Visitation Forecasting and Predicting Use of

NPS Parks and Visitor Centers:

Focus Group Report

James H. Gramann

Visiting Chief Social Scientist

National Park Service Social Science Program

August 2003

NPS SOCIAL SCIENCE PROGRAM
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 2

Executive Summary

On March 12, 2003 a focus group organized by the NPS Park Planning and Special Studies Program and

the NPS Social Science Program met at Turkey Run Park on the George Washington Memorial Parkway.

The purpose of the meeting was to assist the NPS in planning visitor centers and related projects that

are cost-effective and of appropriate scope and size. The focus group provided information on trends

in visitation forecasting and recreation and tourism demand modeling that could inform the planning

and design of visitor centers and other park facilities. 

Group participants discussed ways in which qualitative and quantitative approaches to forecasting

population change and participation in recreation and tourism activities could be applied to predict use

of parks and visitor centers up to 20 years into the future. Key points from the discussion include:

C Little change has occurred in the past 50 years in the fundamental approaches to population

forecasting; however, the data used in forecasting models has been refined. For example,

information on race and ethnicity has become more detailed, and forecasting population change

can be done for smaller geographic areas due to developments in GIS and related databases.

C For projections of visitation two to three years into the future, trend line extensions often work

well and can be locality-specific.

C Qualitative methods are best for long-term forecasts of park or visitor center use. One approach

is to develop alternative scenarios on a large scale, e.g., based on lifestyle or environmental

changes, and consider how these might affect visitation in the future. Delphi panels and crossimpact simulations are two methods for doing this.

C In long-term forecasting and planning, one strategy is to work actively to shape the future,

rather than wait for it to occur. For example, in “normative forecasting” a desirable future

condition is defined and the sequence of steps to achieve it described.

C The amount of visitation a site receives can be influenced by marketing; this will determine the

number of visitors to a location more than demographics will.

C The most important key to forecasting park visitation and use of visitor facilities is continuous

research that tracks trends in who visitors are and correlates these with factors known to affect

visitation and facility use.
1

NPS internal discussion paper, “General management plans and visitor facilities,” December 7, 2001.

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 3

Visitation Forecasting and Predicting Use of 

NPS Parks and Visitor Centers:

Focus Group Report

James H. Gramann

Visiting Chief Social Scientist

National Park Service Social Science Program

Introduction

This report describes the results of a focus group conducted for the Park Planning and Special Studies

Program of the National Park Service (NPS). The purpose of the focus group was to assist the NPS in

planning visitor centers and related projects that are cost-effective and of appropriate scope and size.

More specifically, the focus group provided information on the state of the art in visitation forecasting

and demand modeling related to recreation, heritage tourism, and the use of associated visitor facilities

in the National Park System.

Background

The House Appropriations Committee Report for FY 2002 expressed concern about the cost and size

of proposed visitor centers, heritage centers, and environmental education centers in some national

parks.1

 The committee asserted that several recent proposals for visitor facilities were unacceptable

because they were predicated on unrealistic increases in visitation and staff. These concerns were

repeated in the conference committee report, specifically asserting that NPS General Management Plans

(GMPs) tended to include oversized buildings and other projects that were not essential to the missions

of the parks.

According to a review by the NPS, plans that appear to have attracted the committee’s attention were

those for parks with relatively small annual visitation coupled with what seemed to be costly new visitor

facilities. Examples included Homestead National Monument, Grand Portage National Monument, and

Washita National Battlefield. In response, the NPS Park Planning and Special Studies Program developed

a series of actions that could be taken to examine the committee’s concerns. Two of these were:

C Analyze the role of visitor facilities in light of the NPS mission, emerging technologies, and

changing functions in education, interpretation, and orientation.

C Evaluate the accuracy of past visitation projections in GMPs, and prepare guidelines on effective

visitation forecasting methodologies.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 4

Figure 1 Visitation-forecasting focus group, Turkey

Run Park, March 12, 2003.

The focus group described in this report is one measure taken to address the second of these two

actions. A separate report, “Trends in Demographic and Information Technology Affecting Visitor

Center Use,” addresses the first action.

Focus-group Planning

The focus group on visitation forecasting was organized in consultation with a professional facilitator

experienced in NPS planning issues. Participants in the focus group were identified by the NPS Visiting

Chief Social Scientist with the approval of the Chief of Planning. Those recruited either had national

reputations for their work in population forecasting and demand modeling, or were recommended by

such individuals. 

Population forecasters employ qualitative and quantitative techniques to predict population changes in

a region. The qualitative methods used in population forecasting directly incorporate human judgment

into projections, while the quantitative methods employ mathematical models. The focus group included

experts in population forecasting because change in the regional population around a park is one driver

of visitation. The second group of participants were those with expertise in recreation and tourism

demand modeling. Demand modelers use statistical methods to describe which types of residents in a

region’s population tend to be park-goers and participate in particular recreation activities. (See the

appendix for a list of participants.)

Method

The visitation-forecasting focus group met at

Turkey Run Park on the George Washington

Memorial Parkway on March 12, 2003.

Members were sent a detailed guide before

the meeting which included an agenda and a

list of questions to be discussed. During the

session, the facilitator led the participants

through the guide, focusing on each question

in turn. Participants were asked to consider

forecasting up to 20 years into the future, the

time frame typical of a park’s GMP. The

overall approach was to begin with broad

trends and developments in regional

forecasting and demand modeling and then

turn to the problem of visitation forecasting at a smaller spatial scale, i.e., parks and facilities within

parks. To help direct the latter discussion, participants visited Great Falls Park, a nearby NPS unit in

northern Virginia. This visit included an evaluation of the park’s visitor center and a discussion with

park staff about current visitation and use of park facilities.
2

Billson, J.M. 2003. The power of focus groups - A training manual. Barrington, RI: Skywood Press.

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 5

Figure 2 Visitation-forecasting focus group.

Comments made by participants during the focus group were recorded on flip charts. In line with the

facilitator’s preference, no other recording method was used. 

