An increase in oil and gas plants caused by development of process industry have brought into the increase in use of flammable and toxic materials in the complex process under high temperature and pressure. There is always possibility of fire and explosion of dangerous chemicals, which exist as raw materials, intermediates, and finished goods whether used or stored in the industrial plants. Since there is the need of efforts on disaster damage reduction or mitigation process, we have been conducting a research to relate explosion model on the background of real 3D terrain model. By predicting the extent of damage caused by recent disasters, we will be able to improve efficiency of recovery and, sure, to take preventive measure and emergency counterplan in response to unprepared disaster. For disaster damage prediction, it is general to conduct quantitative risk assessment, using engineering model for environmental description of the target area. There are different engineering models, according to type of disaster, to be used for industry disaster such as UVCE (Unconfined Vapour Cloud Explosion), BLEVE (Boiling Liquid Evaporation Vapour Explosion), Fireball and so on, among them, we estimate explosion damage through UVCE model which is used in the event of explosion of high frequency and severe damage. When flammable gas in a tank is released to the air, firing it brings about explosion, then we can assess the effect of explosion. As 3D terrain information data is utilized to predict and estimate the extent of damage for each human and material. 3D terrain data with synthetic environment (SEDRIS) gives us more accurate damage prediction for industrial disaster and this research will show appropriate prediction results.

We present a technique for constructing a digital elevation model (DEM) from contours. The elevation of each ground point in DEM is computed by interpolating the heights of the two adjacent contours of the point. The technique decomposes each sub-domain between adjacent contours into a set of sub-regions. The decomposition is accomplished by constructing a medial axis of the sub-domain. Each sub-region in the decomposition is classified into a variety of terrain features like hillsides, valleys, ridges, etc. The elevations of points are interpolated with different methods according to terrain features they belong to. For a given point in hillside, an approximate gradient line passing through the point is determined and the elevation of the point is interpolated from the known elevations of the two adjacent contours along the approximate gradient line. The univariate monotone rational Hermite spline is used for the interpolation. The DEM constructed by the technique is to be used to orthorectify the high-resolution KOMPSAT3 imagery.

This study proposes the method to use existing digital maps as one of the technologies to exclude individual differences that occur in the process of manually determining GCP for the geometric correction of KOMPSAT images and applying it to the images and to automate the generation of ortho-images. It is known that, in case high-resolution satellite images are corrected geometrically by using RPC, first order polynomials are generally applied as the correction formula in order to obtain good results. In this study, we matched the corresponding objects between 1:25,000 digital map and a KOMPSAT image to obtain the coefficients of the zero order polynomial and showed the differences in the pixel locations obtained through the matching. We performed proximity corrections using the Boolean operation between the point data of the surface linear objects and the point data of the edge objects of the image. The surface linear objects are road, water, building from topographic map.

KOMPSAT-2 is the seventh high-resolution satellite in the world that provides both 1m panchromatic images and 4m multispectral images of the GSD. It is expected to be used across many different fields including digital mapping, territorial and environmental monitoring. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric data, such as satellite orbits and detailed mapping information. This study aims to generate the DEM and orthoimage by using the stereo images of KOMPSAT-2 and to explore the applicability of geo-spatial information with KOMPSAT-2. In order to ensure generation of DEMs of optimal accuracy, the RPCs data and a suitable number of GCPs were used. The accuracy of DEM generated in this research compared with DEM generated from 1:5,000 digital map. The mean differences between horizontal position of the orthoimage and the digital map data are found to be ${\pm}$3.1m, which is in the range of ${\pm}$3.5m, within the permitted limit of a 1:5,000 digital map. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.

Lee (2008) proposed the pansharpening method to reconstruct at the higher resolution the multispectral images which agree with the spectral values observed from the sensor of the lower resolution values. It outperformed over several current techniques for the statistical analysis with quantitative measures, and generated the imagery of good quality for visual interpretation. However, if a small object stretches over two adjacent pixels with different spectral characteristics at the lower resolution, the pixels of the object at the higher resolution may have different multispectral values according to their location even though they have a same intensity in the panchromatic image of higher resolution. To correct this problem, this study employed an iterative technique similar to the image restoration scheme of Point-Jacobian iterative MAP estimation. The effect of pansharpening on image segmentation/classification was assessed for various techniques. The method was applied to the IKONOS image acquired over the area around Anyang City of Korea.

Aperture synthesis with platform motion has been presented as a useful tool to achieve the high spatial resolution imaging. Using a motion induced synthetic aperture radiometer (MISAR), a passive microwave image can be achieved with a small number of antennas. Moreover, the MISAR is capable of imaging better than the case without motion, using the same configuration of antenna array. With a platform motion, visibility can be sampled more efficiently, and as a result the imaging performance of the MISAR shows higher quality than the case without platform motion. In this paper, the advantage of MISAR is demonstrated experimentally. Using a laboratory model of inteferometric radiometer, the point source images are obtained under the condition with platform motion and without platform motion. In the experimental results, the point source response of the MISAR shows better quality of sidelobe level and beam efficiency than the case without platform motion.

Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

In this paper, we propose one unsupervised classification technique using the degree of polarization (DoP) and the co-polarized phase-difference (CPD) statistics, instead of the entropy and alpha. It is shown that the DoP is closely related to the entropy, and the CPD to the alpha. The DoP explains the feature how much the effect of multiple reflections is contained. Hence, the DoP could be used as an important factor for classifying classes. The CPD can also be computed from the measured Mueller matrix elements. For the smooth surface scattering, the CPD is about $0^{\circ}$, and for dihedral-type scattering, the CPD is about $180^{\circ}$. A DoP-CPD diagram with appropriate boundaries between six different classes is developed based on the SAR image. The classification results are compared with the existing Entropy-alpha diagram as well as the IPL-AirSAR polarimetric data. The technique may have capability to classify an SAR image into six major classes; a bare surface, a village, a crown-layer short vegetation canopy, a trunk-layer short vegetation canopy, a crown-layer forest, and a trunk-dominated forest. Based on the DoP and CPD analysis, a simple three-component decomposition technique was also proposed.

This paper presents soil moisture retrieval from measured polarimetric backscattering coefficients of a vegetated surface. Based on the analysis of the quite complicate first-order radiative transfer scattering model for vegetated surfaces, a simplified scattering model is proposed for an inversion algorithm. Extraction of the surface-scatter component from the total scattering of a vegetation canopy is addressed using the simplified model, and also using the three-component decomposition technique. The backscattering coefficients are measured with a polarimetric L-band scatterometer during two months. At the same time, the biomasses, leaf moisture contents, and soil moisture contents are also measured. Then the measurement data are used to estimate the model parameters for vv-, hh-, and vh-polarizations. The scattering model for tall-grass-covered surfaces is inverted to retrieve the soil moisture content from the measurements using a genetic algorithm. The retrieved soil moisture contents agree quite well with the in-situ measured soil moisture data.

The purpose of this paper is to extract DEMs from Spot-3 strips using orbit modeling technique. Spot-3 stereo strip images along 420km in distance were used for experiments. The orbit modeling technique has been suggested to establish accurate geometric models for a whole strip taken on the same orbit using only a small number of GCPs on the top area of the strip. This method enables extraction of orientation parameters of the scene along the strip that is needed to generate DEMs. Consequently, we were able to extract DEMs over the areas without accurate GCPs obtained by GPS surveying per each scene. Assessment of accuracy was carried out using USGS DTED. DEMs generated from the orbit modelling technique suggested showed satisfactory performance when quantitative analysis of accuracy assessment was carried out.

In this paper, major species of tree were discriminated in compartment by using LiDAR data and optic imagery. This is an important work in forest field. A current digital stock map has created the aerial photo and collecting survey data. Unlike high resolution imagery, LiDAR data is not influenced by topographic effects since it is an active sensory system. LiDAR system can measure three dimension information of individual tree. And the main methods of this study were to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for calculating tree crown 2D parameter. We should estimate the forest inventory for calculating parameter. 2D parameter has need of area, perimeter, diameter, height, crown shape, etc. Eventually, major species of tree were determined the tree parameters, compared a digital stock map.

Since the mid-2000, so-called Web 2.0 paradigm was emerged and has been widely extended to actual Web markets with supporting Web technologies. Among Web 2.0 services, mashups with Open APIs is regarded as one of core technologies. Web mapping is also the most dominant mashup application in Open API-based applications, so that various mashups with Google Map API and other Open APIs are developing. In this paper, current technological status is explained with web GIS file formats of KML. While, a prototype is web-based GIS layer authoring system for general users, without any kinds of GIS tools and external spatial databases. This mashup application will be used web-based feature extraction for geo-spatial web for public users.

New Orleans located in the estuary of the Mississippi River was attacked by Hurricane Katrina and suffered big flood on August 2005. Since unconsolidated Holocene to middle Miocene strata is the main basement rocks, land subsidence has been occurred steadily due to soil compaction and normal faulting. It was reported that the maximum subsidence rate from 2002 to 2005 was -29 mm/yr. Many studies in the area have been carried out for understanding the subsiding and potential risks caused by ground subsidence are weighted by the fact that a large area of the city is located below the mean sea level. A small baseline subset (SBAS) method is applied for effectively measuring time-series LOS (Line-of sight) surface deformation from differential synthetic aperture radar interferograms in this study. The time-series surface deformation at New Orleans was measured from RADARSAT-1 SAR images. The used dataset consists of twenty-one RADARSAT-1 fine beam mode images on descending orbits from February 2005 to February 2007 and another twenty-one RADARSAT-1 standard beam mode images on ascending orbits from January 2005 to February 2007. From this dataset, 25 and 38 differential interferograms on descending and ascending orbits were constructed, respectively. The vertical and horizontal components of surface deformation were extracted from ascending and descending LOS surface deformations. The result from vertical component of surface deformation indicates that subsidence is not significant with a mean rate of -3.1${\pm}$3.2 mm/yr.

