The images of the meteorological satellite NOAA contain geometrical distortions caused by its ambiguous position, its vibration, its sensor's movement, and so on. Geometric correction of satellite images is one of the most important parts in many remote sensing as the primary processing. Ground control points (GCP's) are necessary to check the accuracy of geometric correction and used for precise geometric correction. In this paper, a method for automatically selecting the residual error is presented. Calculating the effective angle and residual errors vector using the succeeded matching GCP's, precise geometric correction using an affine transformation is applied to systematically a corrected image. And the error is decreased by an affine transformation. The above enable the geometric correction of high quality.

Since the advent of high resolution satellite image, possibilities of applying various human interpretation mechanism to these images have increased. Also many studies about these possibilities in many fields such as computer vision, pattern recognition, artificial intellegence and remote sensing have been done. In this field of these studies, texture is defined as a kind of quantity related to spatial distribution of brightness and tone and also plays an important role for interpretation of images. Especially, methods of obtaining texture by statistical model have been studied intensively. Among these methods, texture measurement method based on cooccurrence matrix is highly estimated because it is easy to calculate texture features compared with other methods. In addition, these results in high classification accuracy when this is applied to satellite images and aerial photos. But in the existing studies using cooccurrence matrix, features have been chosen arbitrarily without considering feature variation. And not enough studies have been implemented for appropriate resolution selection in which cooccurrence matrix can extract texture. Therefore, this study reviews the concept of cooccurrence matrix as a texture measurement method, evaluates usefulness of several features obtained from cooccurrence matrix, and proposes appropriate resolution by investigating variance trend of several features.

Land cover map of 30 arc-second grid by NOAA AVHRR data for the whole Asia was produced by the authors as the project of the Asian Association on Remote Sensing(AARS). Land cover change monitoring of continental scale by satellite data needs preprocessing to remove undesirable factors due to noises, atmosphere, or the effect by solar zenith angle. The paper describes the method to remove these factors. The most important thing for better mapping/monitoring in the future is the accumulation of ground truth data by many land cover related researchers. The project of the development of Global Land Cover Ground Truth Database(GLCGT-DB) is proposed.

This paper addresses a new project being carried out at Satellite Technology Research Center. The purpose of the project is to implement a system which receives, processes and stores 1m resolution satellite image transmitted at over 300Mbps down link data rates. In order to develop such a system, a system operational concept design and a requirements study were being carried out As a result of the operational concept design, system objectives, system context and system functions were defined. The system shall be operated according to the philosophy of maximum automation. rapid processing, reliability, integrity, cost effectiveness, and expandability. The system is divided into twelve independent processes and its behavior is modeled by operational scenario, which are combinations of independent processes. Process information and logs generated by the system shall be stored in databases and data received and generated be automatically archived and managed in a hierarchical storage device. The system shall have redundant components in order to be ready for recovering from sudden system failures. This paper will describe in detail the system operational concept design and the system requirements derived from the operational concept design.

This paper covers the development of a highly portable and low cost SPOT image data receiving system. We followed two design approaches. One is the software-based approach by which most of the real-time processing is handled by software. With the complete software-based design, it is simple to add a function for receiving any additional satellite data. Satellite-specific format handlers including error correction, decompression and decryption can easily be accommodated. On the other approach. we used a general hardware platform, IBM-PC and a low cost SCSI RAID (Redundant Away of Independent Disks), and therefore, we can make a low cost system.

The development of a low earth orbit microsatellite is recognized as a good means of enhancing the technological capability, to gain experience and to train engineers to acquire knowledge and experience in space systems. Most developed countries in space technology do not allow the transfer of critical space technologies such as technology involved in attitude determination and control systems. And the export of critical components and equipment such as high precision attitude sensors is tightly controlled. Therefore it is inevitable to independently acquire self-design and manufacturing capability to implement a satellite mission. The KITSAT-3 program was aimed at verifying the capability to design, develop and operate an indigenous microsatellite system, which includes such critical technologies and associated components and equipment, as well as train engineers. KITSAT-3 was launched on May 26, 1999 using the Indian launcher PSLV-C2. The operations team has successfully performed a full functional checkout during the launch and early operations phase and the satellite is presently in a normal operations mode. This paper introduces the KITSAT-3 program and the results of the initial operations.

A compact imaging system, the Multi-spectral Earth Imaging System (MEIS) was developed and operated on an engineering test satellite, KITSAT-3 at the orbital altitude of 720 km. The MEIS takes multi-spectral images of the earth's surface with the swath width of 48 km and the ground sampling distance of 13.8 m in three spectral bands. A brief technical description of the KITSAT-3 MEIS and the result from its initial operation since early June, 1999 are presented. The quality of images produced by the KITSAT-3 MEIS was found comparable to that of images from existing commercial earth observation satellites from its preliminary assessment.

In this paper, we describe the configuration of the KITSAT-3 image data receiving, archiving, processing and distribution system in operation. Following the low-cost and software-based design concept, the whole system is composed of three PCs : two for data receiving, archiving and processing which provide a full dual-redundant configuration and one for image catalog browsing which can be accessed by public users. Except that receiving and archiving PCs have serial data ingest boards plugged in, they are configured by general peripherals. This basic and simple hardware configuration made it possible to show that a very low cost system can support a full ground operation for the utilization of high-resolution satellite image data.

The paper presents an automated method for generating fuzzy rules and fuzzy membership functions for pattern classification from training sets of examples and an application to the land-cover classification. Initially, fuzzy subspaces are created from the partitions formed by the minimum and maximum of individual feature values of each class. The initial membership functions are determined according to the generated fuzzy partitions. The fuzzy subspaces are further iteratively partitioned if the user-specified classification performance has not been archived on the training set. Our classifier was trained and tested on patterns consisting of the DN of each band, (XS1, XS2, XS3), extracted from KITSAT-3 multispectral scene. The result represents that our classification method has higher generalization power.

1999년 5월 26일에 발사된 우리별 3호는 고해상도 지구관측 센서가 담재되어 있으며, SPOT과 거의 유사한 분광대를 갖고 잇다. 따라서 본 보고에서는 우리별 3호에서 획득한 위성영상의 활용가능성을 확인하는 것을 주목적으로 하며, 현재 상용으로 제공되고 있는 대표적인 위성영상인 Landsat TM과 SPOT영상과 비교하는 것을 부목적으로 한다.

The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.

Remote sensing (RS) data show the surfaces of the earth only but cannot provide the shape data of building sides. The proposed method recovers a 3D shape of building sides from stereo images. Its result shows a higher possibility for recovering a large shaped object by overcoming the difficulties of traditional stereo matching techniques. The urban area will be visualized more realistically than the current model based on graphic and vector data.

Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3B GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a file format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(eXtensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for. users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

An efficient modeling and management of a large amount of surface data for a wide rage of geographic information play an important role in determining the functionality of 3D geographic information system. It has been put many efforts to design and manage an effective way to enhence the manipulation of the data by considering geometry type and data structures. Recently, DEM(Data Elevation Model) and TIN(Triangulated Irregular Network) are used for representing surface data. In this paper, we propose a 3D data processing method. The method utilizes the major properties of DEM and TIN, respectively. Furthermore, by approximating DEM with a TIN of an appropriate resolution, we can support a fast and realistic surface modeling. We implement the structure with the following 4 level stages. The first is an optimal resolution of DEM which represent all of wide range of geographic data. The second is the full resolution DEM which is a subarea of original data generated by user's selection in our implemeatation. The third is the TIN approximation of this data with a proper resolution determined by the relative position with the camera. And the last step is multi-resolution TIN data whose resolution is dynamically decided by considering which direction user take notice currently. Specially, the TIN of the last step is designed for realtime camera navigation. By using the structure we implemented realtime surface clipping, efficient approximation of height field and the locally detailed surface LOD(Level of Detail). We used the initial 10-meter sampling DEM data of Seoul, KOREA and implement the structure to the 3D Virtual GIS based on the Internet.

