Deﬁning the Wildland–Urban Interface

Defining the Wildland–UrbanInterface

Susan I. Stewart, Volker C. Radeloff, Roger B. Hammer, andTodd J. Hawbaker

Federal wildland fire policy in the United States has been substantially revised over the past 10 yearsand new emphasis has been given to the wildland– urban interface (WUI), which creates a need forinformation about the WUI’s location and extent. We operationalized a policy definition published inthe Federal Register (US Department of the Interior [USDI] and US Department of Agriculture [USDA]),2001, Urban wildland interface communities within vicinity of federal lands that are at high risk fromwildfire. Fed. Regist. 66(3):751–777) to create national maps and statistics of the WUI to guidestrategic planning. Using geographic information system analysis, we evaluate the national WUI byaltering the definition’s parameters to assess the influence of individual parameters (i.e., housingdensity, vegetation type and density, and interface buffer distance) and stability of outcomes. The mostsensitive parameter was the housing density threshold. Changes in outputs (WUI homes and area) weremuch smaller than parameter variations suggesting the WUI definition generates stable results on mostlandscapes. Overall, modifying the WUI definition resulted in a similar amount of WUI area and numberof homes and affected the precise location of the WUI.

Keywords: wildland– urban interface; wildland fire; housing growth; GIS sensitivity analysis;wildland fire policy

T he wildland–urban interface(WUI) has become the central fo-cus of wildland fire policy in the

United States. The tragic 1994 Storm Kingincident, in which 14 firefighters were killed,initiated intense scrutiny of wildfire policyand management (US Department of theInterior [USDI] and US Department of Ag-riculture [USDA] 2006). When the FederalWildland Fire Management Policy and Pro-gram Review was issued the following year,

it clarified the role of the federal agencies infighting fires in the WUI (USDI and USDA1995). A 10-year overhaul of US wildlandfire policy followed, spurred on by the ex-treme fire season of 2000. Each of the re-ports and initiatives issued in successiveyears—the Report to the President in Sep-tember of 2000, the 10-year ComprehensiveStrategy of 2001, its implementation planand the Healthy Forest Initiative in 2002,and the Healthy Forest Restoration Act

(HFRA), which became law in 2003—reit-erated the need for resource managers towork with communities and homeowners inthe WUI to reduce the risks associated withwildfire.

The increasing national fire policy fo-cus on the WUI came in response to recenthousing trends in the United States. Home-owners want to be near open space and inclose contact with nature. From 1940 to2000, significant housing growth occurredin suburban and rural areas, especially in andnear forests (Radeloff et al. 2005a). Housinggrowth was strong nationwide, including ar-eas with short fire return intervals and highdeparture from historic conditions such asthe Rocky Mountains and the Sierra Nevada(Hammer et al. in press). The effects of re-source management practices, climatechanges, and insect and disease infestations,together with continued housing growth inhigh fire-risk areas thus create an urgentneed to understand and manage fire risk inthe WUI (Pyne 2001).

Governments at all levels share respon-sibility for wildland fire management in theWUI. The federal government’s role is toprovide leadership, coordination, and re-search across the country, a role that benefits

Received June 20, 2006; accepted April 17, 2007.

Susan I. Stewart ([email protected]) is research social scientist, Northern Research Station, USDA Forest Service, 1033 University Avenue, Suite 360, Evanston,IL 60201. Volker C. Radeloff ([email protected]) is associate professor, Department of Forest Ecology and Management, University of Wisconsin, Madison,Wisconsin. Roger B. Hammer ([email protected]) is assistant professor, Department of Sociology, Oregon State University, Corvallis, Oregon. Todd J.Hawbaker ([email protected]) is Ph.D. student, Department of Forest Ecology and Management, University of Wisconsin, Madison, Wisconsin. The authors aregrateful for the comments of Pam Jakes and Don Field on an earlier version of this article. Support for this research was provided by the USDA Forest Service NorthernResearch Station under the National Fire Plan, and by the University of Wisconsin–Madison.

Copyright © 2007 by the Society of American Foresters.

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from the ability to locate and compare theWUI in different states and regions. To sup-port this aspect of WUI management andstrategic planning, we created a map of theWUI across the lower 48 states (Radeloff etal. 2005b). Unlike a community-level WUImap that can be enriched by using detailedlocal data, this “big picture” national maprequired nationally consistent data and a sin-gle standardized WUI definition. Here, wesought to understand how the national WUImap is influenced by the WUI definitionused, the relative effect of each part of thedefinition, and the overall usefulness of themap in identifying homes likely to be af-fected by wildfire. We used geographic in-formation system (GIS) analysis to addressthese questions.