Generally, the quality of satellite images is expressed by GSD (Ground Sample Distance), MTF (Modulation Transfer Function) and SNR (Signal to Noise Ratio). However, these factors are technology-oriented and do not explain interpretability of satellite images. We need a standardized index which shows standard of interpretability. In this study, we estimated NIIRS (National Imagery Interpretability Rating Scale) through the GIQE (General Image Quality Equation) which is able to judge image interpretability with the standardized index. Traditionally, NIIRS has been determined manually by specialized image analysts. We used the GIQE in order to reduce inefficiency and high costs cause by manual interpretation and to produce accurate NIIRS. For monitoring image degradation, we estimated GIQE physical parameters from image analysis and carried out time series analysis about the quality of the KOMPSAT-1 images. On all of the tests, we were able to identify the image degradation due to the changing time. This indicates that NIIRS derived from GIQE will be used for image degradation indicator.

The flow of freshwater into the sea, termed as submarine groundwater discharge, is a key factor for understanding the hydrological cycle in both the sea and land regions. The numerous positions from which freshwater gushes out or its quantity impedes the understanding of its properties. Therefore, this study detects groundwater discharge points arising due to the difference in freshwater and seawater by using the multispectral Landsat ETM+ signals. A case study in coastal regions around Mt. Chokaisan, Japan is performed. This study comprises three procedures: (1) computer simulation of the flow of submarine groundwater discharge in the study area, (2) performance of preliminary experiment on the band properties of the Landsat ETM+, (3) detection of the difference in water properties by using the Landsat multispectral bands. Our experimental results obtained by the Landsat ETM+ are in considerable agreement with the realities in the study area.

Seasonal distribution of the oceanic water intrusion was investigated using satellite SST (sea surface temperature) and chl-a (chlorophyll-a) images taken by the MODIS Aqua sensor. The warm water mass emanating periodically from the meandering Kuroshio Current brings the oceanic water intrusion, known as the 'Kyucho' phenomenon, into Kagoshima bay during the winter. Satellite SST images and buoy robot data show that this warm water intrusion has the characteristics of a semigeostrophic gravity current influenced by the Coriolis effect. However, it is difficult to find the oceanic water intrusion during the summer season considering that it is accompanied by thermal stratification, and SST shows almost the same temperature between the inner side of the bay and the ocean. In this research, the satellite chl-a images taken by MODIS Aqua were employed instead of SST images to reveal the oceanic water intrusion in each season. The enclosed bay has the tendency to undergo eutrophication caused by organic materials from land and differences in chl-a concentration of the bay water and the oceanic water. As a result, distribution of low concentration chl-a with oceanic water intrusion in summer season shows almost the same pattern in winter season. On the other hand, in spring season, both SST and chl-a images are available to differentiate the oceanic water intrusion. Therefore, applying the suitable satellite sensor images for each season is effective in the monitoring of oceanic water intrusion. Moreover, in this area, SST and chl-a distribution reveal not only the oceanic water intrusion into Kagoshima bay but also the intrusion at Fukiage seashore facing East China Sea.

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Most mineral resources are located in subsurface but mineral exploration starts with a step of investigation in wide-area to find evidence of buried ores. Conventional technique for exploration on wide-area as a preliminary survey is an observation using naked eyes by geologist or chemical analysis using lots of samples obtained from target area. Hyperspectral remote sensing can overcome those subjective and time consuming survey and can produce mineral resources distribution map. Precise resource map requires information of mineral distribution in a subpixellevel because mineral is distributed as rock components or narrow veins. But most hyperspectral data is composed of pixels of several meters or more than ten meters scale. We reviewed subpixel unmixing algorithms which have been used for geological field and tested detection ability with Hyperion imagery, geological map and seven spectral curves of mineral and rock specimens which were obtained from study areas.

Our goal is to obtain a better scientific understanding how to define the nature and role of remotely sensed land surface parameters and energy fluxes in the heat island phenomena, and local and regional weather and climate. By using the MODIS visible and thermal imagery data and analyzing the surface energy flux images associated with the change of the landcover and landuse in study area, we will estimate and present how significant is the magnitude of the heat island heat effect and its relation with the surface parameters and the energy fluxes in Taiwan. To achieve our objective, we used the energy budget components such as net radiation, soil heat flux, sensible heat flux, and latent heat flux in the study area of interest derived form remotely sensed data to understand the island heat effect. The result shows that the water is the most important component to decrease the temperature, and the more the consumed net radiation to latent heat, the lower urban surface temperature.

Image segmentation techniques becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Seeded Region Growing (SRG) and Edge Information. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying SRG. Finally the region merging process, using region adjacency graph (RAG), was carried out to get the final segmentation result. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

This study presents the use of multi-temporal JERS-1 SAR images to the land cover classification. So far, land cover classified by high resolution aerial photo and field survey and so on. The study site was located in Non-san area. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then classified land cover. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass

Diverse researches using vegetation index have been carried out to monitor spring droughts that have frequently occurred since 2000. The strength of the drought monitoring using vegetation index lies in that it can reflect characteristics of satellite images: large area coverage, cyclicity, and promptness. However, vegetation index involve uncertainly caused by diverse factors that affect vegetation stress. In this study, multi-temporal vegetation index is compared with the most representative meteorological drought indices like PSDI, SPI. Based on the results from analyses, usability of vegetation index as a tool of drought analysis is proposed.

ATTOL is a software unit testing tool produced by the ATTOL Testware SA in France. It automates the entire software unit testing process: test plan template and test program generation, test program execution, test result analysis and test report generation. ATTOL is suited for the development of embedded software as it allows programmers to operate in native and cross development environments. Particularly, it is used for the development of the flight software which is embedded in the Communication Ocean Meteorological Satellite (COMS). As the flight software is mission-critical, it requires the strict software quality and high testing constraints. The flight software of COMS is verified by ATTOL in native and cross platforms. In 2002, ATTOL was taken over by the IDM Rational Software and has been supplied with the name of Test RealTime (TestRT). The test process of TestRT becomes different from that of ATTOL as TestRT provides the new functionalities that were absent from ATTOL. TestRT provides the new features in the test script language, as well. In this paper, we compare the test process of ATTOL to TestRT With an example of COMS and explain what has been changed in the test script language.

The COMS IMPS (Communication Ocean and Meteorological Satellite IMage Pre-processing Subsystem) is developed for image pre-processing of COMS. For a test of the COMS IMPS, 7 support software are developed in KARI GS using simulated MI/GOCI WB (Wide-Band) data; COMS Fill Adder, MI (Meteorological Imager) CADU generator, GOCI (Geostationary Ocean Colour Imager) CADU generator, COMS CADU combiner, MI SD (Sensor Data) analyzer, GOCI SD analyzer, and COMS DM (Decomposition Module) test harness. This paper explains functions of developed support software and the COMS IMPS test using those software.

The Geostationary Ocean Color Imager (GOCI) is under development to provide a monitoring of ocean-color around the Korean Peninsula from geostationary platforms. It is planned to be loaded on Communication, Ocean, and Meteorological Satellite (COMS) of Korea. The GOCI has been designed to provide multi-spectral data to detect, monitor, quantify, and predict short term changes of coastal ocean environment for marine science research and application purpose. The target area of GOCI observation covers sea area around the Korean Peninsula. Based on the nonlinear radiometric model, the GOCI calibration method has been derived. The radiometric model of GOCI has been validated through radiometric ground test. From this ground test result, GOCI radiometric model has been changed from second order to third order. In this paper, the radiometric test performed to evaluate the radiometric nonlinearity is described and the GOCI radiometric error propagation is analyzed. The GOCI radiometric calibration is based on onboard calibration devices; solar diffuser, DAMD (Diffuser Aging Monitoring Device). The radiometric model error due to the dark current nonlinearity is considered as a systematic error. Also the offset correction error due to gain/offset instability is considered. The radiometric accuracy depends mainly on the ground characterization accuracies of solar diffuser and DAMD.

The MRE (Monitoring Reconfiguration Electronics) board included inside the SCU (Spacecraft Computer Unit) in the COMS (Communication, Ocean and Meteorological Satellite) spacecraft is used to monitor the battery voltage and to detect a battery under voltage (low battery capacity) or a battery overvoltage (overcharge). In case of alarm detection, a reconfiguration is initiated by the MRE board. The MRE configures the overall spacecraft in the survival mode to protect the Li-Ion (lithium ion) battery from overcharge and over discharge. For the EPS (Electrical Power Subsystem) point of view, the survival mode can be trigged from hardware wired thresholds. The aim of this paper to provide and to justify the low and high threshold levels which are associated to the MRE battery voltage monitoring. The MRE trig guarantees minimum battery energy to available for the required 48 hours autonomy duration of the spacecraft after MRE trig in the survival mode.

COMS(Communication, Ocean and Meteorological Satellite) has multiple payloads; Meteorological Image(MI), Ocean Color Imager(GOCI) and Ka-band communication payloads. MI has 4 IR and 1 visible channel. In order to improve the quality of IR image, two calibration sources are used; black body image and cold space look data. In case of COMS, the space look is performed at 10.4 degree away from the nadir in east/west direction. During space look, SUN or moon intrusions are strictly forbidden, because it would degrade the quality of collected IR channel calibration data. Therefore we shall pay attention to select space look side depending on SUN and moon location. This paper proposes and discusses a simple and complete space look side selection logic based on SUN and moon intrusion event file. Computer simulation has been performed to analyze the performance of the proposed algorithm in term of east/west angular distance between space look position and hazardous intrusion sources; SUN and moon.

This paper proposes an image based method for arranging ship blocks in a dockyard. The problem of appropriately arranging numerous blocks has to be carefully planned because it has close relation to the effectiveness of the whole working process. To implement the system, the block shape and feature points have to be obtained from block image. The block arrangement system can be implemented by the fusion of the block shape extraction and image matching technology.

In this study, we propose a system for setting a Destination on CNS(Car Navigation System) or PNS(Personal Navigation System). The present Navigation does set the destination by only static method like name search, address search and wire telegraph telephone number search. But, the kind of setting a static destination does not reflect the dynamic moving situation. So we suggest setting the destination of navigation using Identifier of moving terminal. And it includes privacy protection on personal position information

The existence of noise bands may deform the typical shape of the spectrum, making the accuracy of clustering degraded. This paper proposes a statistical approach to remove noise bands in hyperspectral data using the correlation coefficient of bands as an indicator. Considering each band as a random variable, two adjacent signal bands in hyperspectral data are highly correlative. On the contrary, existence of a noise band will produce a low correlation. For clustering, the unsupervised ${\kappa}$-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID. Furthermore, this paper proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures.

