Using GIS and socio-economical data the relationship between human activities and global environmental change Is Analysed from the view point of food productivity and CO2 emission. Under the assumption that the population problem, the food problem and global warming due to energy consumption can be stabilized through managing land use, impacts of human activities such as consumption of food, energy and timber on global environment changes, and global population capacity are Analysed using developed system dynamics model in the research. In the model the world is divided into two groups: OECD countries and the others. Used global land use data set Is land cover map derived from satellite data, and potential distribution of arable land is estimated by the method of Clamor and Solomon which takes into consideration spatial distribution of climate data such as precipitation and evapotranspiration. In addition, impacts of CO2 emission from human activities on food production through global warming are included in the model as a feedback. The results of the analysis for BaU scenario and Toronto Conference scenario are similar to the results of existing models. From the result of this study, the human habitability in 2020 is 8 billion people, and CO2 emission in 2020 based on BaU Scenario and on Toronto Scenario is 1.7 and 1.2 times more than the 1986's respectively. Improving spatial resolution of the model by using global data to distribute the environmental variables and sauce-economical indices is left for further studies.

The MUBEX (MUtsu Bay sea surface temperature validation EXperiment) campaign has been held from 1995 to 1997 in summer. During the MUBEX campaign, a thermal infrared camera (TIC) installed on a research vessel, which was also equipped with other various observation devices, was intensively used to observe microscopic structure of sea skin surface temperature (SSST) behavior. We have now a total number of 500,000 images observed by the TIC under various weather conditions, i.e., very calm or wavy sea condition, and clear, patchy or cloudy sky condition. In this paper, we show typical SSST patterns observed by the TIC, and describe the result of statistical analysis of SSST.

Solar irradiation controls the exchange of heat energy between atmosphere and land or ocean, and becomes an important factors to the radiance flux at the surface and the biosphere. In order to estimate solar irradiance and earth albedo In Korea peninsula during 1996, GMS date and paramaterization model was combinationally used. In clear sky, the paramaterization model was used to estimate solar iradiance. Also in cloudy sky, the earth albedo was used to calculate the Interceptive effect of solar irradiance. The hourly solar irradiance [the hourly earth albedo] showed generally very low values with <1.00 MJ/m$^2$hr [high values with >0.65] on the middle part (36.00-36.50$^{\circ}$S) and the Southeastern part (near 34.50$^{\circ}$S) in Korea peninsula, respectively. Satellite estimates (GMS data) with pyramometer measurements (in-situ data) were compared for 21 observed stations. Totally, correlation coefficient showed high values with 0.85. In the monthly variation, correlation coefficient of the spring and summer with rms=about 0.42 MJ/m$^2$hr was better than the autumn and winter with rms >0.5 MJ/m$^2$hr. Generally monthly variations of correlation coefficient between satellite estimetes and pyranometer measurements showed r=0.936 in clear sky during 1 year except only May, June, July and August.

Recently many parts of world suffer from chaotic weather, Many scientists believe that this is due to the human made green house emissions, mainly carbon-dioxide Apart from this various pollutants also affect the Earth's environment. These global changes could become a great threat to human survival on the Earth in the future. Therefore many countries are putting great efforts into the study on the global change. This research should take into account whole field of earth sciences, so it becomes interdisciplinary by nature. This will help us to understand the complicated and subtle nature system of the Earth.

By using wind vectors observed by NSCAT and significant wave heights observed by TOPEX/POSEIDON and ERS-2 altimeters, one-dimensional fetch growth of wind waves Is investigated under conditions of strong wind and high waves of the East Asian winter monsoon. The evolution of fetch-limited wind waves can be observed by the altimeters along the ground tracks. The fetch is estimated by using vector wind field observed by NSCAT. The derived growth characteristics of wind waves are compared with empirical relationships between the non-dimensional fetch and significant wave height proposed by previous studies. Good agreement with the empirical fetch graph formula normalized by the friction velocity is discemible, while the formulas normalized by the wind speed at a height of 10 m tend to underestimate the wave height under such severe conditions of high wind and very long fetch.

Latent and sensible heat fluxes over the global oceans are estimated using SSM/I (Special Sensor Microwave Imager) and AVHRR MCSST (Advanced Very High Resolution Radiometer Multi-Channel Sea Surface Temperature). The heat fluxes are computed from SSM/I wind speeds and surface humidity, the MCSST, and NCEP Reanalysis sea level pressures and 2-m temperatures from 1996 to 1997. The diabatic conditions bulk formula (Kondo, 1975) is used to compute the heat fluxes. To validate, the derived fluxes are compared to the measurements of 3 JMA buoys. The wind speeds and surface humidity derived from SSM/I have accuracies of 1.37m/s and 1.7g/kg, respectively. The heat fluxes were estimated these factors and the standard error of the latent and sensible heat fluxes are 5.53 W/m$^2$ and 3.33 W/m$^2$. The latest El-Nino phenomenon started at the beginning of 1997 and this event was larger than any others. We compare the heat fluxes in 1997 with the fluxes in 1996 and investigate the spatial movement of meteorological factors as well as the heat fluxes associated with El-Nino appearance.

Prior to launch, simulated radiances of the Ocean Scanning Multispectral Imager (OSMI) will be very useful to guess the real imagery of OSMI and to check the data processing system for OSMI. The data processing system for OSMI which is one sensor of Korea Mult i - Purpose Satellite (KOMPSAT) scheduled for launch in 1999 is being developed based on the SeaWiFS Data Analysis System (SeaDAS). Such a simulation should include the spectral bands, orbital and scanning characteristics of the OSMI and KOMPSAT spacecraft. The simulation is also very helpful for finding and preparing for problem areas before launch. This paper describes a method to create simulated radiances of the OSMI over the oceans. Our method for constructing a simulated OSMI imagery is to propagate a KOMPSAT orbit over a field of Coastal Zone Color Scanner (CZCS) pigment values and to use the values and atmospheric components to calculate total radiances. A modified Brouwer - Lyddane model with drag was used for the realistic orbit prediction, the CZCS pigment data were used to compute water - leaving radiances, and a variety of radiative transfer models were used to calculate atmospheric contributions to total radiances detected by OSMI. Imagery of the simulated OSMI total radiances for 6 nominal bands was obtained. As expected, water - leaving radiances were only a small fraction of total radiances and sun glint contaminations were observed near the solar declination. Therefore, atmospheric correction is very important in the calculation of pigment concentration from total radiances. Because the imagery near the sun's glitter pattern is virtually useless and must be discarded, more advanced mission planning will be required.