Recently, the necessity of accessing spatial data from remote computer via network has been increased as distributed spatial data have been increased due to their size and cost. Many methods have been used in recent years for transferring spatial data, such as socket, CORBA, HTTP, RPC, FTP, etc. In this paper, we propose spatial clearinghouse components to access distributed spatial data sources via CORBA and Internet. The spatial clearinghouse components are defined as OLE/COM components that enable users to access spatial data that meet their requests from remote computer. For reusability, we design the spatial clearinghouse with UML and implement it as a set of components. In order to enhance interoperability among different platforms in distributed computing environment, we adopt international standards and open architecture such as CORBA, HTTB, and OpenGIS Simple Features Specifications. There are two kinds of spatial clearinghouse: CORBA-based spatial clearinghouse and Internet-based spatial clearinghouse. The CORBA-based spatial clearinghouse supports COM-CORBA bridge to access spatial data from remote data providers that satisfy the OpenGIS Simple Features Specification for OLE/COM using COM and CORBA interfaces. The Internet-based spatial clearinghouse provides Web-service components to access spatial data from remote data providers using Web-browser.

The paper first proposes an empirical algorithm for detecting dust-loaded airmass observed by Sea Wide Field-of-view Scanner (SeaWiFS). The proposed dust index formula is based on the curvature of the spectral reflectance estimated from the SeaWiFS band 4 (510 nm band) through band 8 (865 nm band) data, assuming "clear ocean water" reflectance. Evaluation of the algorithm is made over several typical Asian dust images including the ones over the Pacific in April, 1998, when a major dust event was reported. The study analyzes the performance and the characteristics of the algorithm by comparing the satellite-derived dust index images with contemporaneous columnar concentration of dust particles predicted by a numerical dust transport model. The comparison reveals several small-scale differences although their dust distribution patterns show good agreement generally.

We proposed a new retrieval method for aerosol's real part of refractive index, optical thickness, and Angstrom exponent using POLDER's directional reflectance and polarization data. We showed that aerosol's real part of refractive index can be retrieved systematically using multi-directional PR(polarization and reflectance) diagrams in a single infrared band by our algorithm for the first time. We examined the retrieved results, by comparing with the simultaneously measured sky observation data at the study site and we obtained a reasonable agreement between them.

We have analyzed AVHRR global data set for obtaining aerosol and cloud microphysical parameters, i. e., optical thickness and size index of particle polydispersions. From the results, it is found that the cloud optical thickness increases with increasing aerosol column number, which seems to be caused mainly by decreasing cloud particle radius, The cloud liquid water path was observed to be relatively constant without a significant dependence on the aerosol number. Further comparison of the satellite results with a general circulation model simulation.

The Tropical Rainfall Measuring Mission(TRMM) is a United States-Japan project for rain measurement from space. The first spaceborne Precipitation Radar(PR) has been installed aboard the TRMM satellite. The ground based validation of the TRMM satellite observations was conducted by TRMM science team through a Global Validation Program(GVP) consisted of 10 or more ground validation sites throughout the tropics. However, TRMM radar should always be validated and assessed against reference data to be used in Korean Peninsula because the rainrates measured with satellite varies by time and space. We have analyzed errors in the comparison of rainrates measured with the TRMM/PR and the ground-based instrument i.e. Automatic Weather System(AWS) by means of statistical methods. Preliminary results show that the near surface rainrate of TRMM/PR are highly correlated with ground measurements especially for the very deep convective rain clouds, though the correlation is changed according to the type and amount of precipitating clouds. Results also show that TRMM/PR instrument is inclined to underestimate the rainrate on the whole over Korea than the AWS measurement for the cases of heavy rainfall.

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

Relations between GMS-5 infrared brightness temperature with SSM/I retrieved rain rate are determined by a probability matching method similar to Atlas et al. and Crosson et al. For this study, coincident data sets of the GMS-5 infrared measurements and SSM/I data during two summer seasons of 1997 and 1998 are constructed. The cumulative density functions (CDFs) of infrared brightness temperature and rain rate are matched at pairs of two variables which give the same percentile contribution. The method was applied for estimating rain rate on 31 July 1998, examining heavy rainfall estimation of a flash flood event over Mt. Jiri. Results were compared with surface gauge observations run by Korean Meteorological Administration. It was noted that the method produced reasonably good quality of rain estimate, however, there was large area giving false rain due to the anvil type clouds surrounding deep convective clouds. Extensive validation against surface rain observation is currently under investigation.

The imaging characteristics of a 2-D interferometric synthetic aperture radiometer, such as an angular resolution, depend largely on the type of an antenna array. In this paper, different array configurations of antenna are studied and compared with each array types to get more high resolution image in spatial. T-, X- and Y- types of antenna array are considered and the performances of each type are analyzed considering spatial resolution. The simulation results of candidate antenna types are presented in this paper. In case of Y-type the coverage area of the visibility function is wide and the angular resolution is high more than the others. X-type array shows the good performance for side lobe level.

Typhoons were known by contributing to transporting plus heat or kinetic energy from equatorial region to midlatitude region. Due to the strong damage from typhoon, we acknowledged the theoretical study and the importance of accurate forecast about typhoon. In this study, typhoon forecasting system was developed to search the tracks of past typhoons or to display similar track of past typhoon in comparison with the path of current forecasting typhoon. It was programmed using Interactive Data Language(IDL), which was a complete computing environment for the interactive analysis and visualization of data. Typhoon forecasting system was also included satellite image and auxiliary chart. IR, Water Vapor, Visible satellite images helped users analyze an accurate forecast of typhoon. They were further refined the procedures for generating water vapor winds and gave an initial indication of their utility for numerical weather prediction(NWP), in particular for typhoon track forecasting where they could provide important information. They were also available for its utility in typhoon tracer or intensity.

Rainfall characteristics for designing the optimum millimeter-wave communication systems from two rainfall data set was analyzed. Two rainfall data sets were compared; one-minute rainfall rate data, one-hour synoptic observation data. Each data set has different observation method, sampling frequency. We looked for tendency and quality confluence between two data sets. We showed several results using one-minute rainfall data by millimeter-wave attenuation model. A climatological one-minute rainfall rate data set over Korean Peninsula will be made after data quality control procedure

Wind velocity is one of the primary variables for describing atmospheric state from GMS-5. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP(Numerical Weather Prediction) models. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images. Multi spectral imagery from GMS-5 was used for this purpose and applied to Korean region with together BoM(Bureau of Meteorology). The derivation of wind velocity estimates from low and high resolution visible, split window infrared, and water vapor images, resulted in improvements in the amount and quality of wind data available for forecasting.

SSH(Sea Surface Height) from TOPEX/Poseidon and SST data are analyzed to estimate characteristics of annual and inter-annual variations in the East Asian seas(110E - l80E, 20N - 50N) from November 1992 to May 1998. In EOF analysis of SSH and SST, 57% and 97% of the variance are represented by the first two modes. The first mode of SSH and SST shows strong annual variations expected for steric changes. The second mode of SSH shows a long-term variation, but that of SST shows 3 - 4month offset from annual variation. In the EOF analysis of the SSH and SST, 61% and 54% of the total variance are represented by the first three modes. The first mode represented a long-term variation, and the third mode reflected the bi-ennial variation. The first three mode were not strongly correlated with ENSO. We further apply Canonical Correlation Analysis(CCA) to find the dominant correlation patterns with ENSO.

The objective of this study is to quantitatively evaluate the effects of various SAR speckle reduction methods for multisource land-cover classification by backpropagation neural network, especially over the coastal region. The land-cover classification using neural network has an advantage over conventional statistical approaches in that it is distribution-free and no prior knowledge of the statistical distributions of the classes is needed. The goal of multisource land-cover classification acquired by different sensors is to reduce the classification error, and consequently SAR can be utilized an complementary tool to optical sensors. SAR speckle is, however, an serious limiting factor when it is exploited for land-cover classification. In order to reduce this problem. we test various speckle methods including Frost, Median, Kuan and EPOS. Interpreting the weights about training pixel samples, the “Importance Value” of each SAR images that reduced speckle can be estimated based on its contribution to the classification. In this study, the “Importance Value” is used as a criterion of the effectiveness.