Traditionally, Geographical Information System can only process static spatial data, which include geometries and attributes. Recently, According to Special attention is paid to ubiquitous computing environment, we require a u-GIS convergence middleware to efficiently process ubiquitous data and improves the existing GIS engine in order to enable converged processing of spatial and sensor data. So, in this study, we propose a design of u-GIS Convergence Middleware, which are based on the integration between GIS and USN technologies

Pattern matching is increasingly being employed in various researches as health care service, RFID-based system, facility management, and surveillance. Geosensor filter correlates a data stream to match specific patterns in distribution environments. In this paper, we present a geosensor query language to represent efficiently declarative geosensor query. Geosensor operators are proposed to use for fast query processing in terms of spatial and temporal area in distribution environments. We also propose a geosensor filter to match new query predicates into incoming stream predicates. Our filter can reduce the volume of transmission data and save power consumption of sensors. It can be utilized the stream data mining system to process in real-time various data as location, time, and geosensor information in distribution environments.

Sensors used in many USN (Ubiquitous Sensor Network) domain applications generate a large amount of sensor stream data. The volume of sensor stream data is too huge to store the whole data and data speed is too fast to control each of them. In order to provide rapid and reliable context analysis service over sensor stream data, we propose a WHEN-DO context analysis model that supports the functionality of sliding window. This model is designed to be used as follows: If the sensor stream data satisfies condition in 'WHEN' clause, then it will execute actions in 'DO' clause in WHEN-DO context analysis model. The proposed WHEN-DO context analysis model can be applied to many other USN environment applications such as monitoring the status of a building and then taking actions in corresponding context condition.

In this paper, we proposed a method extracting an object from background of the satellite image. The image segmentation techniques have been widely studied for the technology to segment image and to synthesis segment object with other images. Proposed algorithm is to perform the edge detection of a selected object using genetic algorithm. We segment region of object based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from segment object. And, we make GUI for the application of the proposed algorithm to various tests. To demonstrate the effectiveness of the proposed method, several analysis on the satellite images are performed.

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In this paper, ALOS-AVNIR, PRISM, and JERS-1 images are used in a multilayer perceptron neural network (MLPNN) that relates them to forest variable measurements on the ground. The structure of this MLPNN is a three layers neural network that contains eight input neurons, 10 hidden neurons and five output neurons. It is shown that the biomass estimation accuracy is significantly improved when the MLPNN is used in comparison with Maximum Likelihood algorithm.

Recently many areas require wide field of view images. Such as surveillance, virtual reality, navigation and 3D scene reconstruction. Conventional camera systems have a limited filed of view and provide partial information about the scene. however, omni directional vision system can overcome these disadvantages. Acquiring 360 degree panorama images requires expensive omni camera lens. In this study, 360 degree panorama image was tested using a low cost optical reflector which captures 360 degree panoramic views with single shot. This 360 degree panorama image system can be used with detailed positional information from GPS/INS. Through this study result, we show 360 degree panorama image is very effective tool for mobile monitoring system.

Many studies have been conducted on extracting buildings from ALS(Airborne Laser Scanning) data. After segmentation or classification of building points, additional steps such as generalization is required to get straight boundary lines that better approximate the real ones. In much research, orthogonal constraints are used to improve accuracies and qualities. All the lines of the building boundaries are assumed to be either parallel or perpendicular mutually. However, this assumption is not valid in many cases and more complex shapes of buildings have been increased. A new algorithm is presented that is applicable to various complex buildings. It consists of three steps of boundary tracing, grouping, and regularization. The performance of our approach was evaluated by applying the algorithm to some buildings and the results showed that our proposed method has good potential for extracting building boundaries of various shapes.

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

Information on the area and spatial distribution of crop fields is needed for biomass production, arrangement of water resources, trace gas emission estimates, and food security. The present study aims to monitor crops status during the growing season by estimating its aboveground biomass and leaf area index (LAI) from field reflectance taken with a hand-held radiometer. Field reflectance values were collected over specific spectral bandwidths using a handheld radiometer(LI-1800). A methodology is described to use spectral reflectance as indicators of the vegetative status in crop cultures. Two vegetation indices were derived from these spectral measurements. In this paper, first we analyze each spectral reflectance characteristics of vegetation in the order of growth stage. Vegetation indices (NDVI, GNDVI) were calculated from crop reflectance. And assess the nature of relationships between LAI and VI, as measured by the in situ NDVI and GNDVI. Among the two VI, NDVI showed predictive ability across a wider range of LAI than did GNDVI. Specific objectives were to determine the relative accuracy of these two vegetation indices for predicting LAI. The results of this study indicated that the NDVI and GNDVI could potentially be applied to monitor crop agriculture on a timely and frequent basis.

The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain, and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

KOMPSAT-3 is expected to provide data with 80-cm spatial resolution, which can be used to detect environmental change and create thematic maps such as land-use and land-cover maps. However, to analyze environmental change, change-detection technologies that use multi-resolution and high-resolution satellite images simultaneously must be developed and linked to each other. This paper describes a GIS-based strategy and methodology for revealing global and local environmental change. In the pre-processing step, we performed geometric correction using satellite, auxiliary, and training data and created a new classification system. We also describe the available technology for connecting global and local change-detection analysis.

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

Lake studies play an important role in water management, ecology, and other environmental issues. Typically, monitoring lake levels is the first step on the lake studies. However, for the Prairie Pothole Region (PPR) of North America having millions of small lakes and potholes, on-site measurement for lake levels is almost impossible with the conventional gage stations. Therefore, we employed Geographic Information System (GIS) and remote sensing approach with the Shuttle Radar Topography Mission data to extract lake levels. Several image processing techniques were used to extract lake levels for January, 2000 as a one-time snapshot which will be useful in historic lake level reconstruction. This study is associated with other remote sensing datasets such as Landsat imagery and Digital Orthophoto Quadrangle (DOQ). In this research, firstly, image processing techniques like FFT filtering, Lee-sigma, masking with Canny Edge Detector, and contouring were tested for lake level estimation. The semi-automated contouring technique was developed to accomplish the bulk processing for large amount of lakes in this region. Also, effectiveness of each method for bulk processing was evaluated.

Many researches have been tried to extract building models and created a 3D cyber city from LiDAR data. In this paper, the approach of extracting complex building by using airborne LiDAR data combined with airborne orthoimagery has been performed. The pseudo-building elevations were derived from modified discrete return LiDAR data. Based on information property of the pseudo-height, building features could be extracted. The results of this study indicated the improvement of building extraction.

The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study sequentially utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using DTM and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.

Speckle noise is primarily due to the phase fluctuations of the electromagnetic return signals. Since inherent spatial-correlation characteristics of speckle in SAR images are not exploited in existing multiplicative models for speckle noise. In this paper, we investigate the efficiency of the filters: Kuan, Gamma, Enhanced Lee, and Enhanced Frost filters in reduction of speckle noise in forestry area. Selection of the suitable filter can be played an important role in applications such as estimation of biomass in forestry areas. We employ ALOSPALSAR image use L-band frequency for this investigation. The filters test on different sites in PALSAR image of the northern forests part of Iran.

The Tonle Sap, Cambodia, is a huge lake and periodically flooded due to monsoon climate. The incoming water causes intensive flooding that expands the lake over vast floodplain and wetland consisting mainly of forests and shrubs. Monitoring the water-level change over the floodplain is essential for flood prediction and water resource management. A main objective of this study is flood monitoring over Tonle Sap area using ALOS PALSAR. To study double-bounce effects in the lake, backscattering effect using ALOS PALSAR dual-polarization (HH, HV) data was examined. InSAR technique was applied for detection of water-level change. HH-polarization interferometric pairs between wet and dry seasons were best to measure water level change around northwestern parts of Tonle Sap. The seasonal pattern of water-level variations in Tonle Sap studied by InSAR method is similar to the past and altimeter data. However, water level variation measured by SAR was much smaller than that by altimeter because the DInSAR measurement only represents water level change at a given region of floodplain while altimeter provides water level variation at the central parts of the lake.

Radio occultation (RO) has been used in the planetary science since Microlab-1 was launched in 1995. With the RO technique, the profiles of atmosphere and the global atmospheric data can be obtained. In 2006, Taiwan launched six low Earth orbit (LEO) satellites as the RO constellation mission, known as FORMOSAT-3. In order to retrieve the RO data from original data, a retrieval algorithm, NCURO, is developed. The input of NCURO algorithm is mainly the excess phase of GPS signal, and the output is the dry pressure and dry temperature. Using temperature profiles retrieved by NCURO algorithm, temperature perturbation and potential energy of gravity wave have been evaluated. In this paper, the retrieval algorithm and the global distribution of energy of gravity waves are described and demonstrated.

Lineament is defined generally as a linear feature or pattern on interpretation of a satellite image and indicates the geological structures such as faults and fractures. For this reason, a lineament extraction and analysis using remote sensing images have been widely used for mapping large areas. The Gyeong-gang Fault is a NNE trending structure located in Gangwon-do and Kyeonggi-do district. However, a few geological researches on that fault have been carried out and its trace or continuity is ambiguous. In this study, we investigate the geologic features at Gyeong-gang Fault Zone using LANDSAT ETM+ satellite image and SRTM digital elevation model. In order to extract the characteristics of geologic features effectively, we transform the LANDSAT ETM+ image using Principal Component Analysis (PCA) and create a shade relief from SRTM data with various illumination angles. The results show that it is possible to identify the dimensions and orientations of the geologic features at Gyeong-gang Fault Zone using remote sensing data. An aerial photograph interpretation and a field work will be future tasks for more accurate analysis in this area.

