• Title/Summary/Keyword: Geo-Kompsat 2A

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Conceptual Design of GK2A UHRIT Broadcasting using DVB-S2 (DVB-S2 표준을 적용한 정지궤도복합위성 UHRIT 통신 개념설계)

  • Park, Durk-Jong;Lim, Hyun-Su;Ahn, Sang-Il
    • Aerospace Engineering and Technology
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    • v.12 no.2
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    • pp.156-162
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    • 2013
  • In the communication between satellite and ground station, data rate can be determined from the data volume and required transmission time. Increasing data rate can be limited according to the available bandwidth. For the reason, it has been popularly studying on high spectral-efficient modulation scheme in large volume data application such as digital video broadcasting service. This paper presents the conceptual design of UHRIT broadcasting in GEO-KOMPSAT-2A (GK2A) mission by using DVB-S2 standard. Based on the recently determined data rate, UHRIT bandwidth was calculated at the various modulation schemes and code rates of DVB-S2 standard. Receiving performance of global user station was also evaluated thorough link analysis by considering that user station is located at the edge of beam coverage. Finally, maximum data rate was analyzed in a situation that COMS HRIT bandwidth should be alternatively applied for UHRIT downlink.

A Study on the GK2A/AMI Image Based Cold Water Detection Using Convolutional Neural Network (합성곱신경망을 활용한 천리안위성 2A호 영상 기반의 동해안 냉수대 감지 연구)

  • Park, Sung-Hwan;Kim, Dae-Sun;Kwon, Jae-Il
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1653-1661
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    • 2022
  • In this study, the classification of cold water and normal water based on Geo-Kompsat 2A images was performed. Daily mean surface temperature products provided by the National Meteorological Satellite Center (NMSC) were used, and convolution neural network (CNN) deep learning technique was applied as a classification algorithm. From 2019 to 2022, the cold water occurrence data provided by the National Institute of Fisheries Science (NIFS) were used as the cold water class. As a result of learning, the probability of detection was 82.5% and the false alarm ratio was 54.4%. Through misclassification analysis, it was confirmed that cloud area should be considered and accurate learning data should be considered in the future.

Validation on Solar-array Drive Assembly of GEO-KOMPSAT-2A Through In-orbit Operation (천리안2A호 태양전지판구동기 궤도상 운영 검증)

  • Park, Young-Woong;Park, Keunjoo;Park, Bong-Kyu
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.47 no.4
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    • pp.283-288
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    • 2019
  • In this paper, there is summarized the validation of ground test results through the telemetry acquired during on-orbit initial activation on solar-array drive assembly(SDA) of GK2A launched at Dec-5, 2018. Especially, the decision logic of SDA initial position and the compensation logic are validated and confirmed. The SDA initial position is needed when GK2A enter to geostationary orbit from transfer orbit and the compensation logic is for the accumulated position error due to the open-loop control. Up to now, it is normal operating. Also the periodic offset between the geostationary orbit and Sun position is found that it is not checked on design phase, and then the proper threshold value is applied.

Development of GK2A Convective Initiation Algorithm for Localized Torrential Rainfall Monitoring (국지성 집중호우 감시를 위한 천리안위성 2A호 대류운 전조 탐지 알고리즘 개발)

  • Park, Hye-In;Chung, Sung-Rae;Park, Ki-Hong;Moon, Jae-In
    • Atmosphere
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    • v.31 no.5
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    • pp.489-510
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    • 2021
  • In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.

LiDAR Chip for Automated Geo-referencing of High-Resolution Satellite Imagery (라이다 칩을 이용한 고해상도 위성영상의 자동좌표등록)

  • Lee, Chang No;Oh, Jae Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.4_1
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    • pp.319-326
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    • 2014
  • The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

Development of New Photogrammetric Software for High Quality Geo-Products and Its Performance Assessment

