• Title/Summary/Keyword: 지리객체기반 영상 분석

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Semi-Automated Extraction of Geographic Information using KOMPSAT 2 : Analyzing Image Fusion Methods and Geographic Objected-Based Image Analysis (다목적 실용위성 2호 고해상도 영상을 이용한 지리 정보 추출 기법 - 영상융합과 지리객체 기반 분석을 중심으로 -)

  • Yang, Byung-Yun;Hwang, Chul-Sue
    • Journal of the Korean Geographical Society
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    • v.47 no.2
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    • pp.282-296
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    • 2012
  • This study compared effects of spatial resolution ratio in image fusion by Korea Multi-Purpose SATellite 2 (KOMPSAT II), also known as Arirang-2. Image fusion techniques, also called pansharpening, are required to obtain color imagery with high spatial resolution imagery using panchromatic and multi-spectral images. The higher quality satellite images generated by an image fusion technique enable interpreters to produce better application results. Thus, image fusions categorized in 3 domains were applied to find out significantly improved fused images using KOMPSAT 2. In addition, all fused images were evaluated to satisfy both spectral and spatial quality to investigate an optimum fused image. Additionally, this research compared Pixel-Based Image Analysis (PBIA) with the GEOgraphic Object-Based Image Analysis (GEOBIA) to make better classification results. Specifically, a roof top of building was extracted by both image analysis approaches and was finally evaluated to obtain the best accurate result. This research, therefore, provides the effective use for very high resolution satellite imagery with image interpreter to be used for many applications such as coastal area, urban and regional planning.

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A Study on Object-Based Image Analysis Methods for Land Cover Classification in Agricultural Areas (농촌지역 토지피복분류를 위한 객체기반 영상분석기법 연구)

  • Kim, Hyun-Ok;Yeom, Jong-Min
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.4
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    • pp.26-41
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    • 2012
  • It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.

Construction of Video Information System by Video Structuring (비디오자료 구조화에 의한 동영상정보시스템 구축)

  • Koo, Heung-Dae;Sohn, Duk-Jae;Yoo, Hwan-Hee
    • 한국지형공간정보학회:학술대회논문집
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    • 2004.10a
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    • pp.67-72
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    • 2004
  • 21세기 지식정보화 사회를 당면하면서 정치, 경제, 문화 등의 환경이 다양한 형태로 급속히 변하고 있다. 다양한 형태의 정보를 적절한 기술을 이용하여 보다 효율적으로 수집하고 이를 신속하고 정확하게 분석하여 합리적인 의사결정을 하여야 하는데 사회변화의 속도가 급변함에 따라 당면한 문제들의 해결과 미래의 정보 수요에 부응하기 위한 핵심 기술로서 GIS는 정보화시대에서 무엇보다 정보시스템의 구축을 위한 계획 수립이 절실하게 되었다. 이러한 지리정보시스템에 동영상데이터의 연계기능을 더하여 영상을 기반으로 직접 사용자와 상호작용을 하며 데이터를 분석, 관리, 출력하는 동영상지리정보시스템(Video Geographic Information System: Video GIS)이 GIS 분야에 있어 새로운 연구 분야로 떠오르고 있다. 본 연구에서는 사회변화의 속도가 급변하는 도시기반시설물들을 효율적으로 개발, 관리하고 비행선촬영시스템을 통하여 취득된 동영상 자료를 객체추적 알고리즘에 의해 데이터의 양을 줄였다. 수치지도와 동영상데이터의 공간정보를 연계시켜 도시지역에 존재하는 각종 시설물을 관리할 수 있는 동영상 정보시스템을 Prototype으로 구축하여 그 가능성을 제시하였다.

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Land Cover Classification Using UAV Imagery and Object-Based Image Analysis - Focusing on the Maseo-myeon, Seocheon-gun, Chungcheongnam-do - (UAV와 객체기반 영상분석 기법을 활용한 토지피복 분류 - 충청남도 서천군 마서면 일원을 대상으로 -)

  • MOON, Ho-Gyeong;LEE, Seon-Mi;CHA, Jae-Gyu
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.1
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    • pp.1-14
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    • 2017
  • A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.

