• Title/Summary/Keyword: KOMPSAT-3A

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A Study on Improvement of the Use and Quality Control for New GNSS RO Satellite Data in Korean Integrated Model (한국형모델의 신규 GNSS RO 자료 활용과 품질검사 개선에 관한 연구)

  • Kim, Eun-Hee;Jo, Youngsoon;Lee, Eunhee;Lee, Yong Hee
    • Atmosphere
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    • v.31 no.3
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    • pp.251-265
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    • 2021
  • This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.

A Study of CNN-based Super-Resolution Method for Remote Sensing Image (원격 탐사 영상을 활용한 CNN 기반의 초해상화 기법 연구)

  • Choi, Yeonju;Kim, Minsik;Kim, Yongwoo;Han, Sanghyuck
    • Korean Journal of Remote Sensing
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    • v.36 no.3
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    • pp.449-460
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    • 2020
  • Super-resolution is a technique used to reconstruct an image with low-resolution into that of high-resolution. Recently, deep-learning based super resolution has become the mainstream, and applications of these methods are widely used in the remote sensing field. In this paper, we propose a super-resolution method based on the deep back-projection network model to improve the satellite image resolution by the factor of four. In the process, we customized the loss function with the edge loss to result in a more detailed feature of the boundary of each object and to improve the stability of the model training using generative adversarial network based on Wasserstein distance loss. Also, we have applied the detail preserving image down-scaling method to enhance the naturalness of the training output. Finally, by including the modified-residual learning with a panchromatic feature in the final step of the training process. Our proposed method is able to reconstruct fine features and high frequency information. Comparing the results of our method with that of the others, we propose that the super-resolution method improves the sharpness and the clarity of WorldView-3 and KOMPSAT-2 images.

Evaluation on extraction of pixel-based solar zenith and offnadir angle for high spatial resolution satellite imagery (고해상도 위성영상의 화소기반 태양 천정각 및 촬영각 추출 및 평가)

  • Seong, Seon Kyeong;Seo, Doo Chun;Choi, Jae Wan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.563-569
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    • 2021
  • With the launch of Compact Advanced Satellite 500 series of various characteristics and the operation of KOMPSAT-3/3A, uses of high-resolution satellite images have been continuously increased. Especially, in order to provide satellite images in the form of ARD (Analysis Ready Data), various pre-processing such as geometric correction and radiometric correction have been developed. For pre-processing of high spatial satellite imagery, auxiliary information, such as solar zenith, solar azimuth and offnadir angle, should be required. However, most of the high-resolution satellite images provide the solar zenith and nadir angle for the entire image as a single variable. In this paper, the solar zenith and offnadir angle corresponding to each pixel of the image were calculated using RFM (Rational Function Model) and auxiliary information of the image, and the quality of extracted information were evaluated. In particular, for the utilization of pixel-based solar zenith and offnadir angle, pixel-based auxiliary data were applied in calculating the top of atmospheric reflectance, and comparative evaluation with a single constant-based top of atmospheric reflectance was performed. In the experiments using various satellite imagery, the pixel-based solar zenith and offnadir angle information showed a similar tendency to the auxiliary information of satellite sensor, and it was confirmed that the distortion was reduced in the calculated reflectance in the top of atmospheric reflectance.

Evaluating the Land Surface Characterization of High-Resolution Middle-Infrared Data for Day and Night Time (고해상도 중적외선 영상자료의 주야간 지표면 식별 특성 평가)

  • Baek, Seung-Gyun;Jang, Dong-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.2
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    • pp.113-125
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    • 2012
  • This research is aimed at evaluating the land surface characterization of KOMPSAT-3A middle infrared (MIR) data. Airborne Hyperspectral Scanner (AHS) data, which has MIR bands with high spatial resolution, were used to assess land surface temperature (LST) retrieval and classification accuracy of MIR bands. Firstly, LST values for daytime and nighttime, which were calculated with AHS thermal infrared (TIR) bands, were compared to digital number of AHS MIR bands. The determination coefficient of AHS band 68 (center wavelength $4.64{\mu}m$) was over 0.74, and was higher than other MIR bands. Secondly, The land cover maps were generated by unsupervised classification methods using the AHS MIR bands. Each class of land cover maps for daytime, such as water, trees, green grass, roads, roofs, was distinguished well. But some classes of land cover maps for nighttime, such as trees versus green grass, roads versus roofs, were not separated. The image classification using the difference images between daytime AHS MIR bands and nighttime AHS MIR bands were conducted to enhance the discrimination ability of land surface for AHS MIR imagery. The classification accuracy of the land cover map for zone 1 and zone 2 was 67.5%, 64.3%, respectively. It was improved by 10% compared to land cover map of daytime AHS MIR bands and night AHS MIR bands. Consequently, new algorithm based on land surface characteristics is required for temperature retrieval of high resolution MIR imagery, and the difference images between daytime and nighttime was considered to enhance the ability of land surface characterization using high resolution MIR data.

아리랑2호 반작용휠의 성능 및 기능 시험

  • Kwon, Jae-Wook;Kim, Young-Yun;Choi, Jong-Yeon;Yong, Ki-Lyuk
    • Aerospace Engineering and Technology
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    • v.3 no.2
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    • pp.7-10
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    • 2004
  • KOMPSAT-2 needs fine accuracy attitude control when it is operated in Science mode. Reaction Wheel is a necessary part of fine controlling the attitude of satellite. The reaction Wheel Assembly(RWA) is a device which provides reaction torque for attitude-control of spacecraft. It consists of an electric motor, a rotating flywheel, motor control device electrics, commutation electronics and associated power converters. This document identifies what activities to be carried out to integrate the RW#1 for ETB tests.