CO2 transfer velocity is one of the key parameters for CO2 flux estimation at air - sea interface. However, current studies show that significant inconsistency still exists in its estimation when using different models and remotely sensed data sets, which acts as one of the main uncertainties involved in the computation of CO2 exchange coefficient between air - sea interface. In this study, wind data collected from SSM/I and scatterometer onboard ERS-1, in conjunction with operational NOAA/AVHRR, are applied to different models for calculating CO2 exchange coefficient in the world ocean. Their interrelationship and discrepancies inherent with different models and satellite data are analyzed. Finally, the seasonal and inter-annual variation of CO2 exchanges coefficient for different ocean basins are presented and discussed.

The aim of the present study is to define and tentatively to interpret the distribution of polluted water released from Lake Sihwa into Yellow Sea using Landsat TM. Since the region is an extreme case 2 water, empirical algorithms for chlorophyll-a and suspended sediments have limitations. This work focuses on the use of multi-temporal Landsat TM. We applied PCA to detect evolution of spatial feature of polluted water after release from the lake. The PCA results were compared with in situ data, such as chlorophyll-a, suspended sediments, Secchi disk depth (SDD), surface temperature, radiance reflectance at six bands. The in situ remote sensing reflectance was analysed with PCA. On the basis of these In situ data we found good correlation between first Principal Component and Secchi disk depth ($R^2$=0.7631), although other variables did not result in such a good correlation. The problems in applying PCA techniques to multi-spectral remote sensed data are also discussed.

The chlorophyll-a concentration measured by OCTS could be used for observing the physical phenomena such as eddies, fronts, and up welling in the oceans as well as for studying the ecology of phytoplankton. In this study, biological and physical features in the East Sea/Japan Sea (the East Sea) and the Yellow Sea observed by OCTS are analyzed in comparison with other satellite data. And in situ chlorophyll data were compared with OCTS Level 2 chlorophyll data. There was a striking correspondence between the satellite chlorophyll structure and other satellite data in the East Sea in the spring. Very complicated ring structures in the 557 are reflected in chlorophyll structure. In the Yellow Sea, the surface structure was rather simple. While the discrepancies between in situ and OCTS algorithm version 3 chlorophyll were small in the East Sea, those for the Yellow Sea were rather big. Comparison with CZCS data for similar time of the year (May-June) shows that OCTS chlorophyll is higher in general. Although the error is partly due to the fact that NASDA chlorophyll algorithm is an empirical algorithm for case 1 water, how much of this error is also due to the errors in sensor calibration or in atmospheric correction is not clear.

The comparison of Topex/Poseidon sea surface heights and Tide Gauge sea levels was studied in the South Indian Ocean after Topex/Poseidon mission of about 3 years (11- 121 cycles) from January 1993 through December 1995. The user's handbook (AVISO) for sea surface height data process was used in this study Topex/Poseidon sea suface heights ($\zeta$$^{T/P}$), satellite data at the point which is very closed to Tide Gauge station, were chosen in the same latitude of Tide Gauge station. These data were re-sampled by a linear interpolation with the interval of about 10 days, and were filtered by the gaussian filter with a 60 day-window. Tide Gauge sea levels ($\zeta$$^{Argos}$, $\zeta$$^{In-situ}$ and $\zeta$$^{Model}$), were also treated with the same method as satellite data. The main conclusions obtained from the root-mean-square and correlation coefficient were as follows: 1) to Produce Tide Gauge sea levels from bottom pressure, in-situ data of METEO-FRANCE showed very good values against to the model data of ECMWF and 2) to compare Topex/Poseidon sea surface heights of Tide Gauge sea levels, the results of the open sea areas were better than those of the coast and island areas.

Increase of greenhouse gas due to $CO_2$ and CH$_4$ gases would cause the global warming in the atmosphere. According to the global circulation model, it is pointed out in the Okhotsk Sea that the large increase of atmospheric temperature might be occurredin this region by global warming due to the doubling of greenhouse effectgases. Therefore, it is very important to monitor the sea ice extents in the Okhotsk Sea. To improve the sea ice extents and concentration with more highly accuracy, the field experiments have begun to comparewith Airborne Microwave Radiometer (AMR) and video images installed on the aircraft (Beach-200). The sea ice concentration is generally proportional to the brightness temperature and accurate retrieval of sea ice concentration from the brightness temperature is important because of the sensitivity of multi-channel data with the amount of open water in the sea ice pack. During the field experiments of airborned AMR the multi-frequency data suggest that the sea ice concentration is slightly dependending on the sea ice types since the brightness temperature is different between the thin and small piece of sea ice floes, and a large ice flow with different surface signatures. On the basis of classification of two sea ice types, it is cleary distinguished between the thin ice and the large ice floe in the scatter plot of 36.5 and 89.0GHz, but it does not become to make clear of the scatter plot of 18.7 and 36.5GHz Two algorithms that have been used for deriving sea ice concentrations from airbomed multi-channel data are compared. One is the NASA Team Algorithm and the other is the Bootstrap Algorithm. Intrercomparison on both algorithms with the airborned data and sea ice concentration derived from video images bas shown that the Bootstrap Algorithm is more consistent with the binary maps of video images.

Seasonal variation of attenuation coefficient spectra in Japan sea was extracted from underwater radiance/irradiance spectra observed by a moored buoy system developed by National Space Development Agency of Japan (NASDA). The buoy was deployed 9 months from August 31, 1996 to June 1, 1997. Throughout this period, it was collecting downward irradiance and upward radiance spectra under water at the depth of 1.5m and 6.5m everyday. The dairy averaged diffused attenuation coefficient spectra and underwater reflectance spectra were calculated. The results were compared with the absorption spectra of filtered samples obtained by validation cruises, which carried out 5 times during the moored period. Also, the natural fluorescence of chlorophyll a were extracted from the upward radiance spectra observed at 1.5m depth. The seasonal variation of the calculated attenuation coefficient spectra and the natural fluorescence were examined. The result shows a weak blooming of phytoplankton on November and a large blooming on April.

