• Title/Summary/Keyword: 공간적 세분화

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Land Cover Classification of the Korean Peninsula Using Linear Spectral Mixture Analysis of MODIS Multi-temporal Data (MODIS 다중시기 영상의 선형분광혼합화소분석을 이용한 한반도 토지피복분류도 구축)

  • Jeong, Seung-Gyu;Park, Chong-Hwa;Kim, Sang-Wook
    • Korean Journal of Remote Sensing
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    • v.22 no.6
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    • pp.553-563
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    • 2006
  • This study aims to produce land-cover maps of Korean peninsula using multi-temporal MODIS (Moderate Resolution Imaging Spectroradiometer) imagery. To solve the low spatial resolution of MODIS data and enhance classification accuracy, Linear Spectral Mixture Analysis (LSMA) was employed. LSMA allowed to determine the fraction of each surface type in a pixel and develop vegetation, soil and water fraction images. To eliminate clouds, MVC (Maximum Value Composite) was utilized for vegetation fraction and MinVC (Minimum Value Composite) for soil fraction image respectively. With these images, using ISODATA unsupervised classifier, southern part of Korean peninsula was classified to low and mid level land-cover classes. The results showed that vegetation and soil fraction images reflected phenological characteristics of Korean peninsula. Paddy fields and forest could be easily detected in spring and summer data of the entire peninsula and arable land in North Korea. Secondly, in low level land-cover classification, overall accuracy was 79.94% and Kappa value was 0.70. Classification accuracy of forest (88.12%) and paddy field (85.45%) was higher than that of barren land (60.71%) and grassland (57.14%). In midlevel classification, forest class was sub-divided into deciduous and conifers and field class was sub-divided into paddy and field classes. In mid level, overall accuracy was 82.02% and Kappa value was 0.6986. Classification accuracy of deciduous (86.96%) and paddy (85.38%) were higher than that of conifers (62.50%) and field (77.08%).

The Influence of Self-discrepancy in Virtual and Cross Worlds on Individuals' Activities in Online Communities (가상세계 및 공간간의 자기차이가 온라인 커뮤니티 활동에 미치는 영향에 관한 연구)

  • Lee, Ju-Min;Shin, Kyung-Shik;Suh, A-Young
    • The Journal of Society for e-Business Studies
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    • v.16 no.3
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    • pp.23-45
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    • 2011
  • People could possess different self-identity under virtual world from physical world because of anonymity of the virtual world and this difference could influence their behavior in the virtual world. Based on self-discrepancy theory, this research proposes that continuous use model in self-expression goal. We defined the difference bet ween actual self~identity and ideal self~identity in the virtual world as "self-discrepancy in virtual world", and the difference between actual self-identity in the physical world and actual self-identity in the virtual world as "cross-world self-discrepancy". Before testing hypothesis, we compare the actual self-identity in the online community with the actual self-identity in the physical world, and with ideal self-identity in the virtual world. We derived an index for two different types of self-identity in terms of Personal Self-identity and Social Self-identity through factor analysis. Our results show that online community members have a higher level of ideal self-identity than actual self-identity in online community, and they have better personal self-identity in online community than physical world while a lower level of social self-identity in online community than physical world. The results of the hypothesis testing analysis based on 300 respondents showed that "self-discrepancy in virtual world" negatively influenced perceived usefulness for self-expression while "cross-world self-discrepancy" positively influenced perceived usefulness for self-expression. The perceived usefulness for self-expression and ease of use positively influence both continuous use and knowledge contribution. Specially, the effect of perceived usefulness for self-expression on knowledge contribution is much bigger than the effect of ease of use. This study extends self-discrepancy theory to virtual worlds by suggesting various types of self-discrepancy and by applying the effect of self-discrepancies in online community. Also, this study extends technology acceptance model in the personal goal in terms of self-expression. This study hopes to offer practical insights by suggesting positive effect of self-discrepancy on behavior in the online community.

A Study on NCS-based Team Teaching Operation in Animation Related Department (애니메이션 관련학과 NCS기반 팀 티칭 운영방안에 관한 연구)

