• Title/Summary/Keyword: analyzing mapping errors

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A Study on the Evaluation of the Different Thresholds for Detecting Urban Areas Using Remote-Sensing Index Images: A Case Study for Daegu, South Korea (원격탐사 지수 영상으로부터 도시 지역 탐지를 위한 임계점 평가에 관한 연구: 대구광역시를 사례로)

  • CHOUNG, Yun-Jae;LEE, Eung-Joon;JO, Myung-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.1
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    • pp.129-139
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    • 2019
  • Mapping urban areas using the earth observation satellites is useful for monitoring urban expansions and measuring urban developments. In this research, the different thresholds for detecting the urban areas separately from the remote-sensing index images (normalized-difference built-up index(NDBI) and urban index(UI) images) generated from the Landsat-8 image acquired in Daegu, South Korea were evaluated through the following steps: (1) the NDBI and UI images were separately generated from the given Landsat-8 image; (2) the different thresholds (-0.4, -0.2, and 0) for detecting the urban areas separately from the NDBI and UI images were evaluated; and (3) the accuracy of each detected urban area was assessed. The experiment results showed that the threshold -0.2 had the best performance for detecting the urban areas from the NDBI image, while the threshold -0.4 had the best performance for detecting the urban areas from the UI image. Some misclassification errors, however, occurred in the areas where the bare soil areas were classified into urban areas or where the high-rise apartments were classified into other areas. In the future research, a robust methodology for detecting urban areas, including the various types of urban features, with less misclassification errors will be proposed using the satellite images. In addition, research on analyzing the pattern of urban expansion will be carried out using the urban areas detected from the multi-temporal satellite images.

Automatic Merging of Distributed Topic Maps based on T-MERGE Operator (T-MERGE 연산자에 기반한 분산 토픽맵의 자동 통합)

  • Kim Jung-Min;Shin Hyo-Pil;Kim Hyoung-Joo
    • Journal of KIISE:Software and Applications
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    • v.33 no.9
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    • pp.787-801
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    • 2006
  • Ontology merging describes the process of integrating two ontologies into a new ontology. How this is done best is a subject of ongoing research in the Semantic Web, Data Integration, Knowledge Management System, and other ontology-related application systems. Earlier research on ontology merging, however, has studied for developing effective ontology matching approaches but missed analyzing and solving methods of problems of merging two ontologies given correspondences between them. In this paper, we propose a specific ontology merging process and a generic operator, T-MERGE, for integrating two source ontologies into a new ontology. Also, we define a taxonomy of merging conflicts which is derived from differing representations between input ontologies and a method for detecting and resolving them. Our T-MERGE operator encapsulates the process of detection and resolution of conflicts and merging two entities based on given correspondences between them. We define a data structure, MergeLog, for logging the execution of T-MERGE operator. MergeLog is used to inform detailed results of execution of merging to users or recover errors. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Naver philosophy dictionary as input ontologies. Our experiments show that the automatic merging module compared with manual merging by a expert has advantages in terms of time and effort.

Accuracy Assessment of Feature Collection Method with Unmanned Aerial Vehicle Images Using Stereo Plotting Program StereoCAD (수치도화 프로그램 StereoCAD를 이용한 무인 항공영상의 묘사 정확도 평가)

  • Lee, Jae One;Kim, Doo Pyo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.2
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    • pp.257-264
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    • 2020
  • Vectorization is currently the main method in feature collection (extraction) during digital mapping using UAV-Photogrammetry. However, this method is time consuming and prone to gross elevation errors when extracted from a DSM (Digital Surface Model), because three-dimensional feature coordinates are vectorized separately: plane information from an orthophoto and height from a DSM. Consequently, the demand for stereo plotting method capable of acquiring three- dimensional spatial information simultaneously is increasing. However, this method requires an expensive equipment, a Digital Photogrammetry Workstation (DPW), and the technology itself is still incomplete. In this paper, we evaluated the accuracy of low-cost stereo plotting system, Menci's StereoCAD, by analyzing its three-dimensional spatial information acquisition. Images were taken with a FC 6310 camera mounted on a Phantom4 pro at a 90 m altitude with a Ground Sample Distance (GSD) of 3 cm. The accuracy analysis was performed by comparing differences in coordinates between the results from the ground survey and the stereo plotting at check points, and also at the corner points by layers. The results showed that the Root Mean Square Error (RMSE) at check points was 0.048 m for horizontal and 0.078 m for vertical coordinates, respectively, and for different layers, it ranged from 0.104 m to 0.127 m for horizontal and 0.086 m to 0.092 m for vertical coordinates, respectively. In conclusion, the results showed 1: 1,000 digital topographic map can be generated using a stereo plotting system with UAV images.

Extraction of Water Depth in Coastal Area Using EO-1 Hyperion Imagery (EO-1 Hyperion 영상을 이용한 연안해역의 수심 추출)

  • Seo, Dong-Ju;Kim, Jin-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.716-723
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    • 2008
  • With rapid development of science and technology and recent widening of mankind's range of activities, development of coastal waters and the environment have emerged as global issues. In relation to this, to allow more extensive analyses, the use of satellite images has been on the increase. This study aims at utilizing hyperspectral satellite images in determining the depth of coastal waters more efficiently. For this purpose, a partial image of the research subject was first extracted from an EO-1 Hyperion satellite image, and atmospheric and geometric corrections were made. Minimum noise fraction (MNF) transformation was then performed to compress the bands, and the band most suitable for analyzing the characteristics of the water body was selected. Within the chosen band, the diffuse attenuation coefficient Kd was determined. By deciding the end-member of pixels with pure spectral properties and conducting mapping based on the linear spectral unmixing method, the depth of water at the coastal area in question was ultimately determined. The research findings showed the calculated depth of water differed by an average of 1.2 m from that given on the digital sea map; the errors grew larger when the water to be measured was deeper. If accuracy in atmospheric correction, end-member determination, and Kd calculation is enhanced in the future, it will likely be possible to determine water depths more economically and efficiently.