• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.61-69
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• 2002

The purpose of Electro-Optical Camera (EOC), the primary payload of KOMPSAT-1, is to collect high resolution visible imagery of the Earth including Korean Peninsula. EOC images will be distributed to the public or many user groups including government, public corporations, academic or research institutes. KARI will offer the online service to the users through internet. Some application, e.g., generation of Digital Elevation Model (DEM), needs a secondary data such as satellite ephemeris data, attitude data to process the EOC imagery. EOC imagery with these ancillary information will be distributed in a file of Hierarchical Data Format (HDF) file formal. HDF is a physical file format that allows storage of many different types of scientific data including images, multidimensional data arrays, record oriented data, and point data. By the lack of public domain softwares supporting HDF file format, many public users may not access EOC data without difficulty. The purpose of this research is to develop a browsing system of EOC data for the general users not only for scientists who are the main users of HDF. The system is PC-based and huts user-friendly interface.

• Journal of The Geomorphological Association of Korea
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• v.28 no.1
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• pp.83-99
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• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.83-94
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• 2003

All the urban planning process require land use informations, which should be obtained after through intensive investigation and accurate analysis about the past and current situations and conditions of a city. Until now, the generation of land use informations from remotely sensed imagery has had many limitation because of its spatial resolution. It is now expected that the availability of high resolution satellite imagery whose spatial resolution less than 10m will reduce these limitations. For the purpose of urban growth monitoring we must first establish a urban land use classification nomenclature. In this study, we would like to establish a land use nomenclature for land use classification using remotely sensed data, especially using KOMPSAT EOC imagery.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.151-160
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• 2013

Recently, although many efforts have been made to estimate insolation over Korean Peninsula based on satellite imagery, most of them have utilized overseas satellite imagery. This paper aims to estimate insolation over the Korean Peninsula based on the Korean stationary orbit satellite imagery. It utilizes level 1 data and level 2 cloud image of COMS MI, the first meteorological satellite of Korea, and OMI image of NASA as input data. And Kawamura physical model which has been known to be suitable for East Asian area is applied. Daily global horizontal insolation was estimated by using satellite images of every fifteen minutes for the period from May 2011 to April 2012, and the estimates were compared to the ground based measurements. The estimated and observed daily insolations are highly correlated as the $R^2$ value is 0.86. The error rates of monthly average insolation was under ${\pm}15%$ in most stations, and the annual average error rate of horizontal global insolation ranged from -5% to 5% except for Seoul. The experimental results show that the COMS MI based approach has good potential for estimating insolation over the Korean Peninsula.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.27-37
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• 2002

The classification accuracy of land cover has been considered as one of the major issues to estimate pollution loads generated from diffuse landuse patterns in a watershed. This research aimed to assess the effects of the acquisition methods and sampling size of training reference data on the classification accuracy of land cover using an imagery acquired by optical sensor(OPS) on JERS-1. Two kinds of data acquisition methods were considered to prepare training data. The first was to assign a certain land cover type to a specific pixel based on the researchers subjective discriminating capacity about current land use and the second was attributed to an aerial photograph incorporated with digital maps with GIS. Three different sizes of samples, 0.3%, 0.5%, and 1.0% of all pixels, were applied to examine the consistency of the classified land cover with the training data of corresponding pixels. Maximum likelihood scheme was applied to classify the land use patterns of JERS-1 imagery. Classification run applying an aerial photograph achieved 18 % higher consistency with the training data than the run applying the researchers subjective discriminating capacity. Regarding the sample size, it was proposed that the size of training area should be selected at least over 1% of all of the pixels in the study area in order to obtain the accuracy with 95% for JERS-1 satellite imagery on a typical small-to-medium-size urbanized area.

• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.223-233
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• 2008

