• Title/Summary/Keyword: 우주 탐사

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Development of Intelligent Internet Shopping Mall Supporting Tool Based on Software Agents and Knowledge Discovery Technology (소프트웨어 에이전트 및 지식탐사기술 기반 지능형 인터넷 쇼핑몰 지원도구의 개발)

  • 김재경;김우주;조윤호;김제란
    • Journal of Intelligence and Information Systems
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    • v.7 no.2
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    • pp.153-177
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    • 2001
  • Nowadays, product recommendation is one of the important issues regarding both CRM and Internet shopping mall. Generally, a recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly and thereby automatic recommendation methodologies have got great attentions. But the researches and commercial tools for product recommendation so far, still have many aspects that merit further considerations. To supplement those aspects, we devise a recommendation methodology by which we can get further recommendation effectiveness when applied to Internet shopping mall. The suggested methodology is based on web log information, product taxonomy, association rule mining, and decision tree learning. To implement this we also design and intelligent Internet shopping mall support system based on agent technology and develop it as a prototype system. We applied this methodology and the prototype system to a leading Korean Internet shopping mall and provide some experimental results. Through the experiment, we found that the suggested methodology can perform recommendation tasks both effectively and efficiently in real world problems. Its systematic validity issues are also discussed.

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A VELOCITY STRUCTURE ANALYSIS OF GIANT MOLECULAR CLOUD ASSOCIATED WITH HII REGION S152 (HII 영역 S152에 접해 있는 거대 분자운의 속도 구조 분석)

  • Choi, Woo-Yeol;Min, Y.C.;Lee, Yeong-Ung;Park, Myeong-Gu
    • Journal of Astronomy and Space Sciences
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    • v.22 no.2
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    • pp.125-138
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    • 2005
  • S152 is a small bright emission nebula located in the Perseus arm. Its optical diameter corresponds to 1.5 pc for an adopted distance 3.5 kpc. However, S152 is a part of a giant molecular cloud complex, which consists of several dense cores, containing active star-forming sites, and well aligned arm-like features. We analyzed the FCRAO $^{12}CO(J=\;1{\to}0)$ Outer Galaxy Survey data in this region to study the kinematical structure of this region, which resembles a big "scorpion". We found that there exist three different velocity components, about -54.5, -50.4, -48.8 km $s^{-1}$, depending on the position of the "scorpion". There also exist velocity gradients of 0.21 km $s^{-1}pc^{-1}$ and 0.16 km $s^{-1}pc^{-1}$ through the whole extent of the "scorpion". Interestingly, these two velocity gradients show an opposite direction with each other. It is likely that the velocity structure of this region may result from the mergence of different gas clouds, and the interaction with the SNR 109.1-1.0 occurred later, mostly at the region around the "head of the scorpion" only.

Estimation of stream flow discharge using the satellite synthetic aperture radar images at the mid to small size streams (합성개구레이더 인공위성 영상을 활용한 중소규모 하천에서의 유량 추정)

  • Seo, Minji;Kim, Dongkyun;Ahmad, Waqas;Cha, Jun-Ho
    • Journal of Korea Water Resources Association
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    • v.51 no.12
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    • pp.1181-1194
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    • 2018
  • This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

Accuracy Assessment of the Satellite-based IMERG's Monthly Rainfall Data in the Inland Region of Korea (한반도 육상지역에서의 위성기반 IMERG 월 강수 관측 자료의 정확도 평가)

  • Ryu, Sumin;Hong, Sungwook
    • Journal of the Korean earth science society
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    • v.39 no.6
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    • pp.533-544
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    • 2018
  • Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

Vacuum Pressure Effect on Thermal Conductivity of KLS-1 (진공압에 따른 한국형 인공월면토(KLS-1)의 열전도도 평가)

