• Title/Summary/Keyword: Remote Sensing Imagery

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VARIOGRAM-BASED URBAN CHARACTERIZATION USING HIGH RESOLUTION SATELLITE IMAGERY

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.413-416
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    • 2006
  • As even small features can be classified as high resolution imagery, urban remote sensing is regarded as one of the important application fields in time of wide use of the commercialized high resolution satellite imageries. In this study, we have analyzed the variogram properties of high resolution imagery, which was obtained in urban area through the simple modeling and applied to the real image. Based on the grasped variogram characteristics, we have tried to decomposed two high-resolution imagery such as IKONOS and QuickBird reducing window size until the unique variogram that urban feature has come out and then been indexed. Modeling results will be used as the fundamental data for variographic analysis in urban area using high resolution imagery later on. Index map also can be used for determining urban complexity or land-use classification, because the index is influenced by the feature size.

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Three Dimensional Positioning Accuracy of KOMPSAT-1 Stereo Imagery

  • Jeong, Soo;Kim, Yong-Soo
    • Korean Journal of Remote Sensing
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    • v.16 no.4
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    • pp.339-345
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    • 2000
  • KOMPSAT-1 was launched on 21 December, 1999 and the main mission of the satellite is the cartography to provide the imagery from a remote earth view for the production of maps of Korean territory. For this purpose, the satellite has capability to tilt the spacecraft utmost $\pm$45 degrees to acquire stereo satellite imagery in different paths. This study aims to estimate the three dimensional positioning accuracy of stereo satellite imagery from EOC(electro-optical camera), a payload of KOMPSAT-1 satellite. For this purpose, the ground control points and check points were obtained by GPS surveying. The sensor modeling and the adjustment was performed by PCI software installed in KARI (Korea Aerospace Research Institute), which contained mathematical analysis module for KOMPSAT-1 EOC. The study areas were Taejon and Nonsan, placed in the middle part of Korea. As a result of this study, we found that the RMSE(root mean square error) value of three dimensional positioning KOMPST-1 stereo imagery can be less than 1 pixel (6.6 m) if we can use about 10 GCPs(ground control points). Then, a standarrd of FGDC (Federal Geographic Data Committee) of USA was applied to the result to estimate the three dimensional positioning accuracy of KOMPSAT-1 stereo imagery.

USING SATELLITE SYNTHETIC APERTURE RADAR IMAGERY TO MAP OIL SPILLS IN THE EAST CHINA SEA

  • Shi, Lijian;Ivanov, Andrei Yu.;He, Mingxia;Zhao, Chaofang
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.981-984
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    • 2006
  • Oil pollution of the ocean is a major environmental problem, especially in its coastal zones. Synthetic aperture radar (SAR) flown on satellites, such as ERS-2 and Envisat, has been proved to be a useful tool in oil spill monitoring due to its wide coverage, day and night, and all-weather capability. The total 120 SAR images containing oil spill over the East China Sea were collected and analyzed, ranging in date from July 23, 2002 to November 11, 2005. After preprocessed, SAR images were segmented by adaptive threshold method. The oil spill images were incorporated into GIS after distinguished from look-like phenomena, finally we presented the oil spills distribution map for the East China Sea. The wide-swath and quick-looks SAR imagery for mapping of oil spill distribution over large marine areas were proved to be useful when full resolution data are not available. After the temporal and spatial distribution of the oil spills were analyzed, we found that most of oil spills were distributed along the main ship routes, which means the illegal discharge by ships, and the occurrence of oil spill detected on SAR images acquired during morning and summer is much higher than during evening and winter.

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DSM GENERATION FROM IKONOS STEREO IMAGERY

  • Rau, Jiann-Yeou;Chen, Liang-Chien;Chang, Chih-Li
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.57-59
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    • 2003
  • Digital surface model generation from IKONOS stereo imagery is a new challenge in photogrammetric community, especially when the satellite company does not provide the raw data as well as their ancillary ephemeris data. In this paper we utilized an estimated relief displacement azimuth and the nominal collection elevation data included in the metadata file to correct the relief displacement of GCPs, together with a linear transformation for geometric modeling of IKONOS imagery. Space intersection is performed by the trigonometric intersection assuming a parallel projection of IKONOS imagery due to its small FOV and frame size. In the experiment, less than 2-meters of RMSE in orbit modeling is achieved denoting the potential positioning accuracy of the IKONOS stereo imagery.

