• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.147-155
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• 2015

The existing field survey and aerial photography involve the waste of manpower and economic loss in the coastline survey. To minimize these disadvantages, the digitization for efficient coastline extraction was conducted in this study using the points extracted from the standard coastline of the approximate highest high water and the diverse satellite images (KOMPSAT-3, SPOT-5, Landsat-8 and Quickbird-2), and the comparative accuracy analysis was conducted. The differences between the standard coastline points of the approximate highest high water and the coastline of each satellite were smallest for KOMPSAT-3, followed by Quickbird-2, SPOT-5 and Landsat-8. The significant probability from between the multipurpose applications satellite and Quickbird-2 (significant probability two-tailed) was statistically significant at 1% significance level. Therefore, high-resolution satellite images are required to efficiently extract the coastline, and KOMPSAT-3, from which images are easily acquired at a low cost, will enable the most efficient coastline extraction without external support.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.47-53
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• 2012

Recently many developed countries have used satellite images for classifying cropland areas to reduce time and efforts put into field survey. Korea also has used satellite images for the same purpose since KOMPSAT-2 was successfully launched and operated in 2006, but still far way to go in order to achieve the required accuracy from the products. This study evaluated the accuracy of the calculated croplands by using the objected classification method with various satellite images including ASTER, Spot-5, Rapid eye, Quickbird-2, Geo eye-1. Also, their usability and effectiveness for the cropland survey were verified by comparing with field survey data. As results. Geo eye-1 and Rapid eye showed higher accuracy to calculate the paddy field areas while Geo eye-1 and Quickbird-2 showed higher accuracy to calculate the upland field areas.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.80-85
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• 2008

최근 도심지역이 급변하고 고해상도 위성영상의 보급이 증가함에 따라 고해상도 위성영상을 이용한 수치표고모델과 정사영상 생성에 관한 연구가 활발해 지고 있다. 본 연구에서는 IKONOS, SPOT5, QUICKBIRD, KOMPSAT2 위성영상을 이용하여 DEM 과 정사영상을 생성하였으며 USGS DTED 와 기준점을 이용하여 결과의 정확도를 비교 분석하였다. 보다 정확한 DEM 생성을 위해 자동 피라미드 알고리즘을 적용하고 영상 정합시 에피폴라 기하학을 적용하였다. 정사 영상 생성시 DTED 높이값을 이용하여 보정을 수행하였으며 생성 속도를 높이기 위하여 리샘플링 그리드를 적용하였다. 본 연구에서 DEM 과 정사영상 생성시 QUICKBIRD 와 SPOT5 의 경우 영상의 용량이 매우 커 메모리 부족문제와 알고리즘 수행 속도 저하가 발생함을 확인하였다. 이를 개선하기 위하여 DEM 생성시 정합 후보점의 개수를 줄이는 알고리즘을 고안하여 기존에 메모리 문제로 생성하지 못했던 QUICKBIRD와 SPOT5 의 DEM 을 생성하였으며 정사 영상 생성시 리샘플링 그리드를 적용하여 고해상도 정상영상 생성 속도 개선에 상당한 효과를 가져왔다. 그러나 고해상도 위성 영상의 용량이 점점 커져감에 따라 이러한 메모리 문제와 처리 속도 저하에 관한 문제는 추후 계속적으로 연구되어야 할 부분이라고 할 수 있다. 본 연구에서 생성한 IKONOS, SPOT5, QUICKBIRD DEM 의 정확도를 USGS DTED 와 비교한 결과 13${\sim}$15 m 정도의 RMS 높이 오차가 산출되었으며 생성된 IKONOS, QUICKBIRD, KOMPSAT2 정사영상을 기준점과 비교한 결과 3 m 정도의 거리오차가 산출되었음을 확인하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.163-171
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• 2012

High resolution satellite images have been used for building and road system analysis, landscape analysis, and ecological assessment for several years. However, in high resolution satellite images, shadows are necessarily cast by manmade objects such as buildings and over-pass bridges. This paper develops the shadow extraction procedures in urban area including various land-use classes, and the extracted shadow areas are evaluated by a manually digitized shadow map. For the shadow extraction, the Canny edge operator and the dilation filter are applied to make building edge buffer area. Also, the object-based segmentation was performed using Gram-Schmitt fusion image, and spectral and spatial parameters are calculated from the segmentation results. Finally, we proposed appropriate parameters and extraction rules for the shadow extraction. The accuracy of the shadow extraction results from the various assessment indices is 80% to 90%.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.35-45
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• 2010

