Lewis, USDA Forest Service. We

also thank the condition class workshop participants: Rich

Lasko, Barry Bollenbacher, Pat Green, Mark Grant, Glenda

Scott, Byron Bonney, Jeff Jones, Henry Goehle, Clint Dawson,

Ron Moody, Wayne Robbie, Reggie Fletcher, Steven Zachry,

Dave Thomas, Tim Belton, Kathy Geier-Hayes, Joe Carvelho,

Lynn Bennett, Sue Husari, Neil Sugihara, Bernie Bahro, Mark

Borchert, Tim Rich, Peter Teensma, Dave Powell, John Stivers,

Finis Harris, Andi Koonce, Sybill Amelon, Clint Williams, Jon

Regelbrugge, Louisa Evers, Jeff Rose, Jane Kertis, Paul Tine,

Dave Cleland, and Thomas Phillips with the USDA Forest

Service; Joe Burns with the U.S. Fish and Wildlife Service;

Karen Ogle with the Bureau of Land Management; and Dave

Sapsis with the California Department of Forestry and Fire

Protection.

We also wish to thank our technical reviewers: Emily

Heyerdahl, Russ Parsons, and Bob Keane with the U.S. Department of Agriculture, Forest Service, Rocky Mountain

Research Station, Fire Sciences Laboratory; Cristina Milesi

with the University of Montana; and Mike Hilbruner with the

Forest Service Washington Office.

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22 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Appendix A: Potential Natural Vegetation Groups (after Küchler

1975)

Potential natural vegetation group Küchler PNV

ECORegion 1

1: Pine forest K011 Western ponderosa forest

K016 Eastern ponderosa forest

K017 Black Hills pine forest

3: Pine-Douglas-fir K018 Pine-Douglas-fir forest

4: Douglas-fir K012 Douglas-fir forest

7: Grand fir-Douglas-fir K014 Grand fir-Douglas-fir forest

13: Cedar-hemlock-Douglas-fir K002 Cedar-hemlock-Douglas-fir forest

K013 Cedar-hemlock-pine forest

16: Western spruce-fir K015 Western spruce-fir forest

25: Sagebrush K038 Great Basin sagebrush

K055 Sagebrush steppe

K056 Wheatgrass-needlegrass shrub steppe

28: Desert shrub K040 Saltbrush-greasewood

31: Mountain grassland K050 Fescue-wheatgrass

K051 Wheatgrass-bluegrass

K063 Foothills prairie

32: Plains grassland K064 Grama-needlegrass-wheatgrass

K065 Grama-buffalo grass

K066 Wheatgrass-needlegrass

K067 Wheatgrass-bluestem-needlegrass

K068 Wheatgrass-grama-buffalo grass

33: Prairie K074 Bluestem prairie

K075 Nebraska Sandhills prairie

37: Alpine meadows-barren K052 Alpine meadows and barren

38: Oak savanna (ND) K081 Oak savanna

60: Northern floodplain K098 Northern floodplain forest

ECORegion 2

1: Pine forest K016 Eastern ponderosa forest

K017 Black Hills pine forest

3: Pine-Douglas-fir K018 Pine-Douglas-fir forest

4: Douglas-fir K012 Douglas-fir forest

16: Western spruce-fir K015 Western spruce-fir forest

K021 Southwestern spruce-fir forest

22: Juniper-pinyon K023 Juniper-pinyon woodland

25: Sagebrush K038 Great Basin sagebrush

K055 Sagebrush steppe

K056 Wheatgrass-needlegrass shrub steppe

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USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 23