In the mid 90's, the U.S. government released images acquired by the first generation of photo reconnaissance satellite missions between 1960 and 1972. The Declassified Intelligent Satellite Photographs (DISP) from the Corona mission are of high quality with an astounding ground resolution of about 2 m. The KH-4A panoramic camera system employed a scan angle of $70^{\circ}$ that produces film strips with a dimension of $55\;mm\;{\times}\;757\;mm$. Since GPS/INS did not exist at the time of data acquisition, the exterior orientation must be established in the traditional way by using control information and the interior orientation of the camera. Detailed information about the camera is not available, however. For reconstructing points in object space from DISP imagery to an accuracy that is comparable to high resolution (a few meters), a precise camera model is essential. This paper is concerned with the derivation of a rigorous mathematical model for the KH-4A/B panoramic camera. The proposed model is compared with generic sensor models, such as affine transformation and rational functions. The paper concludes with experimental results concerning the precision of reconstructed points in object space. The rigorous mathematical panoramic camera model for the KH-4A camera system is based on extended collinearity equations assuming that the satellite trajectory during one scan is smooth and the attitude remains unchanged. As a result, the collinearity equations express the perspective center as a function of the scan time. With the known satellite velocity this will translate into a shift along-track. Therefore, the exterior orientation contains seven parameters to be estimated. The reconstruction of object points can now be performed with the exterior orientation parameters, either by intersecting bundle rays with a known surface or by using the stereoscopic KH-4A arrangement with fore and aft cameras mounted an angle of $30^{\circ}$.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1791-1799
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• 2023

The Korea Aerospace Research Institute is responsible for supplying and supporting the utilization of imagery data from the Arirang satellite series for organizations affiliated with the Government Satellite Information Application Consultation. Most of them primarily utilize optical imagery, and there is a relative lack of utilization of Synthetic Aperture Radar (SAR) imagery. In this paper, as part of supporting the use of SAR images, we investigated SAR intensity-based change detection algorithms and their use cases that have been researched to determine SAR intensity-based change detection algorithms to be developed in the future. As a result of the research, we found that various algorithms utilizing intensity difference, correlation coefficients, histograms, or polarimetric information have been researched by numerous researchers to detect and analyze change pixels and the applications of change detection algorithms have been studied in various fields such as a city, flood, forest fire, and vegetation. This study will serve as a reference for the development of SAR change detection algorithms, intended for utilization in the Government Satellite Information Application Consultation.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.14-16
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• 2004

Although there have been wide range of studies to characterize forest stands based upon spectral information of satellite image, it was not fully understood the texture information of forest stand using high resolution data. The objective of this study is to evaluate several texture measures for characterizing forest stand structure, such as species composition, diameter at breast height(DBH), stand density, and age. High resolution IKONOS satellite imagery data were acquired in August 200 lover the forested area near Ulsan, Korea. Primary forest types were plantation pine, mixed forest, and natural deciduous forest of stand age ranging from 10 to 50 years old. Several GLCM-based texture measures were compared with forest stand characteristics. In overall, a texture measure (contrast) calculated using red band were better to differentiate species and age group than other texture measures and near infrared bands.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.59-65
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• 2005

It is very important to detect land cover/land use change from the past and to use it for future urban plan. This paper investigated the application of Landsat satellite imagery for detecting urban growth and assessing its impact on surface temperature in the region. Land cover/land use change detection was carried out by using 30m resolution Landsat satellite images and hierarchial approach was introduced to detect more detail change on the changing area through high resolution aerial photos. Also, surface temperature according to land cover/land use was calculated from Landsat TM thermal infrared data and compared with real temperature to analyze the relationship between urban expansion and surface temperature. As a result, the urban expansion has raised surface radiant temperature in the urbanized area. The method using remote sensing data based on GIS was found to be effective in monitoring and analysing urban growth and in evaluating urbanization impact on surface temperature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.413-423
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• 2016

Worldview-3 satellite sensor provides panchromatic image with high-spatial resolution and 8-band multispectral images. Therefore, an image-sharpening technique, which sharpens the spatial resolution of multispectral images by using high-spatial resolution panchromatic images, is essential for various applications of Worldview-3 images based on image interpretation and processing. The existing pansharpening algorithms tend to tradeoff between spectral distortion and spatial enhancement. In this study, we applied six pansharpening algorithms to Worldview-3 satellite imagery and assessed the quality of pansharpened images qualitatively and quantitatively. We also analyzed the effects of time lag for each multispectral band during the pansharpening process. Quantitative assessment of pansharpened images was performed by comparing ERGAS (Erreur Relative Globale Adimensionnelle de Synthèse), SAM (Spectral Angle Mapper), Q-index and sCC (spatial Correlation Coefficient) based on real data set. In experiment, quantitative results obtained by MRA (Multi-Resolution Analysis)-based algorithm were better than those by the CS (Component Substitution)-based algorithm. Nevertheless, qualitative quality of spectral information was similar to each other. In addition, images obtained by the CS-based algorithm and by division of two multispectral sensors were shaper in terms of spatial quality than those obtained by the other pansharpening algorithm. Therefore, there is a need to determine a pansharpening method for Worldview-3 images for application to remote sensing data, such as spectral and spatial information-based applications.