  • Jung, Dong-hee;An, Dong-kyu;Choi, Jung-woong
    • Cartoon and Animation Studies
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    • s.47
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    • pp.31-52
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    • 2017
  • NCS education was created to realize a society in which skills and abilities are respected, such as transcending specifications, establishing recruitment systems, and developing and disseminating national incompetence standards. At the university level, special lectures and job training are being strengthened to raise industrial experts. Especially, in the field of animation, new technologies are rapidly emerging and demanding convergent talents with various fields. In order to meet these social demands, there is a limit to the existing one-class teaching method. In order to solve this problem, it is necessary to participate in a variety of specialized teachers. In other words, rather than solving problems of students' job training and job creation, It is aimed to solve jointly, Team teaching was suggested as a method for this. The expected effects that can be obtained through this are as follows. First, the field of animation is becoming more diverse and complex. The ability to use NCS job-related skills pools can be matched with professors from other departments to enable a wider range of professional instruction. Second, it is possible to use partial professorships in other departments by actively utilizing professors in the university. This leads to the strengthening of the capacity of teachers in universities. Third, it is possible to build a broader and more integrated educational system through cooperative teaching of professors in other departments. Finally, the advantages of special lectures and mentor support of college professors' pools are broader than those of field specialists. A variety of guidance for students can be made with responsible professors. In other words, time and space constraints can be avoided because the mentor is easily met and guided by the university.

위성자료를 이용한 토지피복에 따른 열환경 평가

  • Jo, Su-Jin;Kim, Hae-Dong;An, Ji-Suk
    • 한국지구과학회:학술대회논문집
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    • 2010.04a
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    • pp.88-89
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    • 2010
  • 최근 인간의 활동범위와 영역이 확대되고 산업이 발전하면서 인간의 삶과 지속가능한 발전 등 도시 기후에 관한 관심도 높아지고 있다. 산업혁명 이후 도시화와 산업화로 인해 인구가 증가하고 도시지역으로 집중됨으로써 도시 열섬화 현상에 대한 도시환경문제가 부각되고 있다. 이는 최근까지도 도시개발에 있어서 기능과 효율성이 우선시 되어 도시기후에 대한 배려가 이루어지지 못하고 있으며, 오히려 과도한 냉난방을 가동하는 등 쾌적한 실내 환경 조성을 위한 노력만을 행해왔다. 도시화에 따른 도시의 열환경 구조의 변화는 토지이용의 변화에 따른 피복상태와 밀접한 관련이 있다는 연구들이 수행된 바 있다. 이렇듯 도시화가 진행됨에 따라서 도심 지표면을 덮고 있는 포장재도 변하고 있다. 대표적인 토지피복재로는 콘크리트와 아스팔트 등의 인공포장재, 수계, 삼림 등으로 크게 나누어 볼 수 있다. 최근 도심의 발달로 인해 도심의 표면은 점차 인공포장재인 아스팔트와 콘크리트로 덮여지고 있다. 인공포장재는 맑은 여름철 낮에 받아들인 열을 야간에도 머금고 있어 도시열섬현상의 주요원인이 된다. 도시화가 진행됨에 따라 토지이용형태가 변화하고 있으며 이러한 토지피복의 변화는 그 지역의 기온과 풍향, 풍속뿐만 아니라 지표온도도 변화시키므로 도시 열환경 구조에 적지 않은 영향을 미치고 있다. 과거에는 자연 환경과 도시공간에 대한 인식이 다른 분야로 나누어져서 다루었지만 현재 위성영상 기술의 발달로 많은 공간 정보를 파악할 수 있게 된 바 도시기후변화에 더욱 직접적이고 근본적인 접근이 쉬워졌다. 원격탐사기법의 활용은 위성자료를 이용하여 동시간대 평면적인 열구조를 정량적으로 파악하는데에 중요한 자료를 제공하여 도시지역을 덮고 있는 인공자재의 존재가 도시열섬의 형성과 밀접하게 연관이 있다는 사실을 짐작할 수 있다. 따라서 도시기후변화의 문제점을 더욱 적극적으로 해결하기 위해서는 토지이용에 따른 지표면 온도 상승의 현황을 파악하고 이를 저감 시킬 수 있는 대책들이 수립되어야 한다. 본 연구는 보다 세분화된 도시 열환경을 정량적으로 분석 평가하기 위해서 토지피복별 분류를 3가지로 대구시 중구 경북대학교 부속 고등학교(이하 사대부고 지점)를 도심지역으로, 경상남도 창녕군 창녕읍 우포늪(이하 우포지점)을 수계지점으로, 경상북도 안동시 길안면 만음리(이하 안동지점) 지점과 대구시 칠곡군 동명면 득명리 팔공산 한티재 도립공원(이하 팔공지점)을 산림으로 분류하여 연구하였다. 대구 계명대학교 기후환경연구실에서 보유하고 있는 AWS(Automatic Weather Station) 자료로 기상요소를 분석하였으며, MODIS Terra 위성영상을 이용하여 지표온도를 추출하고 분석하였다. 또 기상요소와 지표온도를 이용해 회귀식을 도출하여 추정기온을 산출하였다. 그 결과 첫째, 계절에 따른 기온의 시간변화는 여름의 평균기온이 $25.13^{\circ}C$$24.12^{\circ}C$로 사대지점과 우포지점의 평균기온이 가장 높게 나타났으며, 이는 도심에서 발생되는 인공열의 영향으로, 우포지점은 수계의 특징이 반영된 결과라 할 수 있다. 둘째, 계절에 따른 풍속의 시간변화는 여름의 경우 우포지점의 풍속이 1.63m/s로 가장 높은 반면 안동지점의 풍속이 0.27m/s로 가장 낮은 것으로 나타났다. 겨울의 경우 팔공지점의 풍속이 1.82m/s로 가장 높게 나타났다. 토지피복에 따른 지표면의 변화가 도시기후에 미치는 영향을 정량적으로 평가하고, 또 지표면 온도와 기온과의 차이를 알아보기 위하여 MODIS 위성 영상을 이용하여 세 지점을 대상으로 토지피복에 따른 열환경을 평가 분석하여 다음과 같은 결론을 얻을 수 있었다. 첫째, MODIS 위성영상을 이용하여 산출한 지표면 온도는 여름철 주간에 안동지점의 경우 주변지역에 비해 지표면 온도가 약 $26^{\circ}C$로 낮게 나타났으며 우포지점의 경우 수계가 가지는 열 완충능력으로 약 $27^{\circ}C$의 낮은 지표면 온도를 나타내었다. 사대지점의 경우 약 $34^{\circ}C$이상의 높은 지표면 온도를 나타내었다. 둘째, MODIS 위성영상을 이용하여 산출한 지표면 온도와 관측된 기온과의 회귀식을 도출하여 상관분석 한 결과, 모든 지점의 값에서 상관성 및 신뢰도가 높은 것으로 나타났다. 셋째, 상관분석의 결과를 통하여 추정한 기온은 지표면 온도와의 차이가 있지만 유사한 패턴의 결과로 추출되었다. 이러한 결과로 볼 때 도시의 인공자재를 이용한 건축과 개발이 도시열섬현상을 유발하는데 중요한 역할을 하는 것을 정량적으로 평가할 수 있었다. 따라서 본 논문의 연구결과를 바탕으로 도시계획에 있어서 인공구조물에 의한 기온과 풍속이 받는 영향을 고려하여 도심의 인공구조물의 배치나 자재에 대한 개발이 이루어져야 할 것이며 열교환의 방해 및 바람순환이 확보되는 구조로 개선되어야 할 것이다.