The objective of this study is to verify the positional accuracy by performing the orthometric corrections on the high resolution satellite images and to analyze the band correlation between the high resolution images corrected with orthometric correction. The objectives also included an analysis on the correlation of NDVI. For the orthometric correction of images from KOMPSAT2 and IKONOS, systematic errors were removed in use of RPC data, and non-planar distortions were corrected with GPS surveying data. Also, by preempting the image points at the same positions within ortho images, a comparison was performed on positional accuracies between image points of each image and GPS surveying points. The comparison was also made on the positional accuracies of image points. between the images. For correlation of band and correlation of NDVI, the descriptive statistics of DN values were acquired for respective bands by adding the Quickbird images and Aerial Photographs undergone through orthometric correction at the time of purchase. As result, from a comparison on positional accuracies of Orthoimages from KOMPSAT2 and Ortho Images of IKONOS was made. From the comparison the distance between the image points within each image and GPS surveying points was identified as 3.41m for KOMPSAT2 and as 1.45m for IKONOS, presenting a difference of 1.96m. Whereas, RMSE between image points was identified as 1.88m. The level of correlation was measured by using Quickbird, KOMPSAT2, IKONOS and Aerial Photographs between inter-image bands and NDVI, showing that there were high levels of correlation between Quickbird and IKONOS identified from all bands as well as from NDVI, except a high level of correlation that was identified between the Aerial Photographs and KOMPSAT2 from Band 2. Low levels of correlation were also identified between Quickbird and Aerial Photographs from Band 1. and between KOMPSAT2 and IKONOS from Band 2 and Band 4, whereas, KOMPSAT2 showed low correlations with Aerial Photographs from Band 3. For NDVI, KOMPSAT2 showed low level of correlations with both of QuickBird and IKONOS.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.47-54
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• 2012

Additional high resolution satellite images, other period or site, are essential for efficient city modeling and analysis. However, the same ground objects have a radiometric inconsistency in different satellite images and it debase the quality of image processing and analysis. Moreover, in an urban area, buildings, trees, bridges, and other artificial objects cause shadow effects, which lower the performance of relative radiometric normalization. Therefore, in this study, we exclude shadow areas and suggest the selective histogram matching methods for image based application without supplementary digital elevation model or geometric informations of sun and sensor. We extract the shadow objects first using adjacency informations with the building edge buffer and spatial and spectral attributes derived from the image segmentation. And, Outlier objects like a asphalt roads are removed. Finally, selective histogram matching is performed from the shadow masked multi-temporal Quickbird-2 images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.359-365
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• 2008

This paper focused on generation of more accurate DEM and analysis of accuracy. For this, we applied suitable sensor modeling technique for each satellite image and automatic pyramid matching using image pyramid was applied. Matching algorithm based on epipolarity and scene geometry also was applied for stereo matching. IKONOS, Quickbird, SPOT-5, Kompsat-2 were used for experiments. In particular, we applied orbit-attitude sensor modeling technique for Kompsat-2 and performed DEM generation successfully. All DEM generated show good quality. Assessment was carried out using USGS DTED and we also compared between DEM generated in this research and DEM generated from common software. All DEM had $9m{\sim}12m$ Mean Absolute Error and $13m{\sim}16m$ RMS Error. Experimental results show that the DEMs of good performance which is similar to or better than result of DEMs generated from common software.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.274-277
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• 2007

This study is to estimate the spatial distribution of soil loss using the land use data produced from QuickBird satellite imagery. For a small agricultural watershed (1.16 $km^2$) located in the upstream of Gyeongan-cheon watershed, a precise agricultural land use map were prepared using QuickBird satellite image of April 5 of 2003. RUSLE (Revised Universal Soil Loss Equation) was adopted for soil loss estimation. The data (DEM, soil and land use) for the RUSLE were prepared for 5 m and 30 m spatial resolution. The results were compared with each other and the result of 30 m Landsat land use data.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.728-733
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• 2002

The measurement of river discharge is among the most fundamental observations and is necessary for understanding many water-related issues, such as flooding hazards, sediment transportation, and nutrient movement. Traditionally river discharge is estimated by measuring the water stage and converting the measurement to discharge using a stage-discharge rating curve. The possibility of monitoring river discharge from satellites has been largely ignored, because it is difficult to measure water surface information from space with sufficient precision. In this paper, an efficient approach to discharge estimation using mainly satellite data is developed and described. The proposed method, which focuses on the measurement of water-surface width coupled with river width-stage and stage-discharge relationships, is applied to the Yangtze River with good results.

• Proceedings of the KSRS Conference
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• v.2
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• pp.602-605
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• 2006

This study is to apply QuickBird satellite image for the simulation of storm runoff in a small rural watershed. For a 1.05 $km^2$ watershed located in Goesan-Gun of Chungbuk Province, the land use from the QuickBird image was produced by on-screening digitising after ortho-rectifying using 2 m DEM. For 3 cases of land use, soil and elevation scale (1:5,000, 1:25,000 and 1:50,000), SCS (Soil Conservation Service)-CN (Curve Number) and the watershed physical parameters were prepared for the storm runoff model, HEC-HMS (Hydrological Modelling System). The model was evaluated for each case and compared the simulated results with couple of selected storm events.