• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.22 no.3
• /
• pp.277-284
• /
• 2004

The subject of this study is to apply experimentally In resolution stereo imagery of IKONOS to producing 1:50,000 scale maps for Munsan area in Paju, being near the Military Demarcation Line, is inaccessible for aerial photography. Ground control points were acquired from GPS surveying to perform geometric corrections on images. Digital maps were produced from IKONOS stereo imagery on the digital photographic workstation. From field investigation, RMS errors of the plane and vertical positions are estimated respectively at $\pm$1.706m and $\pm$1.231m, respectively. These plane and vertical accuracies are within the tolerance limits of those provided in the NGIS Digital Topographic Map Production Rules. Therefore this suggested method is recommended for producing the large scale digital maps of 'No flight' zone near the M.D.L.

• Korean Journal of Remote Sensing
• /
• v.23 no.4
• /
• pp.273-285
• /
• 2007

Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.6
• /
• pp.655-661
• /
• 2020

SGM (Semi Global Matching) can be used to find all the conjugate points between stereo images. Therefore, it enables high-density DSM (Digital Surface Model) production from high-resolution satellite images. However, water, shadows, and occlusion areas cause mismatching of the surrounding points in this method. Particularly, in buildings with large-parallax and elongated-shapes such as a Korean style apartment, it is difficult to reconstruct the 3D building even if the SGM method is applied to a high-resolution 50cm satellite image. This study proposed and performed the SGM technique with a classified image and an edge image from the IKONOS-2 satellite stereo-image with a 1m resolution to produce DSM. It was compared with the DSMs from the general SGM and the high-density ABM (Area Based Matching) matching of ERDAS software. The results of the apartment DSM by the proposed method were the best in the test area. As a result, despite the image having a resolution of 1m, the outline of the building DSM could be expressed more clearly than the existing method.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.627-632
• /
• 2002

One main purpose of environmental monitoring after oil spill is developing ESI (Environmental Sensitivity) Maps. Environmental impacts caused by the spilt oil are strongly depending upon the coastal topology and geology. Monitoring all impacted shorelines is almost impossible; using high-resolution satellite images such as IKONOS greatly contributes to improve the efficiency of on-site researches, at the same time, reliability of ESI maps.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.13 no.1
• /
• pp.89-100
• /
• 2010

The aim of this study is to produce land cover maps using satellite imagery with various degrees of high resolution and then compare the accuracy of the image types and categories. For the land cover map produced on a small-scale classification the estuary area around the Nakdong river, including an urban area, farming land and waters, was selected. The images were classified by analyzing the aerial photos taken from KOMPSAT2, Quickbird and IKONOS satellites, which all have a resolution of over 1m to the naked eye. Once all of the land cover maps with different images and land cover categories had been produced they were compared to each other. Results show that image accuracy from the aerial photos and Quickbird was relatively higher than with KOMPSAT2 and IKONOS. The agreement ratio for the large-scale classification across the classification methods ranged between 0.934 and 0.956 for most cases. The Kappa value ranged between 0.905 and 0.937; the agreement ratio for the middle-scale classification was 0.888~0.913 and the Kappa value was 0.872~0.901. The agreement ratio for the small-scale classification was 0.833~0.901 and the Kappa value was 0.813~0.888. In addition, in terms of the degree of confusion occurrence across the images, there was confusion on the urbanized arid areas and empty land in the large-scale classification. For the middle-scale classification, the confusion mainly occurred on the rice paddies, fields, house cultivating area and artificial grassland. For the small-scale classification, confusion mainly occurred on natural green fields, cultivating land with facilities, tideland and the surface of the sea. The findings of this study indicate that the classification of the high resolution images with the naked eye showed an agreement ratio of over 80%, which means that it can be used in practice. The findings also suggest that the use of higher resolution images can lead to increased accuracy in classification, indicating that the time when the images are taken is important in producing land cover maps.

• Ocean and Polar Research
• /
• v.32 no.1
• /
• pp.53-61
• /
• 2010

The distribution of coral reefs can be an indicator of environmental or anthropogenic impacts. Here, we present a habitat map of coral reefs developed using high-spatial satellite images. The study area was located on the north-eastern part of Weno island, in the Chuuk lagoon of Federated States of Micronesia. Two fieldwork expeditions were carried out between 2007 and 2008 to acquire optical and environmental data from 121 stations. We used an IKONOS image obtained in December 2000, and a Kompsat-2 image obtained in September 2008 for the purpose of coral reef mapping. We employed an adapted version of the object-based classification method for efficient classification of the high-spatial satellite images. The habitat map generated using Kompsat-2 was 72.22% accurate in terms of comparative analysis with in-situ measurements. The result of change detection analysis between 2000 and 2008 showed that coral reef distribution had decreased by 6.27% while seagrass meadows had increased by 8.0%.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.631-634
• /
• 2006

Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.

• Journal of the Korean association of regional geographers
• /
• v.9 no.3
• /
• pp.385-394
• /
• 2003

Authors tried to classify landforms of civilian-restricted trans-border coastal region of the East Sea by using both field survey and remote sensing data including IKONOS images and digital maps. As a result, authors can draw the boundaries of landform units on satellite images and classify landforms effectively. Typical landforms of undisturbed depositional coastal area such as coastal sand dune, sand bar, lagoons, and tombolo are found within the study area. Also, riverine wetlands and estuarine wetlands are readily discernable on both satellite image and field survey. Even though landforms within the study area are relatively small, they are so dynamically connected that their preservation value is very high.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.525-527
• /
• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

• Korean Journal of Remote Sensing
• /
• v.24 no.3
• /
• pp.257-266
• /
• 2008

This study presents an approach to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. The synthesized images should be similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme is designed to reconstruct the multispectral images at the higher resolution with as less color distortion as possible. It uses a regression model of the second order to fit panchromatic data to multispectral observations. Based on the regression model, the multispectral images at the higher spatial resolution of the panchromatic image are optimized by a quadratic programming. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement over other methods.