The objective of this study is to produce the $CO_2$ (carbon dioxide) absorption map using KOMPSAT-2 imagery. For estimating the amount of $CO_2$ absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated by the crown width extracted from KOMPSAT-2 imagery. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC (Intergovernmental Panel on Climate Change) guideline, was used to convert the stand biomass into the amount of $CO_2$ absorption. Thereafter, the KOMPSAT-2 imagery was classified with the SBC (segment based classification) method in order to quantify $CO_2$ absorption by tree species. As a result, the map of $CO_2$ absorption was produced and the amount of $CO_2$ absorption was estimated by tree species.

The purpose of this study is to identify how much the MODIS NDVI (Normalized Difference Vegetation Index) can explain the soil moisture simulated from SWAT (Soil and Water Assessment Tool) continuous hydrological model. For the application, ChungjuDam watershed (6,661.3 $km^2$) was adopted which covers land uses of 82.2 % forest, 10.3 % paddy field, and 1.8 % upland crop respectively. For the preparation of spatial soil moisture distribution, the SWAT model was calibrated and verified at two locations (watershed outlet and Yeongwol water level gauging station) of the watershed using daily streamflow data of 7 years (2000-2006). The average Nash and Sutcliffe model efficiencies for the verification at two locations were 0.83 and 0.91 respectively. The 16 days spatial correlation between MODIS NDVI and SWAT soil moisture were evaluated especially during the NDVI increasing periods for forest areas.

Band-limited filtering will be applied to remove interference resulted from two neighbored channels in the transmission of KOMPSAT-5 X-Band image data. In that case, receiver in ground station should prepare righteous matched filter to avoid huge BER degradation depending on the matched filter of COTS receiver. As an effort to simulate the bandlimited filtering, test filter was designed and manufactured on the basis of main specification for output filter of KOMPSAT-5 satellite. Consequently, 1.8dB of BER degradation was measured at the output of test band-pass filter, but the degradation was downsized up to 0.4dB thanks to the adaptive matched filter of COTS receiver.

The final product generated from the KOMPSAT-2 Terminal for Polar System, K2PS, is an ellipsoid projected image. This leaves a relief displacement on the image by process of which the height value of subject area is constant. In this paper, orthorectification using the SRTM was used to remove such artifacts, and thereafter, the additional product that could be generated from the K2PS was discussed.

It is necessary to study encryption for protection and safe transmission of the important information. Specially, the security in satellite data is also getting more and more important. This paper introduces DES and TDES algorithm, studies how to apply to satellite data with those algorithms and process of encryption and decryption for satellite data. Proposed encryption process in this paper will be utilized in satellite data for encryption in many satellites.

A camera system for the satellite application performs the mission of observation by measuring radiated light energy from the target on the earth. As a development stage of the system, the signal level analysis by estimating the number of electron collected in a pixel of an applied CCD is a basic tool for the performance analysis like SNR as well as the data path design of focal plane electronic. In this paper, two methods are presented for the calculation of the number of electrons for signal level analysis. One method is a quantitative assessment based on the CCD characteristics and design parameters of optical module of the system itself in which optical module works for concentrating the light energy onto the focal plane where CCD is located to convert light energy into electrical signal. The other method compares the design\ parameters of the system such as quantum efficiency, focal length and the aperture size of the optics in comparison with existing camera system in orbit. By this way, relative count of electrons to the existing camera system is estimated. The number of electrons, as signal level of the camera system, calculated by described methods is used to design input circuits of AD converter for interfacing the image signal coming from the CCD module in the focal plane electronics. This number is also used for the analysis of the signal level of the CCD output which is critical parameter to design data path between CCD and A/D converter. The FPE(Focal Plane Electronics) designer should decide whether the dividing-circuit is necessary or not between them from the analysis. If it is necessary, the optimized dividing factor of the level should be implemented. This paper describes the analysis of the electron count of a camera system for a satellite application and then of the signal level for the interface design between CCD and A/D converter using two methods. One is a quantitative assessment based on the design parameters of the camera system, the other method compares the design parameters in comparison with those of the existing camera system in orbit for relative counting of the electrons and the signal level estimation. Chapter 2 describes the radiometry of the camera system of a satellite application to show equations for electron counting, Chapter 3 describes a camera system briefly to explain the data flow of imagery information from CCD and Chapter 4 explains the two methods for the analysis of the number of electrons and the signal level. Then conclusion is made in chapter 5.

Land cover and its changes, affecting multiple aspects of the environmental system such as energy balance, biogeochemical cycles, hydrological cycles and the climate system, are regarded as critical elements in global change studies. Especially in arid and semiarid regions, the observation of ecosystem that is sensitive to climate change can improve an understanding of the relationships between climate and ecosystem dynamics. The purpose of this research is analyzing the ecosystem surrounding the Gobi desert in North Asia quantitatively as well as qualitatively more concretely. We used Normalized Difference Vegetation Index (NDVI) derived from SPOT-VEGETATION (VGT) sensor during 1999${\sim}$2007. Ecosystem monitoring of this area is necessary because it is a hot spot in global environment change. This study will allow predicting areas, which are prone to the rapid environmental change. Eight classes were classified and compare with MODerate resolution Imaging Spectrometer (MODIS) global land cover. The time-series analysis was carried out for these 8 classes. Class-1 and -2 have least amplitude variation with low NDVI as barren areas, while other vegetated classes increase in May and decrease in October (maximum value occurs in July and August). Although the several classes have the similar features of NDVI time-series, we detected a slight difference of inter-annual variation among these classes.

For a satellite data communication, the technology of frame synchronization is widely used between a sender and a receiver. Last year, we suggested zero-loss frame synchronization [1] using pattern search and using bits threshold search algorithm that is based on SIMD technology [2,3]. This algorithm could solve both of hardware and software drawbacks, which are frame loss and low processing performance. However, this algorithm didn't optimize the processing of output data, synchronized data, which caused overhead to the memory allocation and the memory copy. Consequently, the performance of the frame synchronizer application was degraded. In this paper, we enhance previous work using a circular buffer in order to optimize the output data processing. The performance comparison with the previous algorithm shows that the enhanced proposed approach dramatically outperforms in the output data processing speed.

The mission of the EO(electro-optical) based low earth orbit satellite is provision of the high-resolution images required for GIS(Geographical Information Systems) establishment and the applications for environmental, agriculture and ocean monitoring. AEISS(Advanced Earth Imaging Sensor System) which is the main payload on the satellite consists of EOS(electro-optical subsystem) and PDTS(Payload Data Transmission Sub-system). IDHU(Image Data Handling Unit) which is one of the major unit in PDTS is capable of compression, storage, encryption and encoding. In this paper, the payload system of the EO based satellite is briefly introduced and the influence of the compression on AEISS is analyzed.

Korea Aerospace Research Institute (KARI) has been trying for utilizing the polar station in Svalbard, Norway to receive the KOMPSAT-2 images, which are distributed and applied directly for Europe Space Agency (ESA) users. Now, KARI is operating the SpaceCapture-2 system that provides the KOMPSAT-2 catalogue service via the internet, whereas ESA is operating the EOLI-SA tool that provides access to the online ESA catalogues of Earth Observation (EO) products. This paper describes external interface based on service-oriented architecture in order to provide the KOMPSAT-2 catalogue service from the SpaceCapture-2 system to the EOLI-SA tool. As the KOMPSAT-2 catalogue service is available in the EOLI-SA tool through an implementation of external interface, the extend use of KOMPSAT-2 imageries is expected.

In the present article, we analyze airborne Pi-SAR (Polarimetric-Interferometric SAR) X-band images of ocean waves around the Miyake Island at approximately 180 km south from Tokyo, Japan. Two images of a same scene were produced at approximately 40 min. interval from two directions at right angles. One image shows dominant range travelling waves, but the other image shows a different wave pattern. This difference can be caused by the different image modulations of RCS and velocity bunching. We have estimated the dominant wavelength from the image of range waves, and from the wave phase velocity computed from the dispersion relation (though no wave height data were available), the image intensity is computed by using the velocity bunching model. The comparison of the result with the second image at right angle strongly suggests the evidence of velocity bunching.

The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high quality spectral and high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems shall be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS shall be calibrated and validated with the calibration equipments such as the integrated sphere and spectral lamps. To improve data quality and availability, it is the most important to understand the mechanism of hyperspectral imaging system and the radiometric and spectral characteristics. This paper presents the major characteristics of camera system on the CAISS and summarizes the results of radiometric and spectral experiment during preliminary system verification.

The paper presents the advanced radiometric calibration method, called the lRCM (Iterative Radiometric Calibration Method), in order to avoid an operational constraint (solar source) for calibration. The IRCM assumes that an optical instrument is equipped with a filter assembly which consists of same band filters with different transmission ratios. Given all the noise sources (including the artificial one caused by the filters) of an image sensor, the noncentral ${\chi}^2$ distribution of the output result is induced by the approach of a noise PDF (Power Density Function). Finally, the radiometric calibration problem is transformed into equating two independent relations for the image sensor gains through the specified distribution.

The German radar satellite TerraSAR was launched in 2007. In this study, interferogram is generated using TerraSAR-X data and DEM (Digital Elevation Model). Coregistration procedures used with SAR images (i.e. master and slave) in traditional method results in serious errors for high resolution TerraSARX data because of the mutual shift of the master and slave images due to topography. This error becomes more serious in mountainous areas in which the coherence between interferometric pairs is relatively low. Here we processed a geometric coregistration with DEM exploiting height information. Through the method, interferometry processing is fulfilled to generate a qualified interferogram and coherence is improved. This approach will help high resolution X-band SAR interferometry in mountainous area.

The DEM (Digital Elevation Model) can be obtained from stereo image pair acquired by LEO satellite. Stereo images may consist of at least two images with different viewing angles to the imaging target for one pass or multiple passes. While each image is generally acquired from each pass in cross-track direction for multiple passes, stereo image pair in along-track direction can be acquired during one pass with attitude control capability for the pitch axis of the satellite. Single pass stereo imaging provides stereo pair image more efficiently on the fact that stereo pair image is generated with less orbit resources and less imaging time consumption. In this paper, the feasibility study result on the stereo pair image collection planning algorithm during single pass is addressed.

