The single mature leaf had higher near-infrared relectance than the single young leaf. In multipleleaf, however near-infrared reflectance of the young leaf was higher than that of the mature leaf.
In order to explain the phenomenon, the seasonal spectral reflectance, transmittance and absorbance of single-leaf and multiple-leaf were measured with a spectrophotometer.
Higher near-infrared reflectance of young multiple-leaf was responsible for higher transmittance of the single young leaf than that of the single mature leaf.
The results suggest that multiple-leaf reflectance should be considered to estimate the vigor of vegetation by using the single leaf as a basic reference.
In addition, some factors which affect the spectral properties of leaves were also discussed.

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By using the brightness tempereture data collected by NOAA-9 AVHRR and the sea surface temperature (SST) data by Mutsu Bay automatic marine monitoring buoy system, the SST estimation accuracy by the split window function (SWF) method was validated. From the archived AVHRR images collected during 1986-1988, a validation data set of 390 match-ups was constructed after a rigid cloud-free and noise-free screening. The temporal and spatial coincidence in each match-up is within 30 minutes and 1 pixel resolution.
A split window function for the SST estimation was derived by applying the regression analysis. Its root mean of the squared errors (RMSE) was 0.59^°C. There appeared match-ups with rather large errors. By referring to the meteorological records of various items at their data collections, it is found that large errors tended to appear when large differences existed between the air temperature and the sea surface temperature. The main reason of the large errors was confirmed due to the sea surface effects, i.e., the vertical water temperature distribution just near the sea surface. The satellite detects the skin SST, but the buoy measures the bulk SST at 1 m below the sea surface. By removing the match-ups with large errors from the original data set, a selected data set having 334 match-ups was prepared and its RMSE was 0.34^°C.

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A contextual image classifcation method with a proportion estimation of the pixels composed of several classes, Mixed pixels (MIXELs), is proposed. The method allows us to check the conectivity of separated road segments, which are observed frequently as discontinuity of roads in satellite remote sensing imagery.
Under the assumption of almost same proportions for the MIXELs in the discontinuous portion of road segments, a proportion estimation method utilizing Inverse Problem Solving is proposed.
The experimental results with the simulation data including observation noise show 73.5-98.8(%) of improvements in terms of proportion estimation accuracy (RMS error), compared to the results from the previously proposed method with generalized inverse matrix. Also usefulness of contextual classification based on the proposed proportion estimation was confirmed for the investigation of connectivity of roads in remotely sensed images from space.

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Remotely sensed data from satellites can provide very useful and important information in earth resources observations. However, satellite images usually include several kinds of distortions.
It is necessary for the correction processing of distorions. The correction methods of a geometic and a radiometric distortions for Multi-Spectral Scanner (MSS) imagery have already developed and become available.
But some problems in a Thematic Mapper (TM) and a High Resolution Visible (HRV) images not to stand out in an MSS imagery caused as follows;
(1) The discontinuity distortion peculiar to TM imagery occurs due to the bi-directional scanning. So this distortion cannot be modelized with the MSS geometric correction algorithm.
(2) The geometric and the blur correction processes can be composed of two filtering processes with an interpolation and blur correction capability. The about 90% of the total processing time for geometric correction spend in the interpolation processing. If the two filtering processes is used, the time is two times as much as the MSS imagery processing.
Therefore, I have proposed the geometric models consisting of separate geometric models of the bi-directional scans and frequency compoments and the geometric correction methods taking into account the correction of the blur.
Consequentry, the development of the high-precision modeling techniques for the discontinuity distortin correction and the high-speed filtering techniques in a geometric and a blur correction are necessary for an advanced hereafter sensors.
This paper discribes about the recent topics a geometric and a blur correction techniques for the whiskbroom and the pushbroom sensor imagery like TM and HRV.

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In recent years it has been feared that the forests in neighborhood of cities and industrial complex are to be ruined by air polution. To deal with such environmental deterioration, it is necessary to conduct a continuous monitoring of the air pollution effect on the forests, especially for the effect of the pollution level caused by sulfur oxides. Since the state of growth of plants shows the history of the atmospheric environment in a habitat from the past to the present, it is thinkable that the air pollution level can be estimated by the index related to the state of the growth of plants. To know the state of growth of plant, it is effective to put the vegetation index acquired from the satellite remote sensing data to practical use. Authors have measured the quantity of sulfur dioxide adhered on the surface of the leaf of Japanese cedar in the neigborhood of cities and industrial complex and found from the ground truth that the larger the quantity of sulfur dioxide adhered to Japanese cedar is, the smaller the ratio of NIR to R of the leaves becomes. (where, NIR: Near-infrared wavelangth range reflectance, R: Red wavelength range reflectance)
In this study, we, taking account of the results of basic research, carried out the examine as follows; (1) the relationship between the adhered quantity of sulfur dioxide on the leaves Japanese cedar stand and the sulfur dioxide level at the collecting site, (2) the relationship between the former and the value of (NIR/R) acquired from the Landsat TM data concerning the Japanese cedar stand from which the sample leaves were collected, (3) the propose a practical assessment method of the state of pollution due to sulfur oxides on the forests in the neighborhood of cities and industrial complex with the aid of the satellite data.

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This paper clarifies a method to predict clear air turbulence (CAT) using the 6-7 micron infra-red image data taken from satellite. The existence of CAT could be estimated, when it is accompanied by clouds. But, there is no way of foreseeing it, when it is accompanied by no cloud.
As for the prediction method of CAT, two ways have been considered. One is a radar method, and another is a method using an infra-red sensor instrument. The former principle is to detect the density difference of water vapor along the CAT layer using high power radar. The later is to detect the density difference of water vapor at the front of the aircraft using a pair of infra-red sensors. However, these methods are not capable of observing the CAT uniformly in the wide aviation area.
Proposed method here is a technique to predict the CAT existence by observing the vertical vibration of water vapor by infra-red observation from satellite, upon the knowledge of the hydrodynamics.
CAT is caused from two main reasons, i.e., jet stream and mountain wave. Position of CAT appearance due to jet stream can be determined relatively to the core position. Jet stream observation by the 6-7 micron infra-red image has been reported already.
Position of CAT caused with mountain wave can be determined relatively also from the mountain wave pattern. This paper shows that mountain wave length and amplitude in clear sky can be detected from the 6-7 micron water vapor image.
Besides, when it is accompanied by clouds, the lower atmospheric wave can be observed simultaneously using the 10 micron infra-red image. Namely, this presents us a vertical profile of mountain wave.
Three examples of mountain wave in the clear sky which may involve the CAT are exhibited here from MOS-1/VTIR data. A direct proof of vertical vibration of the atmosphere was obtained by the observation of the jet trail in the layer.

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