Following the group discussion, the facilitator compiled the comments. These were reviewed by the

Social Science Program and the Park Planning and Special Studies Program. In addition, the notes were

sent to all participants for their review. Clarifications were incorporated into the notes. Additional

comments were recorded separately.

It is important to understand what focus groups can and cannot do. Focus groups do not provide

comprehensive information on a subject, such

as visitation forecasting or demand modeling.

Other review methods are more suited to that

task. Nor are focus groups designed to help a

group reach a consensus or make decisions.

Instead, focus groups elicit the full range of

participants’ ideas, experiences, and opinions

on a selected topic.2 Through facilitated,

focused interaction, members provide a wealth

of qualitative data not typically available from

surveys, and group members stimulate each

other with an exchange of ideas not possible in

individual interviews.

Presentation of Results

The results of the visitation-forecasting focus group are presented in three sections:

C State of the art in forecasting population change and modeling recreation and heritage tourism

demand.

C Implications of the state of the art for predicting use of NPS parks and visitor centers.

C General implications for the NPS.

Each of the sections is prefaced with a synopsis of principal questions asked during the discussion.

Following this, sub- topics are introduced with bold- faced titles, and brief background paragraphs place

the participants’ discussion in the larger context of forecasting and modeling. Specific comments are

then detailed in bullet statements drawn from the facilitator’s notes. This allows for a broad synthesis

of the discussion, while also preserving insights of focus-group participants that illustrate the synthesis.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 6

State of the Art in Forecasting Population Change and Modeling Recreation

and Heritage Tourism Demand

Synopsis

Important trends and new developments in forecasting population change and change in recreation and

heritage tourism activity:

C There have been few new developments in population forecasting in the last 50 years.

Ways population change can be forecast effectively:

C When forecasting population change, three sub-populations are relevant: permanent residents,

seasonal residents, and transients.

C Forecasting population change at smaller spatial scales, such as states and counties, presents

more problems than forecasting at a national level. 

Ways recreation organizations can effectively forecast visitation or tourism and recreation activity:

C For projections two to three years into the future, time-series or trend line extensions usually

work well and can be locality-specific.

C For long-term projections, qualitative forecasting methods are often more appropriate than

quantitative ones.

C The type of area and facility visited must be considered in projecting visitation.

C When forecasting participation in recreation activities (rather than visits to locations),

projections based on demographic change have been of limited accuracy. 

C The Army Corps of Engineers is looking at spatial trends in visitation and analyzing them with

respect to demographic trends.

C The gap between site- specific forecasts and national forecasts could be reduced if more

information were collected regularly from visitors.

C Blips in recreation and tourism participation can be forecast if their causes are known.

C The tourism industry through the Travel Industry Association uses county-level data in

projecting tourism demand and arrivals at travel destinations.

Ways use of a single facility can be effectively forecast:

C For facilities with a history of use, changes in ease of access, in the market for the facility, and

in the mix of products offered by it can all affect future use and should be considered in

forecasts.

C For new facilities without a previous history of use, both qualitative and quantitative

comparisons with similar facilities can be used to forecast visitation.

Other ways to forecast visitation not linked to population forecasts:

C Surveys of travel intentions, trends in recreation equipment sales, and projections of community

growth patterns are all used to predict tourism travel and recreation participation.

What Are Some of the Important Trends and New Developments in Forecasting Population

Change and Change in Recreation and Heritage Tourism Activity?

The focus group opened with a discussion of current trends in population forecasting and recreation

and tourism demand modeling. This was done because most visits to NPS units occur in the context of
3

US Department of Transportation. (2001). Population forecasting methods: A report on estimating and

forecasting methods. http://tmip.fhwa.dot.gov/clearinghouse/docs/landuse/pfm/ch1.stm

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 7

Forecasting can be done for smaller and

smaller areas. Because of GIS and new

databases, geographic detail is more precise.

recreational outings, including heritage tourism. Focus- group members discussed both population

forecasting and estimates. Forecasts are projections of change into the future. Estimates are informed

appraisals of current (or past) populations in the absence of actual counts.

There have been few new developments in population forecasting in the last 50 years:

C Little change has occurred in how population estimators think about forecasting. However, there

has been some refinement of the data used for forecasting and estimating population.

C The US Census Bureau cooperates with the Internal Revenue Service and with Medicare, which

has helped it refine its data, but this doesn’t represent change in the underlying way forecasts

and estimates are calculated.

C Data on race has become more detailed – population forecasts are being made for an increasing

number of racial and ethnic categories.

C Forecasting can be done for smaller and

smaller areas. Because of GIS and new

databases, geographic detail is more

precise.

C The frequency of population estimates is

also increasing. The Census Bureau is now

redoing its estimates every two years. In retail and commerce, estimates of the size and

characteristics of market populations are redone annually.

In What Ways Can Population Change Be Forecast Effectively?

Three demographic factors affect whether the population of an area increases, decreases, or remains

stable over time. These are fertility rate, mortality rate, and migration in and out of the region (net

migration).3

 Population forecasts start with the current number of people living in an area, then project

fertility, mortality, and net migration rates to arrive at a future population. The US Census Bureau

projects the size and composition of the US population 100 years into the future using high-, low-, and

mid- range forecasts. These variants incorporate different assumptions about changes in birth, death,

and migration rates. In most cases, fertility and mortality rates are relatively predictable, especially over

the short or medium term. Net migration is less so and tends to be influenced by factors not considered

in demographic forecasting models, such as seasonal cycles, economic fluctuations, and geopolitical

factors that influence the movement of populations. Migration can be permanent or seasonal. Seasonal

migration is characteristic of campus communities, retirement counties, and recreation- dependent

regions, including those surrounding many NPS units. Focus- group participants commented on the

current state of the art in population forecasting, and on the challenge of doing usable state- and

county-level projections of populations.
4

Johnson, K. & Beale, C. 2002. Nonmetro recreation counties – Their identification and rapid growth.