Potential natural vegetation group Küchler PNV

26: Chaparral K037 Mountain mahogany-oak scrub

28: Desert shrub K039 Blackbrush

K040 Saltbrush-greasewood

32: Plains grassland K063 Foothills prairie

K064 Grama-needlegrass-wheatgrass

K065 Grama-buffalo grass

K066 Wheatgrass-needlegrass

K067 Wheatgrass-bluestem-needlegrass

K068 Wheatgrass-grama-buffalo grass

K069 Bluestem-grama prairie

33: Prairie K070 Sandsage-bluestem prairie

K074 Bluestem prairie

K075 Nebraska Sandhills prairie

37: Alpine meadows-barren K052 Alpine meadows and barren

39: Mosaic bluestem/oak-hickory K082 Mosaic of numbers 74 and 100

45: Oak-hickory K084 Cross timbers

K100 Oak-hickory forest

60: Northern floodplain K098 Northern floodplain forest

ECORegion 3

1: Pine forest K019 Arizona pine forest

3: Pine-Douglas-fir K018 Pine-Douglas-fir forest

10: SW mixed conifer (AZ, NM) K020 Spruce-fir-Douglas-fir forest

16: Western spruce-fir K021 Southwestern spruce-fir forest

22: Juniper-pinyon K023 Juniper-pinyon woodland

24: Mesquite bosques (NM) K027 Mesquite bosques

25: Sagebrush K038 Great Basin sagebrush

26: Chaparral K031 Oak-juniper woodland

K032 Transition between 31 and 37

K037 Mountain mahogany-oak scrub

27: Southwest shrub steppe K058 Grama-tobosa shrub steppe

K059 Trans-Pecos shrub savanna

28: Desert shrub K039 Blackbrush

K040 Saltbrush-greasewood

K041 Creosote bush

K042 Creosote bush-bur sage

K043 Palo verde-cactus shrub

K044 Creosote bush-tarbush

K046 Desert: vegetation largely absent

29: Shinnery K071 Shinnery

32: Plains grassland K065 Grama-buffalo grass

K066 Wheatgrass-needlegrass

34: Desert grassland K053 Grama-galleta steppe

K054 Grama-tobosa prairie

37: Alpine meadows-barren K052 Alpine meadows and barren

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24 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Potential natural vegetation group Küchler PNV

ECORegion 4

2: Great Basin pine (NV, UT) K022 Great Basin pine forest

3: Pine-Douglas-fir K011 Western ponderosa forest

K018 Pine-Douglas-fir forest

K019 Arizona pine forest

4: Douglas-fir K012 Douglas-fir forest

7: Grand Fir-Douglas-fir K014 Grand fir-Douglas-fir forest

9: Spruce fir-Douglas-fir K020 Spruce-fir-Douglas-fir forest

16: Western spruce-fir K015 Western spruce-fir forest

K021 Southwestern spruce-fir forest

17: Lodgepole pine-Subalpine (CA) K008 Lodgepole pine-subalpine forest

22: Juniper-pinyon K023 Juniper-pinyon woodland

23: Juniper steppe K024 Juniper steppe woodland

25: Sagebrush K038 Great Basin sagebrush

K055 Sagebrush steppe

26: Chaparral K037 Mountain mahogany-oak scrub

28: Desert shrub K039 Blackbrush

K040 Saltbrush-greasewood

K041 Creosote bush

K042 Creosote bush-bur sage

K043 Palo verde-cactus shrub

K046 Desert: vegetation largely absent

K053 Grama-galleta steppe

K057 Galleta-three awn shrub steppe

31: Mountain grassland K051 Wheatgrass-bluegrass

K063 Foothills prairie

36: Wet grassland K049 Tule marshes

37: Alpine meadows-barren K052 Alpine meadows and barren

ECORegion 5

1: Pine forest K010 Ponderosa shrub forest

K019 Arizona pine forest

2: Great Basin pine (NV, UT) K022 Great Basin pine forest

5: Mixed conifer K005 Mixed conifer forest

8: Red fir (CA) K007 Red fir forest

11: Redwood (CA) K006 Redwood forest

13: Cedar-hemlock-Douglas-fir K002 Cedar-hemlock-Douglas-fir forest

15: Fir-hemlock (WA, OR) K004 Fir-hemlock forest

17: Lodgepole-subalpine K008 Lodgepole pine-subalpine forest

18: California mixed evergreen K029 California mixed evergreen forest

19: Oakwoods (CA) K026 Oregon oakwoods

K030 California oakwoods

K028 Mosaic of 2 and 26

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USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 25

