The purpose of this study is to propose a method to measure sensible heat flux from rough ground surface by using mirrors with scintillation method in order to actualize for setting scintillometers in free place of urban areas. We focused on that the values of sensible heat flux measured even at the different height in constant flux layer could be assumed to be equal. So we proposed an algorithm for estimation of sensible heat flux from measured values by multi-altitudes measurement using scintillometers. To measure by switching laser beam altitudes, we designed a system for multi-altitude measurement for switching altitudes, with combination of mirrors for reflection of laser beams. Measurement was performed on a flat field, and influence of crosstalk did not appear with the measurement result of sensible heat flux except at some particular incident angles. Then to evaluate our system and algorithm, a measurement was performed for two altitudes of one meter and two meters from ground surface on the paddy field. The measured values of sensible heat flux by gradient method and scintillation method almost agreed, therefore our system and algorithm was effective for estimation of sensible heat flux from such rough ground surface.

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A new analyzing method of atmospheric wave propagation in the GMS data is developed using wavelet transformation (WT). The first one of two parameters (dilatation and translation) which are variables in WT is fixed in specified period on the subjective waves. Behavior of the waves is inspected by arranging those results on each point sequentially. This method is applied to GMS IR time sequential data sets (1980-1994) covering the semi-global area. 5 days variation in ITCZ (Inter Tropical Convergence Zone) and inter-seasonal variation are analyzed as typical samples of this method. Intensities on time axis, wavelengths and wave velocities of subjective waves are shown by time vs. longitude diagram. Distributions of the waves are also shown by time cross sections of latitude, longitude and time. This analyzing method is very useful to study atmospheric waves using GMS data.

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Characteristics of the category classification methods for remotely sensed multispectral image data has been mainly evaluated by correct rates of classification, which are given with diagonal term of the confusion matrix. This evaluation method cannot sufficiently considered the information, which off diagonal term of this matrix gives, and the evaluation is in aspect like. In this paper, the characteristics and the tendency of the classification methods are asserted in such a way that it should be analyzed using the whole of this matrix.
Next, an evaluation method using dendrogram is presented as an example. The merit of proposed evaluation method is able to evaluate the relationship among the hierarchies of categories ; here each classification method has been defined. Similarly, recognition and resemblance tendency of categories of a human sense can be also analyzed. It is meant that if the result of the trend analysis among classification methods is compared, it cannot to prove only the classification accuracy but evaluate in the relation with a human sense for various categories.
This example points out the existence of various problems to be discussed in future, that is, the relations between the utilization purpose of a user and statistical category classification method based on spectral characteristics. The evaluation method proposed in this paper is the influential gambit method for the sake. Moreover, this evaluation method can be utilized for the selection of classification method with the classification characteristics in proportion to the change of the hope, if the classification tendency, which the user hopes, changes.

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Recently, remotely sensed images have had very high spatial resolution. It is difficult for the most of conventional classification methods to obtain land use maps by using such high resolution images, because these methods are too sensitive to variations of pixel intensity in the same land use area. The reasons are as follows : 1) these methods are only based on spectral (color) and spatial (shape) information ; 2) these methods process the target images in pixel-by-pixel. Therefore, a new image classification method based on not only spectral and spatial information but also texture information is required to obtain land use maps similar to visual interpretation results.
In this paper, a new texture quantification method for remotely sensed images is proposed. This method has invariant property to translation and rotation of the texture patterns in the target images. In the method, a target image is transformed into spatial amplitude spectra by using 2D-DFT to reduce the influence of image translation, followed by quantifying these spectra by a set of complex Zernike moments to reduce the influence of image rotation.Then, the vector which consists of these moments is normalized to reduce the influence of image size. The normalized Zernike moment vector (NZMV) can describe the texture as a unique vector from the origin to a point on the surface of unit hypersphere in the space spanned by Zernike moments, because the elements of the NZMV (Zernike moments) are mutually orthogonal.
To evaluate the texture discrimination capability of the proposed method, some experiments by using 15 images from Brodatz's photo album and their rotated images with every 30-degree rotation angle are conducted. For discrimination of two texture patterns, the angle between two NZMVs obtained from each texture is employed. The experimental results show that the proposed method can identify the same texture images exactly, even though the target images contain various translations and rotations. The proposed method has been also applied to supervised texture classification of airborne multispectral scanner images. The results obtained by the proposed method are closer to those by visual interpretation in comparison with conventional maximum likelihood method.

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Our research purpose here is to analyze the influence of the change of land covering in the sutra age to the earth albedo as well as other earth surface information using the LANDSAT-TM data. A high resolution satellite data were analyzed to get the detail albedo in the city. NVI, surface temperature and the albedo showed that a correlation-like change was being done due to the change in land covering in the sutra age. Although the albedo of the artificial covering is supposed to take a high value, a low value of the albedo is shown by the present research in the city area. Therefore, an albedo by IKONOS was calculated. The technique to make the shadow figure of the detai city from the artificial satellite was shown newly. It was very clear that a shadow influenced the decline of the albedo in both comparisons.

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An identification method for earth observation data according to a chaotic behavior based on Takens reconstruction theory is proposed. The proposed method is examined by using the observed time series data of SST (Sea Surface Temperature) and the SOI (Southern Oscillation Index) data. The experimental results show that the time for the identification of the proposed method is not later than that of the existing method.

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