  • Jin, Hyunwoo;Lee, Jangguen;Ryu, Byung Hyun;Shin, Hyu-Soung;Chung, Taeil
    • Journal of the Korean Geotechnical Society
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    • v.37 no.8
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    • pp.51-58
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    • 2021
  • South Korea, as the 10th country to join the Artemis program led by NASA, is actively supporting various researches related to the lunar exploration. In particular, the utilization of water as a resource in the Moon has been focused since it was discovered that ice exists at the lunar pole as a form of frozen soil. Information on the thermal conductivity of lunar regolith can be used to estimate the existence for ice water extraction by thermal mining. In this study, the vacuum pressure effect on thermal conductivity of KLS-1 was investigated with a DTVC (Dusty Thermal Vacuum Chamber). The reliability of KLS-1 was reconfirmed through comparison with thermal conductivity of known standard lunar regolith simulants such as JSC-1A. An empirical equation to assess thermal conductivity considering dry unit weight and vacuum pressure was proposed. The results from this study can be implemented to simulate lunar cryogenic environment using the DTVC.

ALGORITHMS FOR MOVING OBJECT DETECTION: YSTAR-NEOPAT SURVEY PROGRAM (이동천체 후보 검출을 위한 알고리즘 개발: YSTAR-NEOPAT 탐사프로그램)

  • Bae, Young-Ho;Byun, Yong-Ik;Kang, Yong-Woo;Park, Sun-Youp;Oh, Se-Heon;Yu, Seoung-Yeol;Han, Won-Young;Yim, Hong-Suh;Moon, Hong-Kyu
    • Journal of Astronomy and Space Sciences
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    • v.22 no.4
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    • pp.393-408
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    • 2005
  • We developed and compared two automatic algorithms for moving object detections in the YSTAR-NEOPAT sky survey program. One method, called starlist comparison method, is to identify moving object candidates by comparing the photometry data tables from successive images. Another method, called image subtraction method, is to identify the candidates by subtracting one image from another which isolates sources moving against background stars. The efficiency and accuracy of these algorithms have been tested using actual survey data from the YSTAR-NEOPAT telescope system. For the detected candidates, we performed eyeball inspection of animated images to confirm validity of asteroid detections. Main conclusions include followings. First, the optical distortion in the YSTAR-NEOPAT wide-field images can be properly corrected by comparison with USNO-B1.0 catalog and the astrometric accuracy can be preserved at around 1.5 arcsec. Secondly, image subtraction provides more robust and accurate detection of moving objects. For two different thresholds of 2.0 and $4.0\sigma$, image subtraction method uncovered 34 and 12 candidates and most of them are confirmed to be real. Starlist comparison method detected many more candidates, 60 and 6 for each threshold level, but nearly half of them turned out to be false detections.

A Comparative Study on the Possibility of Land Cover Classification of the Mosaic Images on the Korean Peninsula (한반도 모자이크 영상의 토지피복분류 활용 가능성 탐색을 위한 비교 연구)

  • Moon, Jiyoon;Lee, Kwang Jae
    • Korean Journal of Remote Sensing
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    • v.35 no.6_4
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    • pp.1319-1326
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    • 2019
  • The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

The Estimation of Gross Primary Productivity over North Korea Using MODIS FPAR and WRF Meteorological Data (MODIS 광합성유효복사흡수율과 WRF 기상자료를 이용한 북한지역의 총일차생산성 추정)

  • Do, Na-Young;Kang, Sin-Kyu;Myeong, Soo-Jeong;Chun, Tae-Hun;Lee, Ji-Hye;Lee, Chong-Bum
    • Korean Journal of Remote Sensing
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    • v.28 no.2
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    • pp.215-226
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    • 2012
  • NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution ($1.25^{\circ}{\times}1^{\circ}$) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km${\times}$3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. The improved GPP was utilized to investigate characteristics of GPP interannual variation and spatial patterns from 2000 to 2008. The GPP varied from 645 to 863 $gC\;m^{-2}\;y^{-1}$ in 2000 and 2008, respectively. Mixed forest showed the highest GPP (1,076 $gC\;m^{-2}\;y^{-1}$). Compared to NASA GPP (790 $gC\;m^{-2}\;y^{-1}$);FPAR enhancement increased GPP (861) but utilization of WRF data decreased GPP (710). Enhancements of both FPAR and meteorological input resulted in GPP increase (809) and the improvement was the greatest for mixed forest regions (+10.2%). The improved GPP showed better spatial heterogeneity reflecting local topography due to high resolution WRF data. It is remarkable that the improved and NASA GPPs showed distinctly different interannual variations with each other. Our study indicates improvement of NASA GPP by enhancing input variables is necessary to monitor region-scale terrestrial vegetation productivity.