Rural America 17(4):12-19.

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 8

Figure 3. Non-metropolitan recreation counties in the US (Johnson

and Beale, op. cit.).

When forecasting population change, three sub-populations are relevant: permanent residents, seasonal

residents, and transients (i.e., people who don’t live either temporarily or permanently in an area):

C For the resident population, census data provides a good basis for projections.

C The Census Bureau has not done a good job of counting seasonal and transient populations, but

this is changing for seasonal residents. The Census Bureau’s American Community Survey is a

new canvassing of 3 million households per year. The 2003 survey includes a question asking if

residents are staying at their address because it is a seasonal or vacation address.

C Internal migration (population movement within the boundaries of a nation or region) is the

biggest component of population change, but predicting migration rates is the weakest link in

population forecasting. However, if it were known, the number of seasonal residents could be

a good predictor of migration rates in many areas.

C The smallest practicable unit for considering migration in population forecasts is the county or

metropolitan area. Below this, migration cannot be factored in as well.

C One way to characterize areas at the county level is by migration patterns. Counties in which

recreation or tourism are important to the economy can be identified by their migration

patterns. Maps exist showing recreation and tourism- dependent counties in the nonmetropolitan US (Figure 3).4
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 9

Forecasting population change at smaller spatial scales, such as states and counties, presents more problems

than forecasting at a national level:

C The Census Bureau produces state population projections and does a good job where population

is changing slowly. States with explosive growth (e.g., Nevada) are more difficult to forecast.

C One problem with state-level Census Bureau projections is that the approach is purely

demographic, e.g., based on birth rates, death rates, and net migration rates. No effort is made

to incorporate the influence of economic swings on population change.

C The Census Bureau does not project population change at the county level. This is left to the

individual states. Therefore, the method of forecasting at the county level is not standardized.

C Each state has a data center that works cooperatively with the Census Bureau to do county-level

forecasts and other population analyses. Individual state demographers are more familiar with

their states than is the Census Bureau.

C Commercially produced population estimates and projections are available. Woods and Poole

and NPA Data Services use similar methods, combining economic data from the Bureau of

Economic Analysis with a population- cohort model. These include estimates and projections

down to the county and metropolitan level, but few analysts are working on them.

In What Ways Can Recreation Organizations Effectively Forecast Visitation or Tourism and

Recreation Activity?

For visitation forecasts two to three years ahead, simple trend line extensions often work well. However,

in long-term forecasting, qualitative approaches based on expert judgement, or a combination of

judgment and quantitative methods, is more appropriate. A factor that is often ignored in forecasting

is the power of marketing to influence consumer choice. The future does not simply happen; in many

cases it can be influenced toward specific end-goals by marketing and education. More attention has

been given to forecasting participation in different recreation activities than to forecasting visits to

specific locations. For example, modeling activity participation and forecasting future participation

based on the demographic characteristics is a major component of many statewide comprehensive

outdoor recreation plans. However, the explanatory power of demographic models is usually low, rarely

accounting for more than 30 percent of the variance in current participation, making their utility for

long-term forecasts questionable. One area in which locality-based forecasts are made is tourism

demand modeling, where travel to specific destinations is predicted based on such factors as surveys of

travel intentions, population size at points of origin, distance to destinations, destination attractiveness,

and macro-economic trends. Even in this case, projections vary in their accuracy, with short- term

forecasts generally being more accurate than long-term predictions of visitor behavior.

For projections two to three years into the future, time- series or trend line extensions usually work well

and can be locality-specific:

C Trend-line extensions can show good short-term forecasts if visitation data is captured

regularly.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 10

Two- or three-year forecasts off a timeseries trend often work well and can be

done at the park or facility level.

C Two- or three-year forecasts off a time-series trend often work well and can be done at the park

or facility level. However, it is risky to push this kind of forecast out to 20 years. The confidence

level is very low.

C In time- series data, sometimes the total use

is stable, but the mix of users changes. Timeseries projections are for the number of

visitors, not the mix, so they don’t predict

changes in the composition of the visitor

population.

For long-term projections, qualitative forecasting methods based on expert judgment are often more

appropriate than quantitative ones:

C One qualitative approach to long- term forecasting is to develop future scenarios on a large scale,

e.g., based on lifestyle or environmental changes, and consider how these might affect visitation.

A Delphi panel could be used to assess which of the scenarios are most likely. 

C For long-term forecasts it’s best to look ahead at five- or ten-year intervals.

C One problem with qualitative forecasting is that often the participants are processing the same

information, but the world is always changing. Good qualitative approaches involve people with

a wide range of expertise and knowledge.

C Some approaches to long- term forecasting, such as cross- impact simulation, quantify expert

judgments about important trends and how the elements of a system interact. These simulation

models can be used to perform policy experiments that evaluate what happens when a chosen

action ripples through the system.

The type of area and facility visited must be considered in projecting visitation:

C Facilities that are designed for repeat visitors will be affected differently by changes in the local

population than facilities that are designed for one- time visitors or those who travel from distant

origin points.

C Non-local use of a facility is generally higher if it is located near a major interstate. For example,

Corps of Engineers campgrounds near an interstate receive a lot of non-local use.

C Ideally, several projection models would be developed based on site characteristics: one for

urban vs. rural sites, a site-age model, and models distinguishing other characteristics of sites,

such as size and types of facilities.

When forecasting participation in recreation activities (rather than visits to locations), projections based

on demographic change have been of limited accuracy: 

C The traditional approach to forecasting recreation demand is to take population data and

establish a visitation or participation rate, assuming that if the population doubles then the

visitation or participation will double.

C This approach can be refined by breaking the population down into different cohorts based on

demographic characteristics, such as age or race, and projecting separately for each cohort.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 11

The amount of use a site receives can be

affected by marketing; promotion and

pricing influence participation and visitor

numbers more than demographics do.

