Fitness Clubs in Omaha





    Geographic Information Systems 

Fall 2003

By Georgia Hatzidaki  


1. Introduction
2. Data Sources
3. Results/Analysis
    3.1 Transportation Relation
    3.2 Serving Area
    3.3 Population Relation
4. Problems
5. Possible Addition and Improvements
6. References


1. Introduction

Fitness clubs are an established part of American culture. Even those who don't own a club membership are at least familiar with names like Gold's Gym and Bally Total Fitness. The rise of the modern American health clubs began in California in the 1940s, but their predecessors came from 19th century Europe (Buck 1). From imitations of German rehabilitation centers and European spas to today's multi-functional facilities, fitness clubs have evolved to match their customers' preferences and satisfy their needs. 

This final project was designed to use GIS applications to relate different sets of data for analyzing the distribution of various fitness clubs around Omaha. The idea for this project came from my own personal research for the closest fitness club to my house, and it was developed after a geocoding lab that we had to do an the beginning of the semester. Finally, further interest on exercise and sports helped me shape the objectives of this project and the final outcome. In this project, I started by address geocoding of all fitness clubs in the area, and using some spatial analysis I tried to explain possible reasons for their location.

2. Data Sources

The locations for the various fitness clubs in the Omaha area were found in the Yellow Pages. However, the data were relatively old and some fitness clubs were not there anymore. In order to determine which places were still there, I had to drive in the area and check some of them, while in some occasions, I was just based on information by people who live in the area. Furthermore, I had to eliminate some places that did not fit the standards of a fitness club but were included in the yellow pages list, such as massage therapy centers and sports equipment stores.

The final list of the fitness clubs that were used in this project is the following:

24 Hours Fitness 2718 N 118 Circle
24 Hours Fitness 3935 S 147 St
Better Bodies Inc. 4117 S 120 St
Big Iron Gym 8902 Grant St
Pilates Fitness 11032 Oak St
Pilates for Everybody 2122 S 156 Circle
Pinnacle Club 2027 Dodge St
Prairie Life Center 8525 Q St
Prairie Life Center 2275 S 132 St
Rockbrook Women's Fitness 10820 Prairie Hills
Gold's Gym - North 10930 Emmet St
Gold's Gym - South 5103 S 108 St
New Lady Fitness 319 N 76 St
Personalized Fitness & Nutrition 15117 Industrial Rd
Curves for Women 15821 West Dodge Rd
Curves for Women 3019 S 83 St
Curves for Women 3908 N 138 St
Fit Express Women's 30 Minute Workout 2067 N 156 St

The streets and block populations shape files were provided by Chris Poole. I had several problems with those files that will be further explained in the appropriate section below.

3. Results / Analysis

3.1 Transportation Relation

The distribution of fitness clubs in the area follows an interesting pattern, as shown in the map below. Most of the fitness clubs in the area are located between 156th St. and 76th St. west to east, and Maple and L St north to south. Omaha is rapidly growing westwards and, apparently, most of the clubs follow that expansion. Note that only one -- the Pinnacle Club-- is located downtown. Most clubs are located close to major streets for easy access. For example, three fitness clubs are next to Industrial Rd., two are around L St. and another two are next to I-680 and I-80.

3.2 Serving Area

Residents in the area can be served by more than one fitness club, as most of them are located close together. The map below shows one-mile serving area zones around each gym location. Apparently, people are willing to travel more than one mile to go to the club of their preference, but for simplicity reasons the radius of the buffer zones is only one mile long. Map units are displayed in meters.

An alternate way to see the area that each fitness club serves is using the Spatial Analyst. In the following map, straight line distance is calculated for each fitness club and the serving area is displayed in meters.

3.3 Population Relation

As mentioned above, in general, location of fitness clubs follows the westward expansion of Omaha. Close related to that is population density. That is, population density of an area also affects the selection of the location of a fitness club. The following maps show the relation between block population density and fitness club location. The first one uses natural breaks and the second one uses the quantile method. I believe that the quantile method is a much better method, and therefore, the second map is more accurate. Both maps use 2000 Census data.

As already mentioned, the following map uses the quantile method to show the population density as a percent of the total population. As we can see, most health clubs are in or close to high density population areas.

4. Problems

I encountered several problems in this project. First of all, I could not change the projection of the population blocks from undefined to Albers Equal Conic because after the transformation my layers could not overlay. Although, I could still zoom close to the blocks and see my data in more detail, nothing seemed to overlay. On the other side, the population blocks worked fine when I did not change the projection, but I could not zoom in any more. Therefore, I left my projection undefined in order to be able to overlay my data, but I could not zoom in.

A second problem was the spatial analyst. It did not work for density, and it partially worked for straight line distance and reclassification of distance. That's why I also used buffer zones in my project. Finally, I could not find the necessary population data for my analysis. For further analysis, I tried to find income information for blocks, but the only data I could find was for tracks. Tracks are not small enough for my analysis, and therefore, I preferred not to do an analysis based on income.

5. Possible Additions and Improvements

As I have already mentioned, I could not find income data for blocks. We could do an additional analysis using income block data and determine if there is a relation between fitness club location and income. Therefore, using population, income, and main transportation routes information we could determine a possible location for a new fitness club.

6. References

Josh Buck. "The Evolution of Health Clubs." Club Industry Website. Dec. 1, 1999.                        <>                                             

Submitted by Georgia Hatzidaki on 12/9/2003