• Title/Summary/Keyword: operational remote sensing

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대전광역시 도시화 패턴 분석을 위한 원격탐사 자료 처리 및 다중시기 토지이용 현황도 제작

  • Kim, Youn-Soo;Lee, Kwang-Jae;Jeon, Gap-Ho
    • Aerospace Engineering and Technology
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    • v.3 no.2
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    • pp.141-148
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    • 2004
  • The importance of satellite data for numerous applications is stressed by the fact that many countries have given the development of space technologies very high priority. Among these, Korea has established a medium-term space development strategy to promote space development both on a scientific as well as commercial level. As part of this strategy, the first operational earth-observation, multi-purpose satellite(KOMPSAT-1) was launched successfully in December, 1999. The Electro-Optical Camera (EOC) on board of KOMPSAT-1 supplies panchromatic images with a spatial resolution of 6.6m Until April, 2004, it collected over 150.000 images of the Korean Peninsula and the rest of the world. This paper examines the use of remote sensing data to analyze urban growth in the city of Daejeon from 1960 to 2003. By using visual interpretation, land use maps are created.

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Introduction to Image Pro-processing Subsystem of Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI) 전처리시스템)

  • Seo, Seok-Bae;Lim, Hyun-Su;Ahn, Sang-Il
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.167-173
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    • 2010
  • This paper introduces Geostationary Ocean Color Imager, IMage Pre-processing Subsystem (GOCI IMPS) of Communication, Ocean, and Meteorological Satellite (COMS), and describes its functions, development states, and operational concepts. The primary and backup systems of GOCI IMPS have been installed in Korea Ocean Satellite Center (KOSC) and Satellite Operation Center (SOC) and the system are the prelaunch test phase after completing all required tests. It is expected that the GOCI data observed continuously over the Korea Peninsular in the geostationary orbit will be usefully utilized in marine environment research fields such as sea surface temperature changes or marine ecosystems.

Development of Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI)의 개발)

  • Cho, Seong-Ick;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Kang, Gm-Sil;Youn, Heong-Sik
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.157-165
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    • 2010
  • In June 2010, Geostationary Ocean Color Imager (GOCI), the world's first ocean color observation satellite will be launched. GOCI is planned for use in real-time monitoring of the ocean environment around Korean Peninsula by daily analysis of ocean environment measurements of chlorophyll concentration, dissolved organic matter, and suspended sediments taken eight times per day for seven years. GOCI primary data will support a fishery information service and red tide forecasting, and ocean climate change research. In this paper, the development background of GOCI, user requirements, GOCI architecture, and the GOCI on-orbit operational concept are explained.

A Study on Comparison of Satellite-Tracked Drifter Temperature with Satellite-Derived Sea Surface Temperature of NOAA/NESDIS

  • Park, Kyung-Ae;Chung, Joug-Yul;Kim, Kuh;Choi, Byung-Ho
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.83-107
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    • 1994
  • Sea surface temperatures (SSTs) estimated by using the operational SST derivation equations of NOAA/NESDIS were compared with satellite-tracked drifter temperatures. As a result of eliminating cloud-filled or contaminated pixels through several cloud tests, 69 matchup points between the drifter temperatures and the SSTs estimated with NOAA satellite 9, 10. 11 and 12 data from August, 1993 to July, 1994 were collected. Multi-channel sea surface temperature(MCSST) using a split window technique showed an approximately $1.0{\circ}C$ rms error as compared with the drifting buoy temperatures for 69 coincidences. Accuracies for satellete-derived sea surface temperatures were evaluated for only NOAA-11 AVHRR data which had relatively large matchups of 35points as compared with other satellites. For the comparison of the oberved temperatures with the calculated SSTs, linear MCSST and nonlinear cross product sea surface temperature(CPSST) algorithms by the split, the dual and the triple window technique were used respectively. As a result, the split window CPSSTs showed the smallest rms error of $0.72{\circ}C$. Defferences between the split window SSTs and the drifter temperatures appeared th have a linear tendency against the drifter temperatures and also against the differences between AVHRR channel 4 and 5 brighness temperatures. This indicates some possibilities that satelite-derived SSTs operationally calculated from the NOAA/NESDIS equation in the seas around Korea have been underestimated as compared with actural SSTs in case sea water temperature is relatively low or the atmosphere over the sea surface is very dry like in winter, while overstimated in case of high temperature or very moist atmospheric equations based on local sea measurements around Korea instead of global measurements should be derived.

