• Title/Summary/Keyword: Kompsat imagery

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Estimating Carbon Sequestration in Forest using KOMPSAT-2 Imagery (KOMPSAT-2 영상을 이용한 산림의 이산화탄소 흡수량 추정)

  • Kim, So-ra;Lee, Woo-kyun;Kwak, Han-bin;Choi, Sung-ho
    • Journal of Korean Society of Forest Science
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    • v.98 no.3
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    • pp.324-330
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    • 2009
  • The objective of this study is to estimate the carbon sequestration in forest stands using KOMPSAT-2 imagery. For estimating the amount of carbon sequestration, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated by the crown width extracted from KOMPSAT-2 imagery. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the Intergovernmental Panel on Climate Change (IPCC) guideline, was used to convert the stand biomass into the amount of carbon sequestration. Thereafter, the KOMPSAT-2 imagery was classified with the segment based classification (SBC) method in order to quantify carbon sequestration by tree species. This approach, estimating the amount of carbon sequestration for certain species in stand, can be available to extend plot-based carbon sequestration to stand-based carbon sequestration.

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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Definition and Generation of Level 0 Product for KOMPSAT-2

  • Shin, Ji-Hyeon;Kim, Moon-Gyu;Park, Sung-Og
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.810-814
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    • 2002
  • According to the image level definition for KOMPSAT-2 in KOMPSAT-2 Ground Station Specification, the level 0 is frame formatted, unprocessed data at full resolution; any and all communications artifacts (e.g., synchronization frames, communications headers) removed. The level 0 is used for two purposes: 1) exchange of imagery between image receiving & processing element (IRPE), and 2) image transfer from the Receiving & Archiving Subsystem to Search & Processing Subsystem. On-board processing of imagery data of KOMPSAT-2 includes JPEG-like compression and encryption besides conventional CCSDS packetization. The encryption is used to secure imagery data from any intervention during downlink and compression allows real-time downlink of image data reducing data rate produced from the camera. While developing ground receiving system for KOMPSAT-2, it was necessarily to define level 0 products. In this paper, we will suggest level 0 product definition for KOMPSAT-2 and explain reasons of the decisions made. The key factor used while defining the level 0 products is the efficiency of whole ground receiving system. The latter half of the paper will explain the implementation of software that generates level 0 products. The necessary steps to produce level 0 products will be explained, and the performance achieved will be presented.

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Comparison of Orbit-attitude Model between Spot and Kompsat-2 Imagery (Spot 영상과 Kompsat-2 영상에서의 궤도 자세각 모델의 성능 비교)

  • Jeong, Jae-Hoon;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.25 no.2
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    • pp.133-143
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    • 2009
  • This paper describes differences of performance when the orbit attitude model is applied to the respective images obtained from two different types of satellite. The one is Spot that rotates its pointing mirror and the other is Kompsat-2 that rotates its whole body when they obtain imagery for target. Our research scope is limited to the orbit-attitude model only as its good performance was proved in prior investigation. Model performances between two images were compared with sensor model accuracy and 3D coordinates calculation. The results show performances of the orbit-attitude model for each image type were different. For Spot imagery, the model required attitude angle to be included as adjustment parameters. For Kompsat-2 imagery, the model required high-order parameter for adjustment. This implies that satellite sensor model may be applied differently in accordance with platform's attitude control scheme and accuracy. Understanding of this information can be a base for improvement and development of model and application for new satellite images.

Applicability for Detecting Trails by Using KOMPSAT Imagery (등산로 탐지를 위한 KOMPSAT 영상의 활용가능성)

  • Bae, Jinsu;Yim, Jongseo;Shin, Young Ho
    • Journal of the Korean Geographical Society
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    • v.50 no.6
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    • pp.607-619
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    • 2015
  • It is important to detect trails accurately for finding a proper management. We examined the applicability of KOMPSAT imagery to detect trails and found that it could be an efficient alternative to track trails correctly. We selected K2 and K3 imagery with different spatial resolution. Then, we processed each imagery to get NDVI, SAVI, and SC data. And then, we identified trails by object-based analysis and network analysis. Finally, we evaluated the potential trails with F-measurement and Jaccard coefficient which are based on correctness and completeness. The results show that the applicability is quite different in each case. Among them, especially the SC data with K3 shows the most highest value; correctness of detecting legal trails is 0.44 and completeness of that is 0.54. F-measurement and Jaccard coefficient are 0.49 and 0.32. In general, although there is a limit in detecting trails by using only KOMPSAT imagery, the usefulness of KOMPSAT imagery can be a higher considering its cost efficiency and availability of acquiring periodic data.

