The author summarized a history of development of groundwater hydrology in Japan. In general, the historical development of hydrology can be viewed through a series of periods and through series of events and articles such as number of books, papers and theories related to groundwater studies.
Correlating to the historical division of Chow, Ven Te and that of Hida, N. et al., he proposed the division of development of groundwater hydrology in Japan as follows:
a) Period of noninterference study (_??_1940), I-II₁
b) Period of study of researcher's own free will ('40_??_'50), II₂
c) Period of study under governmental readerships ('50_??_'55), II₃
d) Period of cooperation with government and researcher ('55_??_'60), II₃
e) Period of independant and free study ('60_??_date), III
Since these periods may overlap, their time division should not be considered exact. Generally speaking, all stages correspond to that of Chow's but those begin on about ten years later than those of western one.
He tried to explain such a stage of development by political and socio-economic situations and stimulation of UNESCO's IHD. Because groundwater science is an interdisciplinal and practical science for needs of water resources in a country.
Finally, he pointed out present problems of modern groundwater sciences on data with regards to accurracy, collection and coordinations, terminology and its redefinition, and groundwater law in Japan.

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The purpose of this paper is to present a couple of useful measurements for the analysis and evaluation of land use in suburban area and to discuss some results of the research with an application of those measurements to Sohka-city located at the urban fringe of Tokyo metropolitan area. The paper is made up of the following five sections;
I Introduction
II Research design
III Results of research
IV Simulations
V Administrative implications of the results of research
The first section is a brief introduction of the problems with which we considered in this article. It is emphasized that various “environmental” problems occurred in local scale are often derived from the “too diversified and mutually inconsistent” land use in the administrative area.
In the second section, the research framework is presented;
1) Definition of the categories in land use is given as Supplement.
2) Given those categories, the administrative area of Sohka-city is devided into 490 unit areas each of which has the size of 1/16 as a basic cell in the Standard Mesh System (Japan Grid Reference System), and the land uses of 100 points in each unit area are identified. Basic data source for the identification is aerial photographs (scale=1: 8, 000). Topographical maps (scale=1: 25, 000) and the directions of public facilities are used as supplements.
3) A couple of measurements for land use evaluation are defined. Among them the following two measurements should be mentioned.
^*) Degree of diversification of land use
_??_
where P_i is percentage of i th land use category in the unit area.
^**) Degree of negative interactions
_??_
where I_ij is the degree of influence of i th land use on j th land use which is defined as I_ij=P_iP_j. Sij is a element of the matrix of negative interaction which indicates the negative interaction between i th land use and j th land use.
The third section presents some results of the analysis and they are summarized as follows:
1) Although major portion of the city area is devoted to urban use (43.1%), a large amount of land is still remained for rural and transitional uses which comprise 33.9% and 23.0% of total area respectively.
2) The category which has the largest share is cultivated land (23.4%), the second is low story dwellings (17.1%) and the third is the land in development (9.6%).
3) Relatively high share of transitional use and the land in development indicate that the city is now undergoing a series of socio-economic and physical changes which are generally considered to reflect rapid transformation from rural to urban land uses.
4) One of the problems derived from such changes is the mutually inconsistent usages of land.
5) Fig. 8 and Fig. 9 shows a series of maps each of which indicates the diversity of land uses, the degree of negative interaction and the final evaluation of land use for each unit area.
The fourth section is a summary of results of simulation and the administrative implication of those results are discussed in the final section.

