• Title/Summary/Keyword: satellite data

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INTRODUCTION OF THE SIMC PROJECT

  • Chae, Gee-Ju;Cho, Seong-Ik;Park, Jong-Hyun;Jo, Kwan-Bok
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.356-359
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    • 2006
  • The high prices and lack of information for satellite images prevent researchers from studying remote sensing and most non-professional people can't have the simple and easy solutions for the manipulation of satellite images. 'Satellite Imagery Information Management Center'(SIMC) project which is promoted by ETRI (Electronics and Telecommunications Research Institute) from 2002 to 2005 in Korea have the purpose to provide the satellite images freely to the public domain and the solutions for the above mentioned problems. Our project have the following five systems; Data Acquisition System, Data Preservation System, Integrated Solution System, Technology Development System, Operation Plan System. Data Acquisition System collects the satellite images such as LANDSAT, IKONOS, etc. Data Preservation System consists of database which registers the diverse satellite images. Integrated Solution System gives the user of public domain for the web service which search, order and transfer the satellite images. Technology Development System has the many processing technologies for the satellite images. Finally, the Operation Plan system has the role to plan the future of our SIMC project. In this paper, we will give the result of SIMC Project for each five systems during the fast four years from 2002 to 2005.

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CONSTRUCTION OF AMSR-E LEVEL-1 PROCESSOR AND RETRIEVAL OF OCEAN PARAMETERS

  • Kim, Seung-Bum;Shin, Ji-Hyun;Im, Yong-Jo;Shin, Ji-Hyun;Park, Sung-Oak;Park, Seung-Hwan;Lee, Jong-Ju;Kim, Moon-Gyu;Park, Hae-Suk;Kim, Keum-Ran
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.828-830
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    • 2003
  • We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced, to our knowledge, this is the first attempt to process about 10-minute long direct-broadcast data. We modified the processor designed for a granule to process the direct-broadcast data. After the modification, our brightness temperature product differs from the reference by 0.2K rms. Sea surface temperatures are retrieved to demonstrate the utility of AMSR-E.

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Dynamic Caching Routing Strategy for LEO Satellite Nodes Based on Gradient Boosting Regression Tree

  • Yang Yang;Shengbo Hu;Guiju Lu
    • Journal of Information Processing Systems
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    • v.20 no.1
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    • pp.131-147
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    • 2024
  • A routing strategy based on traffic prediction and dynamic cache allocation for satellite nodes is proposed to address the issues of high propagation delay and overall delay of inter-satellite and satellite-to-ground links in low Earth orbit (LEO) satellite systems. The spatial and temporal correlations of satellite network traffic were analyzed, and the relevant traffic through the target satellite was extracted as raw input for traffic prediction. An improved gradient boosting regression tree algorithm was used for traffic prediction. Based on the traffic prediction results, a dynamic cache allocation routing strategy is proposed. The satellite nodes periodically monitor the traffic load on inter-satellite links (ISLs) and dynamically allocate cache resources for each ISL with neighboring nodes. Simulation results demonstrate that the proposed routing strategy effectively reduces packet loss rate and average end-to-end delay and improves the distribution of services across the entire network.

Management Information System of the Nanji Islands National Marine Reserve, China

  • Qingmei, XIAO;Huaguo, ZHANG;Changbao, ZHOU;Weigen, HUANG;Dongling, LI;Junhua, Ten
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.298-300
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    • 2003
  • A management information system of the Nanji Islands National Marine Reserve is designed and constructed based on method of integration of remote sensing and geographic information system (GIS). The system consists of two sub-systems, dynamic monitoring information system and general database system. The former is used for storage and manage fundamental geographical data (topographical and bathymetric map), satellite remote sensing data (IKONOS, SPOT, IRS, NOAA and SeaWiFS etc.) and multimedia data. The latter is used for storage and manage resource data (shellfish and alga etc.), environmental data (meteorological and hydrologic) and in situ data. As part of electronic government, this system will be submitted to local government for monitoring, management and decision.

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Evaluation performance of machine learning in merging multiple satellite-based precipitation with gauge observation data

  • Nhuyen, Giang V.;Le, Xuan-hien;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.143-143
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    • 2022
  • Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

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Development of Image Processing Software for Satellite Data

  • Chi, Kwang-Hoon;Suh, Jae-Young;Han, Jong-Kyu
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.361-369
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    • 1998
  • Recently, the improvement of on-board satellite sensors covering hyperspectral image sensors, high spatial resolution sensors provide data on earth in diverse aspect. The application field relating remotely sensed data also varies depending on what type of job one wants. The various resolution of sensors from low to extremely high is also available on the market with a user defined specific location. The expense to purchase remote sensed data is going down compare to the cost it need past few years ago in terms of research or private use. Now, the satellite remote sensed data is used on the field of forecasting, forestry, agriculture, urban reconstruction, geology, or other research field in order to extract meaningful information by applying special techniques of image processing. There are many image processing packages available worldwide and one common aspect is that they are expensive. There need to be a advanced satellite data processing package for people who can not afford commercial packages to apply special remote sensing techniques on their data and produce valued-added product. The study was carried out with the purpose of developing a special satellite data processing package which covers almost every satellite produced data with normal image processing functions and also special functions needed on specific research field with friendly graphical user interface (GUI). And for the people with any background of remote sensing with windows platform.