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Red Tide Detection through Image Fusion of GOCI and Landsat OLI (GOCI와 Landsat OLI 영상 융합을 통한 적조 탐지)

  • Shin, Jisun;Kim, Keunyong;Min, Jee-Eun;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.34 no.2_2
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    • pp.377-391
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    • 2018
  • In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

Optimal Moving Pattern Mining using Frequency of Sequence and Weights (시퀀스 빈발도와 가중치를 이용한 최적 이동 패턴 탐사)

  • Lee, Yon-Sik;Park, Sung-Sook
    • Journal of Internet Computing and Services
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    • v.10 no.5
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    • pp.79-93
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    • 2009
  • For developing the location based service which is individualized and specialized according to the characteristic of the users, the spatio-temporal pattern mining for extracting the meaningful and useful patterns among the various patterns of the mobile object on the spatio-temporal area is needed. Thus, in this paper, as the practical application toward the development of the location based service in which it is able to apply to the real life through the pattern mining from the huge historical data of mobile object, we are proposed STOMP(using Frequency of sequence and Weight) that is the new mining method for extracting the patterns with spatial and temporal constraint based on the problems of mining the optimal moving pattern which are defined in STOMP(F)[25]. Proposed method is the pattern mining method compositively using weighted value(weights) (a distance, the time, a cost, and etc) for our previous research(STOMP(F)[25]) that it uses only the pattern frequent occurrence. As to, it is the method determining the moving pattern in which the pattern frequent occurrence is above special threshold and the weight is most a little bit required among moving patterns of the object as the optimal path. And also, it can search the optimal path more accurate and faster than existing methods($A^*$, Dijkstra algorithm) or with only using pattern frequent occurrence due to less accesses to nodes by using the heuristic moving history.