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Application of RS and GIS in Extraction of Building Damage Caused by Earthquake

  • Wang, X.Q.;Ding, X.;Dou, A.X.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1206-1208
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    • 2003
  • The extraction of earthquake damage from remote sensed imagery requires high spatial resolution and temporal effectiveness of acquisition of imagery. The analog photographs and visual interpretation were taken traditionally. Now it is possible to acquire damage information from many commercial high resolution RS satellites. The key techniques are processing velocity and precision. The authors developed the automatic / semiautomatic image process techniques including feature enhancement, and classification, designed the emergency Earthquake Damage and Losses Evaluate System based on Remote Sensing (RSEDLES). The paper introduced the functions of RSEDLES as well as its application to the earthquakes occurred recently.

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Comparative Study of GDPA and Hough Transformation for Automatic Linear Feature Extraction

  • Ryu, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.238-240
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    • 2003
  • As remote sensing is weighty in GIS updating, it is indispensable to get spatial information quickly and exactly. In this study, we have designed and implemented the program by two algorithms of GDPA (Gradient Direction Profile Analysis) and Hough transformation to extract linear features automatically from high-resolution imagery. We applied the software to embody both algorithms to KOMPSAT-EOC, IKONOS, and Landsat-ETM and made a comparative study of results.

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Adaptive Parametric Estimation and Classification of Remotely Sensed Imagery Using a Pyramid Structure

  • Kim, Kyung-Sook
    • Korean Journal of Remote Sensing
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    • v.7 no.1
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    • pp.69-86
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    • 1991
  • An unsupervised region based image segmentation algorithm implemented with a pyramid structure has been developed. Rather than depending on thraditional local splitting and merging of regions with a similarity test of region statistics, the algorithm identifies the homogenous and boundary regions at each level of pyramid, then the global parameters of esch class are estimated and updated with values of the homogenous regions represented at the level of the pyramid using the mixture distribution estimation. The image is then classified through the pyramid structure. Classification results obtained for both simulated and SPOT imagery are presented.

Efficient Classification of High Resolution Imagery for Urban Area

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.27 no.6
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    • pp.717-728
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    • 2011
  • An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.

Determination of Sampling Unit Size for Cultivation Area Survey using Remote Sensing Technology

  • Park, Jin-Woo;Shin, Gi-Eun;Lee, Suk-Hoon;Byun, Jong-Seok
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.733-741
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    • 2012
  • The successful launch of Arirang satellites allow the acquisition of high resolution satellite imagery of Korean territory and enables the transition from the conventional cultivation area survey method to new image based methods adopted in advanced nations. In this study, we suggested reasonable sizes of the primary sampling unit and the secondary sampling unit for the satellite imagery based sampling design in 8 provinces preselected for this research. The PSU size was determined mainly in consideration of intracorrelation that shows the degree of homogeneity within each cluster and the efficiency of the image process. For the SSU size, we considered the relative standard error and the differences between the land cover maps produced by the Ministry of Environment and the satellite imagery processed by the National Statistical Office.

Applications of Landsat Imagery and Digital Terrain Model Data to River Basin Analyses (Landsat 영상과 DTM 자료의 하천유역 해석에의 응용기법 개발)

  • 조성익;박경윤;최규홍;최원식
    • Korean Journal of Remote Sensing
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    • v.2 no.2
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    • pp.117-131
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    • 1986
  • The purpose of this study was to develop techniques acquiring hydrologic parameters that affect runoff conditions from Landsat imagery. Runoff conditions in a study area were analyzed by employing the U.S. Soil Conservation Service(SCS) Method. SCS runoff curve numbers(CN) were estimated by the computer analysis of Landsat imagery and digiral terrain model(DTM) data. The SCS Method requires land use/cover and soil conditions of the area as input parameters. A land use/cover map of 5 hydrological classes was produced from the Landsat multi-spectral scannerr imagery. Slope-gradient and contour and contour maps were also made using the DTM topographic data. Inundation areas depending on reservoir levels were able to be mapped on the Landsat scene by combining the contour data.