Degree of damages. by earthquake varies with the dynamical signature of the surface soil. Various counterplans have been taken against a probable earthquake in Tokyo, where it has passed over 60 years after the Kanto earthquake in 1923. To estimate the damages by earthquake and also to make an optimum counterplans against it, there needs to know the soil structure in the region and also to make clear the distribution. As for Tokyo 23 wards, the surface soil maps and meshed dangerous degree maps about liquidation have been compiled according to the results of boring surveys carried out so far. The authors approarch a production of such maps by means of remote sensing. This report discribes an examination about the method to classify the soils in the Tokyo area into two categories ; effeminate Alluvia and stable Kanto loam.
Among 64 Landsat MSS scenes of Kanto(Path: 115, Row:35) which EOC of NASDA has received, 3 scenes can be chosen as appropriate ones presenting the similar distribution pattern of surface soil to that seen in the conventional surface soil map of Tokyo 23 wards. Among these 3 scenes, one scene on May 21, 1979 which is considered to reveal the distribution of two types of soil in best is
investigated.
Comparing 4 MSS band images by each, the following becomes clear. Surface soil distribution pattern can not be recognized so clearly in the images of MSS 4, 5, and 6 bands. Whereas, a fairly clear discrimination of soils is seen in that of MSS 7.
Next, the border lines between high and low lands was delineated by observing the enlarged MSS 7 image. This newly described border lines are very similar to that on the conventional surface soil map. A reason of the discrimination of high and low lands in the MSS 7 image may be due to the difference of vegetation.
Finally, the means and standard deviations as of the depth of weak soil strata and the MSS 7 CCT counts in both lands were. obtained on the basis of actual boring data in the lower basin of Tama-gawa. The data distribution for both lands differs a little from each other. This indicates that there is a possibility to classify soil types into two categories using Landsat MSS data.
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