Baikdu-san was a very active volcano during the Cenozoic era and is believed to be formed in late Cenozoic era. Recently it was also reported that there was a major eruption in or around 1002 A.D. and there are evidences which indicate that it is still an active volcano and a potential volcanic hazard. Remote sensing techniques have been widely used to monitor various natural hazards, including volcanic hazards. However, during an active volcanic eruption, volcanic ash can basically cover the sky and often blocks the solar radiation preventing any use of optical sensors. Synthetic aperture radar(SAR) is an ideal tool to monitor the volcanic activities and lava flows, because the wavelength of the microwave signal is considerably longer that the average volcanic ash particle size. In this study we have utilized several sets of SAR data to evaluate the utility of the space-borne SAR system. The data sets include JERS-1(L-band) SAR, and RADARSAT(C-band) data which included both standard mode and the ScanSAR mode data sets. We also utilized several sets of auxiliary data such as local geological maps and JERS-1 OPS data. The routine preprocessing and image processing steps were applied to these data sets before any attempts of classifying and mapping surface geological features. Although we computed sigma nought ($\sigma$$^{0}$) values far the standard mode RADARSAT data, the utility of sigma nought image was minimal in this study. Application of various types of classification algorithms to identify and map several stages of volcanic flows was not very successful. Although this research is still in progress, the following preliminary conclusions could be made: (1) sigma nought (RADARSAT standard mode data) and DN (JERS-1 SAR and RADARSAT ScanSAR data) have limited usefulness for distinguishing early basalt lava flows from late trachyte flows or later trachyte flows from the old basement granitic rocks around Baikdu-san volcano, (2) surface geological structure features such as several faults and volcanic lava flow channels can easily be identified and mapped, and (3) routine application of unsupervised classification methods cannot be used for mapping any types of surface lava flow patterns.

Microwave polarimetric backscattering from a wet soil surface had been measured using a Ku-band polarimetric scatterometer at the incidence angles ranging from 10$^{\circ}$ to 70$^{\circ}$ Since the accurate target parameters as well as the radar parameters are necessary for radar scattering modeling, a complete and accurate set of ground truth data were also collected, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. The measured polarimetric backscattering coefficients (vv-, hh-, vh-, hv-polarizations) were compared with theoretical models and empirical models. A new semi-empirical model for microwave polarimetric radar backscattering from bare soil surfaces was developed using polarimetric radar measurements and the knowledge based on the theoretical and numerical solutions. The model was found to yield very good agreement with the backscattering measurements of this study.

This paper investigated and evaluated the NASA's Shuttle Imaging Radar-C (SIR-C) multiple frequency SAR data for differential backscattering effects of microwave from the surface geological materials overlying the skarn type mineralization. Although an integrated approach in mineral exploration is more cost effective and is well in use, there are still many technical and scientific issues to be further investigated and researched. In this study we have reprocessed several sets of previously surveyed exploration data and experimented with fuzzy logic digital fusion of the preprocessed data with respect to chosen exploration targets. Among the numerous fuzzy logic operators, which are currently available for a data driven integrated exploration strategy, we used varying combinations of fuzzy MIN, fuzzy MAX, and fuzzy SUM operators along with Gamma operator for fusion of exploration data, including the contact metamorphic zone information. The final exploration target tested was a skarn type W-Mo-F mineralization in the study area. The fuzzy logic derived mineral potential anomaly almost exactly matched the differential backscattering anomalies on the C-band and L-band SIR_C data when overlaid on each other. Although this high degree of correlation between these two data sets is remarkable, the differential backscattering anomaly over the skarn type W-Mo-F mineralization in the study area requires further investigation.

Previous technology of remote sensing was focused on analyzing raster image and gaining information through image processing. But now it has extended to diverse fields like automatic map generation, material exploitation or monitoring environmental changes with effort to utilizing practical usage. And with rapid expansion of information exchange on Internet and high-speed network, the demand of public which want to utilize remotely sensed image has been increased. This makes growth of service on acquisition and processing remotely sensed image. GeoNet is a Java-based remotely sensed image processing system. It is based on Java object-oriented paradigm and features cross-platform, web-based execution and extensibility to client/server remotely sensed image processing model. Remotely sensed image processing software made by Java programming language can suggest alternatives to meet readily demand on remotely sensed image processing in proportion to increase of remotely sensed data. In this paper, we introduce GeoNet and explain its architecture.

Intelligent schemes for an automatic generation of DEM (digital elevation model) are implemented. The need for these post-processing schemes is that interpolation alone produces severe blunders, however sophisticated it is. These blunders occur most seriously along the boundaries of a scene, over rivers, and along the coast. Even a state-of-the-art commercial software retains such blunders. The intelligent schemes implemented are (1) center-of-gravity and empty-center-index which quantify how evenly distributed interpolants are within in interpolation radius. (2) a segmentation scheme to discern whether or not an empty segment in stereo-match results should be interpolated, and (3) a segmentation scheme for removing noise-like features, with these methods, in the final DEM, identical coastline and river region to those in the original SPOT scenes are achieved. The DEM exhibits substantial improvements over the products of an existing commercial software.

This paper presents an algorithm for building detection from aerial image using segment measure function and line relation. In the detection algorithm proposed, edge detection, linear approximation and line linking are used and then line measure function is applied to each line segment in order to improve the accuracy of linear approximation. Parallelisms, orthogonalities are applied to the extracted liner segments to extract building. The algorithm was applied to aerial image and the buildings were accurately detected.

Stereo matching is one of the most crucial parts in DEM generation. Naive stereo matching algorithms often create many holes and blunders in a DEM and therefore a carefully designed strategy must be employed to guide stereo matching algorithms to produce “good” 3D information. In this paper, we describe one such a strategy designed by the use of scene geometry, in particular, the epipolarity for generation of a DEM from linear pushbroom images. The epipolarity for perspective images is a well-known property, i.e., in a stereo image pair, a point in the reference image will map to a line in the search image uniquely defined by sensor models of the image pair. This concept has been utilized in stereo matching by applying epipolar resampling prior to matching. However, the epipolar matching for linear pushbroom images is rather complicated. It was found that the epipolarity can only be described by a Hyperbola- shaped curve and that epipolar resampling cannot be applied to linear pushbroom images. Instead, we have developed an algorithm of incorporating such epipolarity directly in least squares correlation matching. Experiments showed that this approach could improve the quality of a DEM.

Technology of GIS evolved as a means of assembling and analyzing diverse spatial data. Many systems have been developed, and almost of systems are proprietary. There is a lots of lack of interoperability and reusability between them. This paper describes the development of Open GIS component software. The developing system have an end in view of GIS tool software which is interoperable and reusable. To increase the interoperability and reusability, the system is based on the OGC(Open GIS Consortium)'s Open GIS Simple Features Specification for OLE/COM. The OGC's specification is announced to increasing the full interoperability of various geospatial data and geoprocessing resources. With the Open specification, component based software ensures the reusability. We implement three kinds of component: Geometry component, Spatial Reference System Component, and MapBase Component. The first two components are compatible to the OGC's specification and the third one is designed to GIS tool software for variant GIS applications. The Open GIS component software system is developed on object-oriented computing environment, ATL/COM and Visual C++. As we made application programs using Visual Basic, the advantages of component based Open GIS software was proved.

In AVL, GIS analyze the information from the vehicles to provide commercial or other value far user. As spatial analysis functions in GIS make a new valuable information using the vehicle's position and geographic object's location, they perform an important roles to improve the management efficiency of vehicles. Most GIS however are used static data for the spatial analysis, so the research area on AVL used dynamic vehicle location has generated unsuitable result. In this study, we use GPS real time tracking data to perform spatial analysis between moving vehicle and static geographic object. The method proposed in this paper considers the driving direction of vehicle and creates the result which is located in forward of vehicle. In this paper, two spatial analysis functions, near and connectivity, are developed.

