Racial Population Distribution and

Corresponding Income Levels of

Douglas County, Nebraska

Eugene F. Dahlem

 


INTRODUCTION

The Omaha Metro Area is built on the eastern border of Nebraska. It is an area that is expanding to the north, south and west. In the process it is engulfing smaller communities and absorbing farmland. In driving around the city, I noticed that in general, the larger, more expensive houses tend to lie outside the downtown area. Also in certain areas, a predominance of non-white people tend to reside in the older, more eastern sections of town.

The propose of this project is to compare the Race and Income geographic distribution throughout Douglas County, Neb. To do this I needed to build thematic maps displaying the appropriate data and then make these maps available on a webpage in a format that would facilitate comparison among these maps.

In order to compare different areas of Douglas County, I originally thought about showing my data by Zip code. They seemed to cover too large of an area for this study and would end up combining separate pockets of racially segregated areas skewing the results. I decided to display the data in a Block Group format. Block Groups were originally designed by state and local officials, in conjunction with the U.S. Census Bureau, to subdivide Census Tracts. They typically hold 452 to 1,100 people, designed to hold 400 housing units. Douglas County, containing both metropolitan and rural farm lands is broken up into 440 Block Groups.


To view the following 11 maps in Adobe Acrobat format you will need to have Adobe Acrobat Reader software installed on your computer. If you do not have this software, it is available through a free download from Adobe Systems at the following website:

http://www.adobe.com/prodindex/acrobat/readstep.html


 

   
 
 
 
   


 

METHODOLOGY

The first step in this project was to acquire 1990 demographic and income information as well as corresponding map files for the Douglas County area from Wessex Incorporated. Wessex is a company formed in 1983, originally as a spreadsheet/database design and consulting firm, and now they make U.S. Census data available to the public. The data for this project was made accessible through a CD-Rom set owned by the Geography Department here at the University of Nebraska at Omaha. Included in this CD set are software programs to help extract US Census data and ArcView formatted shape files for various divisions of the United States such as by: state, county, Block Group, Zip Code. The data are listed in spreadsheet format that through ArcView can be applied to the shape files for display and analysis.

 

Database Work

For this project, I needed the demographic information as well as the ArcView shape files for for Douglas County, Neb., from the Wessex disks. First, I downloaded the Douglas County Block Group shape and database files (.dbf files). Then for a locator map, I also included the water feature and road files. Next I downloaded the population data using the First Street program that came with the Wessex set. I copied the .dbf files for: total population, white, black, one file including American Indian or Eskimo or Aleut, one for Asian or Pacific Islander, and other. Below the ethnic category list was a separate one for Hispanic. I copied this one as well. I was fortunate I did, because after looking at the numbers of all the individual race categories and totaling them up, I noticed that the Hispanic category hadn't been included in the total population numbers. I had to do some spreadsheet adding, using Lotus 123, to get the totals to add up properly. The following table is an example of the top three block group population numbers copied from the Wessex disks:

 

BLOCKGR Total Persons DWHITE DBLACK TOTALHISP AMINESKAL ASIANPACI OTHERRACE
BG 3 705 698 2 13 1 2 2
BG 4 577 541 30 7 1 3 2
BG 5 1,572 1,385 168 33 5 5 9

 

Instead of mapping out the raw numbers for each racial category, I decided to map out the percentages of racial population for each block group. To get these numbers, I just divided the number of people per racial category by the total persons category.

Next, for the income I had to do some more spreadsheet operations. First I had to get the "Aggregate Income per Block Group" by race which got me the following table which has the total income earned for all households of that race within that block group:

 

BLOCKGR White Black American Indian Asian Other Hispanic
BG 3 5,547,293 0 0 0 0 314,400
BG 4 5,934,515 325,384 0 65,000 0 0
BG 5 15,917,668 1,331,182 0 0 0 180,000

 

Then for each race, I downloaded the files for income levels. These files had the numbers of households by race, for each Block Group, whose income levels fit in each of these categories: <5k, 5-10k, 10-15k, 15-25k, 25-35k, 35-50k, 50-75k, 75-100k and >100k. I then totaled up the number of households into one column and copied that column from each racial category file into a separate spreadsheet. Then I divided that number of households into the Aggregate income for each block group to attain the average income per household for each block group. In the compiling of these columns I came up with errors in fields where zero aggregate income was divided by zero households. The only way I knew how to fix this was to manually enter a zero in each "ERR" field. After this I ended up with the following table:

 

BLOCKGR W_HH_IN B_HH_IN H_HH_IN O_HH_IN TOT_HH_IN
BG 3 23,406.3 0 31,440 0 23,731.55
BG 4 28,808.33 81,346 0 13,000 29,418.3
BG 5 33,652.58 22,562.41 30,000 0 32,395.63

 

As you see with this table I combined the Asian, Native American and Other categories into a single Other category. Shortly before hitting this point I realized that due to space, time, percentages of the population, and my sanity, I had to limit my study to four ethnic categories: White (81.2%), Black (13.1%), Hispanic (2.9%), and Other Races (2.8%). Unfortunately the "Other" category includes an incredibly diverse set of peoples: Asians, Pacific Islanders, Native Americans, Middle Eastern and North African peoples.

After compiling all of this data in separate database files, I then combined them into one database file with eleven columns: Block Group ID, total population, white, black, Hispanic and other population percentages as well as average household income for white, black, Hispanic, other, and another for all races.

 

ArcView Map Building

With all of the database work complete, I needed to start work in ArcView to begin mapping out this data. With some map projections, Douglas County, Neb., shows up as narrow and very wide compressing the smaller Block Groups of the Omaha area. In order to show them the best on a computer screen, I selected the Equidistant Conic projection of North America to display Douglas County and its Block Groups as "tall" as possible.