The Design and Implementation of A Video Geographic Information System (비디오 지리 정보 시스템의 설계 및 구현)

  • 유재준;주인학;남광우;이종훈
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10c
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    • pp.274-276
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    • 2002
  • 최근에 지리 정보를 검색, 관리, 분석할 수 있는 지리 정보 시스템(Geographic information System)의 사용이 확대됨에 따라 단순한 수치지도 정보 이외에 좀 더 현실적이고. 사실적인 정보를 제공해 줄 수 있는 시스템에 대한 요구가 커지고 있다 이러한 요구에 부응하는 한 방향으로써 차량에 부착된 카메라 등등 사용하여 획득한 비디오 데이터와 수치지도 정보를 연계하여 특정 수치지도 객체의 영상을 제공함으로써 수치지도 객체에 대한 자세한 현장의 정보를 쉽게 파악할 수 있도록 하는 비디오 지리 정보 시스템이 등장하였다. 하지만 기존의 비디오 지리 정보 시스템은 획득한 비디오 데이터를 수치지도의 한 속성으로서 표현하거나, 수치지도에서 비디오 데이터로의 단순한 링크를 사용하여 수치지도와 연계함으로써 수치지도의 검색을 통한 영상 정보의 출력이라는 단방향 검색만을 지원한다. 즉, 비디오 데이터에 존재하는 수치지도 객체의 검색을 통한 수치지도의 검색 및 관리, 분석은 지원해 주지 못하고 있다. 본 논문에서는 비디오 데이터와 수치지도의 양방향 검색 및 관리를 지원하는 비디오 지리 정보 시스템을 설계하고 구현한다. 이를 위해 1) 비디오 데이터와 수치지도 정보를 효율적으로 연계하기 위한 데이터 모델을 제안하고, 2) 비디오 데이터와 수치지도 정보의 연계 정보를 추출 및 구축하는 과정을 제안하며, 3) 비디오 데이터의 출력 및 검색, 수치지도의 출력 및 검색, 연계 정보를 통한 비디오 데이터와 수치지도 정보의 연동 등을 효율적으로 지원하기 위한 시스템을 컴포넌트(Component) 구조를 사용하여 설계한다. 이해성 및 이를 기반으로 하는 교육용 애플리케이션 개발의 용이성의 증대를 기대할 수 있으며, 모델의 재사용성을 보장할 수 있다. 제안한다.수행하였다. 분석에서는 제품의 효율성뿐만 아니라 보안성을 중요하게 생각하였으며, 앞으로 보안 관련 소프트웨어 개발에 사용될 수 있는 도구들이 가이드 라인에 대한 정보를 제공한다.용할 수 있는지 세부 설계를 제시한다.다.으로서 hemicellulose구조가 polyuronic acid의 형태인 것으로 사료된다. 추출획분의 구성단당은 여러 곡물연구의 보고와 유사하게 glucose, arabinose, xylose 함량이 대체로 높게 나타났다. 점미가 수가용성분에서 goucose대비 용출함량이 고르게 나타나는 경향을 보였고 흑미는 알칼리가용분에서 glucose가 상당량(0.68%) 포함되고 있음을 보여주었고 arabinose(0.68%), xylose(0.05%)도 다른 종류에 비해서 다량 함유한 것으로 나타났다. 흑미는 총식이섬유 함량이 높고 pectic substances, hemicellulose, uronic acid 함량이 높아서 콜레스테롤 저하 등의 효과가 기대되며 고섬유식품으로서 조리 특성 연구가 필요한 것으로 사료된다.리하였다. 얻어진 소견(所見)은 다음과 같았다. 1. 모년령(母年齡), 임신회수(姙娠回數), 임신기간(姙娠其間), 출산시체중등(出産時體重等)의 제요인(諸要因)은 주산기사망(周産基死亡)에 대(對)하여 통계적(統計的)으로 유의(有意)한 영향을 미치고 있어 $25{\sim}29$세(歲)의 연령군에서, 2번째 임신과 2번째의 출산에서 그리고 만삭의

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Spatial Replicability Assessment of Land Cover Classification Using Unmanned Aerial Vehicle and Artificial Intelligence in Urban Area (무인항공기 및 인공지능을 활용한 도시지역 토지피복 분류 기법의 공간적 재현성 평가)