The purpose of this study is to describe the change of the spring bloom and oceanographic condition. The variation of pigment concentration derived from the satellite ocean color data has been analyzed. According to the movement of blooming area, blooming was very concerned with a rising trend of sea surface temperature and a supply of nutrients. A nutrient rich water carried by the Oyashio encounters with the warm Core ring, where mixings and blooms are observed. We examined the correlation by using the satellite observations of the temperature and chlorophyll-a for the spring seasons (May, June, July) of 1998 the off Sanriku area (38-43N, 141- l50E). Using the SeaWiFS data, we process the data into the level-3, which contains the geophysical value of chlorophyll-a. And chlorophyll-a data is mapped for the water between 110E and 160E, and 15N and 52N with a 0.08 * 0.05 degree grid for each image. And Sea Surface Temperature (SST) data is produced using the AVHRR onboard the NOAA. The SST is derived by the MCSST. Then, the data is mapped for the water as much as chi-a data. And these gridded image was made by detection of each water masses, which are Kuroshio Extension, the warm-core ring and the Oyashlo Intrusion, etc., using those satellite images to determine short term change. Off Sanriku is a place where warm-water pool and the Oyashio at-e mixed. When warm streamer has intruded in cold water, the volume of phytoplankton increases at the tip of warm streamer. Warm water streamer was trigger of occurring blooming. And also, SeaWiFS images provided as much information for the studies of chlorophyll-a concentrations in the surface.

A technique on atmospheric correction algorithm for a single band (0.76-0.90 $\mu$m) reflective of Landsat TM imagery has been developed using a radiation transfer model simulation. It proceeds in two steps: First, calculation of the surface reflectance of each pixel based on precomputed planetary albedo functions for actual atmospheres(e. g. radiosonde) and two kinds of atmospheric visibility states. Second, approximate correction of the adjacency pixel effect by taking into account the average reflectance in an 7 $\times$ 7 pixel neighbourhood and using appropriate land cover classification in reflectance. The correction functions are provided by MODTRAN model.

Through the ISODATA method, the micro-landform of Julpo-Bay tidal flat was classified into mudflat, mixedflat, and sandflat using Landsat TM image. Each showed an apparent differences in its topographical characteristics and grain size composition. For example, mudflats are formed with flat faces and tidal channel of dissected gully. Its characteristics of grain size analysis that the grains have less than mean grain size 4 phi. Its sorting is bad (higher than 1 S.D.), and it showed strongly positive skewness. But sandflat is topographically flat without tidal channel. It has developed with ripple marks. According to the grain size analysis of deposits, the soil is coarse size with 90% of sand and its sorting is well(lower than 1 S.D.) Also, it showed strongly negative skewness. Mixed flat is in between mudflat and sandflat in its characteristics.

Global land related datasets such as land use, land cover, vegetation cover percentage, forest cover percentage, are part of important global geospatial environmental datasets for global change studies. Since land cover varies place by place, continental production of dataset is a usual approach. Western academically developed countries have some projects to describe land cover related information in digital form using remote sensing technology in African, American continent and Oceania. In this paper, the author introduce his initiative to coordinate Asian scientists in order to develop land related dataset of Asia for our better understanding of the environment of Asia and for contribution to the development of global dataset. This paper explains activities by Land Cover Working Group (LCWG) of the Asian Association on Remote Sensing(AARS), Data and Information System(DIS) sub-committee of Japan national committee for the International Geosphere and Biosphere Program(IGBP), and the International Society for Photogrammetry and Remote Sensing(ISPRS) Working Group IV/6 on Global databases supporting environmental monitoring.

This paper presents the neuro-fuzzy classifier derived from the generic model of a 3-layer fuzzy perceptron and developed the classification software based on the neuro-fuzzl model. Also, a comparison of the neuro-fuzzy and maximum-likelihood classifiers is presented in this paper. The Airborne Multispectral Scanner(AMS) imagery of Tae-Duk Science Complex Town were used for this comparison. The neuro-fuzzy classifier was more considerably accurate in the mixed composition area like "bare soil" , "dried grass" and "coniferous tree", however, the "cement road" and "asphalt road" classified more correctly with the maximum-likelihood classifier than the neuro-fuzzy classifier. Thus, the neuro-fuzzy model can be used to classify the mixed composition area like the natural environment of korea peninsula. From this research we conclude that the neuro-fuzzy classifier was superior in suppression of mixed pixel classification errors, and more robust to training site heterogeneity and the use of class labels for land use that are mixtures of land cover signatures.

To assess the flood damages and to provide necessary information for preventing future catastrophe, it is necessary to appraise the inundated area with more accurate and rapid manner. This study attempts to evaluate the potential of satellite synthetic aperture radar (SAR) data for mapping of flood inundated area in southern part of Korea. JERS L-band SAR data obtained during the summer of 1997 were used to delineate the inundated areas. In addition, Landsat TM data were also used for analyzing the land cover condition before the flooding. Once the two data sets were co-registered, each data was separately classified. The water surface areas extracted from the SAR data and the land cover map generated using the TM data were overlaid to determine the flood inundated areas. Although manual interpretation of water surfaces from the SAR image seems rather simple, the computer classification of water body requires clear understanding of radar backscattering behavior on the earth's surfaces. It was found that some surface features, such as rice fields, runaway, and tidal flat, have very similar radar backscatter to water surface. Even though satellite SAR data have a great advantage over optical remote sensor data for obtaining imagery on time and would provide valuable information to analyze flood, it should be cautious to separate the exact areas of flood inundation from the similar features.

NOAA satellite data and GMS data have been received at the Institute of Industrial Science, University of Tokyo since early 80's and 1994, respectively. So far, all data are archived and users can look their quick look images through the Internet and get the data by request. The following processed data set will be available soon with the corporation with the Science University of Tokyo: Radiometrically corrected by 65 code and geometrically corrected NOAA data with the corporation with Iwate University and NDVI, SST and cloud classified images as their products. 1 km AVHRR Land Project Data Set of Asia and their 14 regional subsets. Geometrically corrected GMS images and surface temperature maps, sea surface temperature maps and cloud classification maps.

The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about loom underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the way of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. A new hybrid method has been developed for estimating the origin of the underground acoustic source by coupling both methods. The Nelder-Meade simplex search algorithm is then used to numerically estimate the position of the source in those methods. For each method the sound localization is carried out in three dimensions underground. The distance between the true and estimated origins of the source is in some cases less than 6m for a search area of radius 250m.

Nowadays, GIS, as multi-discipline information system, is closely linked with GPS application in conjunction with GIS-T or Logistics GIS. With this R&D trend. CPS/GIS application system for AVL is newly developed in this study. This AVL is designed and implemented by using pure Java computing technology towards com ing Car-equipped wireless Internet PC age, and main features of Java are included at this system: Platform independence, Multi-thread processing, and Object-oriented paradigm. While, because core modules of this AVL are based on GIS spatial engine, unlike other commercial AVLs, large spatial database problem handling digital image/spatial information and attribute information and direct access problem of GIS data is easily dealt with. this system can directly access external database by using JDBC: MS Access for desktop version and Oracle for W/S version. Finally, it is thought that Java-based AVL, one of CPS/CIS applications, can be easily extended into other prospective GIS applications: Land surveyor supporting system, Flight tracking system, 3D facility management system with CPS, and so forth.