C However, one reason forecasts of recreation and tourism demand based on demographic change

don’t work well is that participation rates in some activities are so small that it leads to too much

error in the process. When participation rates are two percent plus or minus two percent,

forecasts can’t be very accurate.

C Another reason for the limited success of demographic- based projections is that the relationship

between demographic characteristics and activity-participation rates may not remain constant,

especially over the long-term.

C When predicting visits to specific locations,

another limitation of standard forecasting

techniques is that, although it is known

which demographic groups are most likely to

participate in many activities, this data is not

site-specific.

C A final shortcoming of standard recreation

demand projections is that the amount of use a site receives can be affected by marketing;

promotion and pricing influence participation and visitor numbers more than demographics do.

The Army Corps of Engineers is looking at spatial trends in visitation and analyzing them with respect to

demographic trends:

C Nationally, visitation to Corps lakes has been flat for the last ten to 12 years, but within the 456

water projects, visitation trends are highly variable. There is huge spatial variability between

sites, which affects trends in the use of those sites.

C The Corps of Engineers needs more spatially explicit information to better account for changes

in visits at the project level. It also needs to know the extent to which demographic variability

and spatial variability interact to influence visitation to locations.

C The Corps sees this interaction in the case of minority recreation use. In areas where there are

increases in the Latino population, there are also increases in Latino recreational use. 

C There is a lot of internal migration by the US Latino population, and this is affecting use of Corps

of Engineers lakes. In 1980, one-quarter of Corps projects were used by Latinos. In 2003, all are.

C If increases in the Asian population in the US are mapped, the areas of increase coincide with

upswings in Asian visitation to Corps recreation areas.

C It’s possible that the same interaction of space and demographics holds in the case of age, but

the Corps has yet to evaluate those numbers.

The gap between site-specific forecasts and national forecasts could be reduced if more information were

collected regularly from visitors:

C Recreation management agencies need five basic pieces of information that should be asked

regularly of visitors: ZIP code, persons-per-vehicle, length of stay in the area, whether there is

an overnight stay, and lodging type.
5

ESRI. 2002. The sourcebook of ZIP code demographics. ESRI Press, Redlands, CA.

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 12

Using ZIP codes a wealth, of additional

demographic and lifestyle information

about visitors can be profiled at useful

levels of accuracy.

C Using ZIP codes, a wealth of additional

demographic and lifestyle information about

visitors can be profiled at useful levels of

accuracy. For example, ESRI5

 publishes

descriptive profiles and five- year projections

of the population for every residential and

non-residential ZIP code in the US.

C There are passive ways to get information about visitors without questioning them. Vehicles can

be observed to record party size, gender, race, approximate age, and vehicle model.

C License plates can be converted to ZIP codes, although there is a charge for such a service, and

in some states it’s very expensive. Also, because of privacy concerns, the trend over the last ten

years has been to restrict access to that data. In some recreation areas the utility of license plate

data is limited by the high percentage of visitors driving rental vehicles.

C The Army Corps of Engineers and the US Forest Service use the National Recreation Reservation

Service for campground reservations. This is a source of additional data about visitors. The NPS

is joining this service, but one problem with using reservation data to describe visitors is that

reservations don’t necessarily translate into visits.

C The Corps of Engineers is also beginning to ask visitors about camping experiences and activity

participation.

C Recreation.gov is the online recreation portal for the federal government. Potentially, people

who query the site for information could be sampled with a Web-based survey to find out who

they are and the types of recreation areas and activities they prefer. However, there are problems

in identifying Web-site users in ways that don’t violate federal privacy protections.

Blips in recreation and tourism participation can be forecast if their causes are known:

C There are both negative blips, such as September 11th, and positive blips, such as special events.

C Visitation at special events can be forecast, looking at the market for the event, similar events,

and the amount of promotion. Along with use, the economic impact of events can be predicted.

C Changes in gasoline prices and gasoline availability have created blips in travel, but this

phenomenon may not continue if people become conditioned to higher prices.

C There are other predictable blips every year tied to season, holidays, and recurring events.

C The visibility of a place or the publicity it receives is an important factor that can create blips.

For example, when a site is used as a location in a major motion picture it frequently experiences

a subsequent increase in tourism.

The tourism industry through the Travel Industry Association (TIA) uses county-level data in projecting

tourism demand and arrivals at travel destinations:

C The TIA methodology is high-quality, with good inputs, including age, sex, and race. The

forecasting model is re-calibrated at every census. 
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 13

C The TIA forecasts are made with a proprietary model that incorporates macro- economic trends,

trend data from a panel of American households, and periodic surveys of travel intentions.

C At the national level the tourism industry does a good job analyzing projected vs. actual demand,

comparing where people went with where they thought they’d go.

In What Ways Can Use of a Single Facility Be Effectively Forecast?

Because forecasting is more reliable at large spatial scales and over short time periods, doing long-term

visitation forecasts for a single visitor center presents many challenges. A further complication is that

predicting use of an existing facility differs from predicting visitation to a new facility. In the second case,

there are no previous visitor statistics to analyze or trend lines to extend. In long-term projections, an

alternative approach to predicting visitation and waiting to see if the forecast is correct is to practice

“normative forecasting.” Using this approach, a desired future condition is set and the sequence of steps

to achieve it is laid out. Normative forecasting has been popular in the defense and space communities.

One example was the plan to put a man on the moon by the end of the 1960s.

For facilities with a history of use, changes in ease of access, in the market for a facility, and in the mix of

products offered by it can all affect future use and should be considered in forecasts:

C To effectively forecast, it’s important to understand the current market for the facility and the

segments that make it up. Forecasting changes in the segments can help predict future visitation.

C Some providers, such as Disney, are very good at marketing for local residents. Looking 20 years

into the future, this is one way to go: build the facility and promote it to the local population

using lecture series and other activities as attractions. In this way, at least a portion of future use

is predictable because it is controlled by the park. 

C One problem with projecting visitor center use is that, for a resource- based area, the visitor

center is not the attraction; it is the resource itself that draws visitors.

