• Title/Summary/Keyword: KOMPSAT-2 satellite imagery

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Geolocation Error Analysis of KOMPSAT-5 SAR Imagery Using Monte-Carlo Simulation Method

  • Choi, Yoon Jo;Hong, Seung Hwan;Sohn, Hong Gyoo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.2
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    • pp.71-79
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    • 2019
  • Geolocation accuracy is one of the important factors in utilizing all weather available SAR satellite imagery. In this study, an error budget analysis was performed on key variables affecting on geolocation accuracy by generating KOMPSAT-5 simulation data. To perform the analysis, a Range-Doppler model was applied as a geometric model of the SAR imagery. The results show that the geolocation errors in satellite position and velocity are linearly related to the biases in the azimuth and range direction. With 0.03cm/s satellite velocity biases, the simulated errors were up to 0.054 pixels and 0.0047 pixels in the azimuth and range direction, and it implies that the geolocation accuracy is sensitive in the azimuth direction. Moreover, while the clock drift causes a geolocation error in the azimuth direction, a signal delay causes in the range direction. Monte-Carlo simulation analysis was performed to analyze the influence of multiple geometric error sources, and the simulated error was up to 3.02 pixels in the azimuth direction.

INTRODUCTION OF NUC ALGORITHM IN ON-BOARD RELATIVE RADIOMERIC CALIBRATION OF KOMPSAT-2

  • Song, J.H.;Choi, M.J.;Seo, D.C.;Lee, D.H.;Lim, H.S.
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.504-507
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    • 2007
  • The KOMPSAT-2 satellite is a push-broom system with MSC (Multi Spectral Camera) which contains a panchromatic band and four multi-spectral bands covering the spectral range from 450nm to 900nm. The PAN band is composed of six CCD array with 2528 pixels. And the MS band has one CCD array with 3792 pixels. Raw imagery generated from a push-broom sensor contains vertical streaks caused by variability in detector response, variability in lens falloff, pixel area, output amplifiers and especially electrical gain and offset. Relative radiometric calibration is necessary to account for the detector-to-detector non-uniformity in this raw imagery. Non-uniformity correction (NUC) is that the process of performing on-board relative correction of gain and offset for each pixel to improve data compressibility and to reduce banding and streaking from aggregation or re-sampling in the imagery. A relative gain and offset are calculated for each detector using scenes from uniform target area such as a large desert, forest, sea. In the NUC of KOMPSAT-2, The NUC table for each pixel are divided as HF NUC (high frequency NUC) and LF NUC (low frequency NUC) to apply to few restricted facts in the operating system ofKOMPSAT-2. This work presents the algorithm and process of NUC table generation and shows the imagery to compare with and without calibration.

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Improvement of KOMPSAT Imagery Locational Accuracy Using Value-Added Processing System (부가처리시스템을 이용한 다목적실용위성 영상자료 위치정확도 개선)

  • LEE, Kwang-Jae;YUN, Hee-Cheon;KIM, Youn-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.4
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    • pp.68-80
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    • 2015
  • To increase the utilization of the KOrea Multi-Purpose SATellite(KOMPSAT) series imagery being developed pursuant to the national space development program, high quality images with enhanced locational accuracy should be created through standardized post-processing processes. In the present study, using the Value-Added Processing System(VAPS) constructed for the post-processing of KOMPSAT imagery, location correction experiments were conducted using KOMPSAT-2 and -3 imagery from domestic and overseas regions. First, 50 pieces from each of KOMPSAT-2 imagery were selected from South Korean and North Korean regions, and modeling was conducted using GCP Chips. According to the results, the Root Mean Square Errors(RMSE) for South Korea and North Korea were 1.59 pixels and 2.04 pixels, respectively, and the locational accuracy of ortho mosaic imagery using check points were 1.33m(RMSE) and 1.90m(RMSE), respectively. Meanwhile, in the case of overseas regions for which GCP could not be easily obtained, the improvement of locational accuracy could be identified through image corrections using Open Street Map(OSM). The VAPS and reference materials used in the present study are expected to be very useful in constructing a precise image DB for entire global regions.

Spatial Pattern Analysis of High Resolution Satellite Imagery: Level Index Approach using Variogram

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.22 no.5
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    • pp.357-366
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    • 2006
  • A traditional image analysis or classification method using satellite imagery is mostly based on the spectral information. However, the spatial information is more important according as the resolution is higher and spatial patterns are more complex. In this study, we attempted to compare and analyze the variogram properties of actual high resolution imageries mainly in the urban area. Through the several experiments, we have understood that the variogram is various according to a sensor type, spatial resolution, a location, a feature type, time, season and so on and shows the information related to a feature size. With simple modeling, we confirmed that the unique variogram types were shown unlike the classical variogram in case of small subsets. Based on the grasped variogram characteristics, we made a level index map for determining urban complexity or land-use classification. These results will become more and more important and be widely applied to the various fields of high-resolution imagery such as KOMPSAT-2 and KOMPSAT-3 which is scheduled to be launched.

