• 제목/요약/키워드: Reference Mapping

검색결과 268건 처리시간 0.024초

RapidEye 위성영상을 이용한 청주시의 불투수면지도 생성기법 (Impervious Surface Mapping of Cheongju by Using RapidEye Satellite Imagery)

  • 박홍련;최재완;최석근
    • 대한공간정보학회지
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    • 제22권1호
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    • pp.71-79
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    • 2014
  • 많은 연구들은 저해상도 위성영상을 이용하여 불투수면을 생성하며, 광역적인 객체 단위의 불투수면을 생성하는 데에 효율적인 성과를 이루지 못하고 있는 실정이다. 본 논문에서는 RapidEye 위성영상을 활용한 객체 기반의 불투수면 생성 기법을 제안하였으며, 이를 실험지역에 적용하고자 하였다. 분광반사율로 변환된 RapidEye 위성영상을 활용하여 추가적인 밴드를 생성하였으며, 훈련자료를 이용하여 그림자 및 수계 클래스를 추출하였다. 해당 클래스를 제외한 나머지 클래스들은 환경부의 중분류 토지피복지도와 분광혼합분석 모델을 활용하여 피복단위의 불투수 비율 영상을 생성하였다. 참조자료와의 정량적 비교평가를 통하여 본 연구에서 적용한 불투수면 생성 방법의 효용성을 검증하였다.

A Bibliometric Approach for Department-Level Disciplinary Analysis and Science Mapping of Research Output Using Multiple Classification Schemes

  • Gautam, Pitambar
    • Journal of Contemporary Eastern Asia
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    • 제18권1호
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    • pp.7-29
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    • 2019
  • This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.

임상용어의 효율적 적용을 위한 참조용어 Subset 에디터의 개발 (A Development of Reference Terminology Subset Editor for effective adaption of Clinical Vocabulary)

  • 조훈;김형회;최병관;최영연;김화선;홍해숙
    • 한국멀티미디어학회논문지
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    • 제11권3호
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    • pp.364-372
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    • 2008
  • 하나의 의학용어체계가 모든 의학 개념을 표현할 수 없으므로 전자의무기록의 각 영역에 적합한 의학용어를 적용하고 용어들을 효과적으로 연계하는 것이 실제 임상에서 매우 유용한 방법이다. 표준용어의 편리하고 효율적인 활용을 위해서는 임상과나 임상의의 사용목적에 적합한 범주를 구분하고, 구분한 범주에 입각하여 사용가능성 높은 용어들을 추출하여 정리한 용어 Subset의 개발이 요구된다. 또한 Subset은 표준용어체계의 변경이나 수정, 사용자의 새로운 요구에 알맞도록 지속적으로 개발과 업그레이드가 가능해야 한다. 본 연구에서는 부산대학교병원 신경외과환자의 퇴원요약지를 대상으로 추출된 주호소, 증상, 진단 및 수술명, 과거 시술명의 추출된 자료를 추출하고 분석하였다. 그리고 subset 데이터베이스를 생성하고 추가되는 용어에 대해서는 임상의가 직접 참조용어와의 매핑을 통해 새로운 데이터베이스를 생성될 수 있도록 Subset 에디터를 개발하였다. 결론적으로 본 연구는 용어체계의 방대함으로 인해 생기는 문제점과 비효율성을 줄일 수 있는 효과적인 관리 방법이 될 것이다.

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Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm

  • Suyon Chang;Kyunghwa Han;Suji Lee;Young Joong Yang;Pan Ki Kim;Byoung Wook Choi;Young Joo Suh
    • Korean Journal of Radiology
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    • 제23권12호
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    • pp.1251-1259
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    • 2022
  • Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

Baseline Refinement for Topographic Phase Estimation using External DEM

  • Lee, Chang-Won;Moon, Wooil-M.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.460-464
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    • 2002
  • Multitemporal interferometric SAR has became an useful geodetic tool for monitoring Earth's surface deformation, generation of precise DEM, and land cover classification even though there still exist certain constraints such as temporal and spatial decorrelation effects, atmospheric artifacts and inaccurate orbit information. The Korea where nearly all areas are heavily vegetated, JERS-1 SAR has advantages in monitoring surface deformations and environmental changes in that it uses 4-times longer wavelength than ERS-l/2 or RADARSAT SAR system. For generating differential SAR interferogram and differential coherence image fer deformation mapping and temporal change detection, respectively, topographic phase removal process is required utilizing a reference inteferogram or external DEM simulation. Because the SAR antenna baseline parameter for JERS-1 is less accurate than those of ERS-l/2, one can not estimate topographic phases from an external DEM and the residual phase appears in differential interferogram. In this paper, we examined topographic phase retrieval method utilizing an external DEM. The baseline refinement is carried out by minimizing the differences between the measured unwrapped phase and the reference points of the DEM.

