Doctoral Dissertations

Abstract

"A method is developed for the identification of the spatial locations about which urban population densities tend to be distributed. The identification of these "influence centers" is based upon the use of available census data. The method is developed for application to any population characteristic which can be logically represented in terms of spatial density. Examples of such characteristics are; total population, population by race, and population by income group. The method is empirically developed and verified for restricted spatial distributions using artifically generated census tract information. These spatial distributions are compatiable with population distributions that are most readily modeled from census data. Data from a five-county area surrounding Atlanta, Georgia are used in an application of the developed method. This application results in plausible sets of influence centers. The developed method would realize its full potential when directly associated with specific modeling techniques. Areas of further investigation which relate to this potential are suggested"--Abstract, page ii.

Advisor(s)

Johnson, R. T. (Richard T.)

Committee Member(s)

Flanigan, V. J.
Faucett, T. R.
Carmichael, Ronald L., 1921-2006
Sieck, Lawrence K.
Pagano, Sylvester J., 1924-2006

Department(s)

Mechanical and Aerospace Engineering

Degree Name

Ph. D. in Mechanical Engineering

Sponsor(s)

University of Missouri--Rolla. Department of Mechanical and Aerospace Engineering

Publisher

University of Missouri--Rolla

Publication Date

1971

Pagination

vii, 96 pages

Note about bibliography

Includes bibliographical references (page 95).

Geographic Coverage

United States

Rights

© 1971 Robert W. Meyer, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Subject Headings

Metropolitan areas
Community development -- United States -- Statistical methods

Thesis Number

T 2628

Print OCLC #

6038869

Electronic OCLC #

878046375

Share

 
COinS