Since the mid-1990′s, researches on 3D GIS have been regarded as one of main issues both in the academic sites and commercial vendors; recently, some prototyped systems or the first versioned software systems of commercial basis are being reported and released. Unlike conventional 2D GIS, which consists in intelligent structured GIS or desktop GIS, every 3D GIS has its own distinguished features according to data structure-supporting capability, GIS-styled functionality, external database accessibility, interfacing extents with 2D GIS, 3D visualization/texture mapping ability, and so forth. In this study, technical aspects related to system development, SERI-Web3D GIS ver. 1.2, are explained. Main features in this revised 3D GIS can be summarized: 2-tier system model(client-server), VGFF(Virtual GIS File Format), internal GIS import, Feature manager(zoning, layering, visualization evironment), Scene manager(manage 3D geographic world), Scene editor, Spatial analyzer(Intersect, Buffering, Network analysis), VRML exporter. While, most other 3D GISes or cartographic mapping systems may be categorized into 3D visualization systems handling terrain height-field processing, 2D GIS extension modules, or 3D geometric feature generation system using orthophoto image: actually, these are eventually considered as several parts of "real 3D GIS". As well as these things, other components, especially web-based 3D GIS, are being implemented in this study: Surface/feature integration, Java/VRML linkage, Mesh/Grid problem, LOD(Level of Detail)/Tiling, Public access security problem, 3-tier architecture extension, Surface handling strategy for VRML.

Land cover and land use classification on a huge scale, e.g. national or continental scale, has become more and more important because environmental researches need land cover: And land use data on such scales. We developed a crop field extraction method, which is one of the steps in our land cover classification system for a huge area. Firstly, a crop field model is defined to characterize "crop field" in terms of NDVI value and textual information Textual information is represented by the density of straight lines which are extracted by wavelet transform. Secondly, candidates of NDVI threshold value are determined by "scale-space filtering" method. The most appropriate threshold value among the candidates is determined by evaluating the line density of the area extracted by the threshold value. Finally, the crop field is extracted by applying level slicing to Landsat TM image with the threshold value determined above. The experiment demonstrates that the extracted area by this method coincides very well with the one extracted by visual interpretation.

Extracting a Digital Elevation Model (DEM) from spaceborne imagery is important for cartographic applications of remote sensing data. The procedure for such DEM generation can be divided into stereo matching, sensor modelling and DEM interpolation. Among these, DEM interpolation contributes significantly to the completeness and accuracy of a DEM and, yet, this technique is often considered "trivial". However, na\ulcornere DEM interpolation may result in a less accurate and sometimes meaningless DEM. This paper reports the performance analysis of various DEM interpolation techniques. Using a manually derived DEM as reference, a number of sample points were created randomly. Different interpolation techniques were applied to the sample points to generate DEMs. The performance of interpolation was assessed by the accuracy of such DEMs. The results showed that kriging gave the best results at all times whereas nearest neighborhood interpolation provided a fast solution with moderate accuracy when sample points were large enough.

Three dimensional database of building use in Central Obihiro City was created and displayed using three dimensional graphics and quicktime movies. Then intra structure of Central Obihiro City was analyzed based on this database using GIS and the results were also displayed using three dimensional graphics and quicklime movies.

In this paper, the radar altimeter for topographic mapping over land is introduced and the characteristics of the return signals are analyzed. The radar system is described briefly and the requirements to get the fine resolution of the terrain surface height are considered. The designed radar altimeter was tested on the landscape in the near of Stuttgart. The measured data shows very fine profile of the test landscape and the height errors induced from different geometrical structure of the land surface are acquired in the measurement. In the test area, most characteristics of radar return signals over land could be tested and the results of the topographic mapping using our radar altimeter can be used for future radar altimeter development for land applications.

Microwave polarimetric backscattering from a various types of grassland canopies has been analyzed by using the first-order radiative transfer theory in this paper. Leaves in the grassland are modeled by rectangular resistive sheets, which sizes (widths and lengths) and orientations (elevation and azimuth angles) are randomly distributed. Surface roughness and soil moisture of the ground plane under the grass canopy is considered in this computation. The backscattering coefficients of grasslands are computed for different radar parameters (angles, frequencies and Polarizations) as well as different canopy Parameters (size and orientation distributions of leaves, canopy depth, moisture contents of leaves and soil, rms height and correlation length of soil surface). A radar system for 15GHz has been fabricated and used for measurement of the scattering coefficient from a grass canopy. The computation result obtained by the scattering model for the grass canopy is compared with the measurements.

The first step in change detection in any SAR monitoring, including SAR interferometry, is the co-registration of the images. CCPs (Ground Control Points) for co-registration are usually detected manually, but for qualitative analyses of enormous volumes of data, some automation of the process will become necessary. An automated determination of common CCPs for the same path/row data is especially desirable. We selected the intersections of linear features as the candidates of common GCPs Very bright point targets, which are commonly used as GCPs, have the drawback of appearing and disappearing depending on the conditions of the observation. But in the case of linear features, some detailed elements may appear differently in some case, but the overall line-likeness will remain. In this study, we selected 18 common GCPs for a single-look JERS-1 SAR image of Omaezaki area in central Japan. Although the GCPs in the first image had to be selected either interactively or semi-automatically, the same GCPs in all other images were successively detected automatically using a tiny sub-image around each GCP and a dilated mask of each linear feature in the first image as the reference data.

This paper demonstrates that it is feasible to evaluate forest degradation and to detect deforestation in the 8156$km^2$ study area affected by expand farming using vegetation indices derived from Landsat TM data. The NDVI-growing stock relation was applied on th Landsat TM data and a 3 second grid DEM, whose coverages could improve the assessment of forest degradation and also estimate the rate of change of forest cover area depending on elevation intervals. The strength of the relationship between the ratio of the greenness and brightness indices and forest degradation conditions would have been more interesting in the deforested areas which were converted to crop farming land.

In this paper, we have considered the method for clustering land cover types over the East Asia from AVHRR data. The feature vectors such that maximum NDVI, amplitude of NDVI, mean NDVI, and NDVI threshold are extracted from the 10-day composite by maximum value composite(MVC) for reducing the effect of cloud contaninations. To find the land cover clusters given by the feature vectors, we are adapted the self-organizing feature map(SOFM) clustering which is the mapping of an input vector space of n-dimensions into a one - or two-dimensional grid of output layer. The approach is to find first the clusters by the first layer SOFM and then merge several clusters of the first layer to a large cluster by the second layer SOFM. In experiments, we were used the 8-km AVHRR data for two years(1992-1993) over the East Asia.

