Remote sensing techniques have provided new scientific tools for measurement of specific quantities in natural environment. However, techniques for measuring groundwater level or soil moisture from LANDSAT MSS data are now under development by many groups. We have been conducting feasibility study for measuring groundwater level or soil moisture of Takasu Polder located at estury of Nagara River. Our final purpose is to apply this method for estimating the effects of the rise of groundwater level due to backwater of Estuary Dam now under planning.
As a first step we intended to analyze the relation between LANDSAT image and groundwater level, using 9 LANDSAT scenes and observed groundwater level data at 10 points. At Takasu Polder region, groundwater level is about 50 cm below ground surface, therefore it is not irrational to assume that the groundwater level affects the moisture content of ground surface, and resulting change of the reflection characteristics of ground surface affects the LANDSAT image.
This paper describes some results on processing techniques and regression analysis. Main results obtained up to now can be summarized as follows.
(1) Land use categorization from LANDSAT MSS data can be attained by two seasonal composite data than one seasonal data. Paddy field in the study area was extracted from two seasonal LANDSAT MSS data.
(2) Following regression equation with a correlation coefficient, 0.89, was obtained for the estimation of groundwater level in the case of no vegetation on paddy field.
These coefficients are applied to the LANDSAT data on December 1. 1980. Also, following regression equation with a correlation coefficient, 0.75, in the case of vegetation on paddy field was obtained.
These coefficients are applied to the LANDSAT data on September 8. 1979 and September 2. 1980. Here, ymeans the distance from groundwater level to the ground surface. X₄, X₅, and X₇ are the values in each band of LANDSAT MSS data.

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A mapping system of NOAA/AVHRR data in large area was developed. Conformal double conic projection was applied to the AVHRR imagery covering the range of about 3, 000 km x 4, 300 km extending over India, Himalaya, and Tibet. Mapping accuracy was performed at 2.2 pixels (about 2.4 km on the Earth surface) in standard deviation Color expression of projected imagery was discussed as of the false IR color expression and false natural color one composed of two AVHRR channel imageries.
Next, Asian Highways and Silk Roads were described on this satellite imagery. The new road map on the satellite imagery can be said a kind of satellite photomap. Compared with conventional layer tints map expressing topography in some school atlas, this satellite photomap seems to be different from them. The authors discussed the features and application feasibility of this newly developed satellite photomap especially in the point of basic requirement for map expression, namely, the fidelity of representation of land shape(topography) and land color (color of landscape). This satellite photomap may be useful to inform us general information of large area, like as vegetation distribution, geological structure, or climatological division.
The authors have an opinion that this satellite photomap should be adopted for school atlas. In the case, considered as a kind of thematic map like as vegetation map, or climate map, etc., conventional layer tints map can be compatible. Namely, users of new atlas will find general information of the land feature from the satellite photomap in the first place, and then, face to conventional thematic maps. Geographical understanding of users will become accurate.

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Meteorological interpretation is conducted concerning the cloud features associated with four different synoptic situations as revealed in the GMS satellite pictures.
Emphasis is placed upon the importance of the following four aspects :
(1) The difference among three small-scale vortical cloud patterns associated with winter cold air outbreak over the Sea of Japan,
(2) The usefulness of specially processed infrared data in the analysis of active convective clouds producing torrential rains,
(3) The cloud evolution in the formation stage of Typhoon 8218 Judy and interaction between the Typhoon clouds and a frontal cloud band and
(4) Severe-storm-producing sharp western edge of the cloud system associated with a developing cyclone.

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Since January, 1979 Landsat Multispectral Scanner (MSS) and Return Beam Vidicon (RBV) data have been received, processed and stored at Earth observation Center (EOC) of National Space Development Agency of Japan (NASDA) in Hatoyama, Saitama Pref., and have been distributed to various users.
In this paper a rather plain explanation is attempted to introduce the process of Landsat-4 MSS data reception, processing of computer compatible tapes (CCT's) and photographic products, and their storage and retrieval at EOC.
In the explanation of the process, the present system in operation is devided into eight subsystems, i.e. receiving, recording, quick-look, imagee data processing, products generating, photographic processing, data inspection-and-evaluation and data storage-and-retrieval subsystems, and their functions, operation flows and the relation among these subsystems are shown including facility photoes and operation snapshots.
This paper will be usefull too in understanding the Landsat Thematic Mapper (TM) data receiving, processing and retrieval system which is planned to be operated also at EOC in future.

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This paper concerns a digital signal processing system for the SEASAT-SAR imagery developed by the Radio Research Laboratories. The system consists of two major parts, those are the host minicomputer and the array processor. High speed processing of SEASAT-SAR imagery is realized by means of following techniques ; (1) Data transfer between the host mini-computer and the external memory, calculation in the host mini-computer, and that in the array processor are performed at the same time, and (2) Doppler FM rate of the echoes are approximated by the third-oder polynominal with respect to the range pixel number to reduce an amount of autofocusing process. This system attains the speed of approximately 5 hours to produce a SEASAT-SAR image of 34 km x 60 km using 4-look overlay.

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