Risk evaluation to identify the occurrence of landslide has been performed so far mainly by the interpretation of aerial photograph, exploitation and observation at actual site. However, there are many problems in conventional method for evaluating wide area at uniform accuracy. One of the methods to solve such problems would be to utilize the remote sensing technology as an objective observation method. Remote sensing makes it possible to increase the contact points with GIS, and provide image analysis from comprehensive viewpoint using various image information over multiple dimensions.
This paper reports on the investigation made to specific area among the landslide area of Tertiary formation in Niigata prefecture using SPOT data, where we grasped the wide area from macro viewpoint and tried to study the possibility of extraction and renewal of landslide information.
This paper places primary focus on the analysis of information about the factors which cause the slide of land, taking advantages of the characteristics of remote sensing techniques, and is composed of the following study components.
(1) For the study area where the landslide occurred already, we tried to analyze the factors to have caused the landslide from the land conditions around there. (Step 1)
(2) Basing on the analysis result of factor information obtained in step 1, we tried to extract landslide points over the wide area using the overlay technique of images. (Step 2)
(3) Using the landslide points information obtained by step 2 and the information on the points of landslide already occurred, we tried to update the landslide distribution information applying overlay technique of images. (Step 3)

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Bed gases (radon and thoron) behaviors of the following geotectonic lines were clarified by the airborne gamma ray remote sensing with a helicopter; Tanakura line dividing the Japanese Islands into southwest and northeast, Itoigawa-Shizuoka line traversing the Islands from north to south, and Median Tectonic line dividing Southwest Japan into inner zone and outer zone. As the results of closer investigations, some excellent relations were recognized, as followings;
(1) For non seismic zone: Thoron, thoron/potassium and thoron/radon in Abukuma mountainland (mainly andesite and metamorphic rock) are rare.
(2) For collapsed zone: Radon and thoron in great land failure zone (Shimanto group) on Mt. Shichimenzan are plenty.
(3) For bed water (in Shimanto group) : In case of lower pressure of pore water in the bed, radon increases but thoron/radon decreases.
(4) For geotectonic lines and diastrophism: Thoron, thoron/potassium, and thoron/radon increase in order of Tanakura line, Itoigawa-Shizuoka line, and Median Tectonic line in proportion to the scales of tectonic movement.
In conclusion, in Abukuma mountainland where bed gases are unactive, no evidence of the active faults and the distructive earthquakes shows. However, on Median Tectonic line where bed gases are active, some large scale earthquakes had occurred in the geological age.

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Solar zenith angle (SZA) dependence of NDVI from NOAA AVHRR data is clarified by the simulation using LOWTRAN7 based on 10 atmospheric models and 4 surface models. In the simulation, the effect of SZA to radiative transfer is taken into account. It becomes evident that NDVI decreases and NDVI contains much path radiance in larger SZA condition. It can be concluded that in a limited condition when the atmospheric condition is uniform, NDVI with SZA less than 80° is correctable by an approximated formulation of SZA dependence of NDVI (5th. order polynominal of cos (SZA) ) . For more precise correction, it is necessary to estimate atmospheric condition.

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We have been provided confusion to some extent by several explanations of dissimilar meanings with respect to a scientif ical terminology.
This paper shows a semantic problem concerning stochastic error term stood for “mean square error” (MSE) which does not exhibit only “root of mean of squared errors” in surveying and photogrammetry, but also indicates “average of squared errors” (or residuals) in statistics.
Therefore, it is highly recommended even in surveying and photogrammetry that precision and accuracy illustrated a dispersion and an extent of measurements, respectively, should be utilized variance and MSE (square of “RMS” (root mean square) error) which can be obtained with sum of squared differences between measurements and most probable parameter (or true value), divided by number of observations, or redundancy of them. Similarly, definition of “MSE” in statistics makes variance added to squared bias (systematic error) .

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