It is not easy to identify a ground control point (GCP) or even locate its vicinity from a SAR image. Although simulated SAR images may be useful to interpret mountain areas, they are not useful in flat areas because they do not show ground coverage or key features such as rivers, lakes and roads. In this study, we developed a method to simulate SAR images integrating geographical features to DEM to facilitate to locate ground control features from SAR images.

This study overviews existing evaluation methods of classification accuracy using confusion matrix proposed by Cohen in 1960's, and proposes ISDd(Index of Spatial Distribution by distance) and ISDs(Index of Spatial Distribution by scatteredness) for the evaluation of spatial distribution of satellite image classification errors, which has not been tried yet. Index of spatial distribution offers the basis of decision on adoption/rejection of classification results at sub-image level by evaluation of distribution, such as status of local aggregation of misclassified pixels. So, users can understand the spatial distribution of misclassified pixels and, can have the basis of judgement of suitability and reliability of classification results.

The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

The purpose of this study is to contribute the development of an El Nino prediction model. The objectives of the study are to (1) extract sea surface height data from the TOPEI/Poseidon altimeter, and (2) compare the relations among the sea surface height, sea surface temperature and wind field. NOAA AVHRR Multi-channel data is used for sea surface temperature and wind data is derived from ERS 1, 2 AMI wind scatterometer. The results showed that sea surface height has increased significantly during the El Nino season. The sea surface height is positively related to sea surface temperature and negatively related to zonal wind.

We have made the cross calibration in terms of space reflectance between POLDER and OCTS sensors on board ADEOS satellite, using the POLDER and OCTS data acquired simultaneously on April 24, 1997. The space reflectance values for the same target computed from the POLDER and OCTS data are in very good agreement, when we adopted the new calibration coefficients of OCTS suggested by the vicarious experiment by NASDA. Then, we estimated aerosol parameters for several target areas (two areas in the Sea of Japan and three in the Pacific Ocean) from ADEOS/POLDER's directional reflectance and polarization data in 760nm and 865nm bands. A single atmospheric layer model with an isotropic Gaussian type ocean surface (Cox-Munk model) was assumed in this study.

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

Interferometric Monitor for Greenhouse Gases (IMG) is a sensor to monitor the earth's radiation balance, the temperature profile of the atmosphere, the temperature of the earth's surface, and physical properties of clouds, and was loaded on ADEOS satellite. In this paper, we estimated IMG level 2 data by comparing with a Clobal Telecommunications System data (GTS). The IMG level 2 data over sea without cloud cover gave good agreement with the value that had been obtained by buoy and sonde.

This paper proposes a new building segmentation method from 1m resolution imagery using an Active Contour Model, known as "Balloons". The original balloons, which was designed by Cohen(Cohen, 1991) to extract features from medical images, are modified for building segmentation. The proposed method consists of two phases. Firstly, building boundaries are extracted by balloons with a given position on buildings from an operator. Since balloons actively adjust their shapes according to the boundaries, there is no more shape limitations on detecting buildings. Secondly, buildings are segmented by connecting the corners detected from the building boundaries, because most buildings, which are man-made objects, are effectively described by polygons. The test results show that most buildings are segmented efficiently and easily. The proposed method is new and timely as 1m resolution spaceborne imagery will be available in the very near future. The proposed method can be used fur operational building segmentation from such imagery.

Accurate mapping of satellite images is one of the most important Parts in many remote sensing applications. Since the position and the attitude of a satellite during image acquisition cannot be determined accurately enough, it is normal to have several hundred meters' ground-mapping errors in the systematically corrected images. The users which require a pixel-level or a sub-pixel level mapping accuracy for high-resolution satellite images must use a number of Ground Control Points (GCPs). In this paper, the performance of two geometric correction algorithms is tested and compared. One is the polynomial warping algorithm which is simple and popular enough to be implemented in most of the commercial satellite image processing software. The other is full camera modelling algorithm using Physical orbit-sensor-Earth geometry which is used in satellite image data receiving, pre-processing and distribution stations. Several criteria were considered for the performance analysis : ultimate correction accuracy, GCP representatibility, number of GCPs required, convergence speed, sensitiveness to inaccurate GCPs, usefulness of the correction results. This paper focuses on the usefulness of the precision correction algorithm for regular image pre-processing operations. This means that not only final correction accuracy but also the number of GCPs and their spatial distribution required for an image correction are important factors. Both correction algorithms were implemented and will be used for the precision correction of KITSAT-3 images.

Two-dimensional wavelet spectrum analysis is applied to Advanced Very High Resolution Radiometer (AVHRR) images from the NOAA meteorological satellites in the area around Japan to unfold the horizontal structure of SST into space and scale (wavenumber), which can yield localized space-wavenumber information. The results reveal significantly new and previously unexplored insights on horizontal structure of sea surface temperature, which cannot be revealed using a traditional Fourier transform approach.

In Synthetic Aperture Radar(SAR) imaging, the echoed data are collected by moving radar's position with respect to the target area, and this operation actually gives effect of synthesizing aperture size, which in turn gives better cross range resolution of reconstructed target scene. Among several inversion scheme for SAR Imaging, we uses an inversion scheme which uses no approximation in wave propagation analysis, and try to verify whether the collected data with synthesized aperture actually gives the same support as that with physical aperture in the same size. To do this, we make a signal subspace comparison of two imaging models with physical and synthesized arrays, respectively. Theoretical comparison and numerical analysis using Gram-Schmidt procedures had been performed. The results showed that the synthesized array data fully span the physical array data with the same system geometry and strongly support the proposed inversion scheme valuable in high resolution radar imaging.

This study applies an on-line system, which employes an adaptive reconstruction technique to monitor and forecast ocean surface changes. The system adaptively generates an appropriate synthetic time series with recovering missing measurements for sequential images. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series. The system sequentially collects the estimated results from the adaptive reconstruction and then statistically analyzes them to monitor and forecast the change in surface characteristics.

For the accurate generation of DEMs, the determination of match quality in adaptive least square matching algorithm is significantly important. Traditionally, only the degree of convergence of a solution matrix in least squares estimation has been considered for the determination of match quality. It is, however, not enough to determine the true match quality. This paper reports two approaches of match quality determination based on adaptive least square correlation : the conventional if-then logic approaches with scene geometry and correlation as additional quality measures; and, the fuzzy logic approaches. Through these, accurate decision of match quality will minimize the number of blunder and maximize the number of exact match. The proposed methods have been tested on JERS and SPOT images and the results show good performance.