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There are two viewpoints in recognizing regions in geography, homogeneity and functional organization. It is necessary, in seeking spatial structure or regional structure, to investigate not only from an aspect of homogeneous regions but also from an aspect of functional or nodal regions.
Recently multivariate analyses(especially factor analysis and principal component analysis) have been employed in geography due to the development of computer and remarkable progress in statistics. As a consequence of these developments, objective and synthetic analyses have become more common in researches. Since the structure of homogeneous regions based on regional characteristics and the structure of nodal regions based on inter-regional flows are understood to a certain degree, attention is now directed to interdepen-dency between the two structures and the spatial structure as a whole. The purposes of this paper are firstly to reveal the structure of homogeneous regions based on socio-economic characteristics (Table 1) and that of nodal regions based on interregional journey-to-work, and secondly to examine the interdependency between the two structures. The study area is Nagoya Metropolitan Area (Fig. 1). The method of this study is similar to the frame-work of Berry's general field theory of spatial behavior. The main results are as follows:
1) Structure of homogeneous regions based on socio-economic characteristics
By factor analysis of socio-economic characteristics of 59 unit areas, eight factors account-ing for 85.68% of the total variance were extracted (Table 2), and interpreted as follows: (1) commercial activities (34.08%), (2) manufacturing activities (16.31%), (3) white collar employment (9.13%), (4) agricultural activities (8.19%) (5) population dynamics (6.45%), (6) age structure of population (4.70%), (7) urban land-use (3.60%), (8) employment in secondary and tertiary industries (3.22%).
Factor one (commercial activities) has the highest percent of explanation, but the other seven factors also have specific meanings. In the spatial arrangement of fac toe scores, concentric spatial patterns for the 1st, 3rd, 5th, and 7th factors were readily recognized (Fig. 2-a_??_h). On the basis of factor scores on the eight factors, the 59 unit areaa were integrated by Ward's hierarchical classification. The integrated regions showed a concentric pattern (Table 3 and Fig. 3). That is, it became clear that the structure of homogeneous regions based on socio-economic characteristics in the Nagoya Metropolitan Area was mainly prescribed by the eight factors mentioned above, and spatialy there was a distinct concentric pattern centering around Naka-ku.
2) Structure of nodal regions based on interregional journey-to-work
The interregional journey-to-work matrix (59, 59) was subjected to R-mode factor analysis, and eighteen factors were extracted (Table 4). On the basis of factor loadings (_??_|0.4|) and factor scores (_??_|1.0|), the 59 unit areas were grouped into 19 nodal regions by Goddard's method (Fig. 4-a_??_f). Each nodal region is composed of continuous unit areas and overlaps partially with other regions. Five nodal regions which were closely connected with the central city Nagoya were identified. Consequently, the structure of journey-to-work regions is characterized by a large number of small regions and the stratification of the regions.
3) The interdependency between the structures of homogeneous regions and of nodal regions
To summarize the interdependency between the structures of homogeneous regions and of nodal regions, canonical analysis was applied to factor score matrices of socio-economic characteristics (59, 8) and interregional journey-to-work (59, 18). Three statistically significant canonical variables were synthesized. A canonical variable isolates an aspect of complex spatial covariation of many regional phenomena by decomposing and reintegrating them.

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The purpose of this paper is to examine the questions raised by John W. Alexander (1954), by analyzing 97 cities in Japan with the index of surplus workers as shown below:
_??_
where S refers to the number of surplus workers (basic activities), C to each city, N to the nation, i to the number of employed persons of each industry, and t to what demands each industry. In this paper employed persons working outside their resident city are aho considered surplus workers because they bring their wages into the city.
In the above formula John M. Mattila and Wilbur R. Thompson (1955) used total employment for t. If we use what demands directly each industry in place of t however, we can obtain a more accurate measure of basic activities. For that purpose we first convert the 1970 Input-Output table in terms of producers' prices into the I-0 table in terms of employment. Then assuming that the individual demand sectors of the table, except the three sectors of primary industry, increase in stock, and export, are what demands each industry, we calculate the number of employed persons each city needs, Di(Ct•Ni/Nt), with the ea uation shown below.
_??_
where j refers to each of the individual demand sectors, and Xij to employment in industry of the sector j. The letter t refers to employment in each industry as to each of the individual intermediate demand sectors, to population as to private consumption-expenditures sector, to the number of office workers of non-primary industry excluding government as to both consumption-expenditures outside household and gross domestic fixed-capital-for-mation sector, and to the number of office workers of government as to government con-sumption-expenditures sector.
Cities for this paper are selected through the following procedure;
We can use only the statistical data of administrative city unit in Japan. However, the administrative city is hardly in accordance with the urbanized area. In many cases the former extends far beyond the latter, and the disaccordance between the two areas varies from city to city. In order to get the criterion for selecting cities, we analyze the industrial structure in terms of employment of densely inhabited districts (DIDs). The DID is instituted as the sole statistical urban area in Japan since the 1970 Population CensLis. The primary industry ratio is under 5% in 80% of 565 DIDs within 579 adminbtr ttive cities.
The administrative cities are divided into two groups, those located within Tokyo or Osaka metropolitan region and the others. In the first roux. there are 32 cities whose primay-industry ratio is under 5 per cent, and all the 52 cities are selected for the analysis. For the cities in the second group, the criterion ratio is raised to 7%=for the cities with more than 300, 000 people, and to 9 per cent for the cities with 200, 000 to 299, 999 people to make the difference between the numbers of selected cities of the two groups as small as possible. Forty-five cities are selected from the second group in the above manner for the study, waking the total number of selected cities 97.
The outline of the results that were obtained by the analysis is as follows:
1) As the population size of tie city increases, the N/B ratio tends to increase. When we divide the 97 cities into 44 independent cities that have less than 100 employed persons working outside the city per 1, 000 inhabitants and 53 dependent citis that have more than 100, we find that the above-mentioned trend is more distinct (Fig. 2). Generally, the N/B ratio of an independent city is higher than that of a dependent city of the same size,
2) The N/B ratios of the independent cities show a discontinuity at the population of ap-proximately 150, 000.

