Prepared in cooperation with the Clackamas County Emergency Management Department

Residential and Service-population Exposure to Multiple Natural 

Hazards in the Mount Hood Region of Clackamas County, Oregon

Open-File Report 2013–1073

U.S. Department of the Interior

U.S. Geological Survey
COVER

Trillium Lake with Mount Hood in the background. Photo by Amy M. Mathie, U.S. Geological Survey. 
Residential and Service-population Exposure to Multiple 

Natural Hazards in the Mount Hood Region of Clackamas 

County, Oregon

By Amy M. Mathie and Nathan Wood

Prepared in cooperation with the Clackamas County Emergency Management Department

Open-File Report 2013–1073

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013 

 

For more information on the USGS—the Federal source for science about the Earth,

its natural and living resources, natural hazards, and the environment—visit 

http://www.usgs.gov or call 1–888–ASK–USGS

For an overview of USGS information products, including maps, imagery, and publications,

visit http://www.usgs.gov/pubprod

Suggested citation:

Mathie, A.M., and Wood, N., 2013, Residential and service-population exposure to multiple natural hazards in the 

Mount Hood region of Clackamas County, Oregon: U.S. Geological Survey Open-File Report 2013–1073, available at

http://pubs. usgs.gov/of/2013/1073/ . 

Any use of trade, product, or firm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.
Contents

Abstract ......................................................................................................................................................................... 1

Introduction.................................................................................................................................................................... 2

Purpose and Scope ................................................................................................................................................... 3

Study Area..................................................................................................................................................................... 4

Population Distributions................................................................................................................................................. 5

Population Locations.................................................................................................................................................. 5

Residents................................................................................................................................................................... 7

Employees ................................................................................................................................................................. 8

Service Populations ................................................................................................................................................... 9

Road Volume ............................................................................................................................................................10

Population Exposure to Natural Hazards......................................................................................................................11

Flood Hazards...........................................................................................................................................................12

Hazard Delineation................................................................................................................................................12

Population Exposure .............................................................................................................................................13

Wildfire Hazards........................................................................................................................................................13

Hazard Delineation................................................................................................................................................13

Population Exposure .............................................................................................................................................14

Volcanic Hazards ......................................................................................................................................................15

Hazard Delineation................................................................................................................................................15

Population Exposure .............................................................................................................................................16

Conclusions..................................................................................................................................................................18

Acknowledgments ........................................................................................................................................................19

References Cited..........................................................................................................................................................20

Appendix A ...................................................................................................................................................................46

Appendix B ...................................................................................................................................................................47

Appendix C...................................................................................................................................................................48

Figures

Figure 1. Location maps of study area within Clackamas County, Oregon. ........................................................... 24

Figure 2. Map (A) and pie graph by area (B) of the land cover classification of the study area (National Land Cover 

Database, 2001), Clackamas County, Oregon ............................................................................................................ 25

Figure 3. Images of the Villages at Mount Hood and Government Camp study area in Clackamas County, Oregon 

(U.S. Geological Survey photographs taken by A. Mathie).......................................................................................... 26

Figure 4. Map of categorized structure point data derived from Master Street Address (MSA) structure file, 

Clackamas County, Oregon......................................................................................................................................... 27

Figure 5. Distribution of residential structures by land cover class (based upon 2001 NLCD land cover), Clackamas 

County, Oregon. .......................................................................................................................................................... 28

Figure 6. General illustration of address-point-based hybrid dasymetric technique used to determine residential 

population distribution.................................................................................................................................................. 29

Figure 7. Maps of residential population at a 30-meter pixel resolution. A, Welches and surrounding unincorporated 

area, and B, Government Camp, Clackamas County, Oregon. ................................................................................... 30

Figure 8. Three hundred-meter pixel resolution density maps of: A, residents by area, and B, employees by area, 

Clackamas County, Oregon......................................................................................................................................... 30
iv

Figure 9. Three hundred-meter pixel resolution density maps of summer season attendance elements:............... 32

Figure 10. Daily vehicle counts from Oregon Department of Transportation permanent recorder station located 

along U.S. Highway 26 east of Zigzag and west of Government Camp, Clackamas County, Oregon......................... 33

Figure 11. Map of 100-year and 500-year Federal Emergency Management Agency Flood Hazard Zones for the 

study area, Clackamas County, Oregon...................................................................................................................... 34

Figure 12. Flood hazard exposure among A, study area homes and B, businesses, Clackamas County, Oregon...

............................................................................................................................................................. 35

Figure 13. Flooding hazard exposure to employees by business sector, Clackamas County, Oregon................. 36

Figure 14. Map of overall wildfire risk to the study region as perceived by Clackamas County (Clackamas County, 

Oregon, 2005) ............................................................................................................................................................. 37

Figure 15. Wildfire-hazard risk within the study area, Clackamas County, Oregon............................................... 38

Figure 16. Wildfire-hazard risk to employees by business sector, Clackamas County, Oregon ........................... 39

Figure 17. Wildfire-hazard risk among seasonal population groups, Clackamas County, Oregon. ...................... 40

Figure 18. Map of volcano hazard zones for the study region (derived from Scott and others, 1997b), Clackamas 

County, Oregon. ......................................................................................................................................................... 41

Figure 19. Effect of Mount Hood’s topographic profile on potential distance traveled by a pyroclastic flow and ashcloud surge (modified from Brantley and Scott, 1993), Clackamas County, Oregon. ................................................. 42

Figure 20. Volcano hazard exposure among A, homes, B, businesses, and C, employees, in the study area, 

Clackamas County, Oregon. ....................................................................................................................................... 43

Figure 21. Volcano hazard exposure to employees by business sector, Clackasmas County, Oregon................ 44

Figure 22. Volcano-hazard exposure among seasonal population groups, Clackamas County, Oregon. . ........... 45

Tables

Table 1. Volcano hazard exposure by service population facilities ...................................................................... 17
Residential and Service-population Exposure to Multiple Natural 

Hazards in the Mount Hood Region of Clackamas County, 

Oregon

By Amy M. Mathie and Nathan Wood

Abstract 

The objective of this research is to document residential and service-population exposure to 

natural hazards in the rural communities of Clackamas County, Oregon, near Mount Hood. The Mount 

Hood region of Clackamas County has a long history of natural events that have impacted its small, 

tourism-based communities. To support preparedness and emergency-management planning in the 

region, a geospatial analysis of population exposure was used to determine the number and type of 

residents and service populations in flood-, wildfire-, and volcano-related hazard zones. Service 

populations are a mix of residents and tourists temporarily benefitting from local services, such as retail, 

education, or recreation. In this study, service population includes day-use visitors at recreational sites, 

overnight visitors at hotels and resorts, children at schools, and community-center visitors. Although the 

heavily-forested, rural landscape suggests few people are in the area, there are seasonal peaks of 

thousands of visitors to the region. “Intelligent” dasymetric mapping efforts using 30-meter resolution 

land-cover imagery and U.S. Census Bureau data proved ineffective at adequately capturing either the 

spatial distribution or magnitude of population at risk. Consequently, an address-point-based hybrid 

dasymetric methodology of assigning population to the physical location of buildings mapped with a 

global positioning system was employed. The resulting maps of the population (1) provide more precise 

spatial distributions for hazard-vulnerability assessments, (2) depict appropriate clustering due to higher 

density structures, such as apartment complexes and multi-unit commercial buildings, and (3) provide 

new information on the spatial distribution and temporal variation of people utilizing services within the 

study area.

Estimates of population exposure to flooding, wildfire, and volcanic hazards were determined by

using overlay analysis in a geographic information system. Population exposure to flood hazards is low 

(less than 10 percent of residents) and does not vary substantially between 100-year and 500-year floodhazard scenarios. Moderate, moderate-to-high, and high wildfire-risk areas within the study region 

account for 72 percent of residents, 62 percent of employees, and 60 percent of daytime visitors to 

recreation sites. Fifteen percent of businesses in the study area are in moderate-to-high or high wildfirerisk areas but these businesses represent 51 percent of the local workforce. A volcanic event at Mount 

Hood could directly impact up to 60 percent of residents in their homes and 87 percent of employees at 

their workplaces. The proximal volcanic-hazard zone alone includes 65 percent of employees, 80 

percent of schools and community facilities, more than 60 percent of overnight visitors in peak seasons, 

and 82–100 percent of daytime visitors to recreation sites during the summer and winter months, 

respectively. The number of day-use visitors to recreation sites in the region is greatest during winter 

months (averaging 129,300 people per month), whereas overnight visitors are greatest during summer 
2 

months (averaging 34,000 per month). This analysis of residential and service-population exposure to 

natural hazards supports the development of targeted risk-reduction efforts in the region, while also 

expanding the discourse on characterizing and assessing population dynamics in tourist-frequented 

areas. 

Introduction 

Societal risk to natural hazards is a function of human development in areas prone to such

physical events. To effectively manage these risks, public officials need to gauge the potential for future 

events (the hazards) and the exposure, sensitivity, and adaptive capacity (collectively referred to as 

vulnerability) of systems relative to the perceived hazards (Wood, 2011). Systems of interest typically 

include populations, economic assets and regional economies, critical facilities and infrastructure, and 

ecosystems. Understanding the vulnerability of these systems to natural hazards enables emergency 

managers, public officials, business owners, and the general public to make informed decisions about 

how they may want to mitigate, prepare for, respond to, and recover from the potential consequences of 

future events. This report describes the exposure of residential and service populations to flood, 

wildfire, and volcano hazards within the Villages at Mount Hood and Government Camp region of 

Clackamas County, Oreg., and results from collaboration between the Clackamas County Department of 

Emergency Management and the U.S. Geological Survey. 

Population vulnerability to natural hazards often is characterized using data compiled in national 

population counts. In the United States, the U.S. Census Bureau provides decadal counts and annual 

estimates of the number and demographic characteristics of the residential population (U.S. Census 

Bureau, 2012). Residential population of an area is based upon an individual’s residence and not by the 

geographic area an individual typically occupies (for example, workplace, recreation sites, and markets). 

Because of privacy concerns, census counts do not reflect individual residences and instead are provided 

in aggregated areal units (for example census blocks, block groups, and tracts) that generalize 

population distribution across the landscape. Although useful for hazards that cover large geographic 

areas (for example, earthquakes and hurricanes), the aggregated areal units have limited utility for other 

hazards that have relatively small footprints, such as floods or volcanic lahars. This is particularly an 

issue in rural areas where census blocks (the smallest census unit) can be large and may be larger than 

hazard zones. 

Another limitation of relying only on census counts for population-exposure assessments is that

various types of visitors (collectively called a service population) can outnumber residents in many 

areas but are not accounted for in census counts. Service populations are defined as the people, either 

residents or tourists, who temporarily enter an area to receive some sort of service or benefit, such as 

transportation access (commuters), recreation (day-use and overnight tourists), goods (shoppers at a 

market), or education (school children) (Cook, 1996; Australian Bureau of Statistics, 2008). Service 

populations are neither discrete nor mutually exclusive and individuals can belong to multiple segments 

(Australian Bureau of Statistics, 2008). For example, a family may live, work, shop, recreate, and send 

children to local daycare at various points within the study area. If individuals are permanent residents, 

U.S. Census Bureau counts will include them at their point of residence (aggregated into a generalized 

census unit), but will not indicate the other areas commonly frequented. If the family only lives in the 

area during a peak tourist season, their presence and use of services in the region is unlikely to be 

recorded at all. The value of recognizing a service-population component is illustrated in a study of 

population exposure to tsunami hazards on the Oregon coast, where Wood and Good (2004) estimated 

that non-residents (for example, commuting employees and tourists) comprised more than two-thirds of 
3 

the at-risk population in two coastal communities. Emergency managers and public officials need better 

methods for assessing residential and service-population exposure to hazards if they are to develop 

realistic mitigation, preparedness, response, and recovery strategies.