Aerosol Optical Thickness Retrieval Using a Small Satellite

  • Wong, Man Sing;Lee, Kwon-Ho;Nichol, Janet;Kim, Young J.
    • Korean Journal of Remote Sensing
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    • v.26 no.6
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    • pp.605-615
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    • 2010
  • This study demonstrates the feasibility of small satellite, namely PROBA platform with the compact high resolution imaging spectrometer (CHRIS), for aerosol retrieval in Hong Kong. The rationale of our technique is to estimate the aerosol reflectances by decomposing the Top of Atmosphere (TOA) reflectances from surface reflectance and Rayleigh path reflectances. For the determination of surface reflectances, the modified Minimum Reflectance Technique (MRT) is used on three winter ortho-rectified CHRIS images: Dec-18-2005, Feb-07-2006, Nov-09-2006. For validation purpose, MRT image was compared with ground based multispectral radiometer measurements and atmospherically corrected Landsat image. Results show good agreements between CHRIS-derived surface reflectance and both by ground measurement data as well as by Landsat image (r>0.84). The Root-Mean-Square Errors (RMSE) at 485, 551 and 660nm are 0.99%, 1.19%, and 1.53%, respectively. For aerosol retrieval, Look Up Tables (LUT) which are aerosol reflectances as a function of various AOT values were calculated by SBDART code with AERONET inversion products. The CHRIS derived Aerosol Optical Thickness (AOT) images were then validated with AERONET sunphotometer measurements and the differences are 0.05~0.11 (error=10~18%) at 440nm wavelength. The errors are relatively small compared to those from the operational moderate resolution imaging spectroradiometer (MODIS) Deep Blue algorithm (within 30%) and MODIS ocean algorithm (within 20%).

Development of Day Fog Detection Algorithm Based on the Optical and Textural Characteristics Using Himawari-8 Data

  • Han, Ji-Hye;Suh, Myoung-Seok;Kim, So-Hyeong
    • Korean Journal of Remote Sensing
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    • v.35 no.1
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    • pp.117-136
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    • 2019
  • In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).

Analysis of Offshore Aquaculture Detection Techniques Using Synthetic Aperture Radar Images (레이더 영상을 이용한 연안 양식장 탐지 기법 분석)

  • Do-Hyun Hwang;Hahn Chul Jung
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1401-1411
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    • 2023
  • In the face of escalating utilization of the marine spatial domain, conflicts have emerged among stakeholders, necessitating effective management strategies beyond conventional government permits and regulations. Particularly within the domain of aquaculture, operational oversight relies on a localized licensing system, posing challenges in accurately assessing the prevailing circumstances. This research employs synthetic aperture radar (SAR) imagery as a tool to monitor coastal aquaculture fish farms, aimed at enhancing insights into management protocols. Leveraging Sentinel-1A imagery and time series SAR data integration, a superimposition technique is utilized, facilitating noise reduction while retaining crucial information regarding smaller-scale facilities, such as fish farms. Through analysis of VH polarization data, a detection overall accuracy of approximately 88% for coastal fish farms was achieved. The findings of this study offer potential applications in the continuous monitoring of aquaculture farms in correspondence with seasonal variations in aquaculture yields, thereby proposing frameworks for the establishment of effective management cycles for marine space utilization.

Camera Controller in MSC(Multi-Spectral Camera)

  • Kim, Young-Sun;Yong, Sang-Soon;Kong, Jong-Pil;Heo, Haeng-Pal;Park, Jong-Euk;Youn, Heong-Sik
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1081-1083
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    • 2003
  • The CC's main objective is to manage and control the various operation of the MSC camera. The CC has capability to control the various camera operation modes such as INIT mode, WAIT mode, STANDBY mode, READY IMAGING, DEFAULT READY IMAGING, IBIT and IMAGING mode as well as to manage the interface of the PMU. This paper also shows not only the design concepts in the both of the hardware and the operational software, but also the implementation results for the various CC functions.

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INVESTIGATION OF CLOUD COVERAGE OVER ASIA WITH NOAA AVHRR TIME SERIES

  • Takeuchit Wataru;Yasuokat Yoshifumi
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.26-29
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    • 2005
  • In order to compute cloud coverage statistics over Asian region, an operational scheme for masking cloud-contaminated pixels in Advanced Very High Resolution Radiometer (AVHRR) daytime data was developed, evaluated and presented. Dynamic thresholding was used with channell, 2 and 3 to automatically create a cloud mask for a single image. Then the IO-day cloud coverage imagery was generated over the whole Asian region along with cloud-free composite imagery. Finally the monthly based statistics were computed based on the derived cloud coverage imagery in terms of land cover and country. As a result, it was found that 20-day is required to acquire the cloud free data over the whole Asia using NOAA AVHRR. The to-day cloud coverage and cloud-free composite imagery derived in this research is available via the web-site http://webpanda.iis.u-tokyo.ac.jp/CloudCover/.

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GOES-9 Raw Data Acquisition & Image Extraction

  • Kang C. H.;Park D. J.;Koo I. H.;Ahn S. I.;Kim E. K.
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.582-585
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    • 2005
  • The Geostationary Operational Environmental Satellite (GOES) 9, which is currently located at 155°E geostationary orbits, has transmitted earth observation data acquired by imager to CDA at NOAA. After the acquisition on ground, observation data are corrected on ground and re-transmitted to GOES-9 for the dissemination to users. In this paper, the procedure and result from raw data acquisition and pre-processing for earth observation imagery retrieval from GOES-9 Raw data acquired in Korea at May 2005 are introduced.

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