• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1171-1177
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• 2017

This special issue introduces recent researches on KOMPSAT(KOrea Multi-Purpose SATellite) image processing and applications. In this paper, the status of KOMPSAT development and national satellite image application policy are introduced and the implications of the papers presented in the special issue are discussed. Satellite image resources and application policy that can be utilized through continuous satellite development are considered to be systematically prepared. Therefore, if data processing and application technology development for various fields such as forest and urban change detection, image correction technology introduced in this paper are continuously carried out, it is expected that the competitiveness of national satellite image will be further strengthened.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.163-168
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• 1998

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

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.207-209
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• 2003

Quantifying crop production is one of the most important applications of remote sensing in which the temporal and up-to-date data can play very important role in avoiding any immediate insufficiency in agricultural production. A combination of climatic data and biophysical parameters derived from Landsat7 ETM+ was used to develop a mathematical model for wheat yield forecast in different geographically wide Wheat growing districts in Egypt. Leaf Area Index (LAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) with temperature were used in the modeling. The model includes three sub-models representing the correlation between the reported yield and each individual variable. Simulation results using district statistics showed high accuracy of the derived correlations to estimate wheat production with a percentage standard error (%S.E.) of 1.5% in El- Qualyobia district and average (%S.E.) of 7% for the whole wheat areas.

• Korean Journal of Remote Sensing
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• v.2 no.2
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• pp.117-131
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• 1986

The purpose of this study was to develop techniques acquiring hydrologic parameters that affect runoff conditions from Landsat imagery. Runoff conditions in a study area were analyzed by employing the U.S. Soil Conservation Service(SCS) Method. SCS runoff curve numbers(CN) were estimated by the computer analysis of Landsat imagery and digiral terrain model(DTM) data. The SCS Method requires land use/cover and soil conditions of the area as input parameters. A land use/cover map of 5 hydrological classes was produced from the Landsat multi-spectral scannerr imagery. Slope-gradient and contour and contour maps were also made using the DTM topographic data. Inundation areas depending on reservoir levels were able to be mapped on the Landsat scene by combining the contour data.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.235-243
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• 2008

Object tracking is a common vision task to detect and trace objects between consecutive frames. It is also important for a variety of applications such as surveillance, video based traffic monitoring system, and so on. An efficient moving vehicle clustering and tracking algorithm suitable for traffic monitoring system is proposed in this paper. First, automatic background extraction method is used to get a reliable background as a reference. The moving blob(object) is then separated from the background by mean shift method. Second, the scale invariant feature based method extracts the salient features from the clustered foreground blob. It is robust to change the illumination, scale, and affine shape. The simulation results on various road situations demonstrate good performance achieved by proposed method.

• Proceedings of the KSRS Conference
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• v.1
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• pp.98-101
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• 2006

In general, stereo images are widely used to remote sensing or photogrametric applications for the purpose of image understanding and feature extraction or cognition. However, the most cases of these stereo-based application deal with 2-D satellite images or the airborne photos so that its main targets are generation of small-scaled or large-scaled DEM(Digital Elevation Model) or DSM(Digital Surface Model), in the 2.5-D. Contrast to these previous approaches, the scope of this study is to investigate 3-D stereo processing and visualization of true geo-referenced 3-D features based on anaglyph technique, and the aim is at the prototype development for stereo visualization system of complex typed 3-D GIS features. As for complex typed 3-D features, the various kinds of urban landscape components are taken into account with their geometric characteristics and attributes. The main functions in this prototype are composed of 3-D feature authoring and modeling along with database schema, stereo matching, and volumetric visualization. Using these functions, several technical aspects for migration into actual 3-D GIS application are provided with experiment results. It is concluded that this result will contribute to more specialized and realistic applications by linking 3-D graphics with geo-spatial information.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.517-524
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• 2008

In order to classify an satellite imagery into geospatial features of interest, the supervised classification needs to be trained to distinguish these features through training sampling. However, even though an imagery is classified, different results of classification could be generated according to operator's experience and expertise in training process. Users who practically exploit an classification result to their applications need the research accomplishment for the consistent result as well as the accuracy improvement. The experiment includes the classification results for training process used VITD polygons as a prior probability and training parameter, instead of manual sampling. As results, classification accuracy using VITD polygons as prior probabilities shows the highest results in several methods. The training using unsupervised classification with VITD have produced similar classification results as manual training and/or with prior probability.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.378-380
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• 2005

Remote sensing of atmospheric aerosol using MODIS satellite data has been proven to be very useful in global/regional scale aerosol monitoring. Due to their large spatial resolution of $10km^2$ MODIS aerosol optical thickness (AOT) data have limitations for local/urban scale aerosol monitoring applications. Modified Bremen Aerosol Retrieval (BAER) algorithm developed by von Hoyningen-Huene et al. (2003) and Lee et al. (2005) has been applied in this study to retrieve AOT in fe resolutions of $500m^2$ over Korea. Look up tables (LUTs) were constructed from the aerosol properties based on sun-photometer observation and radiation transfer model calculations. It was found that relative error between the satellite products and the ground observations was within about $15\%$. Resulting AOT products were correlated with surface PMIO concentration data. There was good correlation between MODIS AOT and surface PM concentration under certain atmospheric conditions, which supports the feasibility of using the high-resolution MODIS AOT for local and urban scale air quality monitoring

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.299-302
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• 1999

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

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1371-1373
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• 2003

The importance of Fundamental Geographical Information Framework for Digital City (FGFDC) is analysed, it provides all city agencies and units with uniform geographic references. Six kind of data are chosen as the core data sets of a FGDC, a web-based distributed mechanism is constructed to promote data sharing among different agencies. Elementary functional requirements of FGDC are analyzed, so that it can serve as a common distributed urban GIS. A practical FGFDC is developed for Yangzhou Development Administrative Region, and an 3D visualization system is developed within this framework.