The present paper treats the periodic change of the distribution and characteristics of population in a contemporary Japanese City in cycles of 24 hours, i. e. ‘the daily rhythm of a city’. As a typical case, Himeji City is dealt with; the analysis is carried out in a way analogous to factorial ecology.
The area which is treated is defined by the municipal boundary of Himeji City. Himeji City consists of an old castle town including a central business district, coastal industrial districts with some centrality, and suburbs which are partly rural in terms of land use. Thus Himeji's multi-nuclei urban structure is obvious in view of journey-to-work patterns (Figure 2).
Taylor and Parkes (1975) and others pointed out that traditional studies using factorial ecology had treated exclusively residential (and hence night time) population. Lack of data has been an obstacle to the treatment of population and its change during the day. In this paper, data from a person-trip survey, which was carried out in autumn 1978, are used. From this data, the population was calculated for each time of a day at intervals of an hour, for 51 unit areas of Himeji City, which was classified into subpopulations.
The characteristics and the spatial distribution of the population at nighttime (3:00 a. m.) and that of daytime (10:00 a. m.) are shown in terms of factorial ecology. First, nighttime population data from each of 51 unit areas are inputted to factor analysis. Each input variable is a component ratio of subpopulation to the total population of the unit area; subpopulations mean groups sorted by sex, age, industry, and social subgroups. Then, daytime population data, which consist of the same variables set, are inputted. Five factors are extracted, both for nighttime and daytime respectively.
The five nighttime factors are interpreted as follows.
Factor 1: occupational composition characterized by the contrast between service and factory workers.
Factor 2: age composition.
Factor 3: industrial composition representing heavy industry workers by negative scores.
Factor 4: sex ratio, which suggests also the midnight activity of heavy industry by negative (male) scores.
Factor 5: age composition representing old people over 65.
Figures 3-5 display the spatial distributions of the first three nighttime factors.
The five daytime factors are interpreted as follows.
Factor 1: central business activity, particularly highly loaded by service workers.
Factor 2: contrast between employed and unemployed people.
Factor 3: educational activity.
Factor 4: light industrial activity.
Factor 5: primary industrial activity by negative scores.
Figures 6-8 show the spatial distribution of scores of the first three daytime factors.
Since the above-mentioned factor analysis was applied to nighttime data and daytime data separately, we cannot compare the scores between two points of time in a day. In order to compare the population chracteristics between them, three crude variables are selected from the input variables set: these are factory workers, service workers, and housewives, which were the most representative of the variation of the population characteristics among parts of the city at both two points of time in the day.
Figures 9 and 10 show the component ratio of these three subpopulations of the 51 unit areas for nighttime and daytime respectively. They suggest that in the daytime, unit areas become more differentiated in terms of population composition than at night.
Figures 11-14 show the population for each time of a day at intervals of an hour for four unit areas selected from among 51 unit areas. Each population is classified into seven social subgroups. The Joson area (Figure 11), which is part of the central business district, has a larger population of all the social subgroups in the daytime than at night

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It is important for the study of an urban system to clarify the functional characteristics of each city as an element of the urban system and to analyse the interrelations among the cities. However, the studies of the latter have not been undertaken till now because of difficulties in data collection. Fortunately, migration data for each city during the one year after October 1979 were published in Vol. 6 of the 1980 Population Census of Japan. Using this the writer atempts to make clear the characteristics of interrelations in the Japanese urban system. The results are summarized as follows:
1. The Japanese urban system presents a typical hierarchical structure as seen in Christaller's model. Differing from Pred's model of innovation diffusion, the migration flows between cities of the same order or between larger and smaller cities, independent of tributary areas, are large on neither volume nor proportion. As shown in Fig. 3, Osaka follows Tokyo, the national centre. Then come Sapporo, Fukuoka, Sendai and Hiroshima, regional urban centres. Viewed functionally and structurally, Nagoya also is included in this group. Following it appear central cities, mostly consisting of prefectural centres, that get nodal flows of over 10 percent from some cities of smaller scale within their own prefecture. Yokohama, Kyoto and Kobe, in the Tokyo and Osaka metropolitan areas respectively, are considered as satellite centres; they do not attain the level of functional allotments in each metropolitan area.
2. As seen in Fig. 1, the metropolitan dominance of Tokyo has expanded remarkably. Not only Ibaragi, Tochigi and Gumma prefectures in the northern Kanto district, but also Fukushima in Tohoku, and Yamanashi and Nagano in the Chubu district are included in its area. It seems that in these prefectures the prefectural centres, occasionally in conjunction with the second largest cities, had once formed their own local urban systems.
3. By the analysis of social increase of the urban population and the net migration ratio of nodal flows for each city, three types of cities are recognized (B, C and D types as shown in Fig. 4). Most of the smaller cities with less than 100, 000 inhabitants show a social decrease and net out-migration to central cities so that they continue to decline as before. Although the return migrations to native town or to neighbouring larger cities has normally been recognized since Japan's high economic growth period (about 1960 to 1973), these phenomena account for only a part of out-migrants. On the other hand, central cities and regional urban centres show social increase in spite of the net out-migration of nodal flows to metropolitan centres. Accordingly, we can see that such central cities and regional urban centres play a role in absorbing the population from surrounding areas and losing their own population to metropolitan centres. Within the metropolitan areas, satellite towns continue to increase in population, not only from natural increase of their own population but also from the net in-migration from the metropolitan centres. Therefore, as long as such migration flows continue, the hierarchical structure of the national urban system will continue to be developed and at the same time the regional disparity between metropolitan and non-metropolitan areas will continue to expand in contrast with Western countries.
4. The metropolitan areas such as Tokyo, Osaka and Nagoya continue to dominate a hierarchical structure. Intermetropolitan migration between them has not been developed until now. Because of the dominance of nodal flows, the second or third largest flows, such as the inter-metropolitan migration between Osaka and Nagoya, are not so great in volume. Without structural changes in the urban system, we cannot say that the Tokaido Megalopolis is completely formed.

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The distribution of warehouses in Japan is highly concentrated in Aichi Pref. and Shizuoka Pref. by comparison with other prefectures. Predominantly stored items of each locality are iron and steel, wheat, beans, other cereals, and tobacco leaves in the Nagoya Port area; food in commercial areas of Nagoya and Shimizu City; textile goods in Ichinomiya City and Fukui City; paper and pulp in Fuji City, and chemicals in Yokkaichi City.
The warehouses are grouped into three types: warehouses in producing areas, those in transit areas, and those in consuming areas. Warehouses in Ichinomiya, Fuji and Fukui are those of the producing-area type; those in the Nagoya port area, Tobishima Village, and Tokai City are of the transit-area type; and those in commercial areas in Nagoya are of the consuming-area type, in the main.
Factors affecting the location of warehouses in the textile-centered producing areas of Ichinomiya and Fukui lie in the division of labor in the production processes and the seasonality of demand; and those in pulp-and-paper producing Fuji and chemical-producing Yokkaichi lie in stagnant freight trading at harbors, and the existence of the consuming-area warehouses corresponds to consumers' demand in the built-up areas of highly centralized cities.
Major conditions affecting the location of a warehouse are: for producing-area warehouses, the producer's development of a stock-reducing plan. Transit-area warehouses are indicated by quantity of goods and intended handling at a harbor. Positional relation to central megalopolises is critical for consuming-area warehouses.

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