大阪大都市圏の24時間構造 : 時空因子生態からのアプローチ
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This paper treats the space-time structure of the socio-demographic characteristics and activities of the Osaka Metropolitan Area in cycles of 24 hours.This method is based on Space-time factorial ecology first devised by Taylor and Parkes (1975), for which there has been no case study applied to metropolitan areas like Osaka. But it is not always possible to extract factors that have clear meaning when the socio-demographic and time-budget variables are inputted together as in Taylors original formula, because the two types of variables show different behaviour in ‘space-time’ as follows:1) The socio-demographic characteristics are invariable in relation to each individual over ‘time’, but in aggregate (zonal) level the characteristics are variable when travel by the individual occurs.2) The time-budget characteristics are closely tied up with spatial distribution of each establishment and are variable over ‘time’ in accordance with diverse urban activities.In addition, there also exists the problem of coarse classification of industry and occupational status for the available data sets.In order to improve the above mentioned problems and to construct a model of complicated space-time structures of metropolitan areas, the analytical technique of cross-aggregation is introduced which enables one to select variables suitable for space-time analysis, and the analytical framework is divided into two parts, from both the ‘travel’ and the ‘activity’ points of view:«Travel in Space-Time Analysis: TSTA» is an analysis using subdivided socio-demographic variables in each space-time unit (STU) and OD flow between two successive times, in order to search for distribution and travel of specific socio-demographic groups, and«Activity Space-Time Analysis: ASTA» is an analysis using cross-aggregated variables {socio-demographic × activity place} in each (STU), in order to classify (STU)s from activities which occur in them.Then, the results of these two analyses are integrated‘stereographically’ to construct the intra-urban structure from both activities in (STU)s and subpopulation travels which connect them(“Urban Dynamic Map”).A) «TSTA»For«TSTA», procedures outlined below are followed:A1. From the cross 64 combination {industry 8 items × occupational status 8 items}, 37 subdivided cross-aggregated variables are acquired. Then a more precise occupational classification is attempted by applying these 37 variables to space-time factor analysis.A2. The occupational subgroups constructed from space-time factorial ecology are extracted from the result.A3. Next the flow pattern of each subgroup existing behind the changing score pattern of space-time factor analysis is investigated.Seven factors are extracted. The earliest four factors in particular are interpreted as follows:Factor 1: white-collar workersFactor 2: transportation and communication sector workersFactor 3: manufacturing workersFactor 4: personal service employeesIt is obvious from the factor loading structure (Tab. 1) that (1) there exists some difference between daily travel-activity patterns of clerk/managers and that of field workers, in {industry × status} types.It is recognizable from the score pattern (Fig. 2) and the travel pattern of each extracted subgroup (Tab. 2) that (2) there exist differences of separation and adjacency of residence and workplace, in regional/occupational types.In tertiary sectors, the difference between daily travel-activity patterns of clerk/managers and that of personal service employees caused a separation into two factors (Factor 1 and Factor 4). Patterns of Factor 1 represent the separation of residence and workplace between the suburbs and the urban core.
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