Potential natural vegetation group Küchler PNV

22: Juniper-pinyon K023 Juniper-pinyon woodland

23: Juniper steppe K024 Juniper steppe woodland

25: Sagebrush K038 Great Basin sagebrush

K055 Sagebrush steppe

26: Chaparral K009 Pine-cypress forest

K033 Chaparral

K034 Montane chaparral

K035 Coastal sagebrush

K036 Mosaic of 30 and 35

28: Desert shrub K040 Saltbrush-greasewood

K041 Creosote bush

K042 Creosote bush-bur sage

K043 Palo verde-cactus shrub

K046 Desert: vegetation largely absent

K058 Grama-tobosa shrub steppe

30: Annual grassland K048 California steppe

31: Mountain grassland K047 Fescue-oatgrass

K051 Wheatgrass-bluegrass

36: Wet grassland K049 Tule marshes

37: Alpine meadows-barren K052 Alpine meadows and barren

ECORegion 6

1: Pine forest K010 Ponderosa shrub forest

K011 Western ponderosa forest

4: Douglas-fir K012 Douglas-fir forest

5: Mixed conifer K005 Mixed conifer forest

6: Silver fir-Douglas-fir K003 Silver fir-Douglas-fir forest

7: Grand fir-Douglas-fir K014 Grand fir-Douglas-fir forest

12: Cedar-hemlock-pine (WA) K013 Cedar-hemlock-pine forest

13: Cedar-hemlock-Douglas-fir K002 Cedar-hemlock-Douglas-fir forest

14: Spruce-cedar-hemlock (WA, OR) K001 Spruce-cedar hemlock forest

15: Fir-hemlock (WA, OR) K004 Fir-hemlock forest

16: Western spruce-fir K015 Western spruce-fir forest

18: California mixed evergreen K029 California mixed evergreen forest

19: Oakwoods K026 Oregon oakwoods

20: Mosaic cedar-hemlock-Douglas-fir and oak (OR) K028 Mosaic numbers 2 and 26

21: Alder-ash (WA, OR) K025 Alder-ash forest

23: Juniper steppe K024 Juniper steppe woodland

25: Sagebrush K038 Great Basin sagebrush

K055 Sagebrush steppe

28: Desert shrub K040 Saltbrush-greasewood

31: Mountain grassland K050 Fescue-wheatgrass

K051 Wheatgrass-bluegrass

37: Alpine meadows-barren K052 Alpine meadows and barren

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26 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Potential natural vegetation group Küchler PNV