Korea Multi-Purpose Satellite-1 (KOMPSAT-1) is developed by the Korea Aerospace Research Institute (KARI) with the aid of TRW and will be launched on the Nov. 24, 1999 at the Vandenberg Air Base in CA, U.S, Now, the satellite application group in KARI is preparing for the service with the KOMPSAT-1 satellite data. For the purpose of supplying good service to the users, data application planning has to be established before launching satellite. To use satellite data effectively, KARI makes a plan for data policy, data price, mission planning, and commercializing strategy. This study was carried out with the purpose of effective use of satellite data. For this purpose, KARI makes a user group first. There are 58 user groups to use KOMPSAT-1 data for public welfare and research sectors. These user groups include government, public corporations, institutes, and universities. KARI will offer the service to users through online using Internet. Secondly, KARI makes a policy for the priority of KOMPSAT-1 missions. These are classified by the mission priority, payloads, and operational states etc. Thirdly, KARI will make data policy and data price of KOMPSAT- 1 based on the basic master 1)tan. Especially, data price will be determined at trte KOMPSAT-1 committee including Ministry of Science and Technology (MOST). KARI is also trying to commercialize the data with the domestic and foreign companies to expand the use of KOMPSAT-1 data in the industries sector. Afterward in this study, KARI will continue the improvement for the effective distribution of KOMPSAT-1 data for all users.

Space Physics Sensor (SPS) on-board the KOMPSAT-1 consists of the High Energy Particle Detector (HEPD) and the Ionospheric Measurement Sensor (IMS). The HEPD is to characterize the low altitude high energy particle environment and the effects on the microelectronics due to these high energy Particles. It is composed of four sensors: Proton and Electron Spectrometer(PES), Linear Energy Transfer Spectrometer (LET), Total Dose Monitor (TDM), and Single Event Monitor(SEM). 35MeV proton beam from the medical KCCH cyclotron, at Korea Cancer Center Hospital in Seoul, is used to calibrate the PES. Primary proton beam of 35MeV scattered by polypropylene target is converted to various energy Protons according to the elastic collision kinematics. In this calibration, the threshold level of the proton in the PES can be determined and the energy ranges of PES channels are also calibrated.

The aim of our study is to develop new algorism for sea fog detection by using Geostational Meteorological Satellite-5(GMS-5) and suggest the techniques of its continuous detection. So as to detect daytime sea fog/stratus(00UTC, May 10, 1999), visible accumulated histogram method and surface albedo method are used. The characteristic value during daytime showed A(min) > 20％ and DA < 10％ when visble accumulated histogram method was applied. And the sea fog region which detected is of similarity in composite image and surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), infrared accumulated histogram method and maximum brightness temperature method are used, respectively. Maximum brightness temperature method(T_max method) detected sea fog better than IR accumulated histogram method. In case of T_max method, when infrared value is larger than T_max, fog is detected, where T_max is an unique value, maximum infrared value in each pixel during one month. Then T_max is beneath 700hpa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which detected by T_max method was similar to the result of National Oceanic and Atmosheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference). But inland visibility and relative humidity didn't always agreed well.

A data assimilation system for a 1-dimensional mixed layer model has been constructed using the adjoint method. The classical adjoint method does not work well for the mixed layer variabilities due to the occurrence of spikes in the gradient of the cost function. To solve this problem, the two techniques of scaling the cost function and optimization in the frequency space are used. As a result, the heat flux can be reliably estimated with an accuracy of 8Wm$^{-2}$ rms error in the identical twin experiments. We then applied this system to the tropical Pacific TOGA-TAO buoy data. The air-sea heat flux as well as the mixed layer variability were estimated in close approximation to the buoy data, particularly on time scales longer than the seasonal one.

Surface solar radiation over the sea is estimated using Visible and Infrared Spin Scan Radiometer data onbord Geostationary Meteorological Satellite(GMS) 5 for January, 1997 to December 1997 in clear and cloudy conditions. The hourly insolation is estimated with a spatial resolution of 5$\times$ 5 km grid. The island pyranometer belonging to the Japan Meteorological Agency is used for validation of the estimated insolation. It is shown that the estimated hourly insolation has RMSE(root mean square) error of 104 W/$m^2$. The variability of the hourly solar radiation was investigated on 3 areas over seas around Korean Peninsula. The solar radiation of East Sea is similar to Yellow Sea. The maximum value of solar radiation is on June of year. The maximum value in south sea is on August because weather is poor by low pressure and front in June

Accurate ocean surface fluxes with high resolution are critical for understanding a mechanism of global climate. However, it is difficult to derive those fluxes by using ocean observation data because the number of ocean observation data is extremely small and the distribution is inhomogeneous. On the other hand. satellite data are characterized by the high density, the high resolution and the homogeneity. Therefore, it can be considered that we obtain accurate ocean surface by using satellite data. Recently we constructed ocean surface data sets mainly using satellite data. The data set is named by Japanese Ocean Flux data sets with Use of Remote sensing Observations (J-OFURO). Here, we introduce J-OFURO. The data set includes shortwave radiation, longwave radiation, latent heat flux, sensible heat flux, and momentum flux etc. Moreover, sea surface dynamic topography data are included in the data set. Radiation data sets covers western Pacific and eastern Indian Ocean because we use a Japanese geostationally satellite (GMS) to estimate radiation fluxes. On the other hand, turbulent heat fluxes are globally estimated. The constructed data sets are used and shows the effectiveness for many scientific studies.

As one of the key parameters to determine $CO_2$ flux between air - sea interface, it is quite important to know p$CO_2$, which has involved much uncertainty, mainly due to the complex variations of sea surface p$CO_2$ and the paucity of samples, made in ocean. In order to improve the interrelationship between partial pressure (p$CO_2$) and different physical and biochemical parameters in global sea surface water, a new empirical relation is established to correlate and parameterize p$CO_2$ in the mixed layer using the data from recent WOCE cruises. Meanwhile, by new empirical relation, abundant historical hydrographic and nutrients ship data, Levitus data set and NOAA/AVHRR(SST), p$CO_2$ have been accumulated and applied. Then effort has to be made fur promotion of this study to correlate and parameterize p$CO_2$ in the mixed Layer with different physical and biochemical parameters. and further attribute this huge historical data sets and NOAA/AVHRR(SST) data to estimate p$CO_2$. In this paper we analyzed more interrelationship between the model and ship/satellite data set. Finally, the inter-annual variations of p$CO_2$ in sea are presented and discussed.

From the lessons after the Nakhodka oil-spill in Jan. 1997, oil slick detection by using remote sensing data and assimilating the data to the simulation program is important for monitoring the oil-drift pattern. For this object, we are going to construct the oil-spill warning system for estimating the oil-drift pattern using remotesensing/numerical simulation Model. Additionally we plan to use this system for restorating oil-spill damage domestically, such as estimating the ecological damage and making the priority fur restorating the oil-spilled shoreline. This report is intended to summarize the role of geo-informatics in the oil spill accident by not only paying attention to the effect of information provision/information management via the map, but also reporting the interim result in part based on the details discussed in the processes of recovery support and environmental impact assessment during the Nakhodka's accident.

Water pollution is becoming a serious problem in the populous cities and coastal areas near industrial complex. Sometimes, phytoplankton is considered as the most important element in the coastal environment. Phytoplankton is easily estimated by measuring chlorophyll content in the laboratory. In this study, to build up estimating algorithm of the chlorophyll amount related to the monitoring of coastal environments in Kwangyang bay, the correlationship the respective in situ observed data with Landsat TM and SeaWiFS satellite Image was analyzed. It showed that Landsat TM band 3 image has the highest correlationship with observed data, and based upon this result the monitoring algorithm of chlorophyll in coastal area was extracted. This algorithm will be an important for extracting and controlling environment elements in coastal areas in the future. And it has a significant meaning that it has established a spatial data construction in which satellite image alone could monitor the coastal environment.