GIS-based spatial data integration tasks have used exhaustive thematic maps generated from sparsely sampled data or satellite-based exhaustive data. Due to a simplification of reality and error in mapping procedures, such spatial data are usually imperfect and of different accuracy. The objective of this study is to carry out a sensitivity analysis in connection with input topographic data for landslide hazard mapping. Two different types of elevation estimates, elevation spot heights and a DEM from ASTER stereo images are considered. The geostatistical framework of kriging is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. The effects of different accuracy arising from different terrain-related maps on the prediction performance of landslide hazard are illustrated from a case study of Boeun, Korea.

We design level 1 traffic thematic map for common data structure. Level 1 means the road that can passing cars. If public office and private company use this form, they can save amount of money from overlapping update. And widely use of traffic analysis, navigation and traffic information system. For design common data structure we compared several data structure(traffic thematic map, ITS standard node/link, Car navigation map), and generalization these characteristic data. After generalization we considered about application parts. It can use of public part(traffic analysis, road management, accident management) and private part(car navigation, map product, marketing by variable analysis) etc.

Urban is more intelligent continuously with the help of the convergence with IT technology. And it requires an integrated control system, which can manage urban facilities or monitor large-scale events based on GIS data, to provide its citizen with various ubiquitous services such as u-Health, u-Traffic, context-awareness etc. In order to realize the intelligent city geo-sensors that have the functionalities of generic sensing as well as location awareness will be established everywhere in the near future. Our system we presented have a rule engine to handle a atomic event as well as complex events that contain control flow or branch among them. And it can allow for visualization and monitoring the results through KML (Keyhole Mark-up Language) in the Google Maps. This paper describes au-GIS event processing system that can deal effectively with u-GIS events coming from various geo-sensor data in ubiquitous computing environments.

Telematics is a leading IT service where wireless internet service represented by information and mobility is extended to the area of transportations to provide Telematics service. One of the killer-application about Telematics is navigation system. Recently, due to the mass storage conversion, the performance of the terminal and mobile communications technology development, navigation system is also changed. It more and more develops into 3D in a pre-existence 2D map. In the future, it is expected to include the remote sensing map or video map. There is also the characteristic of all the information expressed in frequently a change partially happening. That is, POI(Point Of Interest) which is freshly registered or is deleted is many. In a pre-existence, Map Contents Providers offer the new version map by off-line monthly or quarterly. And a user wastes time and is inconvenient because of updating the total map by the off-line. Thus, in this paper, in order to resolve this, we describe MAUS(Map Air Update Server) for updating only the partial map that was changed

At the stage of content convergence into cell phone, technologies for geo-spatial information sharing and searching are being developed. Currently, 2D portable navigation map for mobile navigation is provided by communication companies, but geobrowers for 3D geo-information in cell phone are under developing. In this study, 3D feature transformation among X3D-M3G-KML, on mobile and web environments, is dealt with as the first stage for the further mobile 3D web application. As well, it is possible to real-time interoperable 3D geo-information exchange issues within both environments.

Enhancing the positioning precision is the primary pursuit of GPS users. To achieve this goal, most studies have focused on the relationship between GPS receiver clock errors and GPS positioning precision. This study utilizes undifferentiated phase data to calculate GPS clock errors and to compare with the frequency of cesium clock directly, thus verifying estimated clock errors by the method used in this paper. The relative frequency offsets from this paper and from National Standard Time and Frequency Laboratory of Taiwan match to $1.5{\times}10^{12}$ in the frequency instability, suggesting that the proposed technique has reached a certain level of quality. The built-in quartz clocks in the GPS receivers yield relative frequency offsets that are 3 to 4 orders higher than those of rubidium clocks. The frequency instability of the quartz clocks is on average two orders worse than that of the rubidium clock. Using the rubidium clock instead of the quartz clock, the horizontal and vertical positioning accuracies were improved by 26-78% (0.6-3.6 mm) and 20-34% (1.3-3.0 mm), respectively, for a short baseline. These improvements are 7-25% (0.3-1.7 mm) and 11% (1.7 mm) for a long baseline. Our experiments show that the frequency instability of clock, rather than relative frequency offset, is the governing factor of positioning accuracy.

Due to the remarkable development of the GIS and spatial information technology, the information on the national land and scientific management are disseminated. According to the result of research for an efficient analysis of forest site, it presents distinguishing of satellite image and methodology of TPI (Topographic Position Index). The prediction of forest site distribution through this research, specified Gyeongju-si area, gives an effect to distinguishing honor system through Quickbird image with the resolution 0.6m. Furthermore it was carried out through TPI grid that is abstracted by DEM, slope of study area and type of topography, as well as it put its operation on analysis and verification of relativity between the result of prediction on forest site distribution and the field survey report. It distinguishes distribution of country rock that importantly effects to producing of soil, using 1: 5000 forest maps and grasping distribution type of soil using satellite image and TPI, it is supposed to provide a foundation of the result on prediction of forest site. With the GIS techniques of analysis, inclination of discussion, altitude, etc, and using high resolution satellite image and TPI, it is considered to be capable to provide more exact basis information of forest resources, management of forest management both in rational and efficient.

We analyzed evaporation data in the Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations (J-OFURO) Ver.2. There exists huge evaporation in Gulf Stream, Kuroshio Extension, the ocean dessert and the southern part of the Indian Ocean. The temporal variation of evaporation is overwhelmingly large, of which the standard deviation is more than 120(mm), in the Kuroshio Extension region. Also, the result of harmonic analysis gives that this large variation is closely related to annual variation. In addition, the first EOF mode shows long-term variation showing the maximum amplitude between 1992 and 1994 and remarkable decrease after 1994, and large amplitude in the equatorial region and northeast of Australia. The second and third modes were strongly influenced by El Nino. Moreover, we compared J-OFURO2 evaporation product with other products. We used six kinds of data sets (HOAPS3 and GSSTF2 of satellite data, NRA1, NRA2, ERA40 and JRA25 of reanalysis data) for comparison. Most products show underestimation in the most regions, in particular, in the northern North Pacific, mid-latitudes of the eastern South Pacific, and high-latitudes of the South Pacific compared with J-OFUR02. On the other hand, JRA25 and NRA2 show large overestimation in the equatorial regions. RMS difference between NRA2 and J-OFURO2 in the Kuroshio Extension was significantly large, more than 120(mm).

Recently, several satellite data analyses projects and numerical weather prediction (NWP) reanalysis projects have produced the ocean surface Latent Heat Flux (LHF) data sets in the global coverage. Comparisons of these LHF data sets showed substantial discrepancies in the LHF values. Recently, the increase of LHF in during 1970s-1990s over the global ocean is shown by the LHF data that have been developed at the Objective Analyzed Air-Sea Fluxes (OAFlux) project. It is interesting to investigate the existence of the increase of LHF over a global ocean in the other LHF products. It is interesting to investigate the existence of the increase of LHF over a global ocean in the other LHF products. In this study, we assessed the consistencies and discrepancies of the inter-annual variability and decadal trend for the period 1988-2005 among six LHF products ((J-OFURO2, HOAPS3, IFREMER, NCEP1,2 and OAFlux) over the global ocean. As results, all LHF products showed a positive trend. In particular, the positive trend in satellite-based data analyses (J-OFURO2, HOAPS3, IFREMER) is larger than that in reanalysis products (NCEP1/2). Also, the consistencies and discrepancies are shown on the spatial patterns of the LHF trends across the six data sets. The positive trend of LHF is remarkable in the regions of western boundary currents such as the Kuroshio and the Gulf Stream in all LHF data sets. But, the discrepancies are shown on the spatial patterns of the LHF trends in tropics and subtropics. These discrepancies are primarily caused by the differences of the input meteorological state variables, particularly for the air specific humidity, used to calculate LHF.

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.

High-resolution mesoscale meteorological modeling requires more accurate and higher resolution digital elevation model (DEM) data. Shuttle Radar Topographic Mission (SRTM) has created 90 m DEM for entire globe and that is freely available for meteorological modeling and environmental applications. In this research, the effects of the topographic interpolation methods on high-resolution wind field simulation in the coastal regions were quantitatively analyzed using Weather Research and Forecasting (WRF) model with SRTM data. Sensitivity experiments with three different interpolation schemes (four-point bilinear, sixteen-point overlapping parabolic and nearest neighbor interpolation methods) were preformed using SRTM. In WRF modeling with sixteen-point overlapping parabolic interpolation, the coastal line and some small islands show more clearly than other cases. The maximum height of inland is around 140 meters higher, while the minimum of sea height is about 80 meter lower. As it concerns the results of each scheme it seems that the sixteen-point overlapping parabolic scheme indicates the well agreement with observed surface wind data. Consequently, topographic changes due to interpolation methods can lead to the significant influence on mesoscale wind field simulation of WRF modeling.

Since longer wavelength microwave radiation can penetrate clouds, satellite passive microwave sensors can observe sea ice of the entire polar region on a daily basis. Thus, it is becoming popular to derive sea ice motion vectors from a pair of satellite passive microwave sensor images observed at one or few day interval. Usually, the accuracies of derived vectors are validated by comparing with the position data of drifting buoys. However, the number of buoys for validation is always quite limited compared to a large number of vectors derived from satellite images. In this study, the sea ice motion vectors automatically derived from pairs of AMSR-E 89GHz images (IFOV = 3.5 ${\times}$ 5.9km) by an image-to-image cross correlation were validated by comparing with sea ice motion vectors manually derived from pairs of cloudless MODIS images (IFOV=250 ${\times}$ 250m). Since AMSR-E and MODIS are both on the same Aqua satellite of NASA, the observation time of both sensors are the same. The relative errors of AMSR-E vectors against MODIS vectors were calculated. The accuracy validation has been conducted for 5 scenes. If we accept relative error of less than 30% as correct vectors, 75% to 92% of AMSR-E vectors derived from one scene were correct. On the other hand, the percentage of correct sea ice vectors derived from a pair of SSM/I 85GHz images (IFOV = 15 ${\times}$ 13km) observed nearly simultaneously with one of the AMSR-E images was 46%. The difference of the accuracy between AMSR-E and SSM/I is reflecting the difference of IFOV. The accuracies of H and V polarization were different from scene to scene, which may reflect the difference of sea ice distributions and their snow cover of each scene.