Literature ReviewA good WUI map provides a graphic

representation that matches the conceptualunderstanding of what and where the WUIis. This conceptual understanding of theWUI has evolved over time; the area wherehouses and forests meet has attracted atten-tion for many years. Bradley’s book (Bradley1984) on the resource management issues inthe interface is a major early contribution.Even earlier, Henry Vaux characterized theWUI as the “hotseat of forestry” (Vaux1982) and cautioned foresters not to under-estimate its political and policy significance.Both authors discussed a wide range of WUIissues and neither equated the WUI withwildland fire. However, the focus of WUIdiscussions had narrowed by the end of the1980s, when Davis (1990) characterized theWUI as a setting where wildland fire is aproblem and where conflicts arise over re-sponsibility for protecting homes from wild-fire. A 1997 issue of the Journal of Forestryfeatured a cover photo of a wildland fire en-croaching on a subdivision and included twoarticles about the WUI that emphasized fireplanning and management (Greenberg andBradley 1997, Plevel 1997). The term “wild-land–urban interface” is now used almostexclusively in the context of wildland fire.

Extensive references to the WUI in USfire policy reflect the fire management com-munity’s long familiarity with the concept.Published in the Federal Register in conjunc-tion with the National Fire Plan (NFP), theWUI definition states that “The WUI com-munity exists where humans and their devel-opment meet or intermix with wildland fu-els” (USDA and USDI 2001, p. 752–753).This definition was adapted from a report to

the Western Governor’s Association (Teieand Weatherford 2000), with only minorchanges. The more recent HFRA movesaway from this standardized approach to de-fining the WUI by allowing communities toestablish a buffer zone around the town, thecivic infrastructure, and evacuation routes,including these areas in the WUI as well.This more flexible definition is consistentwith the HFRA’s emphasis on empoweringlocal communities to develop CommunityWildfire Protection Plans.

Throughout its evolution, the WUIdefinition always includes three compo-nents: human presence, wildland vegeta-tion, and a distance that represents the po-tential for effects (e.g., wildland fire andhuman activity) to extend beyond bound-aries and impact neighboring lands. Beyondthese three components, most WUI discus-sions are imprecise regarding what is or isnot included. For example, human presencehas been defined by housing density, popu-lation density, number of houses, orconfiguration of housing developments andneighborhood characteristics. Wildlandvegetation is always mentioned, but the den-sity, extent, and type of vegetation thatmakes some vegetation “wildland vegeta-tion” is not well defined. The distance thatthe WUI extends into wildlands or into ahousing development has been described inmany different ways, including the distancea golf ball will fly off the porch or the dis-tance from which flames or firebrands canreach a structure (Summerfelt 2003), butspecific distances are rarely given.

Conceptually, these many definitionsall refer to the same basic idea, that the WUIis where houses and wildlands meet or over-lap. However, operationally, they differ andin previous WUI maps, definitions vary de-pending on data available at the time andacross the extent of the map. For example,Greenburg and Bradley (1997) used remotesensed data to assess vegetative characteris-tics related to human presence in two cities.In their Eugene, Oregon, WUI map, popu-lation and road densities captured humanpresence; for the Seattle map, distance fromthe city center was used as a proxy for humanpresence. Lein introduced fuzzy methods ofdetermining the WUI’s location, relying onremote sensed data to detect the presence ofboth structures and vegetation (Lein 2006).Two earlier maps attempted to represent riskfrom fire as well as vegetation and housingcharacteristics. Space Imaging’s (2002)Floridawide fire risk tool used Census pop-

ulation data and determined vegetationproximity via detailed fuels mapping, al-though the Census data’s resolution, therules for determining vegetation and popu-lation proximity, and the types of vegetationincluded were not specified, and the distinc-tion between interface and intermix WUIwas made based on population densityalone. A coarse-scale map of the wildlandfire risk to structures was developed as a toolfor strategic planning (Schmidt et al. 2002).Ambient population data (USDE 2005) wasused to derive housing densities and com-bined with extreme fire potential (derivedfrom climate data) and potential fire expo-sure data (derived from vegetation data) tocategorize threat levels at a 1-km resolution.

