{"id":{"repo_id":"must-thes","oai_identifier":"oai:scholarsmine.mst.edu:doctoral_dissertations-3190"},"canonical_url":"https://search.dev.ndltd.org/etd/must-thes/oai:scholarsmine.mst.edu:doctoral_dissertations-3190","repository":{"repo_id":"must-thes","name":"Missouri University of Science and Technology","base_url":"https://scholarsmine.mst.edu/do/oai/"},"display":{"title":"Identification of centers of influence for urban areas","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.","abstract_html":""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.","abstract_has_math":false,"creators":["Meyer, Robert W."],"institution":"University of Missouri--Rolla","degree_name":"Ph. D. in Mechanical Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-02-10T08:00:00Z","date_published":"2016-02-10T08:00:00Z","updated_at":"2026-07-24T03:19:04Z","subjects":["Mechanical Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/2188","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Meyer, Robert W."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-02-10T08:00:00Z"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Mechanical Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Rolla"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mechanical Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/2188"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"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."]},{"key":"dc:title","label":"Title","values":["Identification of centers of influence for urban areas"]}]}],"canonical_facts":{"dc:creator":["Meyer, Robert W."],"dc:date.available":["2016-02-10T08:00:00Z"],"dc:description.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."],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/2188"],"dc:subject":["Mechanical Engineering"],"dc:title":["Identification of centers of influence for urban areas"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Mechanical Engineering"],"thesis:institution_name":["University of Missouri--Rolla"]},"updated_at":"2026-07-24T03:19:04Z"}