C Changes in pricing and maintenance level are other factors affecting visits to existing facilities.

For new facilities without a previous history of use, both quantitative and qualitative comparisons with

similar facilities can be employed to forecast visitation:

C A multiple regression model can be constructed using variables that predict use at similar

existing facilities. One model can be developed from visitation at several existing sites, but the

inputs have to be consistent across all sites. 

C As predictors, it is important to use measures for which good data exists and which also

significantly affect facility visitation. Population within 500 miles, square footage of the visitor

center, and average distance traveled are examples of predictors in multiple regression models.

C Forecasting models must be refined over time. This requires an active tracking program in which

visitation and the inputs affecting it are monitored continually. 

C In the future, access to many types of personal data may be increasingly restricted by privacy

concerns. This could affect the ability of the NPS to track the characteristics of visitors and nonvisitors.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 14

In long-term forecasting and planning,

the NPS could work actively to shape the

future, rather than wait for it to occur.

C When forecasting visits to a specific location or facility, existing substitute sites are important

to consider because they compete for visitors with new facilities. But substitutes are one of the

most difficult variables to incorporate into quantitative forecasting models. An alternative

approach is to employ a measure of the new facility’s uniqueness.

C In long-term forecasting and planning, the

NPS could work actively to shape the future,

rather than wait for it to occur. This is 

“normative forecasting,” i.e., setting a goal

then systematically laying out the sequence of

steps needed to reach it.

C It is desirable to use both qualitative and

quantitative approaches to forecasting the use of new facilities. In a qualitative approach, the

NPS could look at similar existing facilities and their use patterns when they were opened.

Employing a quantitative approach, data on factors affecting visits at similar facilities could be

collected and input into a multiple regression model to forecast visitation to the new facility.

Are There Other Ways to Forecast Visitation that Are Not Linked to Population Forecasts?

Focus-group members discussed several approaches to forecasting that do not rely on applying

participation rates to changes in population or to the market segments within a population. 

Surveys of travel intentions, trends in recreation equipment sales, and projections of community growth

patterns are all used to predict tourism travel and recreation participation:

C Surveys of travel intentions can be reliable predictors of actual behavior in the short- term if

there is no major event that causes intentions to change on a large scale.

C The Travel Industry Association (http://www.tia.org/Travel/) estimates US resident domestic

pleasure travel volumes by season (fall, winter, spring, and summer). The forecasts are based on

a proprietary forecasting model that includes as inputs a survey of US adults’ intentions to travel

in the upcoming season, as well as macro-economic trends and historical travel survey data.

C Economic data, such as recreational equipment sales and license sales, can be used to show the

number of hunters, anglers, and boaters in an area and trends in those numbers over time.

C Local communities and major developments such as Disney World map long- term build- out

(i.e., development potential). This could help forecast use of parks and recreation facilities that

draw their visitors primarily from local populations.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 15

Figure 4 Visitor center, Great Falls Park.

Implications of the State of the Art for Predicting Use of NPS Parks and

Visitor Centers

Synopsis

Feasibility of predicting use of the Great Falls Park visitor center 20 years into the future:

C Forecasting use of Great Falls Park visitor center should be a straightforward task due to the

park’s capacity constraints and the location of its visitor center with respect to traffic flow.

Ways to strengthen the NPS methodology for gathering and reporting annual visitation to parks:

C The current NPS method for counting visits is workable and cost-effective; however, it doesn’t

meet the need to know who visitors are.

C Tracking data describing visitor populations and how they are changing is critical to many

planning and management functions.

C Similar to visitor characteristics, the characteristics of parks change over time and need to be

monitored in order to make accurate forecasts of park and facility use.

Feasibility of forecasting use of different types of NPS visitor centers 20 years into the future:

C One approach to forecasting use of a visitor facility is to start with visitation to the park, then

make the necessary conversions to determine use of the facility.

C Sometimes visitor centers are located outside parks, or there may be no consistent relationship

between park use and use of the visitor center. In these cases, other approaches to forecasting

must be employed.

How the NPS should forecast visitation and predict use of parks and visitor centers 20 years from now:

C The NPS should have a better understanding of who its visitors are.

C The NPS should upgrade the quality of the visitor data it collects, the way it organizes to gather

that information, and the way it delivers that data to managers and other customers.

How Feasible Is It to Predict Use of the

Great Falls Park Visitor Center 20 Years

into the Future?

The approach taken by focus-group

members to forecasting use of the Great

Falls Park visitor center is illustrative of the

reasoning that could be applied to

predicting visits to many existing facilities.

Group members felt that projecting future

use at the Great Falls Park facility would be

relatively easy, given that the park already

appears near its visitor capacity. This

capacity could be increased, but forecasting

would still be feasible because the strategies

to increase visitor capacity are themselves

controllable and predictable.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 16

Figure 5 Parking lot, Great Falls Park.

Forecasting use of Great Falls Park visitor center should be a straightforward task due to the park’s

capacity constraints and the location of its visitor center with respect to traffic flow:

C Because the Great Falls Park visitor center is situated between the parking lot and the park’s

attractions, predicting use of the facility

is easy. This will continue to be the case

as long as the design is not changed. 

C Use of Great Falls Park is primarily a

function of parking spaces, which fill up

on nice weekends. The only

opportunity to significantly increase use

is during the week.

C A capacity factor limiting visitation to

Great Falls Park is that people will turn

away if the queues at the entrance

station are too long. Most people will

not wait 2 1⁄2 hours to see the falls and

have a picnic.

C But one trend that might increase visits

is the growing number of retirees in the

area. Retirees have more flexibility with their time, which could result in more visitation during

the week, a period of under-used capacity.

C Another way to increase visitor capacity would be to redirect people to under- used areas of

Great Falls Park. If this were done, the park could do another forecast taking these changes into

account. However, is it desirable to increase the park’s visitor capacity? The lesser- used days

give the park’s resources and staff an opportunity to recover.