These examples illustrate that despiteall that has been written about the WUI andits significance in fire policy, there is no sin-gle operational definition. A review by theGovernment Accountability Office (GAO)of NFP implementation criticized the fed-eral agencies responsible for wildland firemanagement on this point (Hill 2001). In aformal response included in the GAO re-port, Forest Service Chief Bosworth reaf-firmed his agency’s commitment to main-taining enough flexibility in defining theWUI to accommodate the many differentkinds of landscapes it manages.

Flexibility is valuable for both forest-and community-level mapping and manage-ment but is counterproductive whencomparing WUI across places or over timeperiods. Our research was intended to assessthe WUI across regions and to track itsgrowth and change over time, two purposesthat required standardizing the WUI defini-tion. With no previous standard definitionof the WUI to draw from, we tested the def-inition we developed to ensure its consis-tency with our research aims and with stra-tegic wildland fire planning.

The 2001 Federal Register (USDA andUSDI 2001)WUI definition describes thecharacteristics of houses and vegetation andthe relationship between them that must oc-cur for an area to be classified as WUI. Inthis regard, the definition is a model or ab-stract representation of reality. Sensitivityanalysis is a set of methods used in GIS anal-ysis to assess various characteristics of amodel (Crosetto et al. 2000). The housingand vegetation characteristics and the bufferdistances are the parameters of the WUI def-inition, and the definition can be assessed byvarying the parameters one at a time to iso-late the effect of each on the model output,

202 Journal of Forestry • June 2007

which is the WUI map (Hamby 1994). Sen-sitivity analysis also indicates how sensitiveor stable a model is overall (Store and Kan-gas 2001).

To fulfill its role as a policy tool, ourWUI map needs to be relatively stable asindividual parameters are changed. Stabilitywould indicate that the specific levels wechose for housing density, vegetation char-acteristics, and so on, do not outweigh theimportance of the components in combina-tion. Conceptually, the WUI is a conjunc-tion of housing and vegetation characteris-tics; all are important, so no single parametershould dramatically change the WUI map.However, housing growth is the most vola-tile factor influencing WUI growth. Hence,sensitivity to the housing density parameteris essential to the model’s ability to reflectthe real world where the WUI is sensitive tohousing growth (Rykiel 1996). This charac-teristic of the model will ensure its suitabilityfor sensing WUI change over time.

Although explicit consideration of riskfrom fire is beyond the scope of this project,the policy intent of the WUI definition andmap is to identify those homes most likely tobe affected by wildland fire. For the states ofArizona, California, Colorado, Idaho, Mon-tana, New Mexico, Nevada, Oregon, Utah,Washington, and Wyoming, where fire pe-rimeter data are relatively good, we assess theextent to which houses close to recent fireswere in areas classified as intermix or inter-face WUI and compare them with housesstatewide.

MethodsThe policy definition on which we base

our map was published in the Federal Regis-ter and notes that “Generally, Federal agen-cies will focus on [interface and intermix]communities . . . Interface communities ex-ist where structures directly abut wildlandfuels. . . . Intermix communities exist wherestructures are scattered throughout a wild-land area” (USDA and USDI 2001, p. 753).

In the extensive text that follows, justone of the three major components of theWUI, human presence, is defined in detailsufficient for analysis. We calibrated param-eters for the other two components (wild-land vegetation characteristics and buffersize) to develop an operational definition.The calibration of each parameter of the def-inition is discussed next, and then sensitivityanalysis procedures are explained.

Human Presence. Housing density isthe most appropriate metric for human pres-

ence in this context because of the impor-tance of structure protection in wildlandfirefighting. Because housing density hasgrown faster than population density in re-cent decades, it is the better measure for eval-uating WUI change and projecting futureWUI location and extent (Liu et al. 2003).Furthermore, nonresidential structures arelikely located close to houses; e.g., barns andgarages, bars, and restaurants tend to be clus-tered near homes and are absent from areaswithout homes. We used 2000 Censushousing data to calculate housing density bycensus blocks. The size of census blocks var-ies widely with population density but theyare the smallest geographic unit for whichUS Census data are reported (mean � 25 ac;SD � 2,674 ac), and are always subdivisionsof counties. Housing density calculations in-clude all housing units as defined by theCensus Bureau, such as apartments andhouses, vacant and occupied, including sea-sonal homes (US Census Bureau 2002). Theminimum housing density for WUI speci-fied in the Federal Register (USDA andUSDI 2001) definition is 1 housing unit per40 ac.