ECORegion 8

3: Pine-Douglas-fir K018 Pine-Douglas-fir forest

16: Western spruce-fir K021 Southwestern spruce-fir forest

22: Juniper-pinyon K023 Juniper-pinyon woodland

26: Chaparral K031 Oak-juniper woodland

27: Southwest shrub steppe K058 Grama-tobosa shrub steppe

K059 Trans-Pecos shrub savanna

28: Desert shrub K040 Saltbrush-greasewood

29: Shinnery K071 Shinnery

32: Plains grassland K065 Grama-buffalo grass

K069 Bluestem-grama prairie

K085 Mesquite-buffalo grass

33: Prairie K070 Sandsage-bluestem prairie

K074 Bluestem prairie

K076 Blackland prairie

K077 Bluestem-sacahuista prairie

K083 Cedar glades

K088 Fayette prairie

34: Desert grassland K054 Grama-tobosa prairie

35: Texas savanna K045 Ceniza shrub

K060 Mesquite savanna

K061 Mesquite-acacia savanna

K062 Mesquite-live oak savanna

K086 Juniper-oak savanna

K087 Mesquite-oak savanna

36: Wet grassland K072 Sea oats prairie

K073 Northern cordgrass prairie

K078 Southern cordgrass prairie

K079 Palmetto prairie

K092 Everglades

39: Mosaic bluestem/oak-hickory K082 Mosaic of numbers 74 and 100

40: Cross timbers K084 Cross timbers

43: Eastern spruce-fir K097 Southeastern spruce-fir forest

45: Oak-hickory K100 Oak-hickory forest

48: Mixed mesophytic forest K104 Appalachian oak forest

55: Oak-hickory-pine K111 Oak-hickory-pine forest

56: Southern mixed forest K112 Southern mixed forest

57: Loblolly-shortleaf pine K114 Pocosin

K115 Sand pine scrub

58: Blackbelt K089 Blackbelt

59: Oak-gum-cypress K090 Live oak-sea oats

K091 Cypress savanna

K105 Mangrove

61: Southern floodplain K113 Southern floodplain forest

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USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 27

Potential natural vegetation group Küchler PNV

ECORegion 9

32: Plains grassland K067 Wheatgrass-bluestem-needlegrass

33: Prairie K074 Bluestem prairie

K075 Nebraska Sandhills prairie

K083 Cedar glades

36: Wet grassland K073 Northern cordgrass prairie

39: Mosaic bluestem/oak-hickory K082 Mosaic of numbers 74 and 100

41: Conifer bog (MN) K094 Conifer bog

42: Great Lakes pine forest K095 Great Lakes pine forest

43: Eastern spruce-fir K093 Great Lakes spruce-fir forest

K096 Northeastern spruce-fir forest

44: Maple-basswood K081 Oak savanna

K099 Maple-basswood forest

45: Oak-hickory K100 Oak-hickory forest

46: Elm-ash forest K101 Elm-ash forest

47: Maple-beech-birch K102 Beech-maple forest

48: Mixed mesophytic forest K103 Mixed mesophytic forest

49: Appalachian oak K104 Appalachian oak forest

K105 Mangrove

K106 Northern hardwoods

50: Transition Appalachian oak-northern hardwoods K104 Appalachian oak forest

K106 Northern hardwoods

52: Northern hardwoods-fir K107 Northern hardwoods-fir forest

53: Northern hardwoods-spruce K108 Northern hardwoods-spruce forest

54: Northeastern oak-pine K110 Northeastern oak-pine forest

55: Oak-hickory-pine K111 Oak-hickory-pine forest

60: Northern floodplain K098 Northern floodplain forest

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28 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Appendix B: Current Cover Types (from LCC database, 1990, and

RPA Forest Cover Types, 1992)

Code: Cover type name

1: Agriculture

2: Grassland

3: Wetlands

4: Desert shrub

5: Other shrub

6: Oak-pine

7: Oak-hickory

8: Oak-gum-cypress

9: Elm-ash-cottonwood

10: Maple-beech-birch

11: Aspen-birch

12: Western hardwoods

13: White-red-jack pine

14: Eastern spruce-fir

15: Longleaf-slash pine

16: Loblolly-shortleaf pine

17: Ponderosa pine

18: Douglas-fir

19: Larch

20: Western white pine

21: Lodgepole pine

22: Hemlock-Sitka spruce

23: Western fir-spruce

24: Redwood

25: Pinyon-juniper

26: Alpine tundra

27: Barren

28: Water

30: Urban/development/agriculture
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 29

Appendix C: Example of a Succession Diagram Summary Report

ECOHUC Section: -212A

PNV Group: 43: Spruce - fir Fire Regime: 4 : 35-100+ yrs; Stand Replacement

Cover Types Forest Density Area -Km2

1 10: Maple - beech - birch 2: 33 - 66 % 1

2 10: Maple - beech - birch 3: 67 - 100 % 3

3 11: Aspen - birch 3: 67 - 100 % 2

4 30: Urban/Development/Ag 0: Non Forest 6

PNV Group: 45: Oak - hickory Fire Regime: 3 : 35-100+ yrs; Mixed Severity

Cover Types Forest Density Area -Km2

5 9: Elm - ash- cottonwood 2: 33 - 66 % 5

PNV Group: 48: Mixed mesophytic forest Fire Regime: 3 : 35-100+ yrs; Mixed Severity