C Use of the park’s visitor center could also be increased by marketing, e.g., promoting programs

for local school children. But this still leads to accurate forecasting because the promotion can

be controlled by the park.

C An important constraint on forecasting use of the visitor center is that the park lacks recent data

describing who its visitors are. This means that demographic cohorts cannot be identified in the

population who visit the park. Thus, projection models cannot be cohort-based.

How Can the NPS Methodology for Gathering and Reporting Annual Visitation to Parks Be

Strengthened?

To forecast visitation to a park (or facilities in a park) current visitation must be known, as well as

historical visitation patterns. Thus, a reliable, continuous method for counting visitors is indispensable

to forecasting. The focus group reviewed the current methods used by the NPS to count visitors, which

are based largely on traffic counters, and offered several comments on their strengths and shortcomings.

The most important weakness is that traffic counts tell parks nothing about the composition of their

visitor populations.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 17

An ongoing visitor survey is needed in all

parks, tracking activities, where visitors

come from, the reasons for their visits,

their demographic characteristics, and

whether or not they use a visitor center.

The current NPS method for counting visits is workable and cost-effective; however, it doesn’t meet the need

to know who visitors are:

C Party size estimates are updated on an

irregular basis. Generally, party sizes are

decreasing, so caution must be used when

doing time-series analyses of visitation data.

C An ongoing visitor survey is needed in all

parks, tracking activities, where visitors

come from, the reasons for their visits, their

demographic characteristics, and whether or

not they use a visitor center. Visitor center

characteristics should be measured as part of the tracking system.

C An ideal visitor-tracking process would sort out the monitoring data needed for visitor

forecasting from the data required for a more comprehensive market survey every five to ten

years.

C Traffic counters are not the optimal way to measure visitation. There are re-entry problems and

maintenance problems with the equipment. A tremendous amount of research is needed behind

the scenes to compute conversion factors, and traffic counters are still not a good way to count.

C Sales receipts are a another way to track use of a visitor center. Conversion factors could be

developed that are applied to the number of transactions or the total dollar amount.

C Fee collection works well as a way to count visits in some parks. Cave tour fees at Carlsbad

Caverns National Park are one example.

C A problem with using entrance-fee collection as a way to count visitors is that there may be little

correlation between entrance fees paid and the number of visits. Visitors can use a pass, with one

pass representing one visit or 150 visits.

C The US Forest Service is encountering problems with counting visits in situations where one fee

pays for use of multiple forests. This could be a problem in the NPS as well, e.g., at YellowstoneGrand Teton national parks.

Tracking data describing visitor populations and how they are changing is critical to many planning and

management functions, including forecasting:

C In developing a new way to measure visitation, the initial goal of the US Forest Service was to

come up with visitation forecasts and counts that were defensible before Congress. But the

agency now realizes that the value added from understanding who its visitors are will drive the

future of the Forest Service.

C The NPS has also found that it’s useful to know the basic demographics of visitors, even if this

information is not used for forecasting. For many reasons, it’s also important to understand the

customer base at different types of parks, e.g., urban parks vs. rural parks.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 18

Since 1987, NPS visitation has been flat or

decreasing. Is this because visitor capacity

has been reached in some parks? The NPS

needs to know this to do accurate

forecasting.

C To improve visitation forecasts, research is needed on the stability of the relationship between

demographic characteristics and the probability of visiting parks. Some demographic groups are

more likely to be park- goers than others, but patterns change over generations. Also, differences

in visitation rates between racial groups diminish with increasing education.

C What is counted and how it’s counted depends on what question needs an answer. The number

of nights visitors spend in an area is useful for economic impact analyses, but the number of

hours visitors spend in a park is useful for staffing and maintenance.

C Market research helps evaluate the need for new facilities and programs. If residents around a

national park demand a Ferris wheel, does the NPS give it to them? Not necessarily, but then the

park knows these people are less likely to visit.

Similar to visitor characteristics, the characteristics of parks change over time and need to be monitored

in order to make accurate forecasts of park and facility use:

C A database is needed for all parks that includes a visitor capacity measure, number of hotels in

the area, types of visitor centers, and access to the park. This should be updated at regular

intervals.

C Social scientists and planners don’t fully

understand how a park’s visitor capacity

functions. This is a serious hindrance to

forecasting. Since 1987, NPS visitation has

been flat or decreasing. Is this because visitor

capacity has been reached in some parks?

The NPS needs to know this to do accurate

forecasting.

C To improve the ability to forecast visits it would be useful to break the NPS system into subsystems – parkways, urban parks, rural parks, and destination parks – and develop separate

forecasts for each sub-system.

How Feasible Is it to Forecast Use of Different Types of NPS Visitor Centers 20 Years into the

Future?

In some cases, forecasting use of a visitor center is tantamount to predicting visitation to the park in

which it is located. In other cases, the correlation between park visits and use of the visitor center may

be weak. Even so, park visitation is still an essential input into the forecast of visitor center use in most

parks.

One approach to forecasting use of a visitor facility is to start with visitation to the park, then make the

necessary conversions to determine use of the facility:

C For visitor centers that people must pass through to enter the park, the NPS can forecast use the

same way it forecasts visitation to the park as a whole.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 19

When predictions are much higher or

lower than actual visits, a lot is learned

about what affects or does not affect

visitation. This can be used to refine

future forecasts.

C If the visitor center is drawing solely from park users, a good approach is to start with the park’s

visitation and estimate how much of this the visitor center will capture. As at Great Falls Park,

location of the facility is critical in determining this.

C The past history of existing visitor centers in areas with similar visitation levels can be used to

forecast use of a new facility.

Sometimes visitor centers are located outside parks, or there may be no consistent relationship between

park use and use of the visitor center. In these cases, other approaches to forecasting must be employed:

C Gravity models can be used to forecast visitor center use based on the distance from major triporigin points.

C For facilities located along major travel routes, the number of cars exiting a ramp vs. how many

pass by on the highway could be a good predictor of use.