One area with a wide array of natural hazards, rural development, and substantial service

populations is the upper Sandy River valley and Mount Hood region of Clackamas County, Oregon (fig.

1). The rural residential development and recreational opportunities of this region largely center around 

a primary transportation corridor (U.S. Highway 26) that runs through multiple hazard zones associated 

with volcanic, flood, landslide, and wildfire hazards. Some of the hazards, such as those related to 

volcanic activity, can be highly unpredictable in terms of their speed of onset and event duration, which 

creates significant emergency management and land-use challenges for public officials who are 

attempting to balance public safety, quality of life and livelihoods, and economic development. 

Although there have been several studies to assess the natural hazards in this area, less has been done to 

understand the vulnerability of communities to these hazards (for instance, Burns and others, 2011), and 

no attention has been paid to service populations. 

To better understand population dynamics and hazard exposure in this area, the Clackamas 

County Emergency Management Department sought assistance from the U.S. Geological Survey 

(USGS) to (1) determine the number, type, and temporal trends in residential and service populations 

and (2) determine the exposure of these populations to a variety of natural hazards in the area. This 

information helps public safety officials and community planners to understand where and when people 

are concentrated in hazardous areas for the sake of emergency notification, evacuation planning, 

limiting or restricting access, and estimating losses to economic productivity. This information enables 

emergency managers to develop targeted outreach and preparedness plans that address local needs and 

issues. It also provides a foundation for efficient and effective plans for emergency response and 

recovery. 

Purpose and Scope 

The objective of this report is to document residential and service-population exposure to natural 

hazards in the rural communities of Clackamas County, Oregon, near Mount Hood. The various 

population data sources and population-modeling techniques used to estimate population distributions 

across space and time are discussed in this report. Seasonal variations are estimated for tourism-related 

businesses and locations. Hazard exposure is based on the number of people and locations (for example, 

trailheads and businesses) in published flood, wildfire, and volcano hazard zones. These hazards were 

chosen as a result of county interest and data availability for the study area. Additional natural hazards 

common in the study area include landslides and severe winter storms (Clackamas County, Oregon, 

2007); however, population-exposure estimates were not possible for these hazards because spatiallyexplicit data on hazard susceptibility were insufficient or nonexistent. 

Population-exposure estimates should not be construed as loss estimates for a future extreme 

event because of the unpredictable nature of future events and because of the dynamic nature of 

population magnitudes and distributions. For example, a volcanic eruption is expected to be preceded by 

a period of unrest that will be monitored, which should provide opportunities to protect people and 

property. Similar pre-event opportunities for monitoring and evacuation are likely before extreme flood 

or wildfire conditions emerge. Population estimates are not intended to represent the number of people 

at a specific location as an event occurs because warnings, evacuations, or other emergencymanagement efforts likely will have occurred. These estimates do, however, indicate the magnitude and 

variability of people requiring consideration for success of such emergency plans. This work is intended 
4 

to support local, county, and State emergency managers directly in their efforts to develop realistic and 

effective outreach efforts, plans, and policies. For those outside of the study area, this research will help 

other emergency and land-use managers to become better aware of the dynamic nature of populations 

and of how service-population exposure to various natural hazards is a relevant factor for emergencymanagement planning. 

Study Area

Clackamas County is located in northwest Oregon and is one of three counties that comprise the 

Portland, Oreg., metropolitan area (fig. 1A). With more than 400,000 residents, it is the third most 

populous county in the State (Oregon Blue Book, 2012) and has consistently shown population growth 

in recent decades which is projected to continue (Clackamas County, Oregon, 2002). The landscape is 

dominated by the Mount Hood volcano (within the Mount Hood National Forest) on the northeastern 

border of the county (fig. 1B and C). The county is largely forested and has numerous rivers and 

watersheds (for example, Bull Run, Sandy, Salmon, and Clackamas). Agriculture and urban 

development is concentrated in the western part of the county. The county’s economy has long relied on 

agriculture, timber harvesting, manufacturing, and tourism (Clackamas County, Oregon, 2012), all of 

which are supported by access to nearby U.S. Interstate Highways (5, 205, and 84) and U.S. Highway 

26, which runs west-east across the county. 

This study focuses on the unincorporated communities along U.S. Highway 26 east of the City 

of Sandy to its connection with Oregon State Highway 35 at the southern base of Mount Hood (fig. 1C). 

This includes the community of Government Camp and the Villages at Mount Hood (VMH), which 

represents the communities of Brightwood, Wemme, Welches, Zigzag, and Rhododendron. The study 

area is delineated by the collective extents of seven 2010 U.S. Census Bureau block groups that include 

these unincorporated communities (U.S. Census Bureau, 2012)1

. 

The VMH are part of a nationally recognized, citizen-driven “Hamlets and Villages” program in 

which unincorporated communities are governed by a locally elected board of directors and are

provided staff liaisons and a small operating budget by the county (Clackamas County, Oregon, 2012). 

Although actions related to natural hazards may be taken locally (for example, home evaluations of 

wildfire susceptibility made by Hoodland Fire District), emergency planning and response coordination 

are performed at the county level for these unincorporated towns (Clackamas County, Oregon, 2012). 

The study area lacks hospitals or emergency rooms but has four schools, including three public schools 

of the Oregon Trail School District (Welches Elementary, Firwood Elementary, and Welches Middle 

School) and one private, sport-related school (Mount Hood Academy). There is also a community center

located in Welches that houses a senior center and two separate childcare facilities. 

Based on 2001 land-cover data, the majority of the study area is classified as forest (78 percent 

by area) followed distantly by grassland or shrub (15 percent), agricultural land (3 percent) and 

developed land (less than one percent) (fig. 2). Land cover percentages were derived from the 2001 

National Land Cover Database (NLCD) (Homer and others, 2007), which is generated by automated 

techniques from 30-meter spatial resolution Landsat Enhanced Thematic Mapper Plus digital satellite 

imagery and verified with field visits (Homer and others, 2007; Loveland and Shaw, 1996). NLCD data 

 

1

This differs from the study area used by Burns and others (2011) which included the full extent of the Sandy River in 

Clackamas and Multnomah Counties, as well as the Hood River Valley in Hood River County to the north-east of Mount 

Hood. Results by Burns and others (2011) aggregate populations across the entire study area, therefore, caution should be 

taken in comparing results between the two studies.
5 

include four types of developed classes (open space, low intensity, medium intensity, and high intensity) 

to reflect the level of impervious surfaces in a grid cell (for example, parking lots and roofs). The openspace developed classification is reported separately from the others because it primarily identifies areas 

of managed vegetation (for example parks, private yards) and not structures. For those not familiar with 

data derived from satellite imagery, it is important to note that the developed classes denote the amount 

of impervious surfaces within a grid cell (gauged by reflectance values in satellite data) and not the 

density of development (for example, “high-intensity” developed is not the same as high-density 

developed). 

The study area includes the upper region of the Sandy River basin—an area that commonly 

experiences flooding. The Sandy River is a tributary to the Columbia River, which is the largest river in 

the Pacific Northwest region and serves as much of the border between Oregon and Washington State 

(Taylor, 1998). The Sandy River originates on the steep slopes of Mount Hood and drops more than

3,000 feet in elevation in 56 miles (approximately 90 kilometers)—the vast majority of the elevation 

loss, however, occurs before the confluence of the Sandy River with the Salmon River in the VMH area 

(Pierson and others, 2011). Consequently, the river channels within this section of the watershed can 

flow fast in floods and swiftly funnel lahars derived from Mount Hood volcanic unrest. 

The study area provides a wide range of year-round recreational activities and settings (fig. 3). 

The winter season is dominated by snow sports (for example, snowboarding and alpine and crosscountry skiing), and the summer season has a wide range of activities, such as climbing, hiking, and 

camping on U.S. Forest Service land, resort-style golfing, fishing, lake and river sports, and ski and 

snowboard camps on Mount Hood’s Palmer snowfield. Fall and spring are less busy but still attract 

visitors, as well as school nature programs. Easy access along Highway 26 and close proximity to the 

Portland metropolitan area (approximately 1–2 hours) make this region a significant tourist draw, 

especially on holidays and weekends. To capitalize on these recreational opportunities, an urban 

renewal project was approved in 1989 by Clackamas County to encourage development of retail 

businesses, restaurants, overnight accommodations, and recreational facilities (Clackamas County, 

Oregon, 2012). To date, this tourism-driven development has occurred largely in the communities of 

Government Camp and Welches. 

Population Distributions

To estimate population exposure to natural hazards in the study area, geographic-informationsystem (GIS) tools were used to integrate publicly available hazard and socioeconomic data, as well as 

population data developed specifically for this research. Unlike other population-modeling work done 

for the Mount Hood region (for example, Burns and others, 2011), this study does not limit population 

to permanent residents but focuses on residential and service populations, including residents in homes, 

employees at their workplace, overnight visitors (lodgers), daytime visitors to recreation sites, and 

dependents (children and seniors) at schools and community facilities. There are sure to be overlaps 

among the population groups (for example, residents that work at a local business and hike on a nearby 

trail); therefore, estimates for each group should not be added to estimate total population in the study 

area. The following sections describe how each population was mapped and how their sizes were 

estimated. 

Population Locations

The first step in assessing population exposure to various natural hazards is to locate people on 

the landscape properly. Populations related to outdoor places (for example, trailheads and campgrounds 
6 

entrances) were located using point data provided by the U.S. Forest Service. These data depict 

entrances to outdoor areas but do not delineate the full linear (in the case of trails) or areal (in the case 

of campgrounds) extent; therefore, care should be taken when interpreting results. Delineating 

campground extents and trail paths would improve the understanding of population distributions at these 

sites, but was considered beyond the scope of the current project. 

Populations related to indoor places (for example, homes and businesses) were located using 

point data of building locations in a 2009 Master Street Address (MSA) file provided by Clackamas 

County. These data were developed using global positioning system (GPS) field equipment as part of a 

county wildfire prevention program. The original data simply identified address locations as GIS vector 

points and did not have additional information on building outlines (also known as footprints), type, use, 

or ownership. Tax-parcel data (2009 version) were used as ancillary information to expand the attributes 

of the MSA file but were not used directly in the GIS-based exposure analyses owing to known 

alignment issues between parcel data and other imagery and population data. This alignment issue 

existed because the county, until quite recently, lacked adequate survey-control data in various parts of 

the study area that is necessary to remap the parcels (Kelly Neumeier, Clackamas County Technology 

Services, Geographic Information Systems Division, written commun., 2012). Until this alignment issue 

was resolved, any exposure analysis based on existing parcel data likely will contain errors.