SAR has provided weather independent images on land and sea surface, which can be used for extracting various useful informations. Recently attempts to estimate wind field parameters from SAR images over the oceans have been made by various groups over the world. Although scatterometer loaded in ERS-1 and ERS-2 observes the global wind vector field at spatial resolution of 50 Km with accuracies of $\pm$2m/s in speed, the spatial resolution may not be good enough for applications in coastal regions. It is weil known the sea surface roughness is closely correlated to the wind field, but the wind retrieval algorithms from SAR images are yet in developing stage. Since the radar backscattering properties of the SAR images are principally the same as that of scatterometer, some previous studies conducted by other groups report the success in mesoscale coastal wind field retrievals using ERS SAR images. We have tested SWA (SAR Wind Algorithm) and CMOD4 model for estimation of wind speed using an ERS-1 SAR image acquired near Cheju Island, Korea, in October 11, 1994. The precise estimation of sigma nought and the direction of wind are required for applying the CMOD4 model to estimate wind speed. The wind speed in the test sub-image is estimated to be about 10.5m/s, which relatively well agrees to the observed wind speed about 9.0m/s at Seoguipo station. The wind speed estimation through the SWA is slightly higher than that of CMOD4 model. The sea surface condition may be favorable to SWA on the specific date. Since the CMOD4 model requires either wind direction or wind speed to retrieve the wind field, we should estimate the wind speed first using other algorithm including SWA. So far, it is not conclusive if the SWA can be used to provide input wind speed data for CMOD4 model or not. Since it is only initial stage of implementing the wind field retrieval algorithms and no in-situ observed data is currently avaliable, we are not able to evaluate the accuracy of the results at the moment. Therefore verification studies should be followed in the future to extract reliable wind field information in the coastal region using ERS SAR images.

Korea Aerospace Research Institute (KARI) is developing a Korea Multi-Purpose Satellite I (KOMPSAT-I) which accommodates Electro-Optical Camera (EOC), Ocean Scanning Multi-spectral Imager (OSMI), and Space Physics Sensor (SPS). The satellite has the weight of about 500kg and will be operated on the 10:50 AM sun-synchronized orbit with the altitude of 685 km. The satellite will be launched in 1999 and its lifetime is expected to be over 3 years. The main mission of EOC is the cartography to provide the images from a remote earth view for the production of 1/25000-scale maps of KOREA. EOC collects 510 ~ 730 nm panchromatic imagery with the ground sample distance(GSD) of 6.6 m and the swath width of 17 km by push broom scanning. EOC also can scan $\pm$45 degree across the ground track using body pointing method. The primary mission of OSMI is worldwide ocean color monitoring for the study of biological oceanography. It will generate 6 band ocean color images with 800 km swath width and 1km GSD by whiskbroom scanning. OSMI is designed to provide on-orbit spectral band selectability in the spectral range from 400 nm to 900 nm through ground command. This flexibility in band selection can be used for various applications and will provide research opportunities to support the next generation sensor design. SPS consists of High Energy Particle Detector (HEPD) and ionosphere Measurement Sensor (IMS). HEPD has missions to characterize the low altitude high-energy Particle environment and to study the effects of radiation environment on microelectronics. IMS measures densities and temperature of electrons in the ionosphere and monitors the ionospheric irregularities at the KOMPSAT orbit.

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agency of Japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy-and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is as-sumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays vey similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

Electro-Optical Camera(EOC) is the main payload of Korea Multi-Purpose SATellite(KOMPSAT) with the mission of cartography to build up a digital map of Korean territory including Digital Terrain Elevation Map(DTEM). This instrument which comprises EOC Sensor Assembly and EOC Electronics Assembly produces the panchromatic images of 6.6 m GSD with a swath wider than 17 km by push-broom scanning and spacecraft body pointing in a visible range of wavelength, 510 ~ 730 nm. The high resolution panchromatic image is to be collected for 2 minutes during 98 minutes of orbit cycle covering about 800 km along ground track, over the mission lifetime of 3 years with the functions of programmable rain/offset and on-board image data storage. The image of 8 bit digitization, which is collected by a full reflective type F8.3 triplet without obscuration, is to be transmitted to Ground Station at a rate less than 25 Mbps. EOC was elaborated to have the performance which meets or surpasses its requirements of design phase. The spectral response the modulation transfer function, and the uniformity of all the 2592 pixel of CCD of EOC are illustrated as they were measured for the convenience of end-user. The spectral response was measured with respect to each gain setup of EOC and this is expected to give the capability of generating more accurate panchromatic image to the EOC data users. The modulation transfer function of EOC was measured as greater than 16% at Nyquist frequency over the entire field of view which exceeds its requirement of larger than 10%, The uniformity that shows the relative response of each pixel of CCD was measured at every pixel of the Focal Plane Array of EOC and is illustrated for the data processing.

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography. The instrument images the ocean surface using a whisk-broom motion with a swath width of 800 km and a ground sample distance (GSD) of < 1 km over the entire field-of-view (FOV). The instrument is designed to have an on-orbit operation duty cycle of 20% over the mission lifetime of 3 years with the functions of programmable gain/offset and on-board image data storage. The instrument also performs sun calibration and dark calibration for on-board instrument calibration. The OSMI instrument is a multi-spectral imager covering the spectral range from 400 nm to 900 nm using a CCD Focal Plane Array (FPA). The ocean colors are monitored using 6 spectral channels that can be selected via ground commands after launch. The instrument performances are fully measured for 8 basic spectral bands centered at 412nm, 443nm, 490nm, 510nm, 555nm, 670nm, 765nm and 865nm during ground characterization of instrument. In addition to the ground calibration, the on-board calibration will also be used for the on-orbit band selection. The on-orbit band selection capability can provide great flexibility in ocean color monitoring.

The first Korean remote sensing satellite, Korea Multi-Purpose Satellite (KOMPSAT-1), is going to be launched in 1999. This will carry a 7m resolution Electro-Optical Camera (EOC) for earth observation. The primary mission of the KOMPSAT-1 is to acquire stereo imagery over the Korean peninsular for the generation of 1:25,000 cartographic maps. For this mission, research is being carried out to assess the possibilities of automated or semi-automated mapping of EOC data and to develop, if necessary, such enabling tools. This paper discusses the issue of automated DEM generation from EOC data and identifies some important aspects in developing a for DEM generation system from EOC data. This paper also presents the current status of the development work for such a system. The development work has focused on sensor modelling, stereo matching and DEM interpolation techniques. The performance of the system is shown with a SPOT stereo pair. A DEM generated from a commercial software is also presented for comparison. The paper concludes that the proposed system creates preferable results to the commercial software and suggests future developments for successful generation of DEM for EOC data.