C The functions of a visitor center affect its use and should be incorporated into forecasting. Is the

facility a learning center that draws school groups or field schools? Does the park host

conferences? Are there special events at the visitor center or park?

C If the NPS works actively with communities and school districts to promote use of a visitor

center through special programs and events, it is determining a portion of the visitor center’s

use, making forecasting easier.

C In some cases, an initial forecast might be based on average use of park visitor centers in general,

perhaps combined with other methods, such as multiple regression models and qualitative

comparisons with existing facilities judged to be similar.

C Some visitor facilities may over-perform or

under-perfor m based on their forecasts or

on comparisons with similar facilities. This is

not necessarily bad. When predictions are

much higher or lower than actual visits, a lot

is learned about what affects or does not

affect visitation. This can be used to refine

future forecasts.

C If a new facility is unique, forecasting use of

it is more difficult because there are no similar cases for comparison. The Gettysburg map was

an example. Originally, it was a privately owned attraction, but went out of business because

admissions did not reach the level forecast.

In Your Dreams, How Should the NPS Forecast Visitation and Predict Use of Parks and Visitor

Centers 20 Years from Now?

The visitation-forecasting focus group concluded its discussion with each participant describing his or

her view of the ideal forecasting system of the future. Two points were emphasized: 1) the NPS needs

better ways to track who its visitors are, and 2) the NPS needs a better structure for monitoring and

forecasting visitation. 
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 20

The NPS should have a continuous

planning process. It would predict

visitation by park type or attraction. There

would be regular tracking of visitors with

a feedback loop to compare the forecast

with actual counts in order to calibrate

the model.

The NPS should have a better understanding of who its visitors are:

C The most important point is that the NPS needs to know a lot more about its customers. With

a tracking system in place, the forecasting models will be developed along the way.

C Everyone entering a park would have an NPS card with their name and address that gets scanned

into a database.

C The NPS would conduct a regular national survey to profile visitors and non-visitors, including

their demographic characteristics, types of parks visited, and preferred services and facilities.

The NPS should upgrade the quality of the visitor data it collects, the way it organizes to gather that

information, and the way it delivers that data to managers and other customers:

C The NPS should develop a means to continuously collect high-quality data about its visitors that

is based on something more than tire counts. It should forecast visitation from its own

information, which would be comprehensive and of good quality.

C The NPS should have a continuous planning

process. It would predict visitation by park

type or attraction. There would be regular

tracking of visitors with a feedback loop to

compare the forecast with actual counts in

order to calibrate the model.

C Park-based visitor data would be input into

a large GIS system and mapped, using models

that tie all the data together and make

forecasts.

C Every park would have a forecaster and an economist who understand the forecasting model.

The forecasters in parks would be coordinated through a national research office.

C The NPS would develop various scenarios for visitation and play them out – low, high, and midrange forecasts. Comparing these projections with actual visitation would result in a better grasp

of how to forecast, including an improved understanding of which predictors to use in

projection models and the validity of underlying assumptions.
6

As one example, Disney samples visitors to its parks every day.

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 21

The most important key to forecasting is

continuous research that tracks trends in

visitation.

General Implications for the National Park Service

This section presents a summary and synthesis of the focus-group proceedings as interpreted by the

author. Its purpose is to place the discussion at Turkey Run Park squarely in the context of larger issues

faced by the NPS in forecasting visitation and predicting use of visitor centers. A second purpose is to

consider the implications of the discussion for social science research in the NPS.

Two important points integrate many of the comments from the group’s participants. The first is the

need to understand a park’s products and markets, as well as the various forecasting approaches. The

second is the power of the NPS to influence, as well as predict, future use of visitor centers and related

facilities.

C Forecasting visitation requires an understanding of agency goals, a knowledge of market trends,

and continuous tracking to refine visitor projection models. It also requires an understanding of

the limitations of quantitative and qualitative approaches to forecasting.

Fundamental approaches to visitation and population forecasting have not changed for 50 years. Instead,

improvements have come largely from refinements in the types and quality of data input into projection

models. For example, census information on race and ethnicity is more detailed than in the past and

continues to evolve. Also, due to continued advances in geographic information systems and databases,

demographic and lifestyle information can be geo-coded at smaller spatial scales than before. This gives

forecasters more detailed information on local populations, something that is critical to doing sitespecific projections.

But knowledge of the market “out there” is not as important as knowledge of the specific market

segments parks want to reach. In one sense, the NPS serves the entire American public – even a global

public – but many parks also have populations of visitors and potential visitors that are of special

interest, including school children, seasonal residents, local residents, retirees, or specific racial and

ethnic groups. Forecasting visitation depends on

knowledge of these strategically important market

segments, including changes in their size, geographic

distribution, and share of the overall population.

Because of this, the most important key to forecasting

is continuous research that tracks trends in

visitation.6

 However, tracking should be more than

counting the number of tire tracks over a counter in the road, since that tells little about who park

visitors are. It should involve routinely collecting data that describes how the mix of visitors is changing,

either in response to outside events, such as September 11th, as a result of broad demographic shifts in
7

The NPS uses trend-line extensions in its two-year forecasts of park visitation.

Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 22

Applying quantitative methods to the long

term is almost certain to yield inaccurate

forecasts because most such models make the

dubious assumption that conditions that

prevail in the present will continue into the

future.

Some of the factors influencing use are

controllable, such as marketing, pricing,

and promoting a visitor center’s programs

and services.

a region’s population, or because management actions directly or indirectly affect the types of people

who visit. Continuous tracking also is helpful in identifying and reliably anticipating recurring blips in

visitation caused by time of year, special events, and other recurring factors.