The goal of this study is to retrieve ASTER thermal radiometry using a radiative transfer model. The MODTRAN is used for the model because it is easy to use with high spatial resolution and it is possible to specify input parameters such as profiles of temperature, water vapor density, ozone, aerosols and any of the other gasses. Most of parameters such as temperature and water vapor profiles were obtained from the Terra MODIS. The selected ASTER scene images land and coastal area. The surface radiance of ASTER TIR bands were retrieved by MODTRAN and extracted atmospheric profiles from MOD07 and US standard 76 models. Radiance estimated using MOD07 data was systematically lower by about 0.5-1.0 $W/m^2$ sr ${\mu}m$ than that by US standard 76 model between the two cases.

The advent of high resolution products of surface wind and temperature derived by satellite data has permitted us to investigate ocean and atmosphere interaction studies in detail. Especially the Kuroshio extension region of the western North Pacific is considered to be a key area for such studies. We have constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (Qscat/SeaWinds), available as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO). Using new data based on improved algorithm which have been recently delivered, we are reconstructing gridded product with higher spatial resolution. Intercomparison of this product with the previous one reveals that there are some discrepancies between them in short-period and high wind-speed ranges especially in the westerly wind region. The products are validated by not only comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON in the tropical Pacific and the Kuroshio Extension Observation (KEO) buoys, but also intercomparison with numerical weather prediction model (NWPM) products (the NRA-1 and 2). Our products have much smaller mean difference in the study areas than the NWPM ones, meaning higher reliability compared with the NWPM products. Using the high resolution products together with sea surface temperature (SST) data, we examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region. It is suggested that the spatial relation between the wind speed and SST depends upon, more or less, the surrounding oceanic condition.

Although the positioning accuracy of the Global Positioning System (GPS) has been studied extensively and used widely, it is still limited due to errors from sources such as the ionospheric effect, orbital uncertainty, antenna phase center variation, signal multipath and tropospheric influence. This investigation addresses the tropospheric effect on GPS height determination. Data obtained from GPS receivers and co-located surface meteorological instruments in 2003 are adopted in this study. The Ministry of the Interior (MOl), Taiwan, established these GPS receivers as continuous operating reference stations. Two different approaches, parameter estimation and external correction, are utilized to correct the zenith tropospheric delay (ZTD) by applying the surface meteorological measurements (SMM) data. Yet, incorrect pressure measurement leads to very poor accuracy. The GPS height can be affected by a few meters, and the root-mean-square (rms) of the daily solution ranges from a few millimeters to centimeters, no matter what the approach adopted. The effect is least obvious when using SMM data for the parameter estimation approach, but the constant corrections of the GPS height occur more often at higher altitudes. As for the external correction approach, the Saastamoinen model with SMM data makes the repeatability of the GPS height maintained at few centimeters, while the rms of the daily solution displays an improvement of about 2-3 mm.

Traditionally, it is measured by using basin or empirical formula with meteorology data, while it does not represent the evaportransporation over a regional area. With the advent of improved remote sensing technology, it becomes feasible to assess the ET over a regional scale. Firstly, the IMAGINE ATCOR atmospheric module is used to preprocess for the MODIS imagery. Then MODIS satellite images which have been corrected by radiation and geometry in conjunction with the in-situ surface meteorological measurement are used to estimate the surface heat fluxes such as soil heat flux, sensible heat flux, and latent heat flux. In addition, the correlation coefficient between the derived latent heat and the in-situ measurement is found to be over 0.76. In the future, we will continue to monitor the surface heat fluxes of paddy rice field in Chiayi area.

This study attempts to establish a system extracting and monitoring cultural grounds of seaweeds (lavers, brown seaweeds and seaweed fulvescens) and abalone on the basis of both KOMPSAT-2 and Terrasar-X data. The study areas are located in the northwest and southwest coast of South Korea, famous for coastal cultural grounds. The northwest site is in a high tidal range area (on the average, 6.1 min Asan Bay) and has laver cultural grounds for the most. An semi-automatic detection system of laver facilities is described and assessed for spacebome optic images. On the other hand, the southwest cost is most famous for seaweeds. Aquaculture facilities, which cover extensive portions of this area, can be subdivided into three major groups: brown seaweeds, capsosiphon fulvescens and abalone farms. The study is based on interpretation of optic and SAR satellite data and a detailed image analysis procedure is described here. On May 25 and June 2, 2008 the TerraSAR-X radar satellite took some images of the area. SAR data are unique for mapping those farms. In case of abalone farms, the backscatters from surrounding dykes allows for recognition and separation of abalone ponds from all other water-covered surfaces. But identification of seaweeds such as laver, brown seaweeds and seaweed fulvescens depends on the dampening effect due to the presence of the facilities and is a complex task because objects that resemble seaweeds frequently occur, particularly in low wind or tidal conditions. Lastly, fusion of SAR and optic spatial images is tested to enhance the detection of aquaculture facilities by using the panchromatic image with spatial resolution 1 meter and the corresponding multi-spectral, with spatial resolution 4 meters and 4 spectrum bands, from KOMPSAT-2. The mapping accuracy achieved for farms will be estimated and discussed after field verification of preliminary results.

Microwave remote sensing has great potential, especially in monsoon Asia, since optical observations are often hampered by cloudy conditions. The radar backscattering characteristics of rice crop were investigated with a ground-based automatic scatterometer system. The system was installed inside a shelter in an experimental paddy field at the National Institute of Agricultural Science and Technology (NIAST) before transplanting. The rice cultivar was a kind of Japonica type, called Chuchung. The scatterometer system consists of X-band antennas, HP8720D vector network analyzer, RF cables, and a personal computer that controls frequency, polarization and data storage. This system automatically measures fully-polarimatric backscattering coefficients of rice crop every 10 minutes, accompanied by a digital camera that takes pictures in a fixed position with the same interval. The backscattering coefficients were calculated by applying a radar equation. Plant variables, such as leaf area index (LAI), biomass, plant height and weather conditions were measured periodically throughout the rice growth season. We have performed polarimetric decomposition of paddy data such as single, double and volume scattering to extract the scattering information effectively. We investigated the relationships between backscattering coefficients and the plant variables.

It is possible to extract qualified ground control points (GCPs) solely from SAR data without published maps. TerraSAR-X is now in orbit and provides valuable data that have one of the highest spatial resolutions among civilian SAR systems. In this study, a sophisticated method for GCP coordinate extraction from TerraSAR-X stripmap mode data with a 3 m resolution was tested and the quality of the extracted GCPs was evaluated. An inverse-geolocation algorithm was applied to obtain GCPs from TerraSAR-X data. SRTM 90m DEM was used as an auxiliary data set for azimuth time correction of the SAR data. Mean values of the distance errors were 0.11 m and -3.96 m with standard deviations of 6.52 m and 5.11 m in easting and northing, respectively. The result is one of the best among GCPs possibly extracted from current civilian remote sensing systems. The extracted GCPs were used for geo-rectification of an IKONOS image, which demonstrated the applicability of the GCPs to geo-rectification of high resolution optic image. The method used in this study can be applied to KOMPSAT-5 for geo-rectification of high-resolution optic images acquired by KOMPSAT-2 or follow-up missions.

Newly developing SAR (Synthetic Aperture Radar) sensors commonly include high resolution X-band those data are expected to contribute various applications. Recent few studies are presenting potential of X-band SAR data in forest related application. This study tried to investigate the relationship between forest stand parameters and multi-band SAR normalized backscattering. Multi-band SAR data was radiometric corrected to compare signal from different forest stand condition. Then correlation coefficients were estimated between attribute of forest stand map and normalized backscattering coefficients. Although overall correlation coefficients are not high, only X-band shows strong relationship with DBH class than other bands. The signal of C- and L-band is composed of a large number of discrete tree components such as leaves, stems, even background soil. In forest, strength of radar backscattering is affected by complex parameters. Further study might be considered more various forest stand parameters such as canopy density, stand height, volume, and biomass.

Monthly mean data of Angstrom exponent and Aerosol optical thickness (AOT) from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over the East Asian waters were analyzed. Increasing trend of the satellite-derived Angstrom exponent was found over 1998-2006 while AOT mean was observed stable during the same period. Statistical test showed that annual increase in Angstrom exponent of about 0.01 is statistically significant over three study sub-areas out of six surrounding waters of Japan. Comparison with Aqua/MODIS-derived Angstrom exponent time series over June 2002 through June 2008 showed consistent correlation, with similar statistical significance. The trend of Angstrom exponent was interpreted as increase in fraction of small aerosol particles to give quantitative estimates on the variability of aerosols. The mean increase is evaluated to be about +0.35%/yr or more in terms of the contribution of small particles to the total AOT, or sub-micron fraction (SMF).

The Soya Warm Current (SWC) is a coastal boundary current, which flows along the coast of Hokkaido in the Sea of Okhotsk. Seasonal and subinertial variations in the SWC are investigated using data obtained by high-frequency (HF) ocean radars, coastal tide gauges, and a bottom-mounted acoustic Doppler current profiler (ADCP). The HF radars clearly capture the seasonal variations in the surface current fields of the SWC. The velocity of the SWC reaches its maximum, approximately 1 m/s, in the summer, and becomes weaker in the winter. The velocity core is located 20 to 30 km from the coast, and its width is approximately 50 km. The almost same seasonal cycle was repeated in the period from August 2003 to March 2007. In addition to the annual variation, the SWC exhibits subinertial variations with a period from 10-15 days. The surface transport by the SWC shows a significant correlation with the sea level difference between the Sea of Japan and Sea of Okhotsk for both of the seasonal and subinertial variations, indicating that the SWC is driven by the sea level difference between the two seas. Generation mechanism of the subinertial variation is discussed using wind data from the European Centre for Medium-range Weather Forecasts (ECMWF) analyses. The subinertial variations in the SWC are significantly correlated with the meridional wind component over the region. The subinertial variations in the sea level difference and surface current delay from the meridional wind variations for one or two days. Continental shelf waves triggered by the meridional wind on the east coast of Sakhalin and west coast of Hokkaido are considered to be a possible generation mechanism for the subinertial variations in the SWC.