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Particulate Distribution Map of Tidal Flat using Unsupervised Classification of Multi-Temporary Satellite Data (다중시기 위성영상의 무감독분류에 의한 갯벌의 입자 분포도)

  • 정종철
    • Korean Journal of Remote Sensing
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    • v.18 no.2
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    • pp.71-79
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    • 2002
  • This research presents particulate distribution map of tidal flats of Hampyung bay using reflectance which extracted from satellite data and field survey data during same periods. The spectrum of particulate composition obtained from Landsat TM data was analysed and 7 scenes of satellite image were classified with ISODATA and K-MEANS methods. The results of unsupervised classification were estimated with in-situ data. The classification accuracy of ISODATA and K-MAMS methods were 84.3% and 85.7%. For validation of classified results of multi-temporal satellite images, TM image of May 1999(reference data), which was classified with field survey data was compared with classified results of multi-temporary satellite data.

COMS System Bus Design and Analysis using MIL-STD-1553B (MIL-STD-1553B 버스를 이용한 통신해양기상위성의 시스템 버스 설계 및 분석)

  • Cho, Young-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.7
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    • pp.1285-1289
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    • 2008
  • In this paper, we design COMS system bus that the 1553 Data Bus is able to link all the units of the satellite managed by the SCU using one Prime Data Bus and on Redundant Data Bus. Also we analyze MIL-STD-1553B bus load and relevant exchange memory budgets in system bus of the COMS satellite. This data is used in the satellite mission and software design by system engineer.

Accuracy evaluation of near-surface air temperature from ERA-Interim reanalysis and satellite-based data according to elevation

  • Ryu, Jae-Hyun;Han, Kyung-Soo;Park, Eun-Bin
    • Korean Journal of Remote Sensing
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    • v.29 no.6
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    • pp.595-600
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    • 2013
  • In order to spatially interpolate the near-surface temperature (Ta) values, satellite and reanalysis methods were used from previous studies. Accuracy of reanalysis Ta was generally better than that of satellite-based Ta, but spatial resolution of reanalysis Ta was large to use at local scale studies. Our purpose is to evaluate accuracy of reanalysis Ta and satellite-based Ta according to elevation from April 2011 to March 2012 in Northeast Asia that includes various topographic features. In this study, we used reanalysis data that is ERA-Interim produced by European Centre for Medium-Range Weather Forecasts (ECMWF), and estimated satellite-based Ta using Digital Elevation Meter (DEM), Normalized Difference Vegetation Index (NDVI), difference between brightness temperature of $11{\mu}m$ and $12{\mu}m$, and Land Surface Temperature (LST) data. The DEM data was used as auxiliary data, and observed Ta at 470 meteorological stations was used in order to evaluate accuracy. We confirmed that the accuracy of satellite-based Ta was less accurate than that of ERA-Interim Ta for total data. Results of analyzing according to elevation that was divided nine cases, ERA-Interim Ta showed higher accurate than satellite-based Ta at the low elevation (less than 500 m). However, satellite-based Ta was more accurate than ERA-Interim Ta at the higher elevation from 500 to 3500 m. Also, the width of the upper and lower quartile appeared largely from 2500 to 3500 m. It is clear from these results that ERA-Interim Ta do not consider elevation because of large spatial resolution. Therefore, satellite-based Ta was more effective than ERA-Interim Ta in the regions that is range from 500 m to 3500 m, and satellite-based Ta was recommended at a region of above 2500 m.

SBAS Non-Standard Data Transmission Method for Korea Augmentation Satellite System Applications (KASS 활용을 위한 위성기반 보강항법시스템(SBAS) 비규격 데이터 전송 방법 연구)

  • Park, Jae-ik;Lee, Eunsung;Heo, Moon-beom;Nam, Gi-wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.12
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    • pp.1861-1867
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    • 2016
  • Korea augmentation satellite system (KASS), which is a satellite-based augmentation system tailored for Korea, was launched for development in 2014. SBAS is a standard for aviation but it can also be utilized in non-aviation applications. The type and content of transmitted in SBAS data format are restricted. In order to utilize SBAS in fields that require the precision within centimeters, additional information has to be transmitted. It is important that data transmitted in nonstandard SBAS data not affect any operation of SBAS equipment. In this paper, we propose a non-standard SBAS data transmission method applicable to non-aviation applications that does not affect aviation SBAS receivers.