Global vegetation change is one of major global concerns. Remote sensing images provide an efficient and useful data source to estimate global vegetation covers, and a number of methods have been proposed to estimate them. Among them, the NDVI is one of the most popular indices, and it is_easy to calculate with simple image computing. However, this index is very much affected by the radiometric environment of sensing such as atmospheric conditions and the sun illumination angle. Therefore, it is not appropriate to apply the NDVI to investigate seasonal changes. This paper discusses these problems and proposes an alternative index, MODVI(Modified Vegetation Index), that is less affected by radiometric environment changes. An experiment was conducted to compare these two indices using temporal Landsat TM sub-scenes.

Several commercial companies that plan to provide improved panchromatic and/or multi-spectral remote sensor data in the near future are suggesting that merge datasets will be of significant value. This study evaluated the utility of one major merging process-process components analysis and its inverse. The 6 bands of 30$\times$30m Landsat TM data and the 10$\times$l0m SPOT panchromatic data were used to create a new 10$\times$10m merged data file. For the image classification, 6 bands that is 1st, 2nd, 3rd, 4th, 5th and 7th band may be used in conjunction with supervised classification algorithms except band 6. One of the 7 bands is Band 6 that records thermal IR energy and is rarely used because of its coarse spatial resolution (120m) except being employed in thermal mapping. Because SPOT panchromatic has high resolution it makes 10$\times$10m SPOT panchromatic data be used to classify for the detailed classification. SPOT as the Landsat has acquired hundreds of thousands of images in digital format that are commercially available and are used by scientists in different fields. After the merged, the classifications used supervised classification and neural network. The method of the supervised classification is what used parallelepiped and/or minimum distance and MLC(Maximum Likelihood Classification) The back-propagation in the multi-layer perception is one of the neural network. The used method in this paper is MLC(Maximum Likelihood Classification) of the supervised classification and the back-propagation of the neural network. Later in this research SPOT systems and images are compared with these classification. A comparative analysis of the classifications from the TM and merged SPOT/TM datasets will be resulted in some conclusions.

Use of coherence data from operational satellite based SAR sensors has been experimented both on C and L band to identify landcover in tropics. While coherence data proved useful to improve accuracy in landcover identification, such data are not readily available. On the other hand, integrated use of backcatter data by multiple satellites is readily feasible. The very question to be asked is whether integration of backscatter data on multiple bands (e.g. C and L band) is either inferior or superior to use of coherence data. We therefore still do not have a solid clue to answer to the very question. The aim of this study is to evaluate the performance of "integrated use" of backscatter data on C and L band (by ERS and JERS respectively) to identify landcover, vis-a-vis the same by combination of backscatter and coherence data by single satellite. The study was carried out for an area in the southern part of the Sumatra Island, Indonesia. The area has been intensively converted from natural forest into plantation. Five categories of landcover exist in this study area. By ERS-1, only 2 or 3 classes may be identified with the backscatter data alone, while adding the coherence data could delineate 4 classes. By JERS-1, only 3 to 4 classes may be identified with the backscatter data alone, while 4 classes could be clearly delineated by adding the coherence data. By integrating backscatter data on two bands, 4 to 5 classes may be identified. It represents the best results among cases examined. The outcome of the study suggests that integrated use of backscatter data on two bands by ERS and JERS is as powerful as use of backscatter and coherence data on single band by one of these satellite.

The topographical effect resulted from rugged terrains and inhomogeneous spectral characteristics due to the complexly mixed land cover condition of Korea substantially lower the remotely sensed land cover classification accuracy In this study, a topographic correction method using digital elevation model to alleviate the topographic effects. To deal with inhomogeneous spectral characteristic, a hybrid classifier with inclusion of prior probabilities was introduced. This investigation concluded that the topographical normalization and hybrid classification with prior probabilities are effective on rugged landscape. The overall and average classification accuracies were improved by 0.92％ and 1.016％ respectively. The most substantial and noticeable accuracy improvement was observed in forest areas.

Ground truth measurement system using RC helicopter is very useful to measure BRDF. The helicopter is operated human operator but it can keep its position by GPS aided hovering system. We developed the measurement system and have done ground truth in Mongolia in the summer of 1999 and have made sure the system can measure BRDF expectedly.

A processing system to produce cloud-free composite image data set was developed. In the process, a fine geometric correction based on orbit parameters and ground control points and radiometric correction based on 6S code are applied. Presently, by using AVHRR image data received at Tokyo, Okinawa, Ulaanbaatar and Bangkok, data set of 10 days composite images covering almost whole Asian region.

Lineament extraction from mountain area often provides valuable geological information. In many cases, the lineaments correspond to a series of continuous large valleys. This paper introduces a new lineament extraction method from Digital Elevation Model (DEM) using Raindrop Tracing Algorithm (RTA). The main advantage of this algorithm over conventional Segment Tracing Algorithm (STA) is that it utilizes DEM directly unlike the STA Which utilizes the shaded relief of DEM. The RTA simulates the real life of raindrops that converge into a large valley. The simulation has been done by sprinkling the randomized raindrops over DEM and counting the number of raindrop path that follows the negative gradient of the DEM. The large counting number indicates the location of a big valley where the raindrops converge. With the help of the counting number array (accumulator array) recording the flowing path information, RTA can produce perfectly unbiased binary image of the lineament.

Five institutions, which are very active in data utilization of environmental satellites NOAA and GMS, are connected via high speed networks to construct the databases based on the observations of A AVHRR (Advanced very High Resolution Radiometer) of NOAA satellite and VISSR (Visible and Infrared Scanning Radiometer) of GMS (Geostationary Meteorological Satellite) and to create scientific data sets for land, ocean and ,atmosphere. And vegetation index, sea surface temperature, cloud distribution maps and so on are generated by high speed and huge volume data Processing for studies on long term variations of land, ocean and atmosphere in Asia. In this paper the concept of this project and the activities at the Science University of Tokyo are briefly introduced

Generation of a Digital Elevation Model (DEM) in remote sensing is an important application. The process of DEM generation often requires interpolation. This paper is aimed to introduce a class of interpolation algorithms using spectral information, which is widely used in geophysical applications, and to examine the applicability of the method to DEM interpolation. The interpolation process can be explained in two steps. The first step is for finding spectral information from the known data and the second step is finding missing data so as to follow the spectral trend found in the previous step. The interpolation algorithm has been tested for a real DEM data and problems in the DEM interpolation are discussed.

In this paper, we presents a new disparity map refinement algorithm using statistical characteristics of disparity map and edge information. The proposed algorithm generate a refined disparity map using disparity maps which are obtained from area and feature-based Stereo Matching by selecting a disparity value of edge point based on the statistics of both disparity maps. Experimental results on aerial stereo image show the better results than conventional fusion algorithms in the disparity error. This algorithm can be applied to the reconstruction of building image from the high resolution remote sensing data.

We extracted narrow open water streams from JERS-1 SAR images of the Amazon rain forest. The extracted range of these streams were almost comparable to a high level extraction of the same streams from near-IR images of JERS-1 VNIR data notwithstanding that these features in SAR images show the strong dependence of the observation angle. Large water bodies are relatively easy to extract from JERS-1 SAR images, as they tend to appear as very dark areas; but streams whose width is nearly equal to or less than the spatial resolution no longer appear as very dark features. By using strong scatterers distributed sparsely along the radar facing sides of the streams, we can successfully estimate approximate ranges of waterways and then extract relatively dark line-like features within these ranges.

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability. Especially, snow, soil moisture, surface temperature, vegetation and rain are the key parameters which should be observed in the global scale. In this paper, new algorithms for these land surface hydrological parameters have been developed by introducing frequency and polarization dependencies of these parameters in the microwave radiative-transfer equations. The algorithms were applied to the TRMM Microwave Radiometer. (TMI) and validated by using the ground data obtained in the Tibetan Plateau. The estimated snow, soil moisture, surface temperature, water content of vegetation and rain patterns corresponded reasonably to the observed ones.