Cover Types Forest Density Area -Km2

6 6: Oak - pine 2: 33 - 66 % 6

7 6: Oak - pine 3: 67 - 100 % 6

8 7: Oak - hickory 1: 0 - 32 % 6

PNV Group: 50: Transition Appalachian Oak - Fire Regime: 3 : 35-100+ yrs; Mixed Severity

Northern Hardwood

Cover Types Forest Density Area -Km2

9 10: Maple - beech - birch 2: 33 - 66 % 1

10 10: Maple - beech - birch 3: 67 - 100 % 5

PNV Group: 53: Northern hardwoods - spruce Fire Regime: 5 : 200+ yrs; Stand Replacement

Cover Types Forest Density Area -Km2

32 13: White - red - jack pine 2: 33 - 66 % 4

33 13: White - red - jack pine 3: 67 - 100 % 50

34 14: Spruce - fir (East) 2: 33 - 66 % 124

35 14: Spruce - fir (East) 3: 67 - 100 % 1836

36 30: Urban/Development/Ag 0 : Non Forest 443
30 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Appendix D: Federala and Non-Federal Fire Occurrence Per State,

1986 to 1996

Number of Federal km2 Number of non- Non-Federal Total number Total km2

FIPSb State Federal fires burned Federal fires km2 burned of fires burned

1 Alabama 1,230 106 168 1,398 106

4 Arizona 31,548 4,326 9,201 2,571 40,749 6,897

5 Arkansas 1,853 116 23,626 1,116 25,479 1,232

6 California 36,751 10,337 101,144 6,467 137,895 16,804

8 Colorado 10,182 1,011 4,868 500 15,050 1,511

9 Connecticut 2 0 1,268 16 1,270 16

10 Delaware 19 13 401 not reported 420 13

11 District of Columbia 32 0 0 0 32 0

12 Florida 3,182 1,624 51,519 4,709 54,701 6,333

13 Georgia 1,229 131 91,935 1,492 93,164 1,623

16 Idaho 16,416 16,595 5,169 2,357 21,585 18,952

17 Illinois 362 20 1,201 not reported 1,563 20

18 Indiana 668 21 14,004 291 14,672 312

19 Iowa 102 10 378 not reported 480 10

20 Kansas 191 59 74,933 7,148 75,124 7,207

21 Kentucky 1,641 293 1,191 not reported 2,832 293

22 Louisiana 1,386 428 3,206 not reported 4,592 428

23 Maine 62 1 7,564 96 7,626 97

24 Maryland 123 13 5,850 157 5,973 170

25 Massachusetts 52 0 29,677 156 29,729 156

26 Michigan 839 51 6,166 229 7,005 280

27 Minnesota 3,556 964 18,482 2,206 22,038 3,170

28 Mississippi 2,882 358 39,427 2,213 42,309 2,571

29 Missouri 2,559 328 18,457 1,235 21,016 1,563

30 Montana 13,787 5,638 4,467 1,582 18,254 7,220

31 Nebraska 590 391 14,672 2,420 15,262 2,811

32 Nevada 7,128 4,883 not reported not reported 7,128 4,883

33 New Hampshire 38 1 1,484 not reported 1,522 1

34 New Jersey 81 1 11,237 277 11,318 278

35 New Mexico 10,986 3,385 7,397 4,936 18,383 8,321

36 New York 404 6 4,412 172 4,816 178

37 North Carolina 1,494 271 51,017 4,352 52,511 4,623

38 North Dakota 4,355 368 3,087 447 7,442 815

39 Ohio 481 16 2,412 60 2,893 76

40 Oklahoma 2,617 356 16,781 2,071 19,398 2,427

41 Oregon 20,851 7,556 13,083 1,064 33,934 8,620

42 Pennsylvania 174 5 9,124 239 9,298 244

44 Rhode Island 3 0 335 not reported 338 0

45 South Carolina 1,098 66 28,616 620 29,714 686