  • Geon-Ung, PARK;Bong-Geun, SONG;Kyung-Hun, PARK;Hung-Kyu, LEE
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.4
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    • pp.63-80
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    • 2022
  • As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

Detection Ability of Occlusion Object in Deep Learning Algorithm depending on Image Qualities (영상품질별 학습기반 알고리즘 폐색영역 객체 검출 능력 분석)

  • LEE, Jeong-Min;HAM, Geon-Woo;BAE, Kyoung-Ho;PARK, Hong-Ki
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.3
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    • pp.82-98
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    • 2019
  • The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

A Study on the Sedmentary Facies Change in the Tidal Flat Using High Spatial Resolution Remotely Sensed Data (고해상도 위성영상을 활용한 갯벌 퇴적상 변화 연구)

  • Choi, Jong-Kuk;Ryu, Joo-Hyung
    • Economic and Environmental Geology
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    • v.44 no.1
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    • pp.59-70
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    • 2011
  • The surface sediment distribution in a tidal flat in 2001 was compared with that of 2008 using high spatial resolution remote sensing images and a GIS-based analysis. Maps of the surface sedimentary facies for each time frame were induced by an IKONOS data acquired in February, 2001 and a KOMPSAT-2 data acquired in April, 2008 using an object-based classification method. The area ratio of each surface sedimentary facies were estimated, and the results were compared each other for deducing the change in the sedimentary facies during the time interval. The result showed that the percentage of grains larger than very fine sand (0.0625 mm) has increased considerably since the early 2000s in the Hwangdo tidal flat. Mud flat facies has decreased 5.81 % in the late 2000s compared with the early 2000s. However, mixed flat and sand flat have increased 4.46% and 2.14%, respectively. A field campaign also supported the result. This study showed that the monitoring of changes in the surface sedimentary facies in the tidal flat is possible through a GIS-based analysis using high spatial resolution remote sensing images.

Applicability for Detecting Trails by Using KOMPSAT Imagery (등산로 탐지를 위한 KOMPSAT 영상의 활용가능성)

  • Bae, Jinsu;Yim, Jongseo;Shin, Young Ho
    • Journal of the Korean Geographical Society
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    • v.50 no.6
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    • pp.607-619
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    • 2015
  • It is important to detect trails accurately for finding a proper management. We examined the applicability of KOMPSAT imagery to detect trails and found that it could be an efficient alternative to track trails correctly. We selected K2 and K3 imagery with different spatial resolution. Then, we processed each imagery to get NDVI, SAVI, and SC data. And then, we identified trails by object-based analysis and network analysis. Finally, we evaluated the potential trails with F-measurement and Jaccard coefficient which are based on correctness and completeness. The results show that the applicability is quite different in each case. Among them, especially the SC data with K3 shows the most highest value; correctness of detecting legal trails is 0.44 and completeness of that is 0.54. F-measurement and Jaccard coefficient are 0.49 and 0.32. In general, although there is a limit in detecting trails by using only KOMPSAT imagery, the usefulness of KOMPSAT imagery can be a higher considering its cost efficiency and availability of acquiring periodic data.

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Estimation of Potential Population by IED(Improvised Explosive Device) in Intensive Apartment Area (아파트 밀집지역 급조폭발물 테러 발생 시 잠재피해인구 추정)

  • Lee, Kangsan;Choi, Jinmu
    • Journal of the Economic Geographical Society of Korea
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    • v.18 no.1
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    • pp.76-86
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    • 2015
  • In this study, we presented a method for estimating the potential population damage of the Seoul Nowon-gu area in the event of a terrorist using a vehicle improvised explosive devices (IED). Using the object-based building extraction method with orthophoto image, the area of the apartment has been determined, and the apartment's height and level were estimated based on the elevation data. Using the population estimation method based on total floor area of building, each apartment resident population was estimated, and then potential population damage at the time of terrorist attacks was estimated around the subway station through a scenario analysis. Terrorism damage using IED depends on the type of vehicle greatly because of the amount loadable explosives. Therefore, potential population damage was calculated based on the type of vehicle. In the results, the maximum potential damage population during terrorist attacks has been estimated to occur around Madeul station, Nowon-gu. The method used in this study can be used various population estimation research and disaster damage estimation.

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