• Title/Summary/Keyword: Kompsat-2 image

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An Experiment for Surface Reflectance Image Generation of KOMPSAT 3A Image Data by Open Source Implementation (오픈소스 기반 다목적실용위성 3A호 영상자료의 지표면 반사도 영상 제작 실험)

  • Lee, Kiwon;Kim, Kwangseob
    • Korean Journal of Remote Sensing
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    • v.35 no.6_4
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    • pp.1327-1339
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    • 2019
  • Surface reflectance obtained by absolute atmospheric correction from satellite images is useful for scientific land applications and analysis ready data (ARD). For Landsat and Sentinel-2 images, many types of radiometric processing methods have been developed, and these images are supported by most commercial and open-source software. However, in the case of KOMPSAT 3/3A images, there are currently no tools or open source resources for obtaining the reflectance at the top-of-atmosphere (TOA) and top-of-canopy (TOC). In this study, the atmospheric correction module of KOMPSAT 3/3A images is newly implemented to the optical calibration algorithm supported in the Orfeo ToolBox (OTB), a remote sensing open-source tool. This module contains the sensor model and spectral response data of KOMPSAT 3A. Aerosol measurement properties, such as AERONET data, can be used to generate TOC reflectance image. Using this module, an experiment was conducted, and the reflection products for TOA and TOC with and without AERONET data were obtained. This approach can be used for building the ARD database for surface reflection by absolute atmospheric correction derived from KOMPSAT 3/3A satellite images.

A Pansharpening Algorithm of KOMPSAT-3A Satellite Imagery by Using Dilated Residual Convolutional Neural Network (팽창된 잔차 합성곱신경망을 이용한 KOMPSAT-3A 위성영상의 융합 기법)

  • Choi, Hoseong;Seo, Doochun;Choi, Jaewan
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.961-973
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    • 2020
  • In this manuscript, a new pansharpening model based on Convolutional Neural Network (CNN) was developed. Dilated convolution, which is one of the representative convolution technologies in CNN, was applied to the model by making it deep and complex to improve the performance of the deep learning architecture. Based on the dilated convolution, the residual network is used to enhance the efficiency of training process. In addition, we consider the spatial correlation coefficient in the loss function with traditional L1 norm. We experimented with Dilated Residual Networks (DRNet), which is applied to the structure using only a panchromatic (PAN) image and using both a PAN and multispectral (MS) image. In the experiments using KOMPSAT-3A, DRNet using both a PAN and MS image tended to overfit the spectral characteristics, and DRNet using only a PAN image showed a spatial resolution improvement over existing CNN-based models.

The Structure and Operation of KOMPSAT-II Memory (다목적실용위성 2호 메모리 구조와 운영)

  • 이종태;이상규;이상택;이도경
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.421-424
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    • 2003
  • The KOMPSAT-II has a MSC(Multi-Spectral Camera) payload for earth observatory. The image data acquired during the pass over the Korean Peninsula can be sent to the ground station directly. But the image data out of the contact range should be stored temporally for later transmission. The KOMPSAT-II has a device for this purpose called the DCSU(Data Compression and Storage Unit) and the DCSU also performs compression functions for saving storage space and transmission time to send image data to the ground station. In this paper, we'd like to introduce the DCSU memory structures and operation.

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RADIOMETRIC RESTORATION OF SHADOW AREAS FROM KOMPSAT-2 IMAGERY

  • Choi, Jae-Wan;Kim, Hye-Jin;Han, You-Kyung;Kim, Yong-II
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.371-374
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    • 2008
  • In very high-spatial resolution remote sensing imagery, it is difficult to extract the feature information of various objects because of occlusion and shadows. Moreover, various and feeble information within shadows can be of use in GIS-based applications and remote sensing analysis. In this paper, we developed a radiometric restoration method for shadow areas using KOMPSAT-2 satellite image. After detecting the shadow, non-shadow pixels nearby are extracted using a morphological filter. An iterative linear regression method is applied to calculate the relationship between shadow and non-shadow pixels. The shadows are restored by the parameters of the linear regression algorithm. Tests show that recovery of shadowed areas by our method leads to improved image quality.

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Comparative Analysis of Image Fusion methods using KOMPSAT-2 Imagery (KOMPSAT-2 위성영상을 이용한 영상융합기법 비교연구)

  • Yu, Beong-Hyeok;Chi, Gwang-Hoon
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.196-201
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    • 2009
  • KOMPSAT-2 위성영상은 공간해상도가 우수한 1-m급 전정색 영상과, 상대적으로 분광해상도가 우수한 4-m급 다중분광 영상을 동시 취득하는 다중 센서이다. 영상융합기법의 적용을 통해 1-m급 고해상도 다중분광 영상의 취득이 가능하며, 이것은 1-m급에서 식별 가능한 객체들을 분류하고 변화 탐지하는데 활용될 수 있다. 본 연구는 IHS (Intensity-Hue-Saturation) 융합 기법의 I (Intensity) 와 $\delta$ 값을 조정함으로써 새로운 융합기법을 제안하였으며, 육안분석과 상관계수를 가지고 다른 융합기법들과 비교분석하였다. 실험 결과, 제안된 기법의 융합영상은 원본 다중분광영상과 가장 높은 상관계수를 나타내었으며, 상관계수가 유사한 웨이브릿 융합 또는 고대역 필터링과의 육안분석에서 확연히 우수한 공간 선명도를 나타내는 것으로 평가되었다.