Ocean surface waves may be modified by ocean current and their observation may be severely distorted if the observer is on a moving platform with changing speed. Tidal current near a sill varies inversely with the water depth, and results spatially inhomogeneous modulation on the surface waves near the sill. For waves propagating upstream, they will encounter stronger current before reaching the sill, and therefore, they will shorten their wavelength with frequency unchanged, increase its amplitude, and it may break if the wave height is larger than 1/7 of the wavelength. These small scale (${\sim}$ 1 km changes is not suitable for satellite radar observation. Spatial distribution of wave-height spectra S(x, y) can not be acquired from wave gauges that are designed for collecting 2-D wave spectra at fixed locations, nor from satellite radar image which is more suitable for observing long swells. Optical images collected from cameras on-board a ship, over high-ground, or onboard an unmanned auto-piloting vehicle (UAV) may have pixel size that is small enough to resolve decimeter-scale short gravity waves. If diffuse sky light is the only source of lighting and it is uniform in camera-viewing directions, then the image intensity is proportional to the surface reflectance R(x, y) of diffuse light, and R is directly related to the surface slope. The slope spectrum and wave-height spectra S(x, y) may then be derived from R(x, y). The results are compared with the in situ measurement of wave spectra over Keelung Sill from a research vessel. The application of this method is for analysis and interpretation of satellite images on studies of current and wave interaction that often require fine scale information of wave-height spectra S(x, y) that changes dynamically with time and space.

The classification of the effect of ionospheric disturbances on the radio occultation signal amplitude has been introduced based on an analysis of more than 2000 seances of radio occultation measurements per formed with the help of the CHAMP German satellite. The dependence of the histograms of variations in the radio occultation signal amplitude on the IMF variation index has been revealed. It has been indicated that it is possible to introduce the radio occultation index characterizing the relation between ionospheric disturbances and solar activity. An amplitude radio occultation (RO) method is proposed to study connection between the ionospheric and solar activity on a global scale. Sporadic amplitude scintillation observed in RO experiments contain important information concerning the seasonal, geographical, and temporal distributions of the ionospheric disturbances and depend on solar activity. The probability of strong RO amplitude variations (RO $S_4$ index greater than 0.2) in the CHAMP RO signals diminishes sharply with the weakening of solar activity from 2001 to 2008. The general number of RO events with strong amplitude variations can be used as an indicator of the ionospheric activity. We found that during 2001-2008 the daily globally averaged RO $S_{4a}$ index depends essentially on solar activity. The maximum occurred in January 2002, minimum has been observed in summer 2008. Different temporal behavoir of $S_{4a}$ index has been detected for polar (with latitude greater than $60^{\circ}$) and low latitude (moderate and equatorial) regions. For polar regions $S_{4a}$ index is slowly decreasing with solar activity. In the low latitude areas $S_{4a}$ index is sharply oscillating, depending on the solar ultraviolet emission variations. The different geographical behavoir of $S_{4a}$ index indicates different origin of ionospheric plasma disturbances in polar and low latitude areas. Origin of the plasma disturbances in the polar areas may be connected with influence of solar wind, the ultraviolet emission of the Sun may be the main cause of the ionospheric irregularities in the low latitude zone. Therefore, the $S_{4a}$ index of RO signal is important radio physical indicator of solar activity.

Recently there are many pilot studies for advanced application of first Korea national high resolution satellite image, which is called as KOMPSAT-MSC (Korean Multi-purpose Satellite-Multi-Spectral Camera), in Korea. In this study the forest type classification methodology is developed and its distribution map was constructed by applying high resolution satellite image, KOMPSAT-MSC, based on Tasseled Cap Transformation, especially through comparing the result of detailed filed surveying such as forest type, tree species, tree diameter, tree age and tree crown density in pilot study area.

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

A digital city model represents a 3D environment of a city with various city object information such as 3D building model, road, and land cover. Usually, at least two satellite images with some image overlap are necessary and a complex satellite-related computation needs to be carried out to create a city model. This is an expensive technique, because it requires many resources and excessive computational cost. The authors propose a methodology to create a digital city model including 3D building model and land cover information from a single high resolution satellite image. The approach consists of image pan-sharpening, shadow recovery, building occlusion restoration, building model extraction, and land cover classification. We create a digital city model using a single KOMPSAT-2 image and review the result.

Oil spills are a principal factor of the ocean pollution. The complicated problems involved in detecting oil spills are usually due to varying wind and sea surface condition such as ocean wave and current. The Hebei Spirit accident was happened in the west sea ($36^{\circ}$41'04" N, $126^{\circ}$03'12" E) near about 8 km distant from Tae-An, Korea on December 7, 2007. The aim of this work is to improve the detection and classification performance in order to define a more accurate training set and identifying the feature of oil spill region. This paper deals with an optimization technique for the detection and classification scheme using multi-frequency and multi-polarization SAR and optical image data sets of the oil spilled sea. The used image data are the ENVISAT ASAR WS and Radarsat-1 of C-band and ALOS PALSAR of L-band SAR data and KOMPSAT-2 optical images together with meteorological or oceanographic data. Both the theory and the experimental results obtained are discussed.

In very high-spatial resolution remote sensing imagery, it is difficult to extract the feature information of various objects because of occlusion and shadows. Moreover, various and feeble information within shadows can be of use in GIS-based applications and remote sensing analysis. In this paper, we developed a radiometric restoration method for shadow areas using KOMPSAT-2 satellite image. After detecting the shadow, non-shadow pixels nearby are extracted using a morphological filter. An iterative linear regression method is applied to calculate the relationship between shadow and non-shadow pixels. The shadows are restored by the parameters of the linear regression algorithm. Tests show that recovery of shadowed areas by our method leads to improved image quality.

The KOMPSAT2 Terminal Polar Station was recently installed at near North Pole, Tromso, and Toulouse. The K2PS consists of one receiving station and two processing sites. The receiving station has been installed at SvalSat ($N78^{\circ}$, $E15^{\circ}$ ), and the two receiving sites have been installed at KSAT (Kongsberg Satellite Service AS), Tromso, Norway ($N69^{\circ}$ ,$E18^{\circ}$ ) and SISA, Toulouse, France ($N43^{\circ}$ ,$E1^{\circ}$ ). The products ofK2PS system can be classified to two categories: Level 1R product and Level 1G product. The Level 1R product is radiometric corrected product with RPC (Rational Polynomial Coefficients) and the Level 1G product is geometric corrected product with POD (Precise Orbit Data) and PAD (Precise Attitude Data) data based on Level 1R product. To meet a SISA (Spot Image SA)'s requirement, K2PS system has high performance product producing capability. This paper describes overall K2PS systems' production generation flow and the mass production test result of K2PS systems.

The regulating and relaxing targets in the Land Use Regulation and Total Maximum Daily Loads are influenced by Land cover information. For the providing more accurate land information, this study attempted to generate an impervious surface map using KOMPSAT-2 image which a Korea manufactured high resolution satellite image. The classification progress of this study carried out by tasseled-cap spectral enhancement through each class extraction technique neither existing classification method. KOMPSAT-2 image of this study is enhanced by Soil Brightness Index(SBI), Green vegetation Index(GVI), None-Such wetness Index(NWI). Then ranges of extracted each index in enhanced image are determined. And then, Confidence Interval of classes was determined through the calculating Non-exceedance Probability. Spectral distributions of each class are changed according to changing of Control coefficient(${\alpha}$) at the calculated Non-exceedance Probability. Previously, Land cover classification map was generated based on established ranges of classes, and then, pervious and impervious surface was reclassified. Finally, impervious ratio of reclassified impervious surface map was calculated with blocks in the study area.

MODIS images have a great advantage of high temporal resolution to monitor land cover changes in a large area. The moderate and low spatial resolution satellite images are incomparably economic than high resolution satellite images. As diverse satellite images are provided recently, strategies using satellite images are necessary for continuous, effective and long-term land monitoring. This research purposed to use MODIS images to monitor land cover in Korean peninsula for long-term and continuous change detection. To maximize the advantages of high temporal resolution, the change detection was based on the MODIS temporal profiles of the surface reflectance for one year. In this study as the reflectance patterns of year 2005 were compared with the reflectance patterns of year 2007, the changed pixels could be detected during two years. To set up the threshold value for the decision of change, ASTER images with the higher spatial resolution, 15m, were used for this study. The test area covered the suburban area of metropolitan city, Seoul, where the landcover changes have been frequently happened.

It is important that the training stage of a supervised classification is designed to provide the spectral information. On the design of the training stage of a classification typically calls for the use of a large sample of randomly selected pure pixels in order to characterize the classes. Such guidance is generally made without regard to the specific nature of the application in-hand, including the classifier to be used. An approach to the training of a support vector machine (SVM) classifier that is the opposite of that generally promoted for training set design is suggested. This approach uses a small sample of mixed spectral responses drawn from purposefully selected locations (geographical boundaries) in training. A sample of such data should, however, be easier and cheaper to acquire than that suggested by traditional approaches. In this research, we evaluated them against traditional approaches with high-resolution satellite data. The results proved that it can be used small mixed pixels to derive a classification with similar accuracy using a large number of pure pixels. The approach can also reduce substantial costs in training data acquisition because the sampling locations used are commonly easy to observe.

We analyzed the landuse change, quantify the area covered by majors food crops (Paddy, Wheat, Barely, Maize, Millet and Potato) and their productivity trends in Terai, Nepal from 1987 to 2006. We used series of area covered by each single crop and production data published by Government of Nepal, Central Bureau of Statistics and Ministry of Agriculture and Cooperatives. Our results indicated that the agriculture land has increased by about 47% while forest has decreased by 32% between 1964 and 2001 in Terai. Whilst the total cropped area has increased by 19% between 1987 and 2006. The highest incremental change has observed in Potato by 234% followed by Wheat 31%, Maize 20% and Paddy 12% and so on. However, data revealed with very low crops productivity and it showed less than half of its potential except in Potato. The average yield of food crops /hectare /year during last 20 year has found only 3.094 metric tons. Only Potato has gained high average yield by 10.34 metric tons. While others crops yielded entirely low. 3 periods moving average depicted that the productivity trend of Barely and Millet has stagnant while others crops showed slightly up and down and increasing steadily over time. Further study is needed to comprehend the linkage of food productivity in the present food supply to demand and food security system in Terai, Nepal.