The characteristic of East Asian summer monsoon is investigated using 8-year (March 1987-February 1995) - averaged monthly and 5-day mean 1 degree latitude-longitude gridded GMS high-cloud-amount data (HCA). An analysis of these data shows the convective zone (ITCZ) clouds which defined as the percentage of the total grid area covered by clouds with a cloud-top temperature below the 400 hPa-level climatological temperature. The HCA increased clearly over equatorial zone during December and January and 30-40 $^{\circ}$N during May and June. These HCA patterns are coincided with seasonal cycles of summer monsoon which is introduced in historical references. The relationship with the summer monsoon winds as climatological changing of wind direction is analyzed by ECMWF re-analysis 2.5-degree latitude-longitude grid surface data which is calculated with 8-year averaged from January 1987 to January 1995. In addition, the monsoon winds are showed by separated U, V-wind components far manifestation a tendency of onset and retreat data of seasonal monsoon.

This paper describes the development, operations, and applications of ROCSAT-1 and its Ocean Color Imager(OCI) remote-sensing payload. It is the first satellite program of NSPO. The satellite was successfully launched by Lockheed Martin's Athena on January 26, 1999 from Cape Canaveral, Florida.

The optical sensors of Electro-Optical Camera (EOC) and Ocean Scanning Multi-spectral Imager (OSMI) aboard the Korea Multi-Purpose SATellite (KOMPSAT) will be placed in a sun synchronous orbit in 1999. The EOC and OSMI sensors are expected to produce the land mapping imagery of Korean territory and the ocean color imagery of world oceans, respectively. Utilization of the EOC and OSMI data would encompass the various fields of science and technology such as land mapping, land use and development, flood monitoring, biological oceanography, fishery, and environmental monitoring. Readiness of data support for user community is thus essential to the success of the KOMPSAT program. As part of testing such readiness prior to the KOMPSAT launch, we have performed the preliminary acceptance test for the KOMPSAT data processing system using the simulated EOC and OSMI data sets. The purpose of this paper is to demonstrate the readiness of the KOMPSAT data processing system, and to help data users understand how the KOMPSAT EOC and OSMI data are processed and archived. Test results demonstrate that all requirements described in the data processing specification have been met, and that the image integrity is maintained for all products. It is however noted that since the product accuracy is limited by the simulated sensor data, any quantitative assessment of image products can not be made until actual KOMPSAT images will be acquired.

Satellite images without value-added processing may be nothing but artistic painting. That is in order to benefit from satellite images acquired from money-drinking satellites, we should utilize the paramount information in scientific world and practical lift that can be extracted from image. Hence, the Satellite Technology Research Center has developed a integrated software called "Valadd-Pro". In this paper, the main components of the Valadd-Pro are briefly introduced, its value-added product are compared with PCI$^{\circledR}$ commercial software. Based on the results, the performance of the Valadd-Pro is superior to that of PCI$^{\circledR}$ on 6000$\times$6000 SPOT panchromatic images.

Delineation of watersheds is one of the most basic steps for water resource management and National Park management. The purpose of this study is to investigate how to utilize Thematic Mappers scenes to compare watersheds created by running a model with those produced by digitizing topographic maps of Keum River basin. A methodology is designed and tested using Geographic Information Systems (GIS) and remote sensing to map areas with various thematic maps. A CAD data on watersheds from the Decision Support system for Water Quality is converted into GIS format. The digital elevation model with 100-meter resolution is used to create watershed by cumulative watershed method. TM scenes are also classified by new procedures including stacking method, NDVI, NDWI, and unsupervised classification methods. To evaluate the relative correctness Kyerongsan National Park was studied intensively whose area was divided into 6 watersheds in both cases. The boundaries of watershed from the model are less correct than those of the topographic maps. This result shows that automated watershed creating system needs higher-resolution digital elevation model than 100-meters.

Electro-Optical Camera (EOC) is the main payload of the KOMPSAT-1 satellite to perform the mission of cartography that builds up a digital map of Korean territory including a digital terrain elevation map. This paper discusses the issues of the digital image simulation of EOC for the generation of EOC simulated scene as taken by EOC at 685km altitude on orbit. For the purpose, simulation work has been performed with the sensor models of EOC and the satellite platform motions models through image chain analysis from the illumination source (Sun) to a simulated image output in digital number. MODTRAN fur radiance calculation, MTF models of optics, detector and motions of EOC for system point spread function (PSF), and signal chain equations for digital number output are described. Several noise models of EOC are also considered. The final output is the EOC simulated image in digital number. The simulation technique can be used in several phase of a spaceborne electro-optical system development project, feasibility study phase, design, manufacturing, test phases, ground image processing phases, and so on.

With the ready access to the high resolution satellite image data, users of and areas covered by satellite image data are constantly on the rise world-wide. Korea will also be able to take full advantage of the satellite data once the KOMPSAT is successfully launched. Harmonizing satellite data production and application technology and users' needs, along with the guiding policy is essential for promoting satellite data use. Up to now, the Korean government has mainly concentrated on developing production technology for the satellite units. However, the imminent task of independent satellite data production demands a promotion policy for satellite data use. In this context, the policy is defined as an important medium for identifying the role and status of satellite image information at the national level and also Preparing the legal as well as systematic foundation for producing, building, distributing, and packaging satellite data. For example, in the countries with the advanced satellite technology, such as the United States, the United Kingdom, and Australia, digital ortho image and digital elevation model (DEM) are mandatorily included in the National Geographic Framework Data through policy measures. In addition, in order for the efficient provision of the satellite data, separate organization or agency is being in operation for the exclusive production and distribution of the satellite data. The present paper aims to examine the role and status of the satellite data as well as their current status and problems in Korea in reference to the National Spatial Data Infrastructure, and finally to provide the policy directions to promote the satellite data use in public sector on the basis of the preceding analyses.

Remotely sensed data is regarded as a potentially effective data source for the measurement of water quality and for the environmental change of water bodies. In this study, we measured the spectral reflectance by using multi-spectral image of low resolution camera(LRC) which will be loaded in the OSMI multi-purpose satellite(KOMPSAT) scheduled to be launched on 1999 to use the data in analyzing water pollution. We also investigated the possibility of extraction of water quality factors in water bodies by using remotely sensed low resolution data such as NOAA/AVHRR. In this study, Shiwha-District and Sang-Sam Lake was set up as the subject areas for the study. In this part of the study, we measured the spectral reflectance of the water surface to analyze the radiance of the water bodies in low resolution spectral band and tried to analyze the water quality factors in water bodies by using radiance feature from another remotely sensed data such as NOAA/AVHRR. As the method of this study, first, we measured the spectral reflectance of the water surface by using SFOV( Single Field of View) to measure the reflectance of water quality analysis from every channel in LRC spectral band(0.4~O.9${\mu}{\textrm}{m}$). Second, we investigated the usefulness of ground truth data and the LRC data by measuring every spectral reflectance of water quality factors. Third, we analyzed water quality factors by using the radiance feature from another remotely sensed data such as NOAA/AVHRR. We carried out ratio process of what we selected Chlorophyll-a and suspended sediments as the first factors of the water quality. The results of the analysis are below. First, the amount of pollutants of Shiwha-Lake has been increasing every you since 1987 by factors of eutrophication. Second, as a result of the reflectance, Chlorophyll-a represented high spectral reflectance mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and turbidity represented high spectral reflectance at 0.57${\mu}{\textrm}{m}$. But suspended sediments absorbed high at 0.8${\mu}{\textrm}{m}$. Third, Chlorophyll-a and suspended sediments could have a distribution chart as a result of the water quality analysis by using NOAA/AVHRR data.