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Forest Fire Severity Classification Using Probability Density Function and KOMPSAT-3A (확률밀도함수와 KOMPSAT-3A를 활용한 산불피해강도 분류)

  • Lee, Seung-Min;Jeong, Jong-Chul
    • Korean Journal of Remote Sensing
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    • v.35 no.6_4
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    • pp.1341-1350
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    • 2019
  • This research deals with algorithm for forest fire severity classification using multi-temporal KOMPSAT-3A image to mapping forest fire areas. The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution and multi-spectral imagery with infrared and high resolution electro-optical bands. However, there is a lack of research to classify forest fire severity using KOMPSAT-3A. Therefore, the purpose of this study is to analyze forest fire severity using KOMPSAT-3A images. In addition, this research used pre-fire and post-fire Sentinel-2 with differenced Normalized Burn Ratio (dNBR) to taking for burn severity distribution map. To test the effectiveness of the proposed procedure on April 4, 2019, Gangneung wildfires were considered as a case study. This research used the probability density function for the classification of forest fire damage severity based on R software, a free software environment of statistical computing and graphics. The burn severities were estimated by changing NDVI before and after forest fire. Furthermore, standard deviation of probability density function was used to calculate the size of each class interval. A total of five distribution of forest fire severity were effectively classified.

A Study of Land-Cover Classification Technique for Merging Image Using Fuzzy C-Mean Algorithm (Fuzzy C-Mean 알고리즘을 이용한 중합 영상의 토지피복분류기법 연구)

  • 신석효;안기원;양경주
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.2
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    • pp.171-178
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    • 2004
  • The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study was presented more better land cover classification method through an algorithm development. We accomplished FCM(Fuzzy C-Mean) classification technique with MLC (Maximum Likelihood classification) technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method. This study is used to the high-resolution(6.6m) Electro-Optical Camera(EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1(KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer(MODIS) image data(36 bands).

Image Radiometric Quality Assessment of the Meteorological Payload on GEO-KOMPSAT-2A (정지궤도복합위성 기상탑재체 영상의 복사 성능 품질 측정)

  • Jin, Kyoung-Wook;Yang, Koon-Ho;Choi, Jae-Dong
    • Aerospace Engineering and Technology
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    • v.12 no.2
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    • pp.30-39
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    • 2013
  • In this study, calibration processes and methods of evaluating the radiometric quality of satellite images from the meteorological payload on the GEO-KOMPSAT-2A were described. MTF(Modulation Transfer Function), SNR(Signal-To-Noise Ratio), NEdT(Noise Equivalent Delta Temperature), and Dynamic Range, which are the major parameters for assessment of data radiometric quality of space-borne visible and infrared sensors, are focused. Key process of the quality check of the satellite data is the comparing the image radiometric performance parameters during the In-Oribit Test with those acquired from the ground tests. Validation plan of the image quality of the GEO-KOMPSAT-2A Meteorological Imager is addressed based on the analyses results of COMS MI data during the COMS In-Orbit Test period

Analysis for Practical use as KOMPSAT-2 Imagery for Product of Geo-Spatial Information (지형공간정보 생성을 위한 KOPMSAT-2 영상의 활용성 분석)

  • Lee, Hyun-Jik;You, Ji-Ho;Koh, Young-Chang
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.21-35
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    • 2009
  • KOMPSAT-2 is the seventh high-resolution image satellite in the world that provides both 1m-grade panchromatic images of the GSD and 4m-grade multispectral images of the GSD. It's anticipated to be used across many different areas including mapping, territory monitoring and environmental watch. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric images, such as satellite orbits and detailed mapping information. Therefore, this study aims to produce DEM and orthoimage by using the stereo images of KOMPSAT-2, and to explore the applicability of geo-spatial information with KOMPSAT -2. Orientation interpretations were essential for the production of DEM and orthoimage using KOMPSAT-2 images. In the study, they are performed by utilizing both RPC and GCP. In this study, the orientation interpretations are followed by the generation of DEM and orthoimage, and the analysis of their accuracy based on a 1:5,000 digital map. The accuracy analysis of DEM is performed and the results indicate that their altitudes are, in general, higher than those obtained from the digital map. The altitude discrepancies on plains, hills and mountains are calculated as 1.8m, 7.2m, and 11.9m, respectively. In this study, the mean differences between horizontal position between the orthoimage data and the digital map data are found to be ${\pm}3.081m$, which is in the range of ${\pm}3.5m$, within the permitted limit of a 1:5,000 digital map. KOMPSAT-2 images are used to produce DEM and orthoimage in this research. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.

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Pansharpening Method for KOMPSAT-2/3 High-Spatial Resolution Satellite Image (아리랑 2/3호 고해상도 위성영상에 적합한 융합기법)

  • Oh, Kwan-Young;Jung, Hyung-Sup;Jeong, Nam-Ki
    • Korean Journal of Remote Sensing
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    • v.31 no.2
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    • pp.161-170
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    • 2015
  • This paper presents an efficient image fusion method to be appropriate for the KOMPSAT-2 and 3 satellites. The proposed method is based on the well-established component substitution (CS) approach. The proposed method is divided into two parts: 1) The first step is to create a intensity image by the weighted-averaging operation of a multi-spectral (MS) image and 2) the second step is to produce an optimal high-frequency image using the statistical properties of the original MS and panchromatic (PAN) images. The performance of the proposed method is evaluated in both quantitative and visual analysis. Quantitative assessments are performed by using the relative global dimensional synthesis error (Spatial and Spectral ERGAS), the image quality index (Q4), and the spectral angle mapper index (SAM). The qualitative and quantitative assessment results show that the fusion performance of the proposed method is improved in both the spectral and spatial qualities when it is compared with previous CS-based fusion methods.