Population locations from the U.S. Forest Service and MSA data were classified into several 

building types, including residential homes, vacation homes, lodging accommodations, commercial 

businesses and industry, and recreational sites. This classification was based on several different 

sources, including 2009 tax parcels (Clackamas County Tax Assessor, unpub. data, 2009), 2009 

Employer Database (InfoGroup, 2009), visual interpretation of imagery (National Agriculture Imagery 

Program, 2005), field verification, and private vacation-home locations (U.S. Forest Service, oral 

commun., 2011). 

One issue encountered during the classification process was the inconsistent nature in which 

multiple businesses or homes within one structure were handled in the MSA data. For example, one 

strip mall comprised of several businesses would be described by one MSA point in some cases and as 

individual points in other cases. While a “yes - no” notation in the MSA data reflected the presence of a 

multi-unit building, there was not always additional descriptive information (for example, residential 

complex, multi-unit commercial facility, or mixed-use facility). This issue arose with certain retail 

centers, apartment and townhome complexes, condominium buildings, and large hotels and resorts. 

Many of the resorts (Collins Lake Resort, Whispering Woods Resort, and The Resort at the Mountain) 

had each rental unit marked as a distinct point but others (Shadowhawk Condos and Timberline Lodge) 

were summarized as single points. Although mapping large resorts by unit happened to be beneficial for 

this study (namely, when comparing population at spatially expansive facilities against spatially specific 

hazard zones), the additional feature points do tend to suggest more overnight lodging and day-use 

recreation sites than actually exist according to business license. Effort was made to be consistent with 

this issue; however, some inconsistencies remain. 

Figure 4 depicts a final population-location database summarizing the updated MSA residential 

and business data and data for U.S. Forest Service outdoor locations. This report recognizes three 

classes of structures: (1) residence, (2) commercial or industrial business, and (3) recreational, 

accommodation, and educational facilities. The following sections describe subsequent efforts to attach 

population counts to each of these locations. 
7 

Residents

Burns and others (2011) used 2000 Census data, but residential population in this report is based 

on block group data from the 2010 U.S. Census (U.S. Census Bureau, 2012). According to the 2010 

data, there are 5,711 households and 10,600 residents distributed across the study region. Because 

several of the hazard zones are significantly smaller than the U.S. Census block group data, the 

population data needed to be disaggregated. Two approaches to disaggregating the population data are 

described here. 

One common approach to disaggregating population data is an “intelligent” dasymetric mapping 

technique based on NLCD land-cover data (Mennis 2003; Sleeter and Gould, 2007). This approach 

disaggregates population values from census totals by applying an interpolated areal weight to four 

population-density classes (high, medium, low, and uninhabited) related to various land-cover classes.

The assignment of land-cover classes to the four population-density classes is done by the user and 

significantly influences final results. For example, the study area is heavily forested (fig. 2) and areas 

classified as developed in the NLCD are primarily along the U.S. Highway 26 corridor, trailhead 

parking lots, and major roads in the various communities. If high-intensity developed cells in NLCD 

data are assumed to be the same as high-density development in the dasymetric modeling, and if

forested areas are ruled out as population locations, then resident population would be assigned 

incorrectly to Highway 26 and parking lots (for example, Burns and others, 2011). To resolve this issue, 

one could use ancillary road data (either separate road files or road polygons in the parcel data) to 

exclude these areas from consideration in the dasymetric modeling.

A pie-chart summarizing the percentage of structures in the enhanced MSA data organized by 

the various NLCD classes (fig. 5) indicates that most residential structures are in areas presumed in 

previous dasymetric studies to have no population, such as forest, water, wetland, barren land, and 

developed open space (Mennis and Hultgren, 2006; Reibel and Agrawal, 2007). For example, 51 

percent of residential structures are in areas classified as forest and 23 percent are in areas classified as 

open-space developed—land-cover classes often assigned to an uninhabited population density class 

during dasymetric mapping (Sleeter, 2004; Mennis and Hultgren, 2006). The presence of structures in 

certain classes, such as water and wetland, may be due to floating homes (for example, a permanent 

houseboat) but more likely indicate a resolution or locational accuracy issue with the NLCD. 

Because home locations were georeferenced within the enhanced MSA dataset, residential 

locations did not need to be modeled. Dasymetric-mapping techniques using midresolution land cover

(such as NLCD) were unnecessary and, if employed improperly (for example, Burns and others, 2011), 

likely would lead to population-exposure errors. Instead, block group population data were 

disaggregated across the landscape, in a hybrid binary approach, by using the points classified as 

residential addresses in the MSA data. Population was assigned only to address point locations, and an 

areal weight value was determined for each residence based on census records. This was done by 

dividing block group population values by the number of addresses within the block group. For 

example, if a block group had a population of 12 people and there were 4 addresses within the block 

group, then it was assumed that there were 3 people at each address. Although this method 

disaggregates population from large areal units to actual residences, it assumes equal populations at 

each residence, which is not likely because some homes may have children or extended families and 

others may not. Subsequent population-exposure estimates, therefore, should be considered only first 

approximations, and follow-up work to identify population counts at specific addresses may be 

warranted in areas of high hazards. 

There were several areas where buildings contained multiple addresses; therefore, a map 

showing residential population data using the address points would be difficult to decipher because of
8 

stacked and overlapping points (for example, fig. 4). Although subsequent exposure estimates were 

made using the original point data, a 30-meter raster grid of residential population data was created to 

simplify the visualization of population distributions across the study area. The number of residents in 

each 30-meter grid cell is the population sum for all of the address points in that cell (fig. 6). As 

compared to results from the first disaggregation method described, results from the address-point-based 

areal weighting technique reflect higher residential population counts among grid cells coinciding with 

multiple residential address locations. Data-quality checks, based on follow-up high-resolution imagery 

interpretation and fieldwork, showed the population modeling of this second method to be a reasonable 

estimation. 

Two focus maps of residential population at 30-meter pixel resolution are provided for Welches 

(fig. 7A) and Government Camp (fig. 7B). These maps illustrate the methodology’s ability to identify

high-density areas that reflect apartment complexes, townhome developments, and condominium units. 

Figure 7 also demonstrates the methodology’s ability to properly assign population to neighborhoods as 

opposed to the Highway 26 corridor, as can happen if dasymetric mapping techniques are used 

incorrectly (for example, see Burns and others, 2011). 

To allow comparison of population numbers across the entire study area, a raster with 300-meter 

pixel resolution of residential population was generated (fig. 8A). Clustering of residents is observed 

along valley lows in the VMH and at the base of the mountain in Government Camp. Residents in the 

less rugged western portion of the study area (outside the City of Sandy) are much more dispersed. 

Employees

The number, type, and distribution of employees within the study area were identified using the 

2009 InfoGroup Employer Database, which is a proprietary business database that includes employee 

counts, location (address and latitude/longitude coordinates), generated sales volume, and business type 

based on the North American Industrial Classification System (NAICS; appendix A). Linking this data 

to the MSA records first involved joining data based on street addresses. Manual editing was based on 

imagery interpretation, Internet queries, and fieldwork for businesses with incomplete information or 

multiple records. For businesses with multiple records in the database, it was determined if records were 

duplications (and if so, duplicates were removed), or if distinct businesses existed but shared an address 

or existed within a larger company (for example, restaurants, gift shops, accommodations, and rental 

shops within a ski resort). 

Manual examination and editing of the business data for this area yielded 323 georeferenced 

businesses that employ 3,149 people. Of the original data, some businesses could not be used in the 

exposure analysis owing to lack of address (11 percent), or because they had a U.S. Post Office box as a 

mailing address (4 percent). In addition to estimating employee exposure to various hazards, the types 

of employees in these zones are noted based on NAICS sectors, an indicator commonly used by the U.S. 

Bureau of Labor Statistics (2012) to assess economic trends. Similar to the residential data, business 

data attached to point locations were used in subsequent exposure estimates. A 300-meter-resolution 

map of employee population (fig. 8B) indicates that much of the region’s workforce is focused in 

Welches and Government Camp and at certain businesses, such as Timberline Lodge, on the southern 

flank of Mount Hood. 
9 

Service Populations 

As discussed earlier, several types of visitors temporarily come into the study area to enjoy 

various services or recreational opportunities. Analysis of this service population focused on the 

following groups. 

• Overnight visitors are presumed to be primarily tourists and estimates of their numbers are based on 

occupancy at hotels, motels, resorts, bed and breakfast businesses, and vacation-home rentals, 

• Daytime visitors to recreation sites are likely to be a mix of residents and tourists, and estimates of 

their numbers are based on attendance at public parks, private camps, U.S. Forest Service

campgrounds and trailheads, and several tourist attractions, such as Mount Hood Skibowl, 

Timberline Lodge and Ski Area, Summit Ski Area, and the Mount Hood Cultural Center and 

Museum, 

• Dependents are presumed to be residents, and estimates of their numbers are based on attendance at 

several schools (Welches Elementary, Firwood Elementary, Welches Middle School, and the Mount 

Hood Academy) and other facilities (Mount Hood Senior Center, the Mt. Hood Co-op Preschool, 

and Hoodland Children’s Center). 

Estimates of venue attendance were gathered through field work, email contact, and phone 

interviews. Business owners, property managers, school district managers, and center directors (for 

example, community centers) were asked to provide average monthly attendance totals, as well as peak 

daily estimates if available. U.S. Forest Service permit data (U.S. Forest Service, unpub. data, 2012) 

provided insight on attendance at some campgrounds and trailheads. Visitor estimates provided by 

businesses in the study area include daily estimates (Whispering Woods Resort, The Resort at the 

Mountain, and the Mount Hood Cultural Center and Museum), seasonal estimates (Mount Hood 

Skibowl) and annual estimates (Timberline Lodge and Ski Area). Several businesses did not provide 

any visitor estimates because they could not be reached (for example, private vacation rental homes), 

lacked visitor records, or lacked interest in study participation. Estimates, therefore, should be 

considered first approximations and not definitive statements of service populations. 

Service-population magnitudes were estimated seasonally based upon local knowledge of the 

peak tourist periods: winter (December through February), spring (March through May), summer (June 

through August), and fall (September through November). Collected attendance data was arranged by 

season and calculated into the common unit of a monthly average because that was the most common 

unit used by businesses. For example, among each participating venue, the seasonal monthly average for 

summer was calculated by: (1) determining the attendance totals in June, July, and August; (2) adding 

the individual monthly totals together; and (3) dividing the seasonal grand total by three to obtain an 

average. Overnight visitors to the study area range from a low of 11,000 people per fall month to a peak 

of 34,000 people per summer month. Daytime visitors to recreation sites average from approximately 

27,000 people per fall month to 129,300 people per winter month. Resident dependents at educational 

facilities total 549 people per fall, winter, and spring months and 93 people per summer month. These 

values are general trends in seasonal populations and actual attendance numbers for a given month may 

be higher than the calculated seasonal average. For example: 

• Summertime average monthly attendance at The Resort at the Mountain is approximately 4,500, but 

can exceed 6,100 visitors in July; 

• Summertime average monthly attendance at the U.S. Forest Service Trillium Lake Campground is 

approximately 5,400, but can reach 8,400 in August; and

• Wintertime average monthly attendance at the Summit Ski Area is approximately 3,900 yet January 

attendance can exceed 4,300. 
10

Peak monthly attendance values from exposure analyses were omitted because not all venues were 

able to provide consistent visitor data, and for those that could, an individual venue’s peak month could 

differ. Calculated monthly averages reported for seasonal populations are, in general, conservative 

estimates of the overall service population within the study area and are meant to provide insight on 

seasonal trends. 