The next step was the joining, through ArcView, of the databases I had created to the Douglas County shape file database shown below:

 

BLOCKGR ID AREA PERIMETER STCNTY COUNT
310550002.00:3 1 0.000205 0.073438 31,055 1
310550002.00:4 2 0.000042 0.037448 31,055 1
310550002.00:5 3 0.000048 0.030518 31,055 1

 

I first had a problem getting ArcView to join the databases. The problem was that when attempting to join database files, the columns that you select need to be identical. If you notice, the BLOCKGR column in this table has 12 characters: 31, as the state identifier for Nebraska, 055 county number for Douglas County, and the remaining numbers identify the individual block groups. In the racial and income files the only data in the BLOCKGR field was just BG and the final number. This problem had an easy copy/paste fix, but was still something that posed a several- hour headache.

The next step in this project was the creating of the individual Douglas County maps displaying population distribution and income. To display population numbers and racial percentage of population, I chose the Equal Interval method. This method is computed by subtracting the lowest percentage from the highest and then dividing the remainder into equal classes (i.e. "other races" lowest was 0%, highest 16.1%, broken up into five categories, plus one for zero, with each one covering approximately 3.2%). With the income levels, I needed to choose numbers that could be shown across the board for all categories. I chose the category cutoff levels of 10, 20, 35, 65, 120 and more than 120 thousand dollars per year. I had to include a zero category, because in all racial categories, there are Block Groups of people who had no reported income in the Census data.

After compiling the population and income maps I exported each of them from ArcView in an EPS format that could be read by Adobe Illustrator 7.0.

 

Adobe Graphics Work

The Adobe Illustrator program is a much more powerful graphics program with better editing functions than the ArcView program. With the Illustrator program, I opened each of the maps, cleaned them up and then resaved them back into the EPS format as well as the Adobe Acrobat format for better viewing capabilities.

These Acrobat images maps averaged over 500kb in size. For quicker downloading and viewing of this webpage, I used Adobe Photoshop 3.0 to copy each of the maps into a GIF format (generally under 20kb each) and placed these on the webpage linked to the Acrobat formatted images.

 


RESULTS

When looking at the maps various conclusions can be drawn about the population distribution of Douglas County, Neb. First off, I need to throw out a disclaimer about how the All Races Population map looks. It is a depiction of the number of people in each Block Group. In mapping the population this way, the dark, more populated Block Groups, with a few exceptions, tend to be the larger blocks. A possibly more accurate way to show this data might have been to use a "people per area" method, but in showing the racial distribution in percentages, I felt a "raw number" map was needed for clarity. As I said earlier, Block Groups were originally designed to hold around 1,100 people. The Blocks with larger populations (darker areas on the population maps) are due to overall population growth and generally to the expanding of the Omaha Metro Area out towards the northern and western areas of the county. These darker Blocks probably will be broken down into smaller Block Groups in future Census efforts.

The All Races Average Household Income map shows that the higher income levels tend to be outside Southeast area of the county. With the main exception of the area surrounding the University of Nebraska at Omaha, the lower income areas are generally east of 72nd Street, and south of I-680. The lowest of these are east of 42nd Street, north of I-80 and along and south of Ames Avenue. After comparing this information to the ethnic distribution and income maps, the lowest income area is predominately populated by Black families, with some blocks being over 97% Black. The Hispanic and Other category maps show the highest concentrations of people in the southeast corner of the county. The rest of the county is almost completely white with two of the blocks showing a 100% Caucasian population. A notable exception to the high concentration of whites outside the East and Central Omaha area is a square block off the south side of Dodge street in West Omaha. When looking at a map, I noticed that this area comprised Boys Town, an area that wouldn't exactly match the surrounding ethnic makeup.

After looking at the ethnic Block Group breakdown throughout the county, I then looked at the income level maps. A comparison of the Income per Block Group for each race shows a general following of the All Races income distribution with average household income levels tending to be higher outside the eastern Omaha areas. Another thing I noticed was that in using Block Groups, the income maps can be skewed to look a certain way by the impact of having only a few households of an ethnic category in a particular income area.

 

The overall average household income for Douglas County was $36,290 per year: Whites $36,501; Blacks $13,756; Hispanic $13,973; and Other Races $16,386. The average household income for the entire county is only 0.6% ($211) less than the average for white households, yet the income for black, Hispanic or other households, 18.8% of the population, was less than half that number. The reasons for this disparity are subjects for other papers. This project is just here to display numbers.

Future work expanding this project could take several different tracts. The clustering of people of these racial categories in specific areas (primarily Eastern Omaha), led me to wanting to see other Census categories mapped out. One direction would be the displaying of employment figures, education levels, and housing and rental costs for the county. And then a comparison of the data from this project, with data from the year 2000 U.S. Census. Another tract would be to see the overall expansion of the growing Omaha Metro Area to the north, south, west, and east into Iowa; comparing how towns that in 1990 were "bedroom communities" with residents commuting to the city for work and seeing which communities in 2000 had been absorbed into suburbia.


Source: All data for this project was compiled from 1990 US Census data gathered from Wessex Incorporated generated CD Rom disks.

Wessex Inc.
560 Green Bay Rd.
Winnetka, IL 60093
1-800-892-6906
www.wessex.com
 

 
This project was compiled using the following software products:
ESRI ArcView 3.0 (www.esri.com)
 
and the following Adobe products: (www.adobe.com/prodindex/main.html)
Illustrator 7.0
Photoshop 3.0
Pagemill 2.0
 

Submitted by Eugene F. Dahlem, 2 May 98
for course: GEOG 8056, Geographic Information Systems