Characteristic Response of the OSMI Bands to Estimate Chlorophyll $\alpha$ (클로로필 $\alpha$ 추정시 OSMI 밴드의 광학 반응 특성)

  • 서영상;이나경;장이현;황재동;유신재;임효숙
    • Korean Journal of Remote Sensing
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    • v.18 no.4
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    • pp.187-199
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    • 2002
  • Correlation between chlorophyll a in the East China Sea and spectral bands (412, 443, 490, (510), 555, (676, 765)nm) of Ocean Scanning Multi-Spectral Imager (OSMI) including the profile multi-spectral radiometer (PRR-800) was studied. The values of remote sensing reflectance (Rrs) at the bands corresponding to the field chlorophyll $\alpha$ in the East China Sea were much higher than those in clear waters off California, USA. In case of the particle absorptions related to the chlorophyll a concentration at the spectral bands (440, 670nm) were much higher in the East China Sea than the ones in the clean waters off California. The normalized water leaving radiances (nLw) at 412, 443, 490, 555 nm of OSMI and the field chlorophyll a in the East China Sea were correlated each other. According to the results, the relationship between field chlorophyll $\alpha$ and nLw 410 nm in OSMI bands was the lowest, whereas that between field chlorophyll a and nLw 555 nm in the bands was the highest. Reciprocal action between the field chlorophyll a and the band ratio of the OSMI bands (nLw410/nLw555, nLw443/nLw555, nLw490/nLw555) was also studied. Relationship between the chlorophyll $\alpha$ and the band ratio (nLw490/nLw555) was highest in the OSMI bands. Relationship between the chlorophyll $\alpha$ and the ratio (nLw490/nLw555) was higher than one in the nLw410/nLw555. The difference in the estimated chlorophyll $\alpha$ (mg/m$^3$) between OSMI and SeaWiFS (Sea Viewing Wide Field-of-View Sensor) at the special observing stations in the northern eastern sea of Jeju Island in February 25, 2002 was about less than 0.3 mg/m$^3$ within 3 hours. It is suggested that OC2 (ocean color chlorophyll 2 algorithm) be used to get much better estimation of chlorophyll $\alpha$ from OSMI than the ones from the updated algorithms as OC4.

Detection of Forest Fire Damage from Sentinel-1 SAR Data through the Synergistic Use of Principal Component Analysis and K-means Clustering (Sentinel-1 SAR 영상을 이용한 주성분분석 및 K-means Clustering 기반 산불 탐지)

  • Lee, Jaese;Kim, Woohyeok;Im, Jungho;Kwon, Chunguen;Kim, Sungyong
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1373-1387
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    • 2021
  • Forest fire poses a significant threat to the environment and society, affecting carbon cycle and surface energy balance, and resulting in socioeconomic losses. Widely used multi-spectral satellite image-based approaches for burned area detection have a problem in that they do not work under cloudy conditions. Therefore, in this study, Sentinel-1 Synthetic Aperture Radar (SAR) data from Europe Space Agency, which can be collected in all weather conditions, were used to identify forest fire damaged area based on a series of processes including Principal Component Analysis (PCA) and K-means clustering. Four forest fire cases, which occurred in Gangneung·Donghae and Goseong·Sokcho in Gangwon-do of South Korea and two areas in North Korea on April 4, 2019, were examined. The estimated burned areas were evaluated using fire reference data provided by the National Institute of Forest Science (NIFOS) for two forest fire cases in South Korea, and differenced normalized burn ratio (dNBR) for all four cases. The average accuracy using the NIFOS reference data was 86% for the Gangneung·Donghae and Goseong·Sokcho fires. Evaluation using dNBR showed an average accuracy of 84% for all four forest fire cases. It was also confirmed that the stronger the burned intensity, the higher detection the accuracy, and vice versa. Given the advantage of SAR remote sensing, the proposed statistical processing and K-means clustering-based approach can be used to quickly identify forest fire damaged area across the Korean Peninsula, where a cloud cover rate is high and small-scale forest fires frequently occur.