With high resolution capability, satellite images are expanding their roles from earth resource monitorings to map production. Until now, maps are produced from airborne photos, but as large as at 1:2,400 scale, low cost satellite ortho images will replace the airborne photos. However, there has been no standard for map productions with satellite images. In this paper, we study the process of map productions with the satellite images of SPOT, IRS-lC, KOMPSAT, the positional accuracy of map features extracted from the satellite images, and the relationship between the image resolution and the map scale.

The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding poults of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. In the DEM generation system, this procedure holds most of a processing time, therefore a new fast matching algorithm is proposed to reduce the time for matching. The elevation of each point is calculated using the exterior orientation obtained from modeling and disparity from matching. In this paper, the SPOT satellite images, level IA 6000 $\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM. extraction with the satellite images.

The grid reference system (GRS) has been useful for identifying the geographical location of satellite images. In this study we derive a GRS for the KOMPSAT Electro-Optical Camera (EOC) images. The derivation substantially follows the way that SPOT defines for its GRS, but incorporates the KOMPSAT orbital characteristics. The KOMPSAT EOC GRS (KEGRS) is designed to be a (K,J) coordinate system. The K coordinate parallel to the KOMPSAT ground track denotes the relative longitudinal position and the J coordinate represents the relative latitudinal position. The numbering of K begins with the prime meridian of K=1 with K increasing eastward, and the numbering of J uses a fixed value of J=500 at all center points on the equator with J increasing northward. The lateral and vertical intervals of grids are determined to be 12.5 km about at the 38$^{\circ}$ latitude to allow some margins for the value-added processing. The above design factors are being implemented in a satellite programming module of the KOMPSAT Receiving and Processing System (KRPS) to facilitate the EOC data collection planning over the Korean peninsula.

A small package of plasma instruments, Space Physics Sensor, will monitor the space environment and its effects on microelectronics in the low altitude region as it operates on board the KOMPSAT-1 from 1999 over the maximum of the solar cycle 23. The Space Physics Sensor (SPS) consists of two parts: the Ionospheric Measurement Sensor (IMS) and the High Energy Particle Detector (HEPD). IMS will make in situ Measurements of the thermal electron density and temperature, and is expected to provide a global map of the thermal electron characteristics and the variability according to the solar and geomagnetic activity in the high altitude ionosphere of the KOMPSAT-t orbit. HEPD will measure the fluxes of high energy protons and electrons, monitor the single event upsets caused by these energetic charged particles, and give the information of the total radiation dose received by the spacecraft. The continuous operation of these sensors, along with the ground measurements such as incoherent scatter radars, digital ionosondes and other spacecraft measurements, will enhance our understanding of this important region of practical use for the low earth orbit satellites.

Recently, the improvement of on-board satellite sensors covering hyperspectral image sensors, high spatial resolution sensors provide data on earth in diverse aspect. The application field relating remotely sensed data also varies depending on what type of job one wants. The various resolution of sensors from low to extremely high is also available on the market with a user defined specific location. The expense to purchase remote sensed data is going down compare to the cost it need past few years ago in terms of research or private use. Now, the satellite remote sensed data is used on the field of forecasting, forestry, agriculture, urban reconstruction, geology, or other research field in order to extract meaningful information by applying special techniques of image processing. There are many image processing packages available worldwide and one common aspect is that they are expensive. There need to be a advanced satellite data processing package for people who can not afford commercial packages to apply special remote sensing techniques on their data and produce valued-added product. The study was carried out with the purpose of developing a special satellite data processing package which covers almost every satellite produced data with normal image processing functions and also special functions needed on specific research field with friendly graphical user interface (GUI). And for the people with any background of remote sensing with windows platform.

Spectral reflectance signatures of upland crops at OSMI bands were collected and evaluated for the feasibility of crop discrimination knowledge-based on crop calendar. Effective bands and their ratio values for discriminating corn from two other legumes were defined with OSMI equivalent bands and their ratio values. June 22 among measurements dates was the best date for corn discrimination from two other legumes, peanut and soybean, because all OSMI equivalent bands and their ratio values in June 22 were highly significant for corn separability. Phenological growth stage of a silage corn (rs510) could be estimated as a function of spectral reflectance signatures in vegetative stage. Five growth stage prediction models were generated by the SAS procedures REG and STEPWISE with OSMI equivalent bands and their ratio values in vegetative stage.

In this study, we was measured the radiance reflectance by using multi-spectral image of low resolution camera(LRC) which will be loaded in the multi-purpose satellite(KOMPSAT) to use the data in analyzing water pollution. Also we investigated the possibility of extraction of water quality factors in rivers and water body by using high resolution remote sensing data such as Airborne MSS. Especially, we tried to extract the environmental factors related with eutrophication, and also tried to develop the process technique and the radiance feature of reflectance related with eutrophication. The results were summarized as follows: First, the spectrum of sun's rays which reaches the surface of the earth was consistent with visible rays bands of 0.4${\mu}{\textrm}{m}$~0.7${\mu}{\textrm}{m}$ and about 50% of total quantity of radiation were there. And at around 0.5${\mu}{\textrm}{m}$ of green spectral band in visible rays bands, the spectrum was highest. Second, as a result of the radiance reflectance Chlorophyll-a represented high spectral reflectance mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and suspended sediments and turbidity represented high spectral reflectance at 0.8${\mu}{\textrm}{m}$ and at 0.57${\mu}{\textrm}{m}$ each. Third, as a result of the water quality analysis by using Airborne MSS, Chlorophyll-a could have a distribution chart when carried out ratio of B3 and BS to B7. And Band 7 was useful for making the distribution chart of suspended sediments. And when we carried out PCA, suspended sediments and turbidity had distributions at PC 1 , PC 4 each similarly to ground truth data. Above results can be changed according to the change of season and time. Therefore, in order to analyze more exactly the environmental factors of water quality by using LRC data, we need to investigate constantly the ground truth data and the radiance feature of reflectance of water body. Afterward in this study, we will constantly analyze the radiance feature of the surface of water in water body by measuring the on-the-spot radiance reflectance and using low resolution satellite image(SeaWiFs). Besides, we will gather the data of water quality analysis in water body and analyze the pattern of water pollution.