This research aimed at developing a technique for estimating the tree height using BRF (Bi-directional Reflectance Factor) through the clarification of the relation between shape of the tree crown and the tree height and the relations between the shape of the tree crown and BRF. This paper, reports the results of analyses of data acquired by field measurements done to clarify relation between crown shape and tree height.

With the advance of internet and computer processing technique, users can easily access and use the multimedia contents involving the various pictures, videos and audios information. And users request more convenient and accurate multimedia services. In these environments, it is difficulties to integrate and manage metadata standards because there are various standards in multimedia applications according to types of services and data formats individually. In this paper, we design and implement the multimedia metadata management system for integrating from heterogeneous sources. In our system, we managed heterogeneous metadata by integrating to unified schema using mapping table. Through proposed system, users can search multimedia data easily without considering variety of application services.

This paper is a proposal of Sentinel Asia for Environment (SAFE). The essential to this project is to help environmental agencies in Asia to set up an environmental monitoring system with satellite observation data. It is focused on an environmental issues originated from anthropogenic events detected as land cover and land use change in Asians' daily human life including; agriculture, global warming gas, urban environment and forest resources. It is leaded by Japan Aerospace Exploration Agency (JAXA) along with University of Tokyo and Asian Institute of Technology in Thailand under the umbrella of Sentinel Asia which is dedicated to disaster monitoring issues. It is expected to initiate a information outgoing through WWW for Asian countries to set up their national land information system focusing on environmental changes.

Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

Existing Outlier detections have been widely studied in geosensor networks. Recently, machine learning and data mining have been applied the outlier detection method to build a model that distinguishes outliers based on anchored criterion. However, it is difficult for the existing methods to detect outliers against incoming time-variant data, because outlier detection needs to monitor incoming data and classify irregular attacks. Therefore, in order to solve the problem, we propose a time-variant outlier detection using 2-dimensional grid method based on unanchored criterion. In the paper, outliers using geosensor data was performed to classify efficiently. The proposed method can be utilized applications such as network intrusion detection, stock market analysis, and error data detection in bank account.

We have extracted a surface deformation map of a part of Canisteo Peninsula on Amundsen Sea in West Antarctica by applying 4-pass DInSAR technique to two ERS-1/2 tandem pairs obtained on October 21-22, 1995 (diff-pair) and March 9-10, 1996 (topo-pair), and analyzed changes of glaciers, sea ice, ice shelves, and their kinematic interactions. We observed fast motion of glaciers pushing the adjoining sea ice. Some interferometric phases indicate the up-rise of sea ice of which type is thought to be land-fast ice to exert repulsive force against the pushing glacier. There were other glaciers and sea ice that moved to the same direction, suggesting that the sea ice in these regions was land-fast ice weakly harnessed to sea bottom or pack ice not harnessed at all. Several small circular fringes in ice shelves suggested that islands or seamounts on the bottom of ice shelves deterred the movement of ice shelves, resulting in the rise of ice surface.

Wenchuan earthquake (Mw 7.9) occurred in Sichuan province, China, May 2008 had resulted in a huge fault displacement around the Lungmenshan fault. Preliminary results of the fault displacement observed by ALOS PALSAR interferometry are presented. The surface deformation by the Wenchuan earthquake was reported up to 10m consisting of thrust- and right-slip compnents. A significant reduction in ionospheric density was also reported. Twenty differential interferograms and twenty multiple aperture SAR interferometry (MAI) pairs were produced over four ALOS tracks. It was observed from differential interferograms that i) LOS deformation decreases steadily from northnorthwest of the Longmenshan fault to the fault, ii) the LOS deformation sharply increases at areas around the fault, and iii) the decrease of the LOS deformation is observed from the Longmenshan fault to the south-southeast of the fault. Horizontal movement of the reverse fault displacement can better be observed by MAI technique, and the MAI phases show that i) the south-southeast directional reverse fault displacement (negative along-track deformation for an ascending track) of the north-northwest block gradually increases to the Longmenshan fault, ii) the reverse fault movement of the south-southeast block is sharply reversed to the north-northwest of the fault, and iii) the northnorthwest movement gradually decreases to the south-southeast of fault. Although the Lonmenshan Fault line is a center of earthquake epicenter, the boundary of surface movement exists to the north-northeast of the fault. Since the ionosphere was not stable even forty days after the mainshock, MAI phases were seriously corrupted by ionospheric effect. It is necessary to acquire more data when the ionosphere recovered to a normal state.

TerraSAR-X is new radar satellite operated at X-band, multi polarization, and multi beam mode. Compared with C-band or L-band SAR, the X-band system inherently suffers from more temporal decorrelation, but is more sensitive to surface deformation monitoring due to short wavelength (3.1 cm) and high spatial resolution (1m-3m). It is generally expected that sensitivity to estimate surface movement using TerraSAR-X will be increased by the factor of 10, compared to current C-band system with low spatial resolution such as ERS-2, Envisat. Many urban areas are experiencing land subsidence due to water, oil and natural gas withdrawal, underground excavation, sediment compaction, and so on. Monitoring of surface deformation is valuable for effectively limiting damage areas. In addition high accuracy and spatially dense subsidence map can be achieved by X-band InSAR observation, promoting identification and separation of various subsidence processes and leading to enhanced understanding via mechanical modeling. In this study we will introduce some initial InSAR results using new TerraSAR-X SAR data for surface deformation monitoring.

In this study, we propose the calibration algorithm for the solar channel (550 ${\sim}$ 900 nm) of MTSAT 1R which is the Japanese geostationary satellite launched on 26 Feb. 2005 and located at $140^{\circ}E$. We developed a method utilizing MODIS-derived BRDFs for the solar channel calibration over the bright desert area. Targets are selected based on the desert's brightness, spatial uniformity, temporal stability and spectral stability. The 6S model has been incorporated to account for directional effects of the surface using MODIS-derived BRDF parameters within the spectral interval in interest. Results based on the analysis for the period from November 2007 to June 2008 suggest that MTSAT-1R solar channel measurements have a low bias within 5%.

Visible channel calibration method using deep convective clouds (DCCs) is developed. The method has advantages that visible radiance is not sensitive to cloud optical thickness (COT) for deep convective clouds because visible radiance no longer increases when COT exceeds 100. Therefore, once DCCs are chosen appropriately, and then cloud optical properties can be assumed without operational ancillary data for the specification of cloud conditions in radiative transfer model. In this study, it is investigated whether IR measurements can be used for the selection of DCC targets. To construct appropriate threshold value for the selection of DCCs, the statistics of cloud optical properties are collected with MODIS measurements. When MODIS brightness temperature (TB) at 11 ${\mu}$ m is restricted to be less than 190 K, it is shown that more than 85% of selected pixels show COT ${\geq}$ 100. Moreover, effective radius ($r_e$) distribution shows a sharp peak around 20 ${\mu}m$. Based on those MODIS observations, cloud optical properties are assumed as COT = 200 and $r_e$ = 20 ${\mu}m$ for the simulation of MODIS visible (0.646 ${\mu}m$) band radiances over DCC targets.

A demand on the spatial data management has been rapidly increased with the introduction and diffusion process of ITS, Telematics, and Wireless Sensor Network, and many different people use the digital map that offers various thematic spatial data. Spatial data for digital map can manage to tile-based and feature-based data. The existing tile-based digital map management systems have difficult problems of data construction, history management, and updating based on a spatial object. In order to solve these problems, this paper proposed the data model for the feature-based digital map management system that is designed for feature-based seamless map, history management, real-time updating of spatial data, and analyzed the validity and utility of the proposed model.

In recent years, pollution load calculation has become a topic for research that resulted in the development of numerous GIS modeling methods. The existing pollution method for nonpoint source (NPS) can not be indentified and calculated the amount of the pollution precisely. This research shows that the association of typical pollutant concentrations with land uses in a watershed can provide a reasonably accurate characterization of nonpoint source pollution in the watershed using Expected Mean Concentrations (EMC). The GIS based pollution assessment method is performed for three pollutant constituents: BOD, TN, and TP. First, the runoff grid by means of the precipitation grid and runoff coefficient is estimated. Then, the NPS pollution loads are calculated by grid based method. Finally, the final outputs are evaluated by statistical technique. The results illustrate the merits of the approach. This model verified that GIS based method of estimating spatially distributed NPS pollution loads can lead to more accurate representation of the real world.

This paper describes the development of a circularly polarized microstrip antenna, as a part of the Circularly Polarized Synthetic Aperture Radar (CP-SAR) sensor which is currently under developed at the Microwave Remote Sensing Laboratory (MRSL) in Chiba University. CP-SAR is a new type of sensor developed for the purpose of remote sensing. With this sensor, lower-noise data/image will be obtained due to the absence of depolarization problems from propagation encounter in linearly polarized synthetic aperture radar. As well the data/images obtained will be investigated as the Axial Ratio Image (ARI), which is a new data that hopefully will reveal unique various backscattering characteristics. The sensor will be mounted on an Unmanned Aerial Vehicle (UAV) which will be aimed for fundamental research and applications. The microstrip antenna works in the frequency of 1.27 GHz (L-Band). The microstrip antenna utilized the proximity-coupled method of feeding. Initially, the optimization process of the single patch antenna design involving modifying the microstrip line feed to yield a high gain (above 5 dBi) and low return loss (below -10 dB). A minimum of 10 MHz bandwidth is targeted at below 3 dB of Axial Ratio for the circularly polarized antenna. A planar array from the single patch is formed next. Consideration for the array design is the beam radiation pattern in the azimuth and elevation plane which is specified based on the electrical and mechanical constraints of the UAV CP-SAR system. This research will contribute in the field of radar for remote sensing technology. The potential application is for landcover, disaster monitoring, snow cover, and oceanography mapping.