The type of forecasting depends on the time period for which projections are made and the desired level

of precision. Short-term forecasts are more amenable to formal quantitative approaches, such as timeseries extensions, moving averages, and

structural equation models.7 However, applying

these methods to the long term is almost certain

to yield inaccurate forecasts because most such

models make the dubious assumption that

conditions that prevail in the present will

continue into the future. In the case of longterm projections, e.g., 20 years ahead, various

qualitative approaches are more useful. These

include models in which expert judgment is a

direct input, as in describing alternative future conditions or in evaluating the trends and relationships

employed in cross-impact simulation models. Even more than in the short term, when forecasting

visitation into the distant future it is essential to understand market segments and the many extraneous

factors affecting their behavior, including competing opportunities. It is also important to understand

that precision will differ substantially between short- term and long- term forecasts. Planners and policymakers should expect greater precision in short-term predictions than is possible in the long-term.

C The NPS does not have to wait for the future to happen. It can play an active role in shaping future

events, including use of its parks and visitor centers. 

How many people visit parks is not totally under the

control of the NPS. In both the long term and the

short term many events and trends beyond the

agency’s reach significantly affect visitation. But some

of the factors influencing use are controllable, such as

marketing, pricing, and promoting a visitor center’s

programs and services. Forecasting is much easier if

the effects of these factors on the populations the facility is trying to attract are understood. One school

of practice – normative forecasting – establishes desirable future conditions and then lays out the steps

necessary to reach them. This approach could be applied to forecasting use of new visitor centers.

Important steps toward reaching future visitation goals might include establishing visitor- capacity limits

and square footage for facilities, managing ease of access through location, using publicity and special

events to reach targeted populations, cooperating with partners in offering programs, and employing
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 23

promotional pricing. Continuous tracking of visitation would allow the park to understand how these

controllable factors influence the market segments the park is trying to reach, providing an

understanding of customer behavior that could be used to refine forecasts for other parks and facilities.

Implications for Social Science Research in the NPS

Just as improvements in population forecasting have their roots in better data employed in prediction

models, improvements in projecting use of NPS parks and visitor centers will come from better and more

detailed social science data tracking visitor populations and describing market segments. For example,

visitors’ ZIP codes – input into cash registers at purchase points in park stores and fee stations – would

provide a wealth of market information helpful in understanding the populations that are being served

and in refining projection models. The US Forest Service has developed such a system – Point O Sale –

at its Land-Between-the-Lakes demonstration forest. The Smithsonian Institution employs a similar

system in its museum stores.

There is much that social scientists and planners do not yet understand about the factors affecting future

demand for park experiences and use of visitor centers. These knowledge gaps have been detailed in

previous sections of this report, but the most important are summarized here.

In order to improve its ability to forecast visitation, the NPS needs social science research to:

C Continuously track the characteristics of park visitors.

C Accurately describe non-visitors and their reasons for not using parks and visitor facilities.

C Identify the significant factors influencing visitation at the national level, including:

C macro-economic cycles and other large-scale trends;

C park-specific events, including natural disasters and changes in regional access;

C changes in the size and composition of populations in terms of age, race, and ethnicity;

C management actions, including facility development and fee policies;

C the effects of marketing.

C Better understand the effects on demand of crowding, traffic congestion, and waiting times for

reservations.

C Identify factors affecting visitation to different types of NPS units, such as parkways, destination

parks, urban sites, and remote parks.

In summary, the success of the NPS in forecasting use of parks and visitor centers will depend on its

understanding of the variables affecting visitation at different types of units and its ability to measure

these on a continual basis. As one focus-group member stated, “In forecasting, any information is

helpful if it’s a predictor and you measure it at all of your sites.”
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 24

Appendix: Focus-Group Participants, Affiliations, and Interests

Dr. Donald English

Research Scientist, US Forest Service Southern Center for Urban Forestry Research and Information.

Interests: Outdoor recreation demand modeling and visitation counting.

Dr. Ashley Goldhor-Wilcock

Social Scientist, Bureau of Land Management National Recreation Group. Interests: Environmental

economics, visitor counting systems, carrying capacity, economic impacts, and other recreation and

visitor issues.

Mr. Richard Kasul

Statistician, Engineer Research and Development Center, US Army Engineers Waterways Experiment

Station. Interests: Statistical design and analysis associated with wildlife and recreation resources,

projecting demographic change in visitation.

Mr. Butch Street

Management Analyst, National Park Service Public Use Statistics Office. Interests: Measuring national

park visitation, short-term forecasts of national park visitation.

Dr. Daniel Stynes

Professor of Recreation Economics, Michigan State University. Interests: Recreation demand modeling

and forecasting, economic significance of national park visitation.

Mr. Stephen Tordella

President, Decision Demographics. Interests: Demographic analysis as applied to market research,

population estimates and projections, strategic planning, and evaluations.

Dr. Timothy Tyrrell

Professor of Natural Resource Economics and Director, Office of Travel, Tourism, and Recreation,

University of Rhode Island. Interests: Recreation and tourism demand modeling, spatial analysis of

tourism growth and sustainability. 

Dr. Paul Voss

Professor of Rural Sociology and Director, Applied Population Laboratory, University of WisconsinMadison. Interests: Applied demography, census survey development, population projections.

Cover photo: Rickey Ridge visitor center, Shenandoah National Park. All photos courtesy NPS

Social Science Program.
Visitation Forecasting and Predicting Use of NPS Parks and Visitor Centers 25

Cover photo: Rickey Ridge visitor center, Shenandoah National Park. All photos courtesy NPS Social Science Program.

About the NPS Social Science Program

The role and functions of the NPS Social Science

Program are to: provide leadership and direction to the social

science activities of the NPS, coordinate social science

activities with other programs of the NPS, act as liaison with

the USGS Biological Resources Division and other federal

agencies on social science activities, provide technical support

to parks, park clusters, support offices, and regional offices,

and support a program of applied social science research

related to national research needs of the NPS.

For more information, contact:

Dr. Jim Gramann

Visiting Chief Social Scientist

National Park Service

1849 C Street, NW (2300)

Washington, DC 20240

Telephone: (202) 513-7189

Email: James_Gramann@partner.nps.gov

Web site: http://www.nps.gov/socialscience/