46 South Dakota 6,583 862 382 187 6,965 1,049

47 Tennessee 1,161 111 9,528 365 10,689 476

48 Texas 2,089 899 14,262 1,065 16,351 1,964

49 Utah 8,335 4,236 4,891 2,837 13,226 7,073

50 Vermont 10 1 942 8 952 9

51 Virginia 809 102 4,167 76 4,976 178

53 Washington 7,514 1,965 12,892 852 20,406 2,817

54 West Virginia 240 10 6,294 not reported 6,534 10

55 Wisconsin 1,333 29 19,197 189 20,530 218

56 Wyoming 3,872 5,898 3,235 772 7,107 6,670

Total 212,900 73,861 753,749 57,550 966,649 131,411

a Federal fires include USDA Forest Service, USDI Bureau of Land Management, USDI Bureau of Indian Affairs, USDI Park Service, and

USDI Fish and Wildlife Service. b FIPS: Federal Information Processing Standards.
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 31

Appendix E: National Fire Occurrence GIS Database Fields

Field Name Length Typea Comments

UNIQUENUM 9 B Unique number for each record

State records: State FIPS + FIRENUMBER

Federal records: Agency code + 2-digit year + FIRENUMBER

AGENCY 1 I Federal agency codes:

0 = Non-Federal

1 = BLM, Bureau of Land Management

2 = BIA, Bureau of Indian Affairs

3 = NPS, National Park Service

4 = FWS, Fish and Wildlife Service

5 = U.S. Forest Service

FIRENUMBER 7 B Numeric identifier within each State or agency

FIRENAME 30 C Not always provided

YEAR 4 B Year of fire (4 digit: 1986, 1987, and so forth)

MONTH_DISC 2 I Month discovered (or comparable)

DAY_DISC 2 I Day discovered (or comparable)

TIME_DISC 4 B Time discovered (2400 clock)

MONTH_CONT 2 I Month controlled (or comparable)

DAY_CONT 2 I Day controlled (or comparable)

TIME_CONT 4 B Time controlled (2400 clock)

ACRES_TOTAL 12 F Allow for 2 decimals

CAUSE_STD 2 B Standardized cause code with the following categories:

1 = Lightning 6 = Equipment use

2 = Campfire 7 = Railroad

3 = Smoking 8 = Children

4 = Debris burning 9 = Miscellaneous

5 = Incendiary 0 = Unknown

CAUSE2 2 I Cause of fire reclassified as:

1 = Lightning/natural cause

2 = Human cause

0 = Unknown or not reported

STATE 20 C State name

COUNTY 32 C County name

STATE_FIPS 3 I State Federal Information Processing Standards (FIPS) code

DATA_SOURCE 5 C Source of data recorded as state or agency abbreviation

REG (1-6, 8, 9) = U.S. Forest Service Region

BLM = Bureau of Land Management

BIA = Bureau of Indian Affairs

NPS = National Park Service

FWS = Fish and Wildlife Service

YEARSINDB 25 C Years for which data are present, for example, 1986–1996

LOC_SOURCE 14 C Best location provided by state or agency, for example, County, Legal-TRS

(Township, Range, Section), Legal-TRSQQ (Township, Range, Section, Quarter,

Quarter), UTM, GIS, Lat/Long

NUM_YEARS 3 B Number of years provided in database, for example, 11 if 1986–1996

STATUS 1 I Item specifying status of data based on review by agency or State fire directors