Standardizing Agriculture-related Land Cover Classification Scheme Using IKONOS Satellite Imagery (IKONOS 영상자료를 이용한 농업관련 토지피복 분류기준 설정 연구)

  • 홍성민;정인균;김성준
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.261-265
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    • 2004
  • The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat+ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

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A Study on Extraction of Croplands Located nearby Coastal Areas Using High-Resolution Satellite Imagery and LiDAR Data (고해상도 위성영상과 LiDAR 자료를 활용한 해안지역에 인접한 농경지 추출에 관한 연구)

  • Choung, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.1
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    • pp.170-181
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    • 2015
  • A research on extracting croplands located nearby coastal areas using the spatial information data sets is the important task for managing the agricultural products in coastal areas. This research aims to extract the various croplands(croplands on mountains and croplands on plain areas) located nearby coastal areas using the KOMPSAT-2 imagery, the high-resolution satellite imagery, and the airborne topographic LiDAR(Light Detection And Ranging) data acquired in coastal areas of Uljin, Korea. Firstly, the NDVI(Normalized Difference Vegetation Index) imagery is generated from the KOMPSAT-2 imagery, and the vegetation areas are extracted from the NDVI imagery by using the appropriate threshold. Then, the DSM(Digital Surface Model) and DEM(Digital Elevation Model) are generated from the LiDAR data by using interpolation method, and the CHM(Canopy Height Model) is generated using the differences of the pixel values of the DSM and DEM. Then the plain areas are extracted from the CHM by using the appropriate threshold. The low slope areas are also extracted from the slope map generated using the pixel values of the DEM. Finally, the areas of intersection of the vegetation areas, the plain areas and the low slope areas are extracted with the areas higher than the threshold and they are defined as the croplands located nearby coastal areas. The statistical results show that 85% of the croplands on plain areas and 15% of the croplands on mountains located nearby coastal areas are extracted by using the proposed methodology.

High-resolution Land Cover Mapping of Rural Area Using IKONOS Imagery (IKONOS 영상을 이용한 고해상도 토지피복도 작성)

  • Hong, Seong Min;Jung, In Kyun;Kim, Seong Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.1271-1275
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    • 2004
  • The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat +ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

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STUDY ON THE GRID REFERENCE SYSTEM FOR KOMPSAT-3 IMAGERY

  • Kang, Chi-Ho;Ahn, Sang-Il
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.486-488
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    • 2007
  • The Grid Reference System, which was firstly used in SPOT series, has been successfully adapted in KOMPSAT-1 and KOMPSAT-2 program, which identifies the geographical location to make image collection plans and manage the database of satellite images. Each Grid Reference System for KOMPSAT-1 and KOMPSAT-2 was designed based on system parameters related to each KOMPSAT-1 and KOMPSAT-2 and this fact leads to the need for the design of the Grid Reference System for KOMPSAT-3 (KGRS-3, hereafter), which reflects system parameters for KOMPSAT-3. The (K, J) coordinate system has been defined as the Grid Reference System for KOMPSAT-3 using heritages from KOMPSAT-1 and KOMPSAT-2 programs. The numbering of K begins with the prime meridian of K = 1 with running eastward on earth increasingly, and the numbering of J uses a value of J = 1000 at all points on the equator and begin with running northward increasingly. The Grid Reference System for KOMPSAT-3 is to be implemented in Ground Segment of KOMPSAT-3 system.

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The Land Cover Change Detection of an Urban Area from Aerial Photos and KOMPSAT EOC Satellite Imagery (항공사진과 KOMPSAT EOC 위성영상으로부터 도시지역의 토지피복 변화 검출)

  • 조창환;배상우;이성순;이진덕
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.04a
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    • pp.177-182
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    • 2004
  • This study presents the application of aerial photographs and KOMPSAT-1 Electro-Optical Camera(EOC) imagery in detecting the change of an urban area that has been rapidly growing. For the study, we used multi-time images which were acquired by two different sensors. For all of the images, the coordinate reference system and scale were first made identical through the 1st and 2nd geometric corrections and then image resampling were carried out to spatial resolution of 7m to detect changes under the same conditions. The Image Differencing was employed as a change detection technique. It was confirmed to be able to detect the changes of terrestrial surface like building, structure and road features from aerial photos and KOMPSAT EOC images with single band. The changes could be detected to some extent with the images acquired from different kinds of sensors as well as the same kinds of sensors.

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Semi-Automated Extraction of Geographic Information using KOMPSAT 2 : Analyzing Image Fusion Methods and Geographic Objected-Based Image Analysis (다목적 실용위성 2호 고해상도 영상을 이용한 지리 정보 추출 기법 - 영상융합과 지리객체 기반 분석을 중심으로 -)

  • Yang, Byung-Yun;Hwang, Chul-Sue
    • Journal of the Korean Geographical Society
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    • v.47 no.2
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    • pp.282-296
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    • 2012
  • This study compared effects of spatial resolution ratio in image fusion by Korea Multi-Purpose SATellite 2 (KOMPSAT II), also known as Arirang-2. Image fusion techniques, also called pansharpening, are required to obtain color imagery with high spatial resolution imagery using panchromatic and multi-spectral images. The higher quality satellite images generated by an image fusion technique enable interpreters to produce better application results. Thus, image fusions categorized in 3 domains were applied to find out significantly improved fused images using KOMPSAT 2. In addition, all fused images were evaluated to satisfy both spectral and spatial quality to investigate an optimum fused image. Additionally, this research compared Pixel-Based Image Analysis (PBIA) with the GEOgraphic Object-Based Image Analysis (GEOBIA) to make better classification results. Specifically, a roof top of building was extracted by both image analysis approaches and was finally evaluated to obtain the best accurate result. This research, therefore, provides the effective use for very high resolution satellite imagery with image interpreter to be used for many applications such as coastal area, urban and regional planning.

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