Wildland Vegetation Characteris-tics. Using land cover data to identify wild-land vegetation requires specific directionfor including or excluding each type of veg-etative cover and for determining how muchvegetation must be present for an area to beconsidered “vegetated.” We assessed vegeta-tive cover using the 1992/1993 NationalLand Cover Data (NLCD) from the US

Geological Service, a classification of Land-sat Thematic Mapper imagery, at 30-m res-olution, to determine vegetative cover typeand extent (Vogelmann et al. 2001). We de-fined “wildland vegetation” as all types ofvegetative cover except those that are clearlynot wild, such as urban grass, orchards, andagricultural vegetation. After reviewing theWUI mapping efforts of the California FireAlliance (2001) and analyzing vegetationdensity in several test areas, we chose a veg-etation density threshold of 50% for inter-mix. Thus, a census block was retained aspotential intermix if at least 50% of its areaconsists of forest, shrubland, native grass-land, transitional, or wetland vegetativecover. Census blocks where less than 50% ofpixels were classified as wildland vegetationwere not included as potential intermixWUI, although portions of these blockscould be classified as interface WUI whenthey were close enough to wildland vegeta-tion to fall within the interface buffer (seethe following section).

Interface Vegetation and Buffer Dis-tance. The interface is the area where hous-ing is in close proximity to wildland vegeta-tion. Locating the interface required firstidentifying areas with wildland vegetationand then including areas within “close prox-imity,” represented by a buffer some dis-tance from the vegetation. Interface censusblocks must meet the same housing densityminimum (at least one structure per 40 ac)to be included in the WUI, but do not haveto have more than 50% wildland vegetation.

Figure 1. The WUI definition.


We chose a 1.5-mi buffer distance based onthe precedent of the California Fire Alliance(2001). This distance represents an estimateof how far, on average, a firebrand can flyahead of a fire front, a rationale clearly re-lated to the fire policy application for whichthe WUI map was developed. Althoughwinds and topography affect the distance afirebrand will actually travel, the informa-tion needed to capture these myriad fine-scale variations in fire brand lofting is notavailable. A comprehensive search of pub-lished WUI mapping work uncovered no al-ternative rationale for the buffer distanceand no evidence against the validity of the1.5-mi distance we chose. The vegetatedblock from which the buffer extends was re-quired to meet a higher vegetation densitycriterion of 75% wildland vegetation. Cen-sus blocks that were only partially within the1.5-mi buffer distance were split and onlythe portions within 1.5 mi of the vegetatedblock were defined as interface. The inter-face buffer was extended only from vege-tated areas of at least 1,235 ac (5 km2) to

prevent areas surrounding small urban parksfrom being classified as interface WUI.

WUI Definition. In summary, theWUI definition as we operationalized it isthe area where houses exist at more than 1housing unit per 40 ac and (1) wildland veg-etation covers more than 50% of the landarea (intermix WUI) or (2) wildland vegeta-tion covers less than 50% of the land area,but a large area (over 1,235 ac) covered withmore than 75% wildland vegetation iswithin 1.5 mi (interface WUI). This defini-tion is diagrammed in Figure 1, and the pa-rameters tested in the sensitivity analysis areshown in bold.

GIS Sensitivity Analysis. To test thestability of our operationalization of theWUI definition, we specified that a stabledefinition is one where the percent change inoutput (housing units and area classified asWUI) is always smaller than the percentchange made to any single parameter. One-at-a-time variations in the definition’s pa-rameters were made to determine the influ-ence of each parameter individually

(housing density, vegetation type and den-sity, and buffer distance) on WUI housingunits and area, with particular attentiongiven to the influence of the housing densityparameter. In addition to the individual pa-rameter changes, minimum and maximumWUI scenarios were tested in which all pa-rameters were changed simultaneously to as-sess the extent of overlap across individualparameter responses.