The monthly average-attendance values presented in this study can be translated into estimates 

of daily population, by consideration of the relevant population group. A daily estimate for overnight 

visitors and daytime visitors at recreation sites, can be calculated by dividing the seasonal monthly 

average value by thirty days (chosen as the length for an average month). Although they are easy to 

calculate, daily estimates for high-volume tourist destinations will have varying levels of accuracy 

because they underestimate populations on peak tourist days (weekends and holidays) and overestimate 

them on other days (weekdays and days with inclement weather). The dependent population monthly 

averages are based largely upon the number of children within the local public schools—values that 

reflect a general constant weekday attendance of school age children. Thus, daily estimates of dependent 

population attendance at local educational facilities are roughly equivalent to the seasonal monthly 

averages and do not require further calculations. 

As was the case with the residential and employee data, service-population information was 

attached to point locations in the enhanced MSA data and exposure analyses were performed. Reporting 

a total number of tourist attractions is complex because of variations in how multistructures were 

mapped for the MSA dataset, such as multiple rental units within a resort being identified separately at 

one resort and collectively at another resort. The study area includes 1,068 recreational-site units which

can be effectively summarized by 574 host facilities, of which 521 are lodging sites and 53 are 

recreation sites. Many of the public venues occur between the VMH area and Government Camp, 

including clusters of private vacation homes along the Zigzag River.

Service populations also vary during the day. To demonstrate this variability, raster grids were 

created to visualize attendance numbers for daytime visitors to recreation sites, schoolchildren and 

community-center attendees (fig. 9A), and overnight visitors (fig. 9B). There is variability at all times 

throughout the year; however, for illustrative purposes, only the variation during summer months is 

shown in this report. Overall, the maps suggest how variable the distribution of people enjoying the 

landscape can be between daytime and nighttime. Daytime visitors are more widely dispersed than 

nighttime visitors, which are fairly concentrated in Welches and Government Camp. 

Road Volume

Vehicle-count data from recorders along Highway 26 (Oregon Department of Transportation, 

2012) were analyzed to help understand population fluctuations in and out of the study area. This study 

focused on hourly data recorded from 2009 at Station 03_006 of the Oregon Department of 

Transportation (ODOT) Transportation Monitoring Program because it is on Highway 26 between the 

communities of Zigzag and Government Camp (fig. 1) and, therefore, is a good indicator of traffic 

conditions into the study area. Data recorded hourly was aggregated to daily totals, including the 

maximum number of vehicles within one hour on a given day (fig. 10A) and the total number of 

vehicles on that same day(fig. 10B). Vehicle counts, generally ranging between 2,000 and 12,000, are 

provided for eastbound traffic heading toward Government Camp (shown in black) and westbound 

traffic heading toward Sandy and Portland (shown in red). For example, 1,391 vehicles were counted in 

one hour traveling eastbound on the morning of Saturday, April 4 (fig. 10A), suggesting the peak traffic 

likely was due to snow-sport recreationists heading up to the mountains. The highest number of vehicles 
11

heading westbound (towards Portland) recorded in one hour was 1,307 vehicles and occurred on April 

5, the day after the eastbound maximum value, suggesting that it represents people heading home to the 

Portland area. The one-day offset suggests many of these people spent the night in the study area, but 

also may include people driving westbound from destinations east of the study area such as Bend, Oreg. 

The highest total number of vehicles recorded in one day was 11,368 vehicles traveling 

westbound on Monday, May 25, which was Memorial Day, suggesting a peak from holiday traffic 

returning to the Portland area (fig. 10B). The highest daily number of total vehicles traveling eastbound 

(9,914 vehicles) occurred on the previous Friday, May 22, the start of the holiday weekend. In both 

daily maximum per hour and daily totals, higher numbers were recorded for eastbound traffic than for 

westbound traffic. This may be due to multiple days of eastbound traffic into the area preceding a 

weekend (for example, Thursday through Sunday), many people possibly staying overnight in the area, 

and vehicles collectively leaving on Sunday westbound back to the Portland area. 

The influence of holidays and weekends also is apparent when daily westbound vehicle counts 

are subtracted from eastbound counts for both daily maximum counts per hour (fig. 10C) and daily total 

counts (fig. 10D). For illustrative purposes, positive values indicate eastbound traffic was greater than 

westbound traffic at a given time and negative values indicate westbound traffic was greater. In both 

figures 10C and 10D, the peaks throughout the year typically are associated with Fridays, when people 

are traveling eastbound to recreation sites, and troughs are typically associated with Sundays, when 

people are returning to the Portland area. One exception is traffic associated with Memorial Day, which 

occurred on a Monday and resulted in maximum westbound traffic on this day. The highest traffic 

numbers are related to weekends for Memorial Day, the Fourth of July, Labor Day, and Thanksgiving. 

Population Exposure to Natural Hazards

In addition to dynamic populations, the study area also is home to dynamic natural processes 

that have shaped the landscape, including volcanic and landslide activity at Mount Hood, repeated 

flooding and migration of the Sandy River floodplain, and wildfires in the surrounding forests. During 

the past decades, residents have contended with flooding, wildfires, and concern regarding volcanic 

unrest, especially in the wake of Mount St. Helens’ 1980 eruption (Clackamas County, Oregon, 2002, p. 

1-1). With the growing development and tourism in the study area, these natural processes pose 

increasing threats to people and property. 

GIS-based analysis of population data (for example, homes, businesses, tourist attractions, and 

educational facilities) focused on determining if these locations (depicted as points) were inside hazard 

zones (depicted as polygons). Hazards of interest include flooding, wildfires, and volcanism owing to 

data availability and county interest. The following sub-sections describe each of these hazards, the 

hazard zones used in the population-exposure analysis, and the results of this analysis2

. 

Population-exposure estimates in this report are meant to provide insight on general trends in the 

area and to support emergency-management planning. They are not definitive statements of population 

dynamics or mortality estimates for several reasons. First, exposure estimates assume that people are 

located where they are expected to be during an actual event—for example, residents are at their homes 

and not at work, the local market, or on a hiking trail. In addition, emergency managers and at-risk 

 

2

A direct comparison of population-exposure estimates to those presented in Burns and others (2011) was not done because 

of previously-discussed issues of data alignment and accuracy, their use and assumptions in dasymetric mapping, varying 

time periods for U.S. Census data, their exclusion of service populations, differences in study areas, and varying hazard 

zones (to be discussed in subsequent sections). Population-exposure estimates for each hazard in Burns and others (2011) are 

summarized for their entire three-county study area; therefore, comparisons to just the upper Sandy River study area are not 

possible. 
12

populations likely will have some level of advance notice and warning of floods, wildfires, and volcanic 

eruptions (for example, rising flood stages before a flood, a fire ignition in an uninhabited part of the 

region, or increasing seismic activity before an eruption); therefore, there likely will be opportunities to 

move people and some property out of harm’s way. Second, not all recreation-related businesses 

provided attendance numbers; therefore, the magnitude of the service population is likely to be higher 

than reported here. Third, in disaggregating census population counts to individual addresses, residents 

were distributed evenly among the addresses within a census block group, but in reality this distribution 

is uneven. Additionally, employee-exposure estimates are based on the assumption that all employees 

are present at the same time, as opposed to working in shifts; therefore, actual employee exposure may 

be lower than reported results. Finally, the best available data was used, but the age of the data varied—

2001 NLCD, 2005 high-resolution photography of study region, 2005 wildfire-risk zones, 2008 floodand volcano-hazard zones, 2009 employment data, and 2010 U.S. Census Block Group data. Given 

these issues with the input data, exposure estimates should be viewed as first approximations and as 

vehicles for follow-up work and deeper discussions within the emergency-management community.

Flood Hazards

Hazard Delineation

Clackamas County has a long recorded history of floods dating back to 1861, with most flooding 

occurring from October to April due to seasonal storms coming from the Pacific Ocean (Clackamas 

County, Oregon, 2002, p. 6-2). Floods are a significant hazard in the study area, especially along the 

Sandy River, which also experiences channel migration (Clackamas County, Oregon, 2007, p. 27). The 

most recent flooding event on January 16, 2011, damaged several homes, caused temporary closure of 

Lolo Pass Road, compromised the structural integrity of the new Zigzag River bridge, and resulted in 

significant changes to the Sandy River channel because of extensive bank erosion (KATU News, 2011; 

U.S. Geological Survey National Water Information System, 2012). A channel-migration hazard zone 

for the Sandy River was created (English and others, 2011), but was not included in this analysis owing 

to the concurrent timing of the work. 

Flood-hazard zones for this study are based on the 2008 Federal Emergency Management 

Agency (FEMA) Digital Flood Insurance Rate Map (DFIRM) (Federal Emergency Management 

Agency, 2008), which is the basis of floodplain management, mitigation, and insurance determination 

for the National Flood Insurance Program (NFIP)3

. DFIRM flood zones include 100-year and 500-year 

events, which reflect flood levels with 1 percent and 0.2 percent annual chance, respectively, of being 

equaled or exceeded in any single year (Federal Emergency Management Agency, 2012). Although 

100-year flood data further delineate zones based on known and unknown base elevations, this study 

aggregated the two zones and focused on 100-year and 500-year zones (fig. 11). The 500-year flood 

zone depicted in figure 11 represents the extended area of flooding expected from a larger, lower 

probability event; therefore, potential flooding from this event would include the yellow and red areas. 

Flood-hazard zones are present along the Sandy River, Cedar Creek, Salmon River, Zigzag River, and 

Still Creek and are threats primarily in the fall, winter, and spring seasons. Population-exposure analysis 

focused on the number of people and community features in the two hazard zones. The only exception 

was for visitor populations at recreational areas, where a 0.25-mile GIS buffer was added on to the 

hazard zone. This was done because many recreational areas cover large areas but are mapped only as 

 

3

This varies from the flood-hazard zones used in Burns and others (2011), in which researchers developed their own 25- and 

500-year flood hazard zones.
13

point locations (for example, trailheads recorded by the U.S. Forest Service). This buffer could be used 

to help identify recreational areas that may be impacted by future floods. 

Population Exposure

There are between 381 and 537 households and 717 and 960 residents threatened by flood 

hazards depending upon the severity of the flood (100- versus 500-year events, respectively). This 

translates to approximately 7 percent of households and residents in the study area in the 100-year flood 

zone and as much as 10 percent of households and residents in the 500-year flood hazard zone (fig. 12). 

Business and employee exposure is much less—7 businesses and 6 employees are in the 100-year zone 

(2 percent and less than 1 percent, respectively) and up to 15 businesses and 36 employees are in the 

500-year hazard zone (4 percent and 1 percent, respectively). Of the 36 employees in the flood-hazard 

zones, most are in business sectors related to utilities, manufacturing, and transportation and 

warehousing (fig. 13). Approximately 20 percent of all utility and manufacturing jobs in the study area 

are in the 500-year flood zone. No schools or community centers are within the flood-hazard zones. 

