A Tale of Five Counties

Choosing the Best Place of Residence Using GIS and the Quality of Life Index

Collette Renee Callaway

Advanced GIS

Dr. Jay Lee

December 2, 2002

Abstract

In this day and age it is getting harder to find a decent place to live. Regions have become diluted by the decline of the city and overwrought by crime. It is becoming increasingly more difficult to define oneself by geographic location.

However, the quality of life index is a good place to start when looking for a suitable residence. This paper examines certain indicators (statistical data) to help define the standard of living in Northeast Ohio’s most populous counties. The paper draws conclusions on which county will make the best home.

Introduction

What signifies happiness? Many factors are to be considered to even attempt an answer. Happiness varies from person to person. What was considered happiness in the past may not be the same in this day and age. Many may try to stake the claim that happiness is living the ‘American Dream.’ The ‘American Dream’ can be described as constructing what seems to be the perfect life consisting of marriage, 2.5 children, a nice car, big house, and a great job. I would tend to agree with these factors. I would argue, however, that one of the most important factors in a person’s life is place. Where one resides will affect many of the above parameters and much more.

It is very important to find an area that is right for oneself. This location should be one in which a person is able to prosper economically. The area needs to be safe and a good environment to raise a family in.

So how does one go about finding said area? I have chosen Northeastern Ohio’s most populous counties in order to examine which would be the most beneficial area of residence. Northeastern Ohio is a budding region. Also, one cannot forget that Ohio is the heart of it all. The 2000 Census indicates that the region is improving as a hole in terms of standards of living. For instance due to a boost of jobs in the service sector, median household income has beaten inflation and increased considerably since the 1990 Census. In this region, more housing units were built, home values increased, and the property level declined (Exner, Smith, and Davis, 2002.)

For this analysis I have implemented the quality of life index into GIS. I have used what I thought would be the best indicators of the quality of life index to analyze place and how it affects ones life.

What Is the Quality of Life Index

The quality of life index is a tool that can be used to evaluate one’s place of residence, one’s health, or one’s environment. The quality of life index can examine almost every standard of life according to the researcher’s area of interest.

For this project I have chosen to take a geographical approach to the quality of life index. My research is centered on the examination of place.

Each index whether it is physical/health, environmental, or geographical has a set of indicators. Indicators are the data that is used in the index. The best indicators will enable one to track progress and monitor changes in the study area. The indicator should provide enough information on the quality of life issues to inform the user, such as a developer, where to focus efforts, resources, and funds (Guide to Using the Quality of Life Index, 2002.) As in our case the indicators should be able to inform one on the best areas to reside.

Indicators of the Three Types of Quality of Life

Physical Quality of Life Index

This index is used to measure the level of well being in human life. It examines basic human need in regards to health issues. There are two basic indicators for the index. First, one must examine the requirements for a person such as adequate foods, shelter, and clothing, as well as the availability of certain household equipment and furniture. The second indicator examines essential services provided by and for the community such as safe drinking water, sanitation, public transportation, health facilities, and educational and cultural facilities. A researcher may gather information from such organizations as World Bank, the United States Bureau of the Census, the Population Reference Bureau, and the Center for Disease Control (Morris, 1979.)

Environmental Quality of Life Index

This index was developed to analyze the quality of the physical factors of the space around us. The index takes into consideration six indicators. The indicators are water use, treatment and pollution sources, waste output, recycling programs, landfills, consumption of energy, and sources of air pollution. Researchers can gather much environmental data from the National Solid Waste Management Association, Energy Information Administration, the Integrated Waste Service Association, the United States Department of Energy – Efficient Economy, Office of Technological Assessment, Upper Air Atmospheric Research, NASA, the United States Environmental Protection Agency, as well as others (Hammond, 1993.)

Geographical Quality of Life Index

This index (the focus of this paper) is used to examine the social environment of the study area. The four most widely used indicators include social, crime, physical, and economic. The social indicator would include the poverty level, education, and age composition. Crime would detail areas where crimes are frequently committed and the rate of different types of crime. Physical examines the percent of homeowners, access to public transportation, access to retail and commercial area, and average commute time. Economic would take into consideration such indicators as average amount of income and the amount of money spent on rent or mortgage (Neighborhood Quality of Life Template, 2002.) The best source of data, in my opinion, would be the United States Bureau of the Census which produces new information every ten year. Also data may be acquired from many different government departments.

For this project I focus on median household income, adults who are college educated, those who own their own home, amount of income spent on rent or a mortgage, the poverty level, average commute time, major highway systems, land area, number of housing units, the value of housing units, federal funds and grants, and local government employment for the five most populous counties in Northeastern Ohio.

Why Is the Data Important?

As well as assisting in reporting of which are the best areas to reside, the indicators of a quality of life index also work to improve the area. According to the United States Bureau of the Census, education data affects the distribution of funding for numerous education programs such as vocational and adult education. Poverty data is critical for programs that aim to identify areas of eligibility for housing assistance, employment services, food support, social services, etc. (the United States Census Bureau, 2000.)

Data Acquisition and Data Quality

All data was acquired from the United States Bureau of the Census 2000.