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Spectral Reflectance Patterns by Artificial Acid Rain in Pinus and Quercus species

  • Lee, Seong-Ho;Kim, Cheol-Min;Oh, Dong-Ha
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.382-386
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    • 1998
  • The objectives of this study are to reveal relationship between tree physiology and spectral reflectance on effects of artificial acid rain and to obtain basic data on optimal wave length for forest of LRC sensor on KOMPSAT-2. Three pH levels of artificial acid rain - control, pH4.5 and pH3.0 - were applied to Pinus and Quercus species. Three types of the acid rain were spraied at the amount of 500m1 in every two days. Spectral reflectance data was collected once in a month by using GER 1500 (350~2500nm) or Ll 1800(300~1100nm) Spectroradiometer. The data was measured three times in a pH level. The results of this study are as follows; in April, the spectral reflectance of Pinus species was high in order at the level of pH3.0, control and pH4.5; in May, control, pH3.0 and pH4.5; in June, control, pH4.5 and pH3.0. That of Quercus species was high in the order of control, pH4.5 and pH3.0 in May; in June, control, pH3.0 and pH4.5, especially, within infrared wave length range, control, pH4.5 and ph3.0.

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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.

Change Detection Using Deep Learning Based Semantic Segmentation for Nuclear Activity Detection and Monitoring (핵 활동 탐지 및 감시를 위한 딥러닝 기반 의미론적 분할을 활용한 변화 탐지)

  • Song, Ahram;Lee, Changhui;Lee, Jinmin;Han, Youkyung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.991-1005
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    • 2022
  • Satellite imaging is an effective supplementary data source for detecting and verifying nuclear activity. It is also highly beneficial in regions with limited access and information, such as nuclear installations. Time series analysis, in particular, can identify the process of preparing for the conduction of a nuclear experiment, such as relocating equipment or changing facilities. Differences in the semantic segmentation findings of time series photos were employed in this work to detect changes in meaningful items connected to nuclear activity. Building, road, and small object datasets made of KOMPSAT 3/3A photos given by AIHub were used to train deep learning models such as U-Net, PSPNet, and Attention U-Net. To pick relevant models for targets, many model parameters were adjusted. The final change detection was carried out by including object information into the first change detection, which was obtained as the difference in semantic segmentation findings. The experiment findings demonstrated that the suggested approach could effectively identify altered pixels. Although the suggested approach is dependent on the accuracy of semantic segmentation findings, it is envisaged that as the dataset for the region of interest grows in the future, so will the relevant scope of the proposed method.

Effects of spatial resolution on digital image to detect pine trees damaged by pine wilt disease

  • Lee, Seung-Ho;Cho, Hyun-Kook
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.260-263
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    • 2005
  • This study was carried out to investigate the effects of spatial resolutions on digital image for detecting pine trees damaged by pine wilt disease. Color infrared images taken from PKNU-3 multispectral airborne photographing system with a spatial resolution of 50cm was used as a basic data. Further test images with spatial resolutions of 1m, 2m and 4m were made from the basic data to test the detecting capacity on each spatial resolution. The test was performed with visual interpretation both on mono and stereo modus and compared with field surveying data. It can be conclude that it needs less than 1m spational resolutions or 1m spatial resolutions with stereo pair in order to detect pine trees damaged by pine wilt disease.

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Analysis of Geolocation Accuracy of Precision Image Processing System developed for CAS-500 (국토관측위성용 정밀영상생성시스템의 위치정확도 분석)

  • Lee, Yoojin;Park, Hyeongjun;Kim, Hye-Sung;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.893-906
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    • 2020
  • This paper reports on the analysis of the location accuracy of a precision image generation system manufactured for CAS 500. The planned launch date of the CAS 500 is 2021, and since it has not yet been launched, the analysis was performed using KOMPSAT-3A satellite images having similar specifications to the CAS 500. In this paper, we have checked the geolocation accuracy of initial sensor model, the model point geolocation accuracy of the precise sensor model, the geolocation accuracy of the precise sensor model using the check point, and the geolocation accuracy of the precise orthoimage using 30 images of the Korean Peninsula. In this study, the target geolocation accuracy is to have an RMSE within 2 pixels when an accurate ground control point is secured. As a result, it was confirmed that the geolocation accuracy of the precision sensor model using the checkpoint was about 1.85 pixels in South Korea and about 2.04 pixels in North Korea, and the geolocation accuracy of the precise orthoimage was about 1.15 m in South Korea and about 3.23 m in North Korea. Overall, it was confirmed that the accuracy of North Korea was low compared to that of South Korea, and this was confirmed to have affected the measured accuracy because the GCP (Ground Control Point) quality of the North Korea images was poor compared to that of South Korea. In addition, it was confirmed that the accuracy of the precision orthoimage was slightly lower than that of precision sensor medel, especially in North Korea. It was judged that this occurred from the error of the DTM (Digital Terrain Model) used for orthogonal correction. In addition to the causes suggested by this paper, additional studies should be conducted on factors that may affect the position accuracy.