There are 60 vacation homes and vacation-rental properties within the flood-hazard zones, and

77 percent of them (46 of 60) are in the 100-year flood hazard zone. Most of the vacation homes in the 

flood-hazard zones are concentrated along the Zigzag River and Still Creek near the town of 

Rhododendron. Lack of records on private vacation-home occupancy precludes the ability to estimate 

overnight attendance. Although no campgrounds, trailheads, or other recreational areas fall completely 

within the flood-hazard zones, the U.S. Forest Service Pioneer-Tollgate Campground and trailhead is 

within a quarter mile of the Zigzag River, and visitors in the area could be affected by a flood event 

along the river. Regarding the seasons most prone to flooding, this campground typically averages 173 

visitors per month during fall, 62 visitors per month during spring, and is closed during winter. Flooding 

also could affect access to parts of trails, such as Castle Canyon, Zigzag Mountain #775, Flag Mountain, 

and Old Salmon River, although inclement weather conditions are likely to preclude much usage of 

these trails during flood generation. 

Wildfire Hazards

Hazard Delineation

The majority of the study area is covered by the Mount Hood National Forest; therefore, wildfire 

is a prevalent risk. Greatest risks of wildfires are during late summer and early fall owing to high 

temperatures and low humidity (Clackamas County, Oregon, 2002, p. 8-5). Conditions favoring future 

wildfire disasters include fuel build up and increases in development at the wildland/urban interface 

(Clackamas County, Oregon, 2005, p. 2). The most recent wildfire occurring near the study area (on the 

northern flank of Mount Hood) was the Dollar Lake Fire which ignited by lightning on August 26, 

2011. It led to a declaration of emergency and burned more than 6,300 acres of wilderness (KGW News, 

2011; InciWeb Incident Information System, 2012). 

Wildfire-hazard zones come from the 2005 Clackamas County Community Wildfire Protection 

Plan (Clackamas County, Oregon, 2005) and are actually wildfire relative-risk zones, based on available 

fuel loads, slope, aspect, elevation, weather, historic-fire occurrence, home density and community 

infrastructure, and protection capability (fire-response time and level of community preparedness). Risk 

zones used in this analysis include five relative categories (high, moderate-to-high, moderate, low-tomoderate, and low) (fig. 14). Although risk zones identify specific wildfire-risk characteristics at a 

specific location, fires ignited at one spot can spread quickly to other areas considered to have lower 

risk. Accordingly, the overall size of any future fire cannot be predicted. Fire-prevention efforts by 
14

communities and the Hoodland Fire District also can reduce wildfire risk in specific locations; therefore, 

the wildfire-risk zones and subsequent population-exposure estimates should be viewed as first 

approximations and not as guarantees of either being directly impacted or spared impact from a future 

wildfire. 

Wildfire-risk zones have been established across the entire study region and represent a 

perception of risk rather than a predicted area of impact. The greatest percentage of the study area is 

characterized as moderate-to-high wildfire risk (44 percent) followed by high wildfire risk (25 percent) 

(fig. 15A). Areas of lower risk are concentrated around river channels and in the western-most section of 

the study area (fig. 14). Overall, 90 percent of the study area is considered to have at least a moderate 

risk of wildfire.

Population Exposure

Although most of the study area is classified as moderate-to-high and high wildfire risk, the 

majority of homes and businesses (87 and 85 percent, respectively) are in areas classified as moderate 

wildfire risk or lower (fig. 15). The highest percentage of homes is in moderate wildfire-risk zones (53 

percent) (fig. 15B). Of the 323 businesses in the study area, the greatest percentage of them (33 percent) 

is in low wildfire-risk zones (fig. 15C). Although only 15 percent of businesses are in moderate-to-high

or high wildfire-risk zones, these businesses account for 51 percent of the study-area workforce (fig.

15D).

The various business sectors are not exposed equally to wildfire risk. The distribution of 

employees, by business sector, in the various wildfire-risk zones indicates that some sectors (for 

example, education services, finance and insurance, and retail trade) have high percentages of their 

workforce in moderate-to-high and high wildfire-risk zones (fig. 16). More than 50 percent of the 

workforce within the following business sectors is exposed to moderate or higher risk for wildfire: 

construction, retail trade, professional/scientific services, education services, and health care/social 

assistance. Wildfire risk also is high among employees in the education-services sector, which includes 

businesses outside of the public school system, with nearly 90 percent of the workforce exposed to 

moderate-to-high wildfire risk or greater. 

Evaluation of the wildfire risk posed to service populations focused only on those seasons 

coincident with wildfire occurrence (summer and fall). Figure 17 shows charts of exposure to wildfire 

risk among the three service-population categories—dependents, overnight visitors, and daytime visitors 

to recreation sites. Owing to local public schools being in session, the average monthly attendance 

among school children and individuals at community centers is much higher in the fall and reaches a 

combined attendance estimate of 1,000 people (fig. 17A). Schools are in varying levels of wildfire risk 

including low (Mount Hood Academy and Welches Elementary), low-to-moderate (Welches Middle 

School and Firwood Elementary School) and moderate (community center). In general, the majority of 

the dependent seasonal population has either a low-to-moderate or low risk of wildfire. In the fall, for 

example, approximately two-thirds of the dependent population has a low-to-moderate level of wildfire 

risk. 

Overnight visitors (fig. 17B) and daytime visitors to recreation sites (fig. 17C) are much more 

prevalent in the study area during the summer months and account for tens of thousands of people. 

There are, on average, approximately 34,000 overnight visitors at lodging facilities during a summer 

month and 11,000 overnight visitors during a month in the fall (approximatly 1,133 and 367 overnight 

visitors per day, respectively). Although wildfire danger exposes many more people in the summer 

months, 71 percent of these visitors are exposed to either a low-to-moderate or low level of wildfire 

risk. Thirty percent of the lodging facilities are within moderate or higher wildfire-risk areas
15

The only accommodations in high wildfire risk are private vacation homes which do not have 

attendance records. Moderate-to-high wildfire risk exists for Timberline Lodge and some units at both 

The Resort at the Mountain and Whispering Woods Resort. Overall, the majority of the overnight visitor 

seasonal population has either a low-to-moderate or low level of wildfire risk, but those with greater 

exposure (moderate and higher) equate to an average of about 10,000 and 4,000 people per month in the 

summer and fall, respectively

Among the daytime visitors to recreation sites, the summertime monthly average is roughly 

99,000 people and exceeds the average monthly attendance estimate of 27,000 for the fall (about 3,300 

and 900 daytime visitors to recreation sites per day, respectively). The percentage of daytime visitors to 

recreation sites exposed to wildfire risk of moderate level or higher is roughly the same for both summer 

and fall (58 and 59 percent, respectively); however, on average, 58,000 people per month are vulnerable 

to this wildfire risk in the summer and only 16,000 people per month are at similar risk in the fall

(approximating 1,933 and 533 daytime visitors to recreation sites per day, respectively). Wildfire risk 

for seasonal attendance of daytime visitors to recreation sites was evaluated at sites such as public parks, 

private camps, U.S. Forest Service campgrounds and trailheads, and tourist attractions like Mount Hood 

Ski Bowl, Timberline Lodge and Ski Area, and the Mount Hood Cultural Center and Museum. Those 

sites with higher risk of wildfire include some U.S. Forest Service campgrounds (Trillium Lake and 

Lost Creek) and trailheads (Dry Fir/Veda Lake, Eureka Peak, Grave Trail, West ZZ-Burnt/Cast Lake, 

Upper Horseshoe, and North Burnt Lake) and portions of Windells Snowboard Camp and the Mount 

Hood Summer Ski Camp (specifically at the Lodges at Salmon River). 

Volcanic Hazards

Hazard Delineation

Mount Hood is located on the northeastern edge of Clackamas County and is a composite 

volcano that consists of lava flows, lava domes, and related volcaniclastic debris (Scott and others, 

1997a). Three eruptive periods have been identified for Mount Hood in the past 15,000 years, including 

the Polallie (12,000–15,000 years ago) the Timberline (1,400–1,800 years ago), and the Old Maid (A.D. 

1781 and lasting about a decade) (Scott and others, 1997a, b; Pierson and others, 2011). Although no 

major eruptive events have occurred at Mount Hood since the late 18th century, there have been reports 

of steam emissions and minor tephra falls in the mid-19th century, and small lahars (volcanic debris 

flows), small debris avalanches, and short-lived swarms of small earthquakes in recent decades (Scott 

and others, 1997a; Gardner and others, 2000). The likelihood of a Mount Hood eruption originating near 

Crater Rock, the youngest lava dome on the mountain, is estimated to be between 1 in 15 and 1 in 30 in 

the next 30 years. The likelihood of an extreme event is even lower—1 in 10,000 in the next 30 years, 

but such an event would be catastrophic for the region (Scott and others, 1997b). 

Volcano hazard zones are derived from Scott and others (1997b) with digital updating by 

Schilling and others (2008) and include proximal and distal hazards with subclassification based upon 

vent location, magnitude of event, and probability of inundation4

. In this study detailed hazard 

designations are reclassified into three categories—proximal hazards, distal hazards for a typical

scenario, and distal hazards for a worst-case scenario (maximum credible lahar) (fig. 18). These hazard 

zones, by design, are not necessarily indicative of impact from one specific event and simply represent 

probable areas under threat. In addition, although population estimates are provided for “no volcano 

hazard” areas, these areas should not be considered completely hazard-free as too many uncertainties 

 

4

This varies from the volcanic-hazard zones used in Burns and others (2011), in which researchers developed their own 

lahar-hazard zones.
16

exist in the source, magnitude, and mobility of future events (Scott and others, 1997b). Again, 

population estimates within hazard zones are for emergency-planning purposes as volcanic eruptions 

often are preceded by indicators of unrest which allow emergency managers time to initiate emergencyresponse efforts.

Proximal hazards can travel from source to the hazard boundary in less than 30 minutes and 

include lava flows, ballistic fragments, pyroclastic flows (hot, dense flows of rock debris and gas 

generated by collapses of growing lava domes), debris avalanches (rapid landslides from the steep upper 

slopes of the volcano), and near-source volcanic lahars (volcanic mud flows). Given the topographic 

relief of Mount Hood, a large pyroclastic flow—generated by the collapse of a substantial lava dome at 

the Crater Rock site—could theoretically inundate Timberline Lodge and Government Camp, Oreg., in 

less than 30 minutes time (Brantley and Scott, 1993; William Scott, oral communication, June 2012) 

(fig. 19). Landslides of volcanic debris (volcanic debris surges) are a perceived hazard on the steep 

slopes of the study area’s mountainous terrain (Clackamas County, Oregon, 2002) and can be triggered 

by events other than volcanic eruptions. For example, within the White River valley of Mount Hood, 

volcanic debris surges related to glacial melt water have forced closures of the Oregon Route 35 bridge 

20 times since 1907 (Anderson and others, 2006). The most recent White River valley landslide event

was generated in November 2006 by a major rainstorm. It caused major damage to the bridge, cut a new 

channel through the highway, and moved 2 million cubic yards of mud, debris, and boulders larger than 

pickup trucks (Hood River News, 2012). 

