| dc.description.abstract | What activities are located where and why? This is a fundamental question in urban studies, which should be answered before planning. In urban economics, fine mathematical models have been developed and have provided an internally consistent economic framework for answering these questions. However, as cities grow and get larger, the spatial structure of cities has changed and become increasingly complicated. The emergence of sub-centers and socioeconomically distinct clusters within the metropolitan areas weaken the assumptions on which the urban economic models are based. Also, there are increasing needs of the people and space interaction models at the micro level, or neighborhood level. This thesis revisits this fundamental issue in a different way. In particular, it investigates the spatial patterns of residents within the metropolitan areas at the census blockgroup level, using Database Management Systems (DBMS) with Structured Query Language (SQL), Geographic Information Systems (GIS), and statistical methods including factor analysis and cluster analysis. What socioeconomic factors make one type of neighborhood different from another within the metropolitan areas? This thesis finds four common socioeconomic factors; baseline factor, children factor, income factor, and age factor. Baseline factor shows that the major generic whites are, roughly speaking, more likely to be citizens, to speak only English at home, to drive to work, not to be poor, to own homes, and to live in the lower population density areas. These above variables move synchronously, so we can reduce them into one factor which we have abbreviated as the 'baseline factor'. Using the same factor analysis, we developed the four such socioeconomic factors above. Then, I investigate where they are located? In all four metropolitan areas there are wedges of clustered neighborhoods with similar socioeconomic characteristics around the urban center. Each section contrasts with each other, for example, rich versus poor, or white versus non-white. Younger people formed their own wedges, too. Second, the downtown and subcenters, where the jobs are located, are more likely occupied by non-whites or low income individuals. So, they also appear along the circumferential highway corridor where the subcenters are located. In addition to the common pattern over all metropolitan areas, each metropolitan area also has its own peculiar characteristics. In the Boston Metropolitan Area, the delineation of socioeconomically different neighborhoods coincides with town boundaries. That is, the characteristics of neighborhoods are discrete rather than continuous over the space. In the Chicago Metropolitan Area, the percentage of citizens is another key factor differentiating neighborhoods, and, hence, noncitizens occupy a separate cluster. The unique geography of the San Francisco Metropolitan Area creates two stark types of neighborhoods; affluent neighborhoods at the west of the bay along the ocean, and poor neighborhoods at the east of the bay, especially at the entering points of the bridges to the downtown. In Dallas Metropolitan Areas, the geographic contrast between rich and poor neighborhoods are clearer, i.e., the northern area is wealthier while the southern area is poorer. In this thesis, I find the key socioeconomic factors characterizing the neighborhoods and the spatial pattern of residents. Also, I developed a different methodology to look at this issue. This study gives us a foundation for micro level urban simulation modeling by providing a systematic method of quantifying neighborhood characteristics in ways that can be incorporated into economic models. Furthermore, we can analyze the urban structure of diverse land uses over space and time simultaneously. This can make participatory planning far easier by supplying a clear picture of a city's profile, stimulating communications, and facilitating understanding among residents. | en_US |