The objectives of this study are to reveal relationship between tree physiology and spectral reflectance on effects of artificial acid rain and to obtain basic data on optimal wave length for forest of LRC sensor on KOMPSAT-2. Three pH levels of artificial acid rain - control, pH4.5 and pH3.0 - were applied to Pinus and Quercus species. Three types of the acid rain were spraied at the amount of 500m1 in every two days. Spectral reflectance data was collected once in a month by using GER 1500 (350~2500nm) or Ll 1800(300~1100nm) Spectroradiometer. The data was measured three times in a pH level. The results of this study are as follows; in April, the spectral reflectance of Pinus species was high in order at the level of pH3.0, control and pH4.5; in May, control, pH3.0 and pH4.5; in June, control, pH4.5 and pH3.0. That of Quercus species was high in the order of control, pH4.5 and pH3.0 in May; in June, control, pH3.0 and pH4.5, especially, within infrared wave length range, control, pH4.5 and ph3.0.

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests were performed to see how cloud cover and sun glint affect the priority determined by pigment concentration distributions, and consequently to minimize their seasonal effects upon the data collection planning.

Absorption coefficient per mass unit of particles, specific absorption coefficient, is one of main parameters in developing algorithms for ocean color remote sensing. Specific absorption coefficient of chlorophyll (a$^*_{ph}$) and suspended sediment (SS) were analyzed by "wet filter technique" and "Kishino method" for data sets observed in the Yellow and Mediterranean Seas. A new data-recovering method for the filter technique was also developed using spectrum slopes. This method recovered the baseline of spectrum that was often missed in the Kishino method. High a$^*_{ph}$($\lambda$) values in the oligotrophic Mediterranean Sea and low values in the Yellow Sea were observed, spanning over the range of 0.02 to 0.12 $m^2$/mg, at the chlorophyll maximum absorption wavelength 440nm. The empirical relationship between a$^*_{ph}$ and chlorophyll concentration was found to fit a power function, which was slightly different from that proposed by Bricaud et ai. (1995). Absorption specific coefficients for suspended sediment (a$^*_{SS}$) didn't show any relationship with concentrations of suspended sediment. However, the average value of a$^*_{SS}$ at 440nm was close to the specific absorption coefficient of soil (loess) measured by Ahn (1990). The more-pronounced variability of a$^*_{SS}$ than a$^*_{ph}$ perhaps can explain more wide range of size-distribution for SS, which were determined by their specific gravity and agitation of water mass in the sea surface.

Yellow sand event has been studied using SeaWiFS data in order to examine the aerosol optical characteristics in the Yellow Sea and their influences on the atmospheric correction for the ocean color remote sensing. Two SeaWiFS images of April 18 and April 25, 1998, representing Yellow Sand event and clear-sky case respectively, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. SeaWiFS aerosol optical thickness is compared with nearby ground-based sun photometer measurements and also is compared with radiative transfer simulation in conjunction with yellow sand model, examining the performance of NASA's atmospheric correction algorithm in case of the heavy dust event.

To examine the detectability of the aerosol and/or Yellow dust from China crossing over the Yellow sea, three works carried out as follows , Firstly, a comparison was made of the visible(VIS), water vapor(WV), and Infrared(IR) images of the GMS-5 and NOAA/AVHRR on the cases of yellow sand event over Korea. Secondly, the spectral radiance and reflectance(%) was observed during the yellow sand phenomena on April, 1998 in Seoul using the GER-2600 spectroradiometer, which observed the reflected radiance from 350 to 2500 nm in the atmosphere. We selected the optimum wavelength for detecting of the yellow sand from this observation, considering the effects of atmospheric absorption. Finally, the atmospheric radiance emerging from the LOWTRAN-7 radiative transfer model was simulated with and without yellow sand, where we used the estimated aerosol column optical depth ($\tau$ 673 nm) in the Meteorological Research Institute and the d'Almeida's statistical atmospheric aerosol radiative characteristics. The image analysis showed that it was very difficult to detect the yellow sand region only by the image processing because the albedo characteristics of the sand vary irregularly according to the density, size, components and depth of the yellow sand clouds. We found that the 670-680 nm band was useful to simulate aerosol characteristics considering the absorption band from the radiance observation. We are now processing the simulation of atmospheric radiance distribution in the range of 400-900 nm. The purpose of this study is to present the preliminary results of the aerosol and/or Yellow dust detectability using the Ocean Scanning Multispectral Imager(OSMI), which will be mounted on KOMPSAT-1 as the ocean color monitoring sensor with the range of 400-900 nm wavelength.

In this paper, we propose a new method for multispectral image compression that is based on highly correlated relational properly taken from a spatial image and its wavelet transform. The highly active regions, such as edges or contour, in the spatial domain are appeared as significant coefficients in the wavelet transform domain; and the low active regions like background as insignificant. These characteristics play an important role in designing the system. The simulation results have shown us that the proposed method has better performance in terms of the reconstructed image quality and the transmitted bit rakes. Practically, our system can be successfully applied to the application areas that require of progressive transmission. For some multispectral images with relatively low activity, we have obtained the more good results.

The earth's environmental problems have attracted serious attention worldwide. Various kinds of environmental data, such as remote sensing data, have become available for examining. Although this data is crucial to understanding such problems, there has become an over-abundance in variety of size, format, and filetype which makes it difficult for researchers to handle. We feel that earth environmental researchers should not be burdened by such cumbersome tasks. Therefore, we are developing a digital library for earth environmental information and a VRML based data visualization system for it. Even now, content-based image retrieval systems have many problems attributed to the degree of difficulty in implementing them. Thus, we are trying to visualize this data so that researchers can utilize it more efficiently, effectively, and easily. A great advantage for VRML users is that people can see environmental data from any perspective above the earth and with any resolution easily. Also by using MPEG-movie, users can observe the changes of data drawn from time series files.

Flood is the main natural disaster mostly in the world. It is a care problem to prevent flood disaster generally. The frequency of flood disaster is high and the distributing field is wide, the 50 percent population and 70 percent properties distribute at the threaten field of flood disaster in China. Flood disaster has caused a huge amount of economical losses and these losses have an increasing trend. Along with the development of reducing natural disaster action, it has become one of the most attentive problems for monitoring flood, preventing flood and forecasting flood efficiently. Remote sensing has the characteristics of large spatial observing areas, wide spectrum ranges, and imaging far away from the targets, imaging capabilities all weather. Spatial remote sensing information, which records the full, processes of the disaster's occurrence and development in real-time. It is a scientific basis for management, planning and decision-making. Through systemic analyzing the RS monitoring theory, based on compounding RS information, the technology and method of monitoring flood disaster are studied.