The size of the national WUI data set(8.9 million census blocks) precluded usingthe whole data set for sensitivity analyses.Instead, the following states were chosenrepresenting different geographic regions ofthe country, with different ecotypes andhousing patterns: California, Colorado,Florida, Michigan, North Carolina, NewHampshire, and Washington. For each pa-rameter modification, data were reprocessedfor all census blocks in each sample state (atotal of 1.7 million census blocks, 20% ofthe national data set), and results were re-ported for WUI area and number of houses.Because one aim of the WUI mapping

Figure 2. Distribution of WUI area and housing units by US county in 2000.


project was to support fire policy, we made aseries of eight individual parameter changesthat represent plausible policy alternatives.Plausible alternatives are those that do notviolate the underlying WUI concept in wild-land fire management. For example, if we setthe housing density threshold too low (e.g.,1 house per 150 ac), the resulting mapwould no longer match what most landmanagers envision as “WUI” because vastareas would have no structures. The samelogic guided all our test parameter choices;the alternative parameters varied from start-ing values as far as was plausible, withoutlosing sight of the WUI concept and themap’s policy purpose.

Two test values were chosen for eachparameter, typically a maximum and mini-mum. The housing density threshold andinterface buffer distance were both doubledand halved; intermix vegetation density wasincreased and decreased by 50%. Vegetativecover types were eliminated to create twomore limited conceptions of “wildland,” onewith only uplands (eliminating all wetlandvegetation classes) and the other, just forests,excluding wetlands, grasslands, and shrub-lands. Responses were expressed as percentchange in WUI homes and area.

The WUI and Recent Western Fires.Fire perimeters for 2006 available in theGeoMac database (USDI and USDA 2007)representing 169 fires that covered 1.27 mil-lion ac were used to assess the amount ofWUI near recent western fires. The numberand classification of housing units within1-mi-wide buffers at distances of 1–10 mifrom the fire perimeters were analyzed.Within 10 mi from the fire, potential effectswill vary; closer homes would be more likelyto experience evacuation orders, and homesthat are more distant may be affected only bysmoke; but homes within this distance sel-dom would be considered too distant forconcern.

ResultsWUI in the Lower 48 States. Using

the initial values for housing density, vege-tation type, vegetation density, and interfacebuffer size, the NLCD and Census housingdata were processed in a GIS and maps wereprepared (Figure 2). WUI occurred in all thelower 48 states, with concentrations alongthe Eastern Seaboard, in amenity-rich re-gions of the northern Great Lakes and theMissouri Ozarks, and around the metropol-itan areas of the Rocky Mountains and the

Southwest. In western states, relatively smallamounts of the land area, but a high percent-age (well over 50% in many states) of thehousing units fell into the WUI. IntermixWUI covered more land area (81% of allWUI area) than interface WUI; but becausehousing density is typically higher in inter-face areas, intermix WUI contained just overone-half (53%) of all WUI homes nation-ally.

Varying Individual Parameters.Housing density threshold changes (100%increase and 50% decrease) affected WUIarea more than any other single parameterchange across all test states (Table 1). Inboth California and Florida, lowering thehousing density threshold increased theWUI extent by over 11 million ac, and rais-ing it reduced the size of the WUI by 8.5 and9.5 million ac, respectively. Effects on WUIhouses are small, averaging a 3.2% increasewith a lower threshold and a 5.2% decreasewith a higher threshold.

Intermix vegetation density changes(50% increase and 50% decrease) had littleimpact in most states, averaging a 12.8% in-crease with a lower vegetation requirementand a 7.1% decrease in area when a higherdensity of vegetation is required. A lower

Table 1. Percent change in WUI area and WUI housing units in response to parameter changes, by state.

California Colorado Florida Michigan North Carolina New Hampshire Washington Average

Original WUIArea (1,000,000 ac) 7.23 1.98 6.97 5.84 13.66 2.38 3.75 —Housing (100,000 HUs) 50.9 8.4 25.9 9.7 23.2 4.5 12.0 —

Percent change in response to parameter changes (percent change in area, percent change in housing units)Housing density (original, �1 HU/40 ac)

�1 HU/ 80 ac 40.6 71.7 39.8 62.3 34.0 40.0 36.9 46.51.0 3.0 1.9 6.7 3.7 3.9 2.0 3.2

�1 HU/ 20 ac �29.2 �39.6 �33.7 �45.6 �39.4 �39.0 �29.8 �36.5�1.5 �3.3 �3.2 �9.7 �8.3 �7.4 �3.3 �5.2

Intermix vegetation density (origina,l �50% of pixel)�25% of pixel 4.9 5.4 11.1 47.4 13.7 0.6 6.4 12.8