Distal volcanic hazards refer to lahars that can travel tens of miles down valleys from the 

volcano. Two levels of distal lahar hazards exist (referred to as typical and worst-case scenarios) based 

on frequency and magnitude. As was the case with the 100- and 500-year flood data, the worst-case 

distal lahar-hazard zone includes the inundation areas associated with a typical event. Distal laharhazard zones are not tied to a specific single event, and eruptive periods that last for months to years can 

include events of a wide range of sizes. In addition, sedimentation from numerous lahars associated with 

an eruptive period can fill valleys over time and cause wider inundation of volcanic material (William 

Scott, oral communication, June 2012). Distal hazards can range from a chronic problem that gradually 

encroaches on broad areas to single catastrophic events of large size that inundate all or most of a hazard 

zone. Monitoring likely will detect the onset of unrest prior to a large event, providing opportunities to 

protect people and some property. 

Population Exposure

Proximal volcanic hazards threaten 1,315 homes and 104 businesses, representing 1,501 

residents and 2,041 employees (fig. 20). The percentages of all homes and businesses for the study area 

that are in the proximal hazard zones are similar (23 and 32 percent, respectively); however, the 

percentages for residents and employees in these homes and businesses diverge substantially. Although 

23 percent of study-area homes are in the proximal hazard zone, only 14 percent of residents are in that 

area, suggesting that these homes do not contain many families (fig. 20A). Conversely, the 32 percent of 

study-area businesses that are in the proximal hazard zone represent 65 percent of the study-area 

workforce, suggesting these businesses on the flanks of the volcano are primary drivers for the local 

economy (fig. 20B and C). 

Distal volcanic hazards also pose significant threats to downstream communities and businesses 

(fig. 20). The typical distal hazard zone contains 2,047 homes and 99 businesses, representing 3,834 

residents and 617 employees. This accounts for 36 percent of all households and residents in the area, 

31 percent of businesses, and 20 percent of employees. The decrease in employee exposure relative to 

the proximal hazard suggests the larger businesses are on the upper reaches of Mount Hood (for 
17

example, Timberline Lodge) and smaller businesses (such as restaurants and retail stores) are more 

characteristic in the foothill valleys. A worst-case distal hazard zone would increase the number of 

threatened homes and businesses, but the difference in those exposed does not exceed 10 percent among 

the different categories. The worst-case scenario includes an additional 503 homes (9 percent of study 

area), 1,055 residents (10 percent), 34 businesses (10 percent), and 91 employees (2 percent) to those 

already accounted for in the typical distal hazard zone. Assuming, the potential for typical or worst-case 

scenarios, volcanic hazards threaten 3,362–3,865 homes (59–68 percent) and 203–237 businesses (63–

73 percent). These homes and businesses represent 5,335–6,390 residents (50–60 percent) and 2,658–

2,749 employees (84–87 percent). Again, the distinction in population-exposure estimates between a 

typical and worst-case scenario is not dramatically different because most development occurs in the 

low-lying areas along the river valleys and therefore could be impacted by any distal event, regardless 

of magnitude or event duration. 

Business exposure to volcano hazards varies by sector (fig. 21). Many business sectors have a 

high percentage of their employees in the proximal hazard zone, such as education services (95 percent), 

arts, entertainment, and recreation (95 percent), public administration (89 percent), and accommodation 

and food services (65 percent). These businesses are threatened by volcanic hazards regardless of the 

magnitude of related distal hazards. Other business sectors, such as information, finance and insurance, 

real estate, health care, and social assistance, are primarily in the typical distal hazard zones. A worstcase scenario event would not substantially change the exposure of most business sectors, except for 

agriculture (0–15 percent of study-area employees in this sector), transportation and warehousing (33–

77 percent of employees), and construction (45–68 percent of employees). 

Of the 579 locations with service populations in the study area, 460 of them (approximately 80 

percent) are in proximal volcanic-hazard zones, including 420 lodging facilities, 36 recreation sites, and 

4 schools or community centers (table 1). Distal hazard zones include a range of 15 lodging facilities 

and 5 recreation sites (typical scenario) to 96 lodging facilities and 8 recreation sites (worst-case 

scenario). This suggests that 8– 97 percent of non-residential addresses, depending on hazard scenario

(typical and worst-case scenarios, respectively), are in areas prone to volcanic hazards. 

Table 1. Volcano-hazard exposure by service population facilities, Mount Hood region of Clackamas County, 

Oregon.

Volcano hazards

Total 

servicepopulation 

locations

Lodging Day-use 

recreation

Schools and 

community 

centers 

Proximal hazards 460 420 36 4 

Distal lahar hazard (typical scenario) 20 15 5 0 

Distal lahar hazards (worst-case scenario) 104 96 8 0 

No hazard 15 5 9 1 

Study area total 579 521 53 5 
18

Unlike floods and wildfires, volcanic eruptions are not seasonal and could occur at any time of 

year; therefore, volcano exposure to service populations is presented for all four seasons (fig. 22). 

Populations at the schools and community centers are consistent throughout the school year (nearly 550 

people) and decrease only in the summer months (fig. 22A). Summer months have the greatest number 

of overnight visitors, with approximately 22,000 people in the proximal zone, 10,750 people in the 

typical distal hazard zone, plus an additional 820 people if the distal scenario is a worst-case-scenario 

event (fig. 22B). This is approximately 34,000 people per summer month, or 1,100 people per day. 

Approximately two-thirds of overnight visitors are in the proximal hazard zone, including all lodging 

within Government Camp and much of that within the VMH area. As was the case with extreme flood 

events, the distinction in population exposure between typical and worst-case-scenario events is not 

substantial (an addition of approximately 2 percent of overnight visitors). Winter months have the 

second highest number of overnight visitors in volcanic-hazard zones (approximately 20,500 per 

month), followed by spring and fall months (12,500 and 11,000, respectively). 

The number of daytime visitors to recreation sites in volcanic-hazard zones is greatest during 

winter months —approximately 129,300 people per month or 4,300 people per day (fig. 22C). The vast 

majority of these daytime visitors are in the proximal hazard zone (approximately 128,800 people per 

month), reflecting snow-sport activity on the upper flanks of Mount Hood. Summer months have the 

second highest number of daytime visitors to recreation sites in volcanic-hazard zones (approximately 

94,000 people per month or 3,100 people per day on average), with about 82 percent in the proximal 

zone, 18 percent in the typical distal hazard zone, and a negligible additional percentage in the worstcase scenario event distal hazard zone. The number of daytime visitors to recreation sites in volcanichazard zones is less but still substantial during spring months (approximately 63,000 per month) and fall 

months (approximately 25,500 per month). Regardless of season, results suggest that the majority of 

seasonal populations are in the proximal hazard zone and that there is little difference in population 

exposure between typical and worst-case-scenarios for distal hazards. The proximal zone likely will be 

devoid of residents or visitors at the time of an event owing to the monitored period of volcanic unrest 

leading to an eruption. 

Conclusions

This study, a collaboration of the U.S. Geological Survey and the Clackamas County 

Department of Emergency Management, evaluates community vulnerability to flood, wildfire, and 

volcano hazards within the VMH and Government Camp region of Clackamas County, Oreg. The 

work’s intent is to develop methodology for exposure research, to improve understanding of community 

vulnerability, and to assist with further development of emergency plans and community-outreach 

activities. Documenting the composition and spatial distribution of populations within a rural, touristdestination setting is challenging owing to the highly dynamic and dispersed nature of residents, 

employees, overnight visitors, daytime visitors to recreation sites, and dependents. Based on a 

geospatial analysis of population exposure to flood, wildfire, and volcanic hazards, the following 

conclusions can be made: 

• The heavily forested landscape and limited development in study area would suggest low 

population; however, tens of thousands among the various population groups are present. 

• Much of the development within the study region occurs in valley-floor areas, which increases the 

chance for residents, employees, and visitors to be exposed to flooding and distal (lahar) volcanic 

hazards. 
19

• Visitors are a substantial component of the region’s service population at any given time. Summer 

months are dominated by overnight visitors and winter months are dominated by daytime visitors to 

recreation sites. 

• Flooding could impact up to 10 percent of homes and residents, 4 percent of businesses, and 1 

percent of employees, depending on event magnitude. Population exposure to flood hazards within 

the study area does not increase dramatically with increasing flood severity—the difference in 

population exposed between a 100-year flood and a 500-year flood event scenario is 3 percent or 

less.

• Although the majority of the study area is classified as moderate-to-high or greater wildfire risk, 

most homes, businesses, and overnight accommodations are in areas classified as moderate wildfire 

risk or lower. Only 15 percent of businesses are within moderate-to-high or high wildfire-risk areas, 

but the employees on site account for 51 percent of the local workforce. These areas also attract 

approximately 60 percent of daytime visitors to recreation sites where they are exposed to moderate

or higher wildfire risk.

• A period of eruption at Mount Hood could impact up to 68 percent of homes, 60 percent of 

residents, 73 percent of businesses, and 87 percent of employees. A worst-case scenario would 

increase population exposure during a typical event, but the increase is not substantial—typically 10 

percent or less of an increase in population exposed. Service-population exposure to volcano hazards 

is largest in the proximal hazard zone, including 65 percent of the local workforce, 80 percent of 

educational facilities, 82–100 percent of daytime visitors to recreation sites (summer and winter 

month averages, respectively), and approximately two-thirds of overnight visitors. 

• Factors adding complexity to emergency response and evacuation efforts include: (1) thousands of 

vehicles passing through the region on any given day, (2) several tourist draws located entirely in 

the proximal volcanic-hazard zone (such as Mount Hood Skibowl, Timberline Lodge and Ski Area, 

and Summit Ski Area), and (3) the dependence of the local road network on the single-corridor 

outlet of U.S. Highway 26. 

This project explored research methods, information synthesis, and the various geographic-data 

inputs required to better estimate population distributions of residents, employees, and visitors within a 

rural community setting. By better understanding how much of the population within Clackamas 

County around Mount Hood is exposed to natural hazards, public officials can identify locations within 

communities and their respective business sectors that may require additional preparedness, mitigation, 

recovery planning, and outreach activities. The information provided in this report is intended to 

enhance the dialogue regarding societal risk and resilience in areas prone to multiple natural hazards. 

Acknowledgments

We specifically acknowledge Jay Wilson (Clackamas County Emergency Management 

Department) for his collaboration since the project’s inception; his thoughtful contributions toward this 

report are greatly appreciated. Research work was supported by the U.S. Geological Survey Geographic 

Analysis and Monitoring Program. William Scott (U.S. Geological Survey Cascade Volcano 

Observatory), Kelly Neumeier (Clackamas County Technology Services, Geographic Information 

Systems Division), and Cindy Kolomechuk (Oregon Department of Forestry) gave insightful reviews of 

this manuscript. We also thank Dave Ramsey (U.S. Geological Survey Cascade Volcano Observatory) 

for insights on appropriate recoding of volcano hazards GIS data.
20

References Cited

Anderson, D.A., DeRoo, T.G., and Hedeen, C.D., 2006, Response to 1998 debris flow in the upper 

White River valley, Oregon, Oregon Geology, v. 67, no. 1, Fall 2006, p. 7–10, accessed May 30, 

2012, at http://www.oregongeology.org/pubs/og/OGv67n01.pdf . 

Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E., 1976, A land use and land cover 

classification system for use with remote sensor data: U.S. Geological Survey Professional Paper 964, 

accessed May 30, 2012, at http://landcover.usgs.gov/pdf/anderson.pdf .