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Development of GIS based Water Quality Simulation System for Han River and Kyeonggi Bay Area (한강과 경기만 지역 GIS 기반 통합수질모의 시스템 개발)

  • Lee, Chol-Young;Kim, Kye-Hyun
    • Journal of Korea Spatial Information System Society
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    • v.10 no.4
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    • pp.77-88
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    • 2008
  • There has been growing demands to manage the water quality of west coastal region due to the large scale urbanization along the coastal zone, the possibility of application of TMDL(Total Maximum Daily Loadings) to Han river, and the natural disaster such as oil spill incident in Taean, Chungnam. However, no system has been developed for such purposes. In this background, the demand of GIS based effective water quality management has been increased to monitor water quality environment and propose best management alternatives for Han river and Kyeonggi bay. This study mainly focused on the development of integrated water quality management system for Han river bas in and its estuary are a connected to Kyeonggi bay to support integrated water quality management and its plan. Integration was made based on GIS by spatial linking between water quality attributes and location information. A GIS DB was built to estimate the amount of generated and discharged water pollutants according to TMDL technical guide and it included input data to use two different water quality models--W ASP7 for Han river and EFDC for coastal area--to forecast water quality and to suggest BMP(Best management Practices). The results of BOD, TN, and TP from WASP7 were used as the input to run EFDC. Based on the study results, some critical areas which have relatively higher pollutant loadings were identified, and it was also identified that the locations discharging water pollutant loadings to river and seasonal factor affected water quality. And the relationship of water quality between river and its estuary area was quantitatively verified. The results showed that GIS based integrated system could be used as a tool for estimating status-quo of water quality and proposing economically effective BMPs to mitigate water pollution. Further studies need to be made for improving system's capabilities such as adding decision making function as well as cost-benefit analysis, etc. Also, the concrete methodology for water quality management using the system need to be developed.

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Consumer Segmentation based on Consideration Set of Stores and Importance of Store Image (고려점포군에 따른 소비자 세분화와 점포이미지 중요도에 관한 연구)

  • Kim, Han-Na;Rhee, Eun-Young
    • Journal of Distribution Research
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    • v.12 no.2
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    • pp.79-102
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    • 2007
  • Consumers evaluate stores by comparing stores that we, in their minds, similar and are competitive with one another; and in this way, the term "consideration set of stores" is defined as those store alternatives the consumer is aware of and evaluates positively. The purpose of this study is to aid in understanding the consideration set of stores in store choice processes in apparel product purchases. More specifically, this study aims to clarify the relation between consideration set of stores and importance of store image. As a result, the respondents of quantitative study were classified into seven groups by the number of stores and store types they considered: 1) "small-road shop sets group" ; 2) "small-market sets group" ; 3) "small- department store sets group" ; 4) "small-department store/outlet sets group" ; 5) "large-department store/market sets group" ; 6) "large-department store/road shop sets group" ; and 7) "large-department store sets group". Further, significant differences among the groups in the importance of store image were observed. For example, low prices were an important factor in both the small-market considering group and large-department store/market considering group when choosing a retail store, there were also differences in the considering groups in that for the small-department store considering group, store mileage-discount cards were important whereas ample space for relaxation around the stores were important retail store selection factors for the large-department store/road shop considering group. This study may provide a useful direction to retailers in finding out who the target customers and competitive stores are and allow retailers to make proper marketing strategies.

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An Electric Load Forecasting Scheme with High Time Resolution Based on Artificial Neural Network (인공 신경망 기반의 고시간 해상도를 갖는 전력수요 예측기법)

  • Park, Jinwoong;Moon, Jihoon;Hwang, Eenjun
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.11
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    • pp.527-536
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    • 2017
  • With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.

Analysis for Practical use as a Learning Diagnostic Assessment Instruments through the Knowledge State Analysis Method (지식상태분석법을 이용한 학습 진단평가도구로의 활용성 분석)

  • Park, Sang-Tae;Lee, Hee-Bok;Jeong, Kee-Ju;Kim, Seok-Cheon
    • Journal of The Korean Association For Science Education
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    • v.27 no.4
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    • pp.346-353
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    • 2007
  • In order to be efficient in teaching, a teacher should understand the current learner's level through diagnostic evaluation. This study has examined the major issues arising from the noble diagnostic assessment tool based on the theory of knowledge space. The knowledge state analysis method is actualizing the theory of knowledge space for practical use. The knowledge state analysis method is very advantageous when a certain group or individual student's knowledge structure is analyzed especially for strong hierarchical subjects such as mathematics, physics, chemistry, etc. Students' knowledge state helps design an efficient teaching plan by referring their hierarchical knowledge structure. The knowledge state analysis method can be enhanced by computer due to fast data processing. In addition, each student's knowledge can be improved effectively through individualistic feedback depending on individualized knowledge structure. In this study, we have developed a diagnostic assessment test for measuring student's learning outcome which is unattainable from the conventional examination. The diagnostic assessment test was administered to middle school students and analyzed by the knowledge state analysis method. The analyzed results show that students' knowledge structure after learning found to be more structured and well-defined than the knowledge structure before the learning.