1 = Satisfactory 2 = Unsatisfactory 0 = Not reviewed

LONG_DD 8,18 F Longitude in decimal degrees, 5 decimals

LAT_DD 8,18 F Latitude in decimal degrees, 5 decimals

a Type: Binary, Integer, Character, Floating.
32 USDA Forest Service General Technical Report RMRS-GTR-87. 2002. Appendix F: Non-Federal Fire Data Completeness (* indicates field was included in database obtained from State) Location Years in Fire Discovered Contained Area Cause State source database Statusa name Month Day Time Month Day Time burned of fire Arizona UTM 1986–1996 0 * * * * * * * * California GIS 1986–1996 1,2b * ** * ** * * Colorado GIS 1986–1995 0 * * * * Connecticut County 1991–1997 0 * * * * * Delaware NFIRS 1987–1988, 2 * * * 1990, 1995–1996 Florida Legal–TRSc 1986–1996 0 * * * * * * * * Georgia County 1986–1996 0 * * * * * * Iowa NFIRS 1987–1988, 2 * * * 1990–1996 Idaho Legal–TRS 1986–1989, 0 * * * * * * * * * 1991–1996 Illinois NFIRS 1987–1988, 2 * * * 1990–1996 Indiana County 1986–1996 0 * * * * Kansas County 1986–1996 0 * * * * * Kentucky NFIRS 1987–1988, 2 * * * 1990–1996 Louisiana NFIRS 1987–1988, 2 * * * 1990–1996 Massachusetts County 1991–1997 2 * * * * * Maryland County 1987–1992, 0 * * * * 1994–1996 Maine Lat/Long 1986–1996 0 * * * * * * * * * Michigan Legal–TRS 1986–1996 1 * * * * * * * * Minnesota Legal–TRS 1986–1996 1 * * * * * * * * Missouri Legal–TRS, 1990–1997 0 * * * * * * * * County Mississippi GIS 1988–1997 0 * * * * * * Montana Legal–TRS 1986–1996 0 * * * * * * * * * North Carolina County 1986–1996 0 * * * * * * * * North Dakota County 1988–1996 0 * * * * Nebraska County 1987–1996 0 * * * * Nevada Non–Federal fires not reported New Hampshire NFIRS 1987–1988, 2 * * * 1990–1996 New Jersey Lat/Long 1986, 0 * * * * 1989–1995 New Mexico Legal–TRS 1986–1996 0 * * * * * * * * * New York County 1986–1997 0 * * * * * * * Ohio County 1993–1996 0 * * * *
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 33 Oklahoma Legal–TRS 1989–1996 0 * * * * * * * Oregon Legal–TRS 1986–1996 0 * * * * * * * * Pennsylvania County 1986–1992 0 * * * * Rhode Island NFIRS 1987–1988, 2 * * * 1990–1995 South Carolina Lat/Long 1988–1992 0 * * * * South Dakota Legal–TRS 1988–1996 0 * * * * * * Tennessee County 1993–1996 0 * * * * * * * * * Texas County 1988–1993, 0 * * * * * * 1995–1996 Utah Legal–TRS 1986–1996 0 * * * * Virginia County 1990–1992 0 * * * * Vermont County 1992–1996 0 * * * * * Washington Legal–TRS 1986–1996 0 * * * * * * * * Wisconsin Legal–TRSQQ 1986–1996 1 * * * * * * * * West Virginia NFIRS 1987–1988, 2 * * * 1990–1996 Wyoming Legal–TRS 1991–1996 0 * * * * a Status codes: 1 = Satisfactory, 2 = Unsatisfactory, 0 = Not reviewed.

b Data for years 1987, 1991, 1993, and 1996 were given an “unsatisfactory” in review by State Foresters.c TRS is Township, Range, Section; TRSQQ is Township, Range, Section, Quarter, Quarter.
34 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.

Appendix G: All Maps
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 35
36 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 37
38 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 39
40 USDA Forest Service General Technical Report RMRS-GTR-87. 2002.
USDA Forest Service General Technical Report RMRS-GTR-87. 2002. 41
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