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In dieser Arbeit wurden die Landnutzungsformen in den nordwestlichen Randgebieten von Hamburg klargemacht. Das Untersuchungsgebiet umfaßt folgende Stadtteile von Hamburg: Lurup, Groß Flottbek, Osdorf, Nienstedten, Sülldorf, Iserbrook, Blankenese, einen Teil von den Stadtteilen: Eidelstedt, Bahrenfeld, Othmarschen, Rissen and Gemeinden von Scnleswig-Holstein: Schenefeld and einen Teil von den Gemeinden: Halstenbek, Pinneberg, Appen, Holm, Wedel (Abb. 1). Dieses Gebiet verstädtert sich besonders schnell; Einzelhäuser, Hochhauser, Einkaufszentren, Industrie wurden gebaut. Aber in Hamburg and semen Vororten wird der Flächennutzungsplan genau entworfen. Auf Basis diesel Plans sind strenge Regel einzuhalten, darum kann man in diesem Gebiet ordentliche Landnutzungsformen beobachten.
Um diese Arbeit durchzuführen, wurden zuerst vom November 1973 bis März 1975 die Landnutzungen untersucht and 27 Landnutzungskarten (1:5000) gezeichnet. Dabei wurden die Landnutzungsarten in 29 geteilt: 1. Einzel- and Großhandel, 2. Service, 3. Finanzen, 4. Unterhaltungen, 5. multifunktionelle Geschäfte, 6. Handwerk, 7. Industrie, 8. Einzel- and Reihenhäuser, 9. Hochhäuser and Wohnblöcke, 10. Sozialfunktionen (Krankenhaus, Altesheim usw.), 11. öffentliche Funktionen (Schule, Polizeiamt, Feueranstalt usw.), 12. Friedhof, 13. Kaserne, 14. Parkplatz, 15. Park and Grünland, 16. Sportplatz, Golfplatz Spielplatz and Rennbahn, 17. Straßen, 18. Bauernhäuser, 19. Ackerbau, 20.Obstbau, 21. Baumschulen, 22. Blumen, 23. Weide and Weide, 24. Schrebergarten, 25. Wald, 26. Heide, Moor and Sumpf, 27. Ödland, 28. unbenutzt, 29. anders. Danach wurden auf die Landnutzungskarten Gitternetze (200m×200m) gestellt and anhand der Dot-Methode die Prozentsatz jeder Landnutzungsart für jedes Gitternetz gerechnet. Dann wurden die Gitternetzkarten, in denen der Prozentsatz der Landnutzungsarten über 1% beträgt, gezeichnet and damit die Verbreitungsformen jeder Landnutzung klargestellt.
Auf diesen Verbreitungsformen hin die Landnutzungsformen dieses Gebietes erklärt. Bei der Betrachtung der Landnutzungsformen wurden 29 Landnutzungsarten in 11 umgruppiert: (1) Handel...1, 2, 3, 4, 5, (2) Hochhäuser and Wohnblöcke...9, (3) Einzel- and Reihenhäuser...8, (4) Industrie...6, 7, (5) öffentliche and Sozialfunktionen...10, 11, (6) Beförderungsanlagen and Kaserne...13, 14, (7). Straßen...17, (8) Erholungsanlagen and Friedhof...12, 15, 16, (9) Bauernhäuser...18, (10) Agrarland...19, 20, 21, 22, 23, (11) Quasiagrarland...24, 25, 26, 27, 28, 29.
Schließlich wurden von der Weaver-Methode (von K. Doi) die Kombination der Landnutzungsarten in jedem Gitternetz berechnet (Abb. 8) and die Landnutzungsformen dieses Gebietes ausgewählt.
Das Gitternetz jeder einzelnen Landnutzungsart ((1), (2), (3), (4), (5), (6), (8)) oder das Gitternetz, das aus dieser Landnutzungsart and eine anders bestehen, wurden als Handels-, Hochhäuser and Wohnblöcke-, Einzel- and Reihenhäuser-, Industrie-, öffentliche and Sozialfunktionen-, Beförderungsanlagen- and Kaserne-, and Erholungsanlagen- and Friedhofsgitternetz bezeichnet. Das Gitternetz, das aus Agrarland, Quasiagrarland, oder Agrarland and Quasiagrarland, oder Agrarland and eine andere Landnutzungsart oder Quasiagrarland and eine antlers bestehen, warden als Agrargitternetz bezeichnet. Pas aus drei and mehr als drei verschiedenen Landnutzungsarten bestehende Gitternetz wurde als Komplexgitternetz genannt. Auf Basis oben erwähntes wurde Abb. 9 gestellt. Das Untersuchungsgebiet konnte mit den 9 verschiedenen Gitternetzen dargestellt werden.
Von dieser Abb. 9 and der Verbreitungsformen der Landnutzung ausgehend, können die Landnutzungsformen dieses Gebietes in Abb. 10 gezeigt werden.

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