In this study, characteristics and usefulness of the land cover image classified photo taken by a digital camera were discussed on the slopes of Hiiji-dake, Kuju Mountains.
The geometric correction using affine transform was applied to the images of 5 triangle areas in a taken image. The corrected image could be classified into six area types, Rhododendron kiusianum, thicket full of Alunus firma S. et Z., grass land, damaged area by insects, and others by maximum likelihood method. Considering the present relationship between land cover classification and landforms, the stable area of crest, upper sideslope and lower sideslope is dominated by Rhododendron kiusianum and the unstable area of side-hollow is dominated by thicket full of Alunus firma S. et Z. According to the land cover image classified aerial photograph before 30 years, the area of lower sideslope and side-hollow was dominated by grass land larger than now. So we can estimate that the area was more unstable than now. We think that the land cover data by the digital camera are useful for estimation of stability on the slope.
Where the target slopes about 200 meters away from the taken point, the difference in coordinates between the corrected images are estimated less than 1 meter. In this study, it cleared that the coverage rate of the each land cover classification is about 80 % on an average. The rate fluctuates about 20 % by a reason of the seasonal color change of leaves, flowers and damage by insect. The area of Rhododendron kiusianum and thicket full of Alunus firma S. et Z. tend to be larger in flourishing season and smaller in defoliate season.
Consequently, the photos taken by the digital camera can be used for the useful land cover classification maps, and we can estimate landforms in detail by maps. In the study on environmental problem and natural disaster, a lot of kinds of uses are to be expected on the photos in GIS analyses.

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In this paper, we describe characteristics of streets in Japan and France using an image map questionnaire.
Nowadays, in developed countries like Japan and France, two contradictory aspects in the street space could be found. One is a functional homologousness regarding motorization, and the other is a cultural heterogeneity as a public space.
This space in Japan and in France might be different from a semiotic point of view. “TORI” in Japanese and “RUE” in French is translatable designation of street (signifiant). But each designation might have different meaning (signifie).
The image is focused to describe a cultural meaning of street space. The image is not just a copy of perception, but it is an expression of meaning of the object. Then, the image map questionnaire that asks images of streets is used as an investigation method.
To analyze data from questionnaires, we propose “Matrix Ordonnable (orderable matrix)” as an analyze method that was developed by J. Bertin. In “Matrix Ordonnable”. the numerical data of matrix is replaced by the pictorial figure. That lets us visually review relations of all data. Comparing to reading a numerical statistical matrix, “Matrix Ordonnable” : visualized matrix is assumed to reduce the time to recognize all relations of data in the matrix.
As a result, characteristics of streets in Japan and France could be explained by common elements of images. Some particular equipments or peculiar uses in each culture are not only representative factors to explain the street space in Japan and France. We find also an ambiguous distinction among the streets in Japan. In France, there is a clear distinction between spaces for automobile and for pedestrian. However, Japanese street space does not have such a binary distinction, but polythetic distinction.
This characteristic could be also found when we observe a hierarchy of street on map. The streets in Japan can be presented with using tree scales of map. On the other hand, in case of France, we can see them by two scales of map. Therefore, Japanese street space is pointed out by multiply layered maps.
The analysis by the “Matrix Ordonnable” let us observe basic elements with which streets spaces are composite. Even if replacing numerical data to pictorial figure lost the stringency of the data, this method enables us to observe and to search visually useful information from data.

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