14.0 5.8 17.8 57.1 20.3 2.6 22.5 20.0�5% of pixel �2.3 �2.3 �8.2 �18.5 �14.1 �0.8 �3.8 �7.1

�3.7 �1.9 �6.2 �20.3 �11.5 �1.4 �8.2 �7.6Interface buffer size (original, 1.5 mi)

3.0 mi 12.6 10.0 13.7 12.1 7.4 1.2 9.4 9.546.7 33.3 49.0 19.9 21.7 15.7 29.3 30.8

0.75 mi �9.9 �8.5 �9.6 �6.8 �5.3 �1.8 �7.5 �7.1�3.7 �24.1 �27.9 �13.5 �14.7 �13.5 �20.2 �20.7

Vegetation (original all wildland vegetation)Upland only �0.6 0.2 �12.7 �30.8 �17.9 �1.8 �0.6 �13.9

�0.8 0.2 �71.5 �3.6 �18.8 �9.9 �1.9 �20.0Forest only �65.9 �57.6 �20.7 �37.9 �18.8 �1.9 �19.5 �39.3

�87.8 �76.2 �86.8 �4.3 �20.3 �11.0 �31.0 �51.0WUI scenariosa (simultaneous changes)

Maximum 58.9 91.2 64.3 134.2 50.4 41.3 52.8 70Extent 55.5 39.3 61.4 79.0 20.9 19.8 45.4 46

Minimum �84.3 �80.7 �94.4 �83.1 �50.9 �48.0 �52.9 �71Extent �92.5 �83.4 �95.5 �75.7 �22.9 �37.9 �55.3 �66

aMaximum extent: housing density � 1 HU/80 ac, intermix vegetation density �25%, interface buffer 3 mi, vegetation all wildland; minimum extent: housing density � 1 HU/20 ac, intermixvegetation density � 75%, interface buffer 0.75 mi, vegetation forest only.Note: Figures in italics give percent change in housing units.


vegetation density threshold does, however,increase the number of WUI homes on av-erage by 20%, with a wide variation in set-tings evidenced in the range of responses,from a 57.1% increase in Michigan to a2.6% increase in New Hampshire. Takentogether, the two modifications in intermixvegetation density tested affected the classi-fication of 750,000 Michigan homes.

Interface buffer distance changes(100% increase and 50% decrease) hadsmall effects in terms of area and mixed ef-fects on housing. The impact of using alarger buffer was particularly high in Califor-nia (46.7%) and Florida (49%) because ex-tensive areas of high density housing oc-curred within 3 mi of wildlands. However,in percentage terms across the test states, thechanges in interface buffer distance gener-ated only a 26% change in the number ofWUI homes and an 8% change in WUIarea.

Vegetation type definition changesyielded mixed results because the distribu-tion of nonforest vegetation varies acrossstates, and the changes to the vegetation typedefinition that we tested focused on nonfor-est vegetation. In areas where the wildlandvegetation is mostly shrublands or grassland,such as California, the “forest only” defini-tion eliminated large areas from the WUI.For those where wetlands are extensive suchas Florida, the “uplands only” definition hadsimilar effects. New Hampshire was least af-fected by the changes because its land coveris largely forest.

Overall Map Stability. When changeswere made in individual parameters, themagnitude of responses to each change asmeasured by percent change in the numberof homes or WUI area was less than the mag-nitude of the parameter change (Table 1),satisfying our criterion for stability. Thehighest average response was a 51% drop inWUI housing units associated with use ofthe “forest only” vegetation parameter(dropping wetlands, grasslands, and shrub-lands from the vegetative classes defined aswildlands) and a 46.5% increase in WUIarea in response to a 100% increase in thehousing density threshold. The states wesampled differed in their sensitivity tochanges. Michigan, Florida, and Coloradowere more sensitive to changes in the WUIdefinition. In these three states, there aremany housing units, a diverse array of vege-tative characteristics, and large land areas.Even with the greater sensitivity in thesestates to some individual changes, responses

never exceeded the magnitude of the param-eter change. The WUI scenarios with theirsuite of simultaneous changes confirm thatmany responses overlap, so that changing allthe parameters simultaneously generates asmaller response than the sum of responsesto individual parameter changes.