Australian Bureau of Statistics, 2008, Information paper—Population Concepts, 2008: Australia, no. 

3107.0.55.006, accessed July 24, 2012, at 

http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3107.0.55.0062008?OpenDocument .

Brantley, S.R., and Scott, W.E., 1993, The danger of collapsing lava domes: Lessons for Mount Hood, 

Oregon: Earthquakes and Volcanoes, v. 24, no. 6, p. 244–269. 

Bureau of Labor Statistics, 2012, Overview of BLS statistics on employment: U.S. Department of 

Labor, accessed May 4, 2012, at http://www.bls.gov/bls/employment.htm .

Burns, W.J., Hughes, K.L.B., Olson, K.V., McClaughry, J.D., Mickelson, K.A., Coe, D.E., English, 

J.T., Roberts, J.T., Lyles Smith, R.R., and Madin, I.P., 2011,Multi-hazard and risk study for the 

Mount Hood region, Multnomah, Clackamas, and Hood River counties: Oregon, Oregon Department 

of Geology and Mineral Industries, Open-File Report O-11-16, accessed May 30, 2012, at 

http://www.oregongeology.org/pubs/ofr/p-O-11-16.htm .

Clackamas County, Oregon, 2002, Clackamas County—Natural hazard mitigation plan, 302 p., 

accessed August 22, 2011, at http://scholarsbank.uoregon.edu/jspui/handle/1794/2341 .

Clackamas County, Oregon, 2007, The Clackamas County natural hazard mitigation plan, accessed 

August 30, 2012, at http://www.clackamas.us/emergency/naturalhazard.html . 

Clackamas County, Oregon, 2005, Clackamas County Community Wildfire Protection Plan, 119 p. 

Clackamas County, Oregon, 2012, About Clackamas County, accessed May 2012 at, 

http://www.co.clackamas.or.us/about.htm .

Cook, Tricia, 1996, When ERP aren’t enough—A discussion of issues associated with service 

population estimation: ABS Demongraphy Working Paper 1996, v. 4, accessed July 2012 at, 

http://www.abs.gov.au/ausstats/abs@.nsf/mf/3112.0 .

Cruden, D.M., 1991, A simple definition of a landslide: Bulletin of the International Association of 

Engineering Geology, no. 43, p. 27–29. 

English, J.T., Coe, D.E., Chappell, R.D., 2011, Channel migration hazards maps for the Sandy River, 

Multnomah and Clackamas counties, Oregon, Oregon Department of Geology and Mineral Industries 
21

(DOGAMI), Open-File Report O-11-13, accessed July 24, 2012, at 

http://www.oregongeology.org/pubs/ofr/p-O-11-13.htm . 

Federal Emergency Management Agency, 2008, Map Service Center: U.S. Department of Homeland 

Security, available at 

https://msc.fema.gov/webapp/wcs/stores/servlet/FemaWelcomeView?storeId=10001&catalogId=10001&langId=-1. 

Federal Emergency Management Agency, 2012, Flood zones: NFIP Policy Index: U.S. Department of 

Homeland Security, accessed June 2012 at, 

http://www.fema.gov/plan/prevent/floodplain/nfipkeywords/flood_zones.shtm .

Gardner, C.A., Scott, W.E., Major, J.J., and Pierson, T.C., 2000, Mount Hood—History and hazards of 

Oregon’s most recently active volcano: U.S. Geological Survey Fact Sheet 060-00, accessed August 

2012 at http://pubs.usgs.gov/fs/2000/fs060-00/ . 

Homer, Collin, Dewiltz, Jon, Fry, Joyce, Coan, Michael, Hossain, Nazmul, Larson, Charles, Herold, 

Nate, McKerrow, Alexa, VanDriel, J. N., and Wickham, James, 2007, Completion of the 2001 

National Land Cover Database for the Conterminous United States: Photogrammetric Engineering 

and Remote Sensing, v. 73, no. 4, p. 337–341, available at http://www.mrlc.gov/nlcd2001.php. 

Hood River News, 2012, Highway 35 improvement projects complete six years after washout—Bridge 

rededicated: Eagle Newspapers, Inc., accessed March 2013 at 

http://www.hoodrivernews.com/news/2012/nov/13/highway-35-improvement-projects-complete-six-years/.

InciWeb Incident Information System, 2012, Final Dollar Lake Fire daily update 10-1-2011, accessed 

August 30, 2012, at http://www.inciweb.org/incident/2563/ .

InfoGroup, 2009, Employer database, available at http://referenceusagov.com/Static/Home .

KATU News, 2011, Sandy River flood 2011, January 17, 2011: Fisher Interactive Network, accessed 

May 30, 2012, at http://www.katu.com/younews/113991494.html . 

KGW News, 2011, Oregon governor declares emergency amid wildfires, September 8, 2011: King 

Broadcasting Company, accessed August 30, 2012, at http://www.kgw.com/news/Governor-Will-Tour-DollarLake-Fire-129500953.html . 

Loveland, T.R., and Shaw, D.M., 1996, Multi-resolution land characterization—Building collaborative 

partnerships, in Scott, J.M., Tear, T.H., and Davis, F.W., eds., GAP Analysis—A landscape approach 

to biodiversity planning: Bethesda, Md., American Society for Photogrammetry and Remote Sensing, 

p. 79–85. 

Mennis, J., 2003, Generating surface models of population using dasymetric mapping: The Professional 

Geographer, v. 55, no. 1, p. 31–42. 

Mennis, J. and Hultgren, T., 2006, Intelligent dasymetric mapping and its application to areal 

interpolation: Cartography and Geographic Information Science, v. 33, no. 3, p. 179–194. 
22

National Agriculture Imagery Program, 2005, Clackamas County, OR, U.S. Department of Agriculture, 

Aerial Photography Field Office, accessed November 2009 at 

http://www.fsa.usda.gov/FSA/apfoapp?area=home&subject=prog&topic=nai . 

Oregon Department of Transportation, 2012, Traffic Counting Program: ODOT Transportation Data 

Section, accessed June 2012 at http://www.oregon.gov/ODOT/TD/TDATA/pages/tsm/tvt.aspx . 

Oregon Blue Book, 2012, County populations—1970-2009: Oregon Secretary of State, accessed May 

2010 at http://bluebook.state.or.us/local/populations/pop06.htm . 

Pierson, T.C., Pringle, P.T., and Cameron, K.A., 2011, Magnitude and timing of downstream channel 

aggradation and degradation in response to a dome-building eruption at Mount Hood, Oregon: 

Geological Society of America Bulletin. v. 123, no. 1–2, p. 3–20, accessed August 2012 

http://bulletin.geoscienceworld.org/cgi/content/full/123/1-2/3?ijkey=4xxL7.WGKnpY.&keytype=ref&siteid=gsabull .

Reibel, Michael, and Agrawal, Aditya, 2007, Areal interpolation of population counts using preclassified land cover data: Population Research and Policy Review, v. 26, p. 619–613. 

Schilling, S.P., Doelger, Sarah., Scott, W.E., Pierson, T.C., Costa, J.E., Gardner, C.A., Vallance, J.W., 

and Major, J.J., 2008, Digital data for volcano hazards for the Mount Hood region, Oregon (data to 

accompany U.S. Geological Survery Open-File Report 97-89), U.S. Geological Survey Open-File 

Report 2007-1222, accessed August 2012 at http://vulcan.wr.usgs.gov/Volcanoes/Hood/Hazards/OFR2007-

1222/framework.html. 

Scott, W.E., Gardner, C.A., Sherrod, D.R., Tilling, R.I., Lanphere, M.A., and Conrey, R.M., 1997a, 

Geologic history of Mount Hood Volcano, Oregon—A field-trip guidebook, U.S. Geological Survey 

Open-File Report 97-263, 38 p., accessed August 26, 2011, at 

http://vulcan.wr.usgs.gov/Volcanoes/Hood/Publications/OFR97-263/framework.html . 

Scott, W.E., Pierson, T.C., Schilling, S.P., Costa, J.E., Gardner, C.A., Vallance, J.W., and Major, J.J., 

1997b, Volcano hazards in the Mount Hood region, Oregon: U.S. Geological Survey Open-File 

Report 97-89, 14 p., available at http://vulcan.wr.usgs.gov/Volcanoes/Hood/Hazards/OFR97-89/framework.html.

Sleeter, R., 2004, Dasymetric mapping techniques for the San Francisco Bay region, California: Urban 

and Regional Information Systems Association, Annual Conference, Reno, Nev., November 7–10, 

2004 [Proceedings], available at http://geography.wr.usgs.gov/science/dasymetric/data/URISA_Journal.pdf . 

Sleeter, R., and Gould, M., 2007, Geographic information system software to remodel population data 

using dasymetric mapping methods: U.S. Geological Survey Techniques and Methods 11-C2, 15 p., 

available at http://pubs.usgs.gov/tm/tm11c2/ . 

Taylor, Barbara, 1998, Salmon and steelhead runs and related events of the Sandy River Basin—A 

historical perspective: Oreg., Portland General Electric, accessed July 25, 2012, at 

http://www.portlandgeneral.com/community_environment/initiatives/protecting_fish/sandy_river/docs/sandy_river_histor

y_full.pdf . 
23

U.S. Census Bureau, 2012, State & County Quickfacts: U.S. Department of Commerce, accessed May 

30, 2012, at http://quickfacts.census.gov/qfd/index.html . 

U.S. Department of Agriculture National Agriculture Imagery Program, 2009, Archived NAIP data: 

U.S. Department of Agriculture, Farm Service Agency, National Agriculture Imagery Program, 

accessed November 2009, at http://www.fsa.usda.gov/FSA/apfoapp?area=home&subject=maps&topic=arc. 

U.S. Geological Survey The National Map, 2009, The National Map viewer and download platform: 

U.S. Geological Survey, The National Map, accessed November 2009, at 

http://nationalmap.gov/viewer.html. 

U.S. Geological Survey National Water Information System, 2012, Surface Water for Oregon—Peak 

Streamflow, USGS 14142500 Sandy River BLW Bull Run River, NR Bull Run, OR: U.S. Geological 

Survey Water Resources, accessed May 2012, at 

http://nwis.waterdata.usgs.gov/or/nwis/peak?site_no=14142500&agency_cd=USGS&format=html . 

Wood, Nathan, 2011, Understanding risk and resilience to natural hazards: U.S. Geological Survey Fact 

Sheet 2011-3008, 2 p. 

Wood, N.J., and Good, J.W., 2004, Vulnerability of a port and harbor community to earthquake and 

tsunami hazards—The use of GIS in community hazard planning: Coastal Management, v. 32, no. 3, 

p. 243–269. 