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A Method to Improve Matching Success Rate between KOMPSAT-3A Imagery and Aerial Ortho-Images (KOMPSAT-3A 영상과 항공정사영상의 영상정합 성공률 향상 방법)

  • Shin, Jung-Il;Yoon, Wan-Sang;Park, Hyeong-Jun;Oh, Kwan-Young;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.893-903
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    • 2018
  • The necessity of automatic precise georeferencing is increasing with the increase applications of high-resolution satellite imagery. One of the methods for collecting ground control points (GCPs) for precise georeferencing is to use chip images obtained by extracting a subset of an image map such as an ortho-aerial image, and can be automated using an image matching technique. In this case, the importance of the image matching success rate is increased due to the limitation of the number of the chip images for the known reference points such as the unified control point. This study aims to propose a method to improve the success rate of image matching between KOMPSAT-3A images and GCP chip images from aerial ortho-images. We performed the image matching with 7 cases of band pair using KOMPSAT-3A panchromatic (PAN), multispectral (MS), pansharpened (PS) imagery and GCP chip images, then compared matching success rates. As a result, about 10-30% of success rate is increased to about 40-50% when using PS imagery by using PAN and MS imagery. Therefore, using PS imagery for image matching of KOMPSAT-3A images and aerial ortho-images would be helpful to improve the matching success rate.

Analysis of Geolocation Accuracy of KOMPSAT-3 Imagery (KOMPSAT-3 영상의 기하정확도 분석)

  • Jeong, Jaehoon;Kim, Jaein;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.37-45
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    • 2014
  • This paper reports the geolocation accuracy of KOMPSAT-3 imagery. KOMPSAT-3 was launched successfully on May 18, 2012 and has been released last March. In this paper, we have checked the geolocation accuracy of initial sensor model, precise sensor model and stereo-and multi-image model using four KOMPSAT-3 images covering the same area. The KOMPSAT-3 images without GCPs provided the geolocation accuracy of about 30m and the geocorrected KOMPSAT-3 images provided the geolocation accuracy of about 1m or less. KOMPSAT-3 stereo- and multi-images models yield threedimensional points with sub-meter accuracy in horizontal and vertical direction. Overall, KOMPSAT-3 showed much improved performance in terms of the geolocation accuracy over KOMPSAT-2. KOMPSAT-3 is expected to be able to replace foreign satellite data with sub-meter accuracy level for achieving accurate geometric information.

Building Detection Using Shadow Information in KOMPSAT Satellite Imagery (그림자 정보를 이용한 KOMPSAT 위성영상에서의 건물 검출)

  • 예철수;이쾌희
    • Korean Journal of Remote Sensing
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    • v.16 no.3
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    • pp.235-242
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    • 2000
  • This paper presents a method to detect buildings using shadow information in satellite imagery. We classify image into three categories of building region, shadow region and background region to find buildings with consistent intensity. After the removal of noises in building regions and shadow regions, buildings adjacent to shadow regions are detected using the constraint of building and shadow sizes. The algorithm has been applied to KOMPSAT and SPOT images and the result showed buildings are efficiently detected.

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.

Carbon Storage Estimation of Urban Area Using KOMPSAT-2 Imagery (KOMPSAT-2호 위성영상을 이용한 도시지역 탄소저장량 추정)

  • Kim, Ki-Tae;Cho, Jin-Woo;Yoo, Hwan-Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.2
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    • pp.49-54
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    • 2011
  • Recently Korean government announced the vision for low-carbon green growth. Quantifying of the carbon storage, distribution, and change of urban trees is vital to understanding the role of vegetation in the urban environment. In the city planning the carbon storage estimation has become an important factor. In this paper, KOMPSAT-2 satellite imagery was used to develop a method to predict the urban forest carbon storage from the Normalized Difference Vegetation Index (NDVI) computed from a time sequence image data. The total carbon storage change by trees in the 6 administrative zonings of Jinju was estimated using the image data in 2007 and 2009. Therefore the paper presents a method based on the satellite images, which can estimate the spread of urban tree and carbon storage variation using KOMPSAT-2.