The WUI and Recent Western Fires.GIS analysis of the WUI classification ofhomes with a 1- to 10-mi distance from2006 western fires revealed that nearly allhousing units within 10 mi of the fires wereclassified as WUI (73%), but the proportiondeclined with increasing distance from thefire (Figure 3). Within 1 mi of the fire pe-rimeter, 92% of homes were classified asWUI. Homes 9–10 mi from the perimeterstill include a majority of WUI homes(65%), which far exceeded the overall pro-portion of WUI homes in these westernstates. The limited number of fire perimetersavailable made this analysis less comprehen-sive than our wall-to-wall WUI map, butresults suggested that the WUI definitionmapped here tends to capture homes close tothe areas where wildland fire occurs, sup-porting the validity of the national map.

Implications and ConclusionsResults of the sensitivity analysis sug-

gested that the operational definition devel-oped for this mapping effort is stable.Changes made across a plausible range ofalternatives for the WUI definition’s param-eters showed that at the national scale forwhich the map was developed, modifyingthe settings to use other conceptually similarvalues did not change the overall pattern orprevalence of WUI areas.

The involvement of governments at lo-cal, state, and federal levels testifies to thesignificance of wildland fire in US society at

the present time. Tensions over where bestto concentrate decisionmaking authorityand funding responsibility are natural out-comes of shared responsibility. In this con-text, defining and classifying the WUI takeson greater significance. Our purpose herewas to provide those who use the WUI datawith more information about how a differ-ent WUI definition would have affected thenational WUI map and statistics.

Although a single national definitionsuch as the one we mapped may be unwork-able for day-to-day management of individ-ual national forests in the United States, itserves a valuable purpose for strategic plan-ning by providing consistency and credibil-ity to estimates of the scope of the WUI na-tionwide. Trends suggest the WUI willcontinue to grow, which makes a nationalperspective on the scope of the WUI fireproblems even more critical. Furthermore,the USDA’s Office of the Inspector Generalissued a report in November of 2006(USDA 2006) suggesting WUI growth ispushing firefighting costs higher, adding ur-gency to our need to understand the WUI.

Beyond its strategic purposes, the na-tional WUI map also provides informationfor every state and community regardless ofthe other resources available to local plan-ners. Certainly, communities can go beyondthe WUI data in detail (e.g., locating indi-vidual structures) and specificity to wildlandfire issues (e.g., distinguishing high- fromlow-hazard WUI areas based on locallyavailable fuels data), but for communitieswithout the resources and technical staff tocreate a customized local WUI map, thisclassification is a suitable guide to the loca-tion and extent of WUI.

Among the parameters we tested, thechange that generated the largest response

Figure 3. WUI classification of homes near 2006 western wildland fires.


was housing density, and housing densitywas the only parameter defined directly inthe Federal Register. The rest of the WUIdefinition was less specific. Testing thesedefinition changes showed how the defini-tion interacts with local conditions. Wetested just those changes that seemed mostplausible in light of the focus on forest policyand the availability of data, but even so,most changes we tested would make theWUI definition less representative of the un-derlying WUI concept.

The sensitivity of the WUI definition tohousing density was reassuring because it in-dicated that as housing growth occurs, theWUI will grow accordingly. Analysis ofchange over time interests those concernedwith resource impacts, particularly becausethere is reason to expect that the full effect ofhousing development on wildland resourceswill take time to become apparent. The abil-ity of the WUI definition to represent effectsof change over a long time period enhancesits usefulness for resource management.

When the WUI data are combined withdata regarding fire risk, the exclusion of low-risk WUI areas will alter the distribution ofWUI across the country. But the temporaland spatial variability in fire hazard and themany diverse factors (e.g., weather, fuels,and topography) that determine it will al-ways limit our ability to make fire risk pre-dictions on the same scale and with the sameconfidence as we can map the WUI. Wild-land vegetation and housing units changeonly slowly over time relative to the com-plex, dynamic factors determining fire risk.

Last but not least, although the currentperception of the WUI centers on wildlandfire, the concept is applicable much morebroadly. The WUI is an area where the in-fluence of human development is mani-fested in many different ways, among them,through impacts on birds, mammals, plantsand other ecosystem structures, functions,and services. The WUI also is an area wherepeople come into contact with wildland andits management, and the full range of publicresponses to management play out. Thus,tracking the growth and change of the WUIis essential to dealing with the consequencesof housing growth and, ultimately, to sus-taining the wildlands in the face of mount-ing development pressures.

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Deﬁning the Wildland–Urban Interface

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