  • Jeong, Jae-Hoon;Lee, Tae-Yoon;Rhee, Soo-Ahm;Kim, Hyeon;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.28 no.3
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    • pp.319-327
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    • 2012
  • In this paper, we introduce a newly developed photogrammetric software for automatic generation of high quality geo-products and its performance assessment carried out using various satellite images. Our newly developed software provides the latest techniques of an optimized sensor modelling, ortho-image generation and automated Digital Elevation Model (DEM) generation for diverse remote sensing images. In particular, images from dual- and multi-sensor images can be integrated for 3D mapping. This can be a novel innovation toward a wider applicability of remote sensing data, since 3D mapping has been limited within only single-sensor so far. We used Kompsat-2, Ikonos, QuickBird, Spot-5 high resolution satellite images to test an accuracy of 3D points and ortho-image generated by the software. Outputs were assessed by comparing reliable reference data. From various sensor combinations 3D mapping were implemented and their accuracy was evaluated using independent check points. Model accuracy of 1~2 pixels or better was achieved regardless of sensor combination type. The high resolution ortho-image results are consistent with the reference map on a scale of 1:5,000 after being rectified by the software and an accuracy of 1~2 pixels could be achieved through quantitative assessment. The developed software offers efficient critical geo-processing modules of various remote sensing images and it is expected that the software can be widely used to meet the demand on the high-quality geo products.

Overlay Rendering of Multiple Geo-Based Images Using WebGL Blending Technique (WebGL 블렌딩 기법을 이용한 다중 공간영상정보 중첩 가시화)

  • Kim, Kwang-Seob;Lee, Ki-Won
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.4
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    • pp.104-113
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    • 2012
  • Followed by that HTML5(Hypertext Markup Language5) was introduced, many kinds of program and services based on this have been developed and released. HTML5 is technical standard specifications for cross platform for personal computers and mobile devices so that it is expected that continuing progress and wide application in the both sides of the academic and the industrial fields increase. This study is to design and implement a mobile application program for overlay rendering with DEM and other geo-based image sets using HTML5 WebGL for 3D graphic processing on web environment. Particularly, the blending technique was used for overlay processing with multiple images. Among available WebGL frameworks, CubicVR.js was adopted, and various blending techniques were provided in the user interface for general users. For the actual application in the study area around the Sejong city, serveral types of geo-based data sets were used and processed: KOMPSAT-2 images, ALOS PALSAR SAR images, and grid data by environment measurements. While, DEM for 3D viewing with these geo-based images was produced using contour information of the digital map sets. This work demonstrates possibilities that new types of contents and service system using geo-based images can be extracted and applied.

A Study of Geostationary Atmospheric Environmental Monitoring Satellite Data Management Policies (정지궤도 대기환경 관측 위성 자료 관리 정책 방안 연구)

  • Choi, Won Jun;Eun, Jong Won
    • Journal of Satellite, Information and Communications
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    • v.11 no.4
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    • pp.10-14
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    • 2016
  • Korean satellite development projects were divided military objectives such as national security, and commercial communication satellites. The First geostationary Korean earth observation satellite, GeoKOMPSAT is a turning point to concern another way to utilizing satellite. In the past, the main concern was the sharp ground images, now days, it is more important to make high added value from satellite data. In particular, environmental payload, GEMS mounted on the satellite GeoKOMPSAT-2 will monitor air quality which is not observed by visual material, may be referred to as case by utilizing the satellite. Satellite data utilization is likely to receive a great influence on the appropriate public policy data. If the public is expected to be fully revealed that potential demand. It is time to change the management policy on the security aspects of weak satellite data. Depending on the expanding use of satellites, it is necessary to investigate the status of disclosing satellite data, and suggests policy options for the distribution of materials for the environment satellite characteristics.

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.

Atmospheric Correction of Sentinel-2 Images Using GK2A AOD: A Comparison between FLAASH, Sen2Cor, 6SV1.1, and 6SV2.1 (GK2A AOD를 이용한 Sentinel-2 영상의 대기보정: FLAASH, Sen2Cor, 6SV1.1, 6SV2.1의 비교평가)

  • Kim, Seoyeon;Youn, Youjeong;Jeong, Yemin;Park, Chan-Won;Na, Sang-Il;Ahn, Hoyong;Ryu, Jae-Hyun;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.5_1
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    • pp.647-660
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    • 2022
  • To prepare an atmospheric correction model suitable for CAS500-4 (Compact Advanced Satellite 500-4), this letter examined an atmospheric correction experiment using Sentinel-2 images having similar spectral characteristics to CAS500-4. Studies to compare the atmospheric correction results depending on different Aerosol Optical Depth (AOD) data are rarely found. We conducted a comparison of Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), Sen2Cor, and Second Simulation of the Satellite Signal in the Solar Spectrum - Vector (6SV) version 1.1 and 2.1, using Geo-Kompsat 2A (GK2A) Advanced Meteorological Imager (AMI) and Aerosol Robotic Network (AERONET) AOD data. In this experiment, 6SV2.1 seemed more stable than others when considering the correlation matrices and the output images for each band and Normalized Difference Vegetation Index (NDVI).