• Title/Summary/Keyword: 영상대차법

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A Comparative Study of Wetland Change Detection Techniques Using Post-Classification Comparison and Image Differencing on Landsat-5 TM Data (랜�V-5호(號) TM 데이타를 이용(利用)한 구분후(區分后) 비교(比較) 및 영상대차(映像對差)의 습지대(濕地帶) 변화(變化) 탐지(探知) 기법(技法)에 관(關)한 비교연구(比較硏究))

  • Choung, Song Hak;Ulliman, Joseph J.
    • Journal of Korean Society of Forest Science
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    • v.81 no.4
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    • pp.346-356
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    • 1992
  • The extensive Snake River floodplain in Northwest United States has experienced major changes in water channels and vegetation types due to floodings. To detect the change of wetland cover-types for the period of 1985 and 1988, post-classification comparison and image differencing change detection techniques were evaluated using Landsat-5 TM digital data. Differenced infrared-band images indicated better accuracy indices than any visible-band images. A thresholding technique was applied to identify the change and no change categories from the transformed images produced by image differencing. The problems in using different accuracy indices, including the Kappa coefficient of agreement, overall accuracy, producer's accuracy, user's accuracy, and average accuracy(based on both the producer's and user's accuracy approaches) in determining an optimal threshold level, were examined.

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Change Detection of a Small Town Area from Multi-Temporal Aerial Photos using Image Differencing and Image Ratio Techniques (다시기 항공사진으로부터 영상대차법과 영상대비법을 이용한 소도읍 지역의 변화 검출)

  • Lee, Jin-Duk;Yeon, Sang-Ho;Lee, Dong-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.1
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    • pp.116-124
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    • 2008
  • This study presents the application of multi-temporal and multi-scale panchromatic aerial photos for change detection in a small urban area. For aerial photos of the scale of 1:20,000 taken in 1987 and 1996 and the scale of 1:37,500 taken in 2000. Pre-processing that make the same conditions to all of the aerial photos was carried out through geometric correction, registration, contrasting, resamplimg, and mosaicking and then change detection were carried out respectively by image differencing and image ratio techniques. As a result, the change of urban features and landcover were able to be detected from panchromatic aerial photos that is single-band images and then the detected change results were compared between both techniques.

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Change Detection of a Small Town Area from Multi-Temporal Aerial Photographs (다시기 항공사진으로부터 소도읍 지역의 변화탐지)

  • Lee, Jin-Duk;Yeon, Sang-Ho;Lee, Dong-Ho
    • Proceedings of the Korea Contents Association Conference
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    • 2004.11a
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    • pp.131-137
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    • 2004
  • This study presents the application of multi-temporal aerial photographs in detecting change in a small urban area. For the panchromatic aerial images of the scale of 1/20000 and 1/37500 photographed in 1987, 1996 and 2000, image geometric correction and registration were carried out before performing change detection in a common reference system and then image mosaicking. The image differencing technigue was employed to detect urban features and landcover change and then the results were compared to those of image ratioing techniques. Also threshold values were suggested in applying image differencing for change detection.

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Change Vector Analysis : Change detection of flood area using LANDSAT TM Data (LANDSAT TM을 이용한 홍수지역의 변화탐지 : Change Vector Analysis 방법을 중심으로)

  • Yoon, Geun-Won;Yun, Young-Bo;Park, Jong-Hyun
    • Journal of Korean Society for Geospatial Information Science
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    • v.11 no.2 s.25
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    • pp.47-52
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    • 2003
  • Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the LANDSAT TM data was used to detect the change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korea peninsular. Among the several change detection techniques, change vector analysis(CVA), principle component analysis(PCA) and image difference approach are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel values. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood. CVA with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.

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