I believe for my studies that I have acquired the best data available. However, is this still accurate? The data is for the most part accurate yet it can never be precise. In the case of Census data, there will always be ‘holes’ left unfilled. For instance, not everyone in a region can be counted. Data acquired from the population of a county is gathered solely from their address of residence. Albeit, where does this leave the homeless? Since they have no permanent place of residence they are not recorded.

Another issue is the use of aggregated data. Most Census data is formed around sensitive or private information such as income, race, sex, ethnicity, etc. Many people are not willing to give out this information. Some will even refuse altogether. After many tries to record a resident’s information, a Census enumerator must gather the information from any place possible.

Another issue is currency. The data we gather today will be out of date tomorrow.

Data Input

The seven indicators of quality of life that I have examined (amount of income, college educated, amount of rent or mortgage paid, commute time, poverty level, and number of home owners,) were brought into ArcView 3.3. I used basemap shapefiles from the Magic 2001 CD and imported them into ArcView. I added each of the seven indicators along with population data into the attribute table.

The examination of roadways in Northeast Ohio’s most populous counties was downloaded from the Census 2000 TIGER files. The data had to be unzipped and street records were extracted from the files. Through the use of TIGERTOOLS in ArcInfo I was able to extract out all street records and produce a coverage of these records for each county. These coverages were to be imported into ArcView 3.3 and overlayed onto the county boundaries (which I had acquired from the Magic 2001 CD.) However, the coverages that I had just created were in UTM projection and the shapefiles were in Stateplane projection. I had to change the projection of the coverages in ArcInfo. I used the project command and specified a Stateplane projection with North American Datum type 83. I specified the units as feet, used the default parameters, and zone 4976.

Methodology

In my research I focused on physical, social, and economical indicators of the geographical quality of life index. Crime is an important indicator, yet crime dtat is harder to obtain.

Physical Indicators

In my opinion, one of the most important sub indicators is the number of housing units in an area. The more units there are, the better the chance of availability for in migrating persons. I have also examined the median value of owner – occupied housing units, land area, average commute time, and the number of major roadways (See Appendix A and B.)

Here is how each county ranked according to:

Number of Housing Units:

Cuyahoga: 616, 903

Summit: 217, 788

Stark: 157, 024

Mahoning: 111, 762

Lorain: 111, 368

Median Value of Owner – Occupied Housing Units:

Lorain: $115, 100

Cuyahoga: $113, 800

Summit: $109, 100

Stark: $100, 300

Mahoning: $79, 700

Land Area in Square Miles

Stark: 576

Lorain: 492

Cuyahoga: 458

Mahoning: 415

Summit: 413

Social Indicators

I have examined the percent of the population that have been living in the same home since 1995, the percent of college educated adults, the percent of the population living below the poverty level, and the total population (See Appendix C, D, and E.)

Here is how each county ranked according to:

Percent of Population Still Living in the Same Home Since 1995

Mahoning: 64.2

Stark: 61.8

Cuyahoga: 59.6

Lorain: 59.4

Summit: 58.4

Economic Indicators

In examining economic factors, the sub indicators of the amount of federal grants and funds, the amount of local government positions, the percent of population who spend thirty percent or less of their income on rent or a mortgage, the overall average income, and the percent of population who own their own home were analyzed (See Appendix F,G,H,and I.)

Here is how each county ranked according to:

The Amount of Federal Funds and Grants Appointed to the Area

Cuyahoga: $8, 778, 721

Summit: $2, 675, 705

Stark: $1, 697, 197

Mahoning: $1, 450, 850

Lorain: $1, 149, 900

The Amount of Local Government Positions

Cuyahoga: 66, 998

Summit: 19, 301

Lorain: 9, 696

Mahoning: 9, 696

Results

(See Appendix J)

In reviewing each indicator and weighting out the most important factors, it seems to show that Lorain would be the best place of residency, with Summit County not far behind. Lorain ranked highest in median value of owner – occupied housing units, in the percent of population who pay thirty percent or less of their income on rent, overall average income, and percent who own their own home. Summit ranked high in the amount of major roadways, percent of population who paid less than thirty percent of their income for a mortgage, and percent of college educated adults. Summit was also ranked lowest for percent of population below the poverty level.

Further Research

In the future I would like to add more indicators. Although some of the indicators in this project might not seem as necessary as others, I think it is good that they are there. As in finding a place to settle, everyone has different wants and needs. The more indicators, the easier it is to find the area that best suits a particular person.

I would like to focus more on land use, particularly commercial and residential. Also, I would like to profile the careers of residents in the study area.

Bibliography

Exner, Rich; Smith, Robert L.; Davis, David. Service Jobs Show Increase; Home Values Up In Region. The Plain Dealer. Tuesday, June 4, 2002.

“Guide To Using the Quality of Life Index,” City of Pasadena, 2002. http://www.ci.pasadena.ca.us/publichealth/qualityoflife/guidetoindex.asp.

Hammond, Allen. The 1993 Information Please Environmental Almanac. Houghton Mifflin Company: Boston, 1993.

Morris, David Morris. Measuring the Condition of the Poor: The Physical Quality of Life Index. Pergamon Press: New York, 1979.

“Neighborhood Quality of Life Profile Template.” Neighborhood Development, 2002. http://charmeck.org/apps/qol/template.

The United States Bureau of the Census. 2000. www.census.gov