Ocean Scanning Multispectral Imager (OSMI) is a payload on the KOMPSAT satellite to perform worldwide ocean color monitoring for the study of biological oceanography. The instrument images the ocean surface using a wisk-broom motion with a swath width of 800 km and a ground sample distance (GSD) of<1km 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 compression/storage. The instrument also performs sun and dark calibration for on-board instrument calibration. The OSMI instrument is a multi-spectral imager covering the spectral range from 400nm to 900nm using CCD Focal Plane Array (FPA). The ocean colors are monitored using 6 spectral channels that can be selected via ground commands. KOMPSAT satellite with OSMI was integrated and the satellite level environment tests and instrument aliveness/functional test as well, such as launch environment, on-orbit environment (Thermal/vacuum) and EMl/EMC test were performed at KARI. Test results met the requirements and the OSMI data were collected and analyzed during each test phase. The instrument is launched on the KOMPSAT satellite in the late 1999 and the image is scheduled to start collecting ocean color data in the early 2000 upon completion of on-orbit instrument checkout.

As an example of many possible applications of OSMI data, we present a method to detect red tides. In Korean waters, red tides usually occur in the South Sea where the turbidity is usually high due to strong tidal mixing in the shallow sea. The conventional case 1 chlorophyll algorithm cannot be applied since it cannot distinguish chlorophyll from SS (suspended sediments). In October 1998, a red tide outbreak occurred off the coast of Kunsan. We analyzed the SeaWiFS data of the outbreak. The standard SeaWiFS chlorophyll algorithm OC2 was poor in identifying the red tides. However, comparison of spectra of normalized water-leaving radiance indicates that red tide pixels can be distinguished from sediment-laden pixels. Channel 443 and 555 were effective in showing the spectral characteristics. We suggest K490 algorithm as an example in summarizing the information of the spectra and thereby in distinguishing the red tide pixels. Further development is desirable.

In this study, visible and near infrared channels of NOAA/AVHRR data were used to classify land use and vegetation types over Korean peninsula. Analyzing forest stand structures and prediction of forest productivity using satellite data were also reviewed. Land use and land cover classification was made by unsupervised clustering methods. After monthly Normalized Difference Vegetation Index (NDVI) composite images were derived from April to November 1998, the derived composite images were used as temporal feature vector's in this clustering analysis. Visually interpreted, the classification result was satisfactory in overall for it matched well with the general land cover patterns. But subclassification of forests into coniferous, deciduous, and mixed forests were much confused due to the effects of low ground resolution of AVHRR data and without defined classification scheme. To investigate into the forest stand structures, digital forest type maps were used as an ancillary data. Forest type maps, which were compiled and digitalized by Forestry Research Institute, were registered to AVHRR image coordinates. Two data sets were compared and percent forest cover over whole region was estimated by multiple regression analysis. Using this method, other forest stand structure characteristics within the primary data pixels are expected to be extracted and estimated.

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 KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

The aim of this study is to assess the OSMI (Ocean Scanning Multi-spectral Imager), whose central bands are 443nm, 490nm, 510nm, 555nm, 670nm, and 865nm, for agricultural applications. Radiance measurements, used to determine per cent reflectance of canopies and soils, were acquired with spectro-radiometers (Li-1800;330~1,100nm, GER-SFOV;350 ~2,500nm, and MSR-7000; 300~2,500nm) in situ for crops and indoors for soils. OSMI equivalent bands and their ratio values were prepared(20nm interval for bands 1~5; 4nm interval for band 6) by averaging spectral reflectance values to the real OSMI bands and analyzed as to crop growth parameters, leaf area index (LAI), total dry matter, and growth index in crops and physiochemical properties in soils. Spectral variations for each growth stage in rice and for crop discrimination in upland crops were significant statistically. In soils, clay and water content, CEC (Cation Exchange Capacity), free iron oxide, and some cation content were correlated with the OSMI equivalent bands. The result of this study shows OSMI wave bands would be promising for agricultural application in terms of spectral information and resolution.

Topographic maps can be made and updated with satellite images, but it requires many human interactions that are inefficient and costly. Therefore, the automatizing of the road extraction procedures could increase efficiency in terms of time and cost. Although methods of extracting roads, railroads and rivers from satellite images have been developed in many studies, studies on the road extraction from satellite images of urbanized area are still not relevant, because many artificial components In the city makes the delineation of the roads difficult. So, to extract roads from high resolution satellite images of urbanized area, this study has proposed the combined use of wavelet transform and multi-resolution analysis. In consequence, this study verifies that it is possible to automatize the road extraction from satellite images of urbanized area. And to realize the automatization more completely, various algorithms need to be developed.

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

The purpose of this study is to demonstrate a variety of methods for reducing the speckle noise content of SAR images, whilst at the same time retaining the fined details and average radiometric properties of the original data. In order to increase the accuracy of classification, Two categories of filters are used (speckleblind(simple), Speckle aware(intelligent)) and Segmentation of highly speckled radar imagery is achieved by the use of the Gaussian Markov Random Field model(GMRF). The problems in applying filtering techniques to different object types are discussed and the GMRF procedure and efficiency of the segmentation also discussed.

The radar interferogram represents phase differences between the two synthetic aperture radar observations acquired in slightly different angle. The success of the radar interferometric application largely depends on the quality of the interferogram generated from two or more synthetic aperture radar data sets. We propose here to apply the wavenumber correlation analysis to the in-phase and quadrature phase of the radar interferogram. The wavenumber correlation analysis is to resolve the highly correlated components from the low correlation components by estimating correlation coefficients for each wavenumber component. Through this approach, one can easily distinguish the signal components from the noise components in the wavenumber domain. Therefore, the wavenumber correlation analysis of the radar interferogram can be utilized to design post filter and to estimate the quality of interferogram. We have tested the wavenumber correlation analysis using a Radarsat SAR data pair to demonstrated the effectiveness of

Vegetation cover classification is examined based on a time series NOAA/AVHRR data. Time series data analysis methods including Fourier transform, Auto-Regressive (AR) model and temporal signature similarity matching are developed to extract phenological features of vegetation from a time series NDVI data from NOAA/AVHRR and to classify vegetation types. In the Fourier transform method, typical three spectral components expressing the phenological features of vegetation are selected for classification, and also in the AR model method AR coefficients are selected. In the temporal signature similarity matching method a new index evaluating the similarity of temporal pattern of the NDVI is introduced for classification.

The land use type of Korea is high-density. So, the image classification using coarse resolution satellite image may not provide land cover classification results as good as expected. The purpose of this paper is to compare the result of visual interpretation with that of digital image classification of 20 m resolution SPOT satellite image at Kwangju-eup, Kyunggi-do, Korea. Classes are forest, cultivated field, pasture, water and residential area, which are clearly discriminated in visual interpretation. Maximum likelihood classifier was used for digital image classification. Accuracy assessment was done by comparing each classification result with ground truth data obtained from field checking. The classification result from the visual interpretation presented an total accuracy 9.23 percent higher than that of the digital image classification. This proves the importance of visual interpretation for the area with high density land use like the study site in Korea.

It is important to analyze the seasonal change profiles of land cover type in large scale for establishing preservation strategy and environmental monitoring. Because the NOAA-AVHRR data sets provide global data with high temporal resolution, it is suitable for the land cover classification of the large area. The objectives of this study were to classify land cover of Korea, to investigate the phenological profiles of land cover. The NOAA-AVHRR data from Jan. 1998 to Dec. 1998 were received by Korea Ocean Research & Development Institute(KORDI) and were used for this study. The NDVI data were produced from this data. And monthly maximum value composite data were made for reducing cloud effect and temporal classification. And the data were classified using the method of supervised classification. To label the land cover classes, they were classified again using generalized vegetation map and Landsat-TM classified image. And the profiles of each class was analyzed according to each month. Results of this study can be summarized as follows. First, it was verified that the use of vegetation map and TM classified map was available to obtain the temporal class labeling with NOAA-AVHRR. Second, phenological characteristics of plant communities of Korea using NOAA-AVHRR was identified. Third, NDVI of North Korea is lower on Summer than that of South Korea. And finally, Forest cover is higher than another cover types. Broadleaf forest is highest on may. Outline of covertype profiles was investigated.

