Spatio-temporal dynamics of economic clusters in urban polynucleation: A case study analysis of Erie County, New York

Polynucleation of metropolitan areas, especially related to economic activities, has been the subject of analysis and speculation by many authors over the past thirty years. This dissertation takes a different perspective on this phenomenon. It examines, at an individual property scale, the appearance and the changes of nucleated centers of employment, over time in Erie County, State of New York. In other words, spatio-temporal changes of urban economic functions are examined at a micro-scale framework, and the focus is upon especially effects of urban commercial and manufacturing clusters on the urban internal structures. The purposes of this research are to detect economic clusters in urban polynucleation and, to explore changes of nucleated centers in terms of the characteristics of the clusters and urban internal structure.; From the empirical analysis for the commercial and manufacturing clusters for 1970--2000, several significant empirical findings were observed. First, compared to results of classical urban form models (concentric and sector model), the clustering results were helpful to find the more accurate and detailed information of the clusters. Second, newly established commercial clusters mainly tended to locate in the suburbs, rather than near the CBD, and this trend became more obvious over time. Unlike the case of the commercial clusters, I couldn't find clear evidence of a strong trend of suburbanization in the manufacturing clusters. Rather, it was like the strong centralized larger-sized clusters near the CBD with scattered suburban clusters in the manufacturing function.; Third, the location of economic clusters was closely related to that of the urban population. Review of the maps of the two types of spatial patterns (urban population and commercial clusters) supported this close relationship. Fourth, linear arrangements were detected along the major local roads in Erie County. The commercial clusters were more subject to the location of the major roads than the manufacturing ones. Lastly, with regard to the characteristics of the clusters, the composition of the industry type of the manufacturing companies within and outside the clusters was different with changes over time. The average distances to the CBD and major subcenters increased over time. For the internal characteristics, there were higher correlations between total employment and the number of companies within a manufacturing cluster, and this correlation coefficient decreased over time.