Zandbergen, P.A., and Ignizio, D.A., 2010, Comparison of dasymetric mapping techniques for smallarea population estimates; Cartography and Geographic Information Science, v. 37, no. 3, p. 199–214. 
24

Figure 1. Location maps of study area within Clackamas County, Oregon. Map A shows the county’s location 

and interstate highway transportation routes within Oregon (metropolitan area of Portland, Oreg., marked with 

a dashed yellow line). Map B shows the county’s topography with shaded relief (generated from a 10-meter 

digital elevation model) and location of study area (outlined in black) (U.S. Census Bureau, 2012). Data for 

roads, government boundaries, and shaded relief sourced from The National Map (U.S. Geological Survey, 

2009). Features of study area shown on Map C with 2005 high-resolution photography (U.S. Department of 

Agriculture National Agriculture Imagery Program, 2009)—villages of unincorporated area (labeled in white), 

Mount Hood (labeled in black), and major highways (U.S. Route 26 and Oregon Route 35). 
25

Figure 2. Map (A) and pie graph by area (B) of the land cover classification of the study area (National Land 

Cover Database, 2001), Clackamas County, Oregon. 
26

Figure 3. Images of the Villages at Mount Hood and Government Camp study area in Clackamas County, Oregon

(U.S. Geological Survey photographs taken by A. Mathie): A, Government Camp, Oreg.; B, Hiking along U.S. 

Forest Service Mirror Lake Trail, located off U.S. Route 26 along western boundary of Government Camp, 

Oreg.; C, Golfing in Welches, Oreg.; D, “Hood to Coast” relay race start at Timberline Lodge, Government 

Camp, Oreg.; E, Mount Hood Skibowl winter resort and summer adventure park (Government Camp, Oreg.)

with U.S. Highway 26 in foreground; F, U.S. Forest Service Trillium Lake Campground, located 4 miles south of 

Government Camp, Oreg. off U.S. Route 26; G, Festival information at Wildwood Recreation Site, located near 

Wemme, Oreg. on U.S. Route 26. 
27

Figure 4. Map of categorized structure point data derived from Master Street Address (MSA) structure file, 

Clackamas County, Oregon. 
28

Figure 5. Distribution of residential structures by land cover class (based upon 2001 NLCD land cover), 

Clackamas County, Oregon. The total number of residences (”n-value”) in the research area is 5,711, and 

residence counts associated with listed percentages are in parentheses. 
29

Figure 6. General illustration of address-point-based hybrid dasymetric technique used to determine residential 

population distribution. Each block group (A and B, represented by black squares) has an aggregated 

population of 12 people. Block group A contains 4 residential structures, which distributes 3 people to each 

house (12 / 4 = 3). Block group B contains 5 residential structures, which equates to 2.4 people per house.

Converting the point data to raster pixels (represented with dashed lines) sums resident population per 

household in areas of higher housing density.
30

Figure 7. Maps of residential population at a 30-meter pixel resolution. A, Welches and surrounding 

unincorporated area, and B, Government Camp, Clackamas County, Oregon. 
31

Figure 8. Three hundred-meter pixel resolution density maps of: A, residents by area, and B, employees by area, 

Clackamas County, Oregon. 
32

Figure 9. Three hundred-meter pixel resolution density maps of summer season attendance elements: A, daytime 

visitors to recreation sites and resident dependents by area, and B, overnight visitors by area, Clackamas 

County, Oregon. 
33

Figure 10. Daily vehicle counts from Oregon Department of Transportation permanent recorder station located along U.S. Highway 26 east of 

Zigzag and west of Government Camp, Clackamas County, Oregon. A, daily maximum number of vehicles within any given hour, B, total daily 

count of vehicles, C, difference between east- and westbound traffic count of daily maximum, and D, difference between east- and westbound 

traffic count of daily total. No data were recorded in January or on isolated days in October and November. 
34

Figure 11. Map of 100-year and 500-year Federal Emergency Management Agency Flood Hazard Zones for the 

study area, Clackamas County, Oregon. Rivers mentioned in the report are labeled. 
35

Figure 12. Flood hazard exposure among A, study area homes and B, businesses, Clackamas County, Oregon. 

Values for a 500-year event are read as additions to the exposure calculated for a 100-year flood. Calculations 

are based on a total of 5,711 homes and 323 businesses; counts corresponding to listed percentages are in 

parentheses. 
36

Figure 13. Flooding hazard exposure to employees by business sector, Clackamas County, Oregon. Values for a 

500-year event are read as additions to the exposure calculated for a 100-year flood.
37

Figure 14. Map of overall wildfire risk to the study region as perceived by Clackamas County (Clackamas County, 

Oregon, 2005). 
38

Figure 15. Wildfire-hazard risk within the study area, Clackamas County, Oregon. A, total area; B, among homes; 

C, among businesses; and D, among employees. Percentages are based on 5,711 homes and 323 businesses 

in the study area. The number of homes and businesses in each category are in parentheses. 
39

Figure 16. Wildfire-hazard risk to employees by business sector, Clackamas County, Oregon. 
40

Figure 17. Wildfire-hazard risk among seasonal population groups, Clackamas County, Oregon. A, average 

monthly attendance by season, among resident dependents, at educational facilities; B, average monthly 

attendance by season, among overnight visitors, at lodging accommodations; and C, average monthly 

attendance by season, among residents and tourists, at day-use recreational areas and facilities. Daily 

attendance numbers are essentially equivalent to the monthly values in chart A, but are estimated in charts B

and C by dividing seasonal monthly averages by 30. 
41

Figure 18. Map of volcano hazard zones for the study region (derived from Scott and others, 1997b), Clackamas 

County, Oregon. Three different hazard zone types are noted: (1) a proximal hazard zone, (2) a distal lahar 

hazard zone for a typical eruption event, and (3) an extended distal lahar hazard zone for a worst-case 

scenario event. Crater Rock, the remnant of a previously erupted lava dome and an area of active volcanic 

fumaroles, is labeled on Mount Hood.

 
42

Figure 19. Effect of Mount Hood’s topographic profile on potential distance traveled by a pyroclastic flow and ashcloud surge (modified from Brantley and Scott, 1993), Clackamas County, Oregon. Diagram depicts a 

hypothetical maximum flow generated by collapse of a substantial lava dome at Crater Rock. A flow of this size 

would take less than 30 minutes to reach its maximum extent. However, such an event likely would be 

preceeded by indicators of volcanic unrest that would be detected by U.S. Geological Survey monitoring 

(William Scott, oral communication, June 2012. 
43

Figure 20. Volcano hazard exposure among A, homes, B, businesses, and C, employees, in the study area, 

Clackamas County, Oregon. Values for a worst-case scenario lahar event are read as additions to the 

exposure calculated for a typical event. Calculations are based on a total of 5,711 homes, 323 businesses, and 

3,149 employees.
44

Figure 21. Volcano hazard exposure to employees by business sector, Clackasmas County, Oregon. Presented 

are two types of hazard categories (proximal and distal) and two levels of events (typical eruption and worstcase scenario) influencing the distal hazards; values for a worst-case scenario lahar event are read as 

additions to the exposure calculated for a typical event. 
45

Figure 22. Volcano-hazard exposure among seasonal population groups, Clackamas County, Oregon. A, average 

monthly attendance by season, among resident dependents, at educational facilities; B, average monthly 

attendance by season, among overnight visitors, at lodging accommodations; and C, average monthly 

attendance by season, among residents and tourists, at day-use recreational areas and facilities. Daily 

attendance numbers in chart A are essentially equivalent to the monthly values, but can be estimated in charts 

B and C by dividing seasonal monthly averages by 30. Proximal-hazard exposure remains the same regardless 

of event magnitude, and the difference in population exposure between event magnitudes among distal 

hazards is generally negligible.

 
46

Appendix A

The North American Classification System (NAICS) is used to categorize economic activity in 

Canada, Mexico, and the United States. Of the entire eight-digit code used by NAICS, the first two 

digits denote a business sector. The following chart provides descriptions for each business sector 

recognized within this study. 

Sector 

number Description

11 Agriculture, forestry, fishing, and hunting

22 Utilities

23 Construction

31-33 Manufacturing

42 Wholesale trade

44-45 Retail trade

48-49 Transportation and warehousing

51 Information

52 Finance and insurance

53 Real estate and rental and leasing

54 Professional, scientific, and technical services

56 Administrative and support and waste management and remediation services

61 Education services

61 Health care and social assistance

71 Arts, entertainment, and recreation

72 Accommodation and food services

81 Other services (except public administration)

92 Public administration
47

Appendix B

Master data table of hazard exposure among resident and employee population groups, 

Clackamas County, Oregon. 

Hazard Exposure Households Residents Businesses Employees Sales Volume

# % # % # % # % # %

Study Area Total 5,711 100 10,600 100 323 100 3,149 100 $361,296,000 100 

Flood

100-year 381 7 717 7 7 2 6 <1 $1,408,000 <1

500-year 537 10 960 9 15 4 36 1 $18,771,000 5 

Wildfire

High 36 1 74 1 2 1 26 1 $4,464,000 1

Moderate-to-high 907 16 1,846 17 44 14 1,597 51 $115,692,000 32

Moderate 3,066 53 5,742 54 91 28 311 10 $63,398,000 18

Low-to-moderate 732 13 1,449 14 79 24 595 19 $97,705,000 27

Low 970 17 1,489 14 107 33 620 20 $80,037,000 22 

Volcano

Proximal hazards 1,315 23 1,501 14 104 32 2,041 65 $166,533,000 46

Distal hazard (typical 

scenario) 2,047 36 3,834 36 99 31 617 20 $87,907,000 24 

Distal hazard (worstcase scenario) 2,550 45 4,889 46 133 41 708 22 $100,300,000 28 

Total hazards (typical 

scenario ) 3,362 59 5,335 50 203 63 2,658 84 $254,440,000 70 

Total hazards (worstcase scenario) 3,865 68 6,390 60 237 73 2,749 87 $266,833,000 74 
48

Appendix C

Master data table of hazard exposure among service populations, Clackamas County, Oregon. 

Hazard Exposure Winter Spring Summer Fall

Resident dependents at educational facilities

Wildfire

High 0 0 0 0

Moderate-to-high 0 0 0 0

Moderate 123 123 93 123

Low-to-moderate 623 623 0 623

Low 266 266 0 266

Grand total 1,012 1,012 93 1,012

Volcano

Proximal hazards 549 549 93 549

Distal hazard (typical) 0 0 0 0

Distal hazard (worst-case) 0 0 0 0

Grand total (typical) 549 549 93 549

Grand total (worst-case) 549 549 93 549

Overnight visitors

Wildfire

High 15 1 80 1

Moderate-to-high 6,882 4,783 6,677 3,456

Moderate 1,313 1,065 2,908 676

Low-to-moderate 6,493 3,205 12,918 3,336

Low 5,673 3,303 10,982 3,525

Grand total 20,376 12,357 33,565 10,994

Volcano

Proximal hazards 13,912 5,844 21,992 3,807

Distal hazard (typical) 5,918 6,045 10,750 6,589

Distal hazard (worst-case) 6,464 6,513 11,573 7,187

Grand total (typical) 19,830 11,889 32,742 10,396

Grand total (worst-case) 20,376 12,357 33,565 10,994

Daytime visitors to recreation sites

Wildfire

High 0 94 6,770 2,281

Moderate-to-high 49,658 32,434 29,264 3,626

Moderate 0 9,205 21,529 9,894

Low-to-moderate 78,905 21,616 38,520 10,041

Low 700 617 2,635 742

Grand total 129,263 63,966 98,718 26,584

Volcano

Proximal hazards 128,813 54,664 76,809 17,068

Distal hazard (typical) 450 8,188 17,057 8,286

Distal hazard (worst-case) 450 8,200 17,107 8,318

Grand total (typical) 129,263 62,852 93,866 25,354

Grand total (worst-case) 129,263 62,864 93,916 25,386