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Algorithms for Multi-sensor and Multi-primitive Photogrammetric Triangulation

  • Shin, Sung-Woong;Habib, Ayman F.;Ghanma, Mwafag;Kim, Chang-Jae;Kim, Eui-Myoung
    • ETRI Journal
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    • 제29권4호
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    • pp.411-420
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    • 2007
  • The steady evolution of mapping technology is leading to an increasing availability of multi-sensory geo-spatial datasets, such as data acquired by single-head frame cameras, multi-head frame cameras, line cameras, and light detection and ranging systems, at a reasonable cost. The complementary nature of the data collected by these systems makes their integration to obtain a complete description of the object space. However, such integration is only possible after accurate co-registration of the collected data to a common reference frame. The registration can be carried out reliably through a triangulation procedure which considers the characteristics of the involved data. This paper introduces algorithms for a multi-primitive and multi-sensory triangulation environment, which is geared towards taking advantage of the complementary characteristics of spatial data available from the above mentioned sensors. The triangulation procedure ensures the alignment of involved data to a common reference frame. The devised methodologies are tested and proven efficient through experiments using real multi-sensory data.

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THE LAND COVER MAPPING IN NORTH KOREA USING MODIS IMAGE;THE CLASSIFICATION ACCURACY ENHANCEMENT FOR INACCESSIBLE AREA USING GOOGLE EARTH

  • Cha, Su-Young;Park, Chong-Hwa
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.341-344
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    • 2007
  • A major obstacle to classify and validate Land Cover maps is the high cost of generating reference data or multiple thematic maps for subsequent comparative analysis. In case of inaccessible area such as North Korea, the high resolution satellite imagery may be used as in situ data so as to overcome the lack of reliable reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird (0.6m) of North Korea obtained from Google Earth data provided thru internet. Monthly NDVI images of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes; coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water and built-up area. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional in situ data collection on the site where the accessibility is severely limited.

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GIS와 데이터베이스를 이용한 가로수정보 관리프로그램 구축 (Construction of Street Trees Information Management Program Using GIS and Database)

  • 김희년;정성관;박경훈;유주한
    • Current Research on Agriculture and Life Sciences
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    • 제26권
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    • pp.45-54
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    • 2008
  • The purpose of this research is to develope street trees management program for more an effective street trees management. The principal point of this program is to relate spatial data and attribute data that is the main concept in GIS(Geographic Information System). To do this function, MapObjects which is ESRI's mapping and GIS components was used to process spatial data and Access which had been developed by MS was used to manipulate attribute data in this program. Visual Basic also was used to design and develop user interfaces and procedures, relate two sort of data, and lastly complete Application. Relational data model was adopted to design tables and their relation, Antenucci's GIS development model was selected to design and complete this program. The configuration of this application is composed of management data and reference data. The management data includes the location of street tree, a growth condition, a surrounding environment, the characters of tree, an equipments, a management records and etc. The reference data include general information about tree, blight and insects.

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Classification of Imbalanced Data Based on MTS-CBPSO Method: A Case Study of Financial Distress Prediction

  • Gu, Yuping;Cheng, Longsheng;Chang, Zhipeng
    • Journal of Information Processing Systems
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    • 제15권3호
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    • pp.682-693
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    • 2019
  • The traditional classification methods mostly assume that the data for class distribution is balanced, while imbalanced data is widely found in the real world. So it is important to solve the problem of classification with imbalanced data. In Mahalanobis-Taguchi system (MTS) algorithm, data classification model is constructed with the reference space and measurement reference scale which is come from a single normal group, and thus it is suitable to handle the imbalanced data problem. In this paper, an improved method of MTS-CBPSO is constructed by introducing the chaotic mapping and binary particle swarm optimization algorithm instead of orthogonal array and signal-to-noise ratio (SNR) to select the valid variables, in which G-means, F-measure, dimensionality reduction are regarded as the classification optimization target. This proposed method is also applied to the financial distress prediction of Chinese listed companies. Compared with the traditional MTS and the common classification methods such as SVM, C4.5, k-NN, it is showed that the MTS-CBPSO method has better result of prediction accuracy and dimensionality reduction.

Land Cover Classification Map of Northeast Asia Using GOCI Data

  • Son, Sanghun;Kim, Jinsoo
    • 대한원격탐사학회지
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    • 제35권1호
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    • pp.83-92
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    • 2019
  • Land cover (LC) is an important factor in socioeconomic and environmental studies. According to various studies, a number of LC maps, including global land cover (GLC) datasets, are made using polar orbit satellite data. Due to the insufficiencies of reference datasets in Northeast Asia, several LC maps display discrepancies in that region. In this paper, we performed a feasibility assessment of LC mapping using Geostationary Ocean Color Imager (GOCI) data over Northeast Asia. To produce the LC map, the GOCI normalized difference vegetation index (NDVI) was used as an input dataset and a level-2 LC map of South Korea was used as a reference dataset to evaluate the LC map. In this paper, 7 LC types(urban, croplands, forest, grasslands, wetlands, barren, and water) were defined to reflect Northeast Asian LC. The LC map was produced via principal component analysis (PCA) with K-means clustering, and a sensitivity analysis was performed. The overall accuracy was calculated to be 77.94%. Furthermore, to assess the accuracy of the LC map not only in South Korea but also in Northeast Asia, 6 GLC datasets (IGBP, UMD, GLC2000, GlobCover2009, MCD12Q1, GlobeLand30) were used as comparison datasets. The accuracy scores for the 6 GLC datasets were calculated to be 59.41%, 56.82%, 60.97%, 51.71%, 70.24%, and 72.80%, respectively. Therefore, the first attempt to produce the LC map using geostationary satellite data is considered to be acceptable.