The investigation of the amount of the ecosystem damage on the shoreline due to the NAHODKA oil-spill accident, which occurred in the Sea of Japan, was attempted by using geoinformatics. At first, it was assumed that symbolical vegetation's distribution could be specified in the coast in Ishikawa Pref. where the heavy oil was washed, and surveyed the regional distribution. Then, the presumption result of those environmental capacities was arranged by GIS. In addition, the amount of the ecosystem damage was presumed as cost necessary though a symbolical living thing for the retreat because of the base line by the heavy oil drifting ashore was recovered. By comparing the vegetation line and the surveying data which shows environmental capacity, the retreat areas of the vegetation were 1100-1200 $m^2$. When the amount of damage on the ecosystem of the NAHODKA oil-spill accident was presumed based on the retreat area of this vegetation and the restoration cost, the amount of damage within Shioya beach which 150m in the surveying range became 2 to 2.5 million Yen. Because the extension distance from the Shioya beach to the Katano beach was about 3,500m, the amount of damage became about 46 to 65 million Yen. As a result of calculation for the amount of damage on the ecosystem of the NAHODKA oil-spill accident, it was estimated approximately 1,400 to 2,000 million Yen in the shoreline of Ishikawa Pref., because the total extension of beaches in Ishikawa Pref. is about 110km.

It is very important for monitoring the interannual variability of sea ice extents in the Okhotsk Sea because the global warming has firstly appeared around the Okhotsk Sea, locating around the southernmost region of sea ice cover in the Northern Hemisphere. In order to develop the sea ice concentration algorithm by microwave sensors onboard satellite, electromagnetic properties of sea ice in the Okhotsk Sea, therefore, were observed by airborne microwave radiometer (AMR), which has the same frequencies as AMSR (Advanced Microwave Scanning Radiometer), ADEOS-II, launching on November, 2000. On this study, it is discussed how to make the image of AMR-EFOV and the video image with nadir angle under flight at the same time, and superimpose the brightness temperature data by AMR-EFOV on the video mosaiced images. For comparing SPOT image, it is clearly that the variation of brightness temperature is small in 89GHz V-pol without the sea ice types and increase at the lower frequency-band.

In this paper, very high performance millimeter-wave radiometer of 92 GHz is presented. Radiometer system design, brightness temperature measurement and calibration methods are described. The architecture of radiometer including data acquisition, storage and digital signal processing using a notebook computer are explained and some experimental data in the laboratory are introduced. The system noise figure and total gain of implemented radiometer are 12 dB and 56 dB, respectively. The system stability is evaluated from the experiment. The difference of the detector output voltage for two targets, whose brightness temperature are 80 K and 300K, is 4 mV. The mechanical scanning method is considered to get a brightness temperature Image of the earth surface scene.

This study was carried out to assess the use of RADARSAT data which is C-band with HH polarization for the rice growth monitoring in Korea. Nine time-series data were taken by shallow incidence angle (standard beam mode 5 or 6) during rice growing season. And then, backscatter coefficient ($\sigma$$^{\circ}$) were extracted by calibration process for comparing with rice growth parameters such as plant height leaf area index(LAI), and fresh and dry biomass. Field experimental data concerned with rice growth were collected 8 times for the ground truth at the study area, Tangjin, Chungnam, Korea. At the maximum vegetative stage of rice, backscatter coefficients were the highest at the flooded rice field ranging from -4.4dB~-3.1dB. The temporal variation of backscatter coefficient($\sigma$$^{\circ}$) in rice field was significant in this study Backscatter coefficient ($\sigma$$^{\circ}$) of rice field was a little bit lower again after heading stage. This results show RADARSTA data is promising for rice monitoring.

SAR interferometry (InSAR) using the space-borne Synthetic Aperture Radar (SAR) have recently become one of the most effective tools monitoring surface changes caused by landslides, earthquakes, subsidences or volcanic eruption. This study focuses on examining the feasibility of InSAR using the RADARSAT data. Although the RABARSAT SAR with its high resolution and variable incidence angle has several advantages for repeat-pass InSAR, it has two key limitations: first, the orbit is not precisely known; and second, RADARSAT's 24-day repeat pass interval is not very favourable for retaining useful coherence. In this study, two pairs of RADARSAT data in the Nahanni area, NWT, Canada have been tested. We will discuss about the special consideration required on the interferometric processing steps specifically for RADARSAT data including image co-registration, spectral filtering in both azimuth and range, estimation of the interferometric baseline, and correction of the interferogram with respect to the "flat earth" phase contribution. Preliminary results can be summarized as: i) the properly designed azimuth filter based upon the antenna characteristic improves coherence considerably if difference in Doppler centroid of the two images is relatively large; ii) the co-registration process combined by fringe spectrum and amplitude cross-correlation techniques results in optimal matching; iii) the baseline is not always possible to be estimated from the definitive orbit information.

Rice crop has relatively short growing season during the summer in Korea and, therefore, it is often difficult to acquire cloud-free imagery on time. This study was attempt to define the temporal characteristics of radar backscattering observed from satellite L-band SAR data on different growing stages of rice crop. Six scenes of multi-temporal JERS SAR data were obtained from the transplanting season to the harvesting month of October. Six layers of multi-temporal SAR data were registered on a common geographic coordinate system. Using topographic maps, field collected data, and Landsat TM data, several sample rice fields were delineated from the imagery and their relative radar backscatters were calculated by using a set of reference targets. The temporal pattern of radar backscattering was very distinctive by the growing stage of rice crop. It was also separable between two types of rice fields having different cultivation practices. Considering the temporal characteristics of radar backscattering observed from the study, it is obvious that a certain date of the growing season can be more effective to delineate the exact area of the cultivated rice crop field.

Wind vector information over the ocean is currently obtained using multiple beam scatterometer data. The scatterometers on ERS-1/2 generate wind vector information with a spatial resolution of 50km and accuracies of $\pm$2m/s in wind speed and $\pm$20$^{\circ}$ in wind direction. Synthetic aperture radar (SAR) data over the ocean have the potential of providing wind vector information independent of weather conditions with finer resolution. Finer resolution wind vector information can often be useful particularly in coastal regions where the scatterometer wind information is often corrupted because of the lower resolution system characteristics which is often contaminated by the signal returns from the coastal areas or ice in the case of arctic environments. In this paper we tested CMOD_4 and CMOD_IFR2 algorithms for extracting the wind vector from SAR data. These algorithms require precise estimation of normalized radar cross-section and wind direction from the SAR data and the local incidence angle. The CMOD series algorithms were developed for the C-band, VV-Polarized SAR data, typically for the ERS SAR data. Since RADARSAT operates at the same C-band but with HH-Polarization, the CMOD series algorithms should not be used directly. As a preliminary approach of resolving with this problem, we applied the polarization ratio between the HH and VV polarizations in the wind vectors estimation. Two test areas, one in front of Inchon and several sites around Jeju island were selected and investigated for wind vector estimation. The new results were compared with the wind vectors obtained from CMOD algorithms. The wind vector results agree well with the observed wind speed data. However the estimation of wind direction agree with the observed wind direction only when the wind speed is greater than approximately 3.0m/s.

We compared the satellite observed temperature with the radiosonde observed temperature in the Korean Peninsula. The radiosonde observed data were obtained from four upper air observation stations in the Korean Peninsula from 1981 to 1998, and that was compared with the satellite observed data of the channel-2 and channel-4 of microwave sounding unit(MSU) on board NOAA series of polar-orbiting satellites. The radiosonde data were reconstructed into monthly radiosonde T$_{b}$ using MSU weighting function. The monthly climatology shows radiosonde T$_{b2}$ is higher than MSU T$_{b2}$ in summer. The correlation between MSU T$_{b2}$ and radiosonde T$_{b2}$ is 0.72-0.76 and 0.73-0.81 between MSU T$_{b4}$ and radiosonde T$_{b4}$.