• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.437-444
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• 2008

In the paper, a methodology is verified to integrate IKONOS-2 satellite imagery and ALS dataset by compensating biases of RPC models. To achieve this, conjugate features from both data should be extracted in advance. For this purpose, linear features are chosen as conjugate features because they can be accurately extracted from man-made structures in urban area and more easily extracted than point features from ALS data. Then, observation equations are established from similarity measurements of the extracted features. During the process, several kinds of transformation functions were selected and used to register them. In addition, it was also analyzed how the number of linear features used as control features affects the accuracy of registration results. Finally, the results were evaluated by using check-points obtained from DGPS surveying techniques and it was clearly demonstrated that the proposed algorithms are appropriate to integrate these data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.2
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• pp.165-172
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• 2003

IKONOS satellite images are particularly well suited for stereo feature extraction. But, because IKONOS doesn't offer information about the satellite ephemeris and attitude, we have to use IKONOS RPC(Rational Polynomial Coefficients) data for 3-D feature extraction. In this study, it was intended to increase the accuracy and the efficiency in application of high resolution satellite images. Therefore, this study develop the program to extract 3-D feature information and have analyzed the geometric accuracy of the IKONOS satellite images by means of the change with the number, distribution and height of GCPs. This study will provide basic information for luther studies of the accuracy correction in IKONOS and high resolution satellite images.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.195-203
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• 2008

Burn severity is an important role for rehabilitation of burned forest area. This factor led to the pilot study to determine if high resolution IKONOS images could be used to classify and delinenate the bum severity over burned areas of Samchock Fire and Cheongyang-Yesan Fire. The results of this study can be summarized as follows: 1. The modified Normalized Bum Ratio (NBR) for IKONOS imagery can be evaluated using burn severity mapping. 2. IKONOS-derived NBR imagery could provide fire scar and detail mapping of burned areas at Samchock fire and Cheongyang-Yesan Burns.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.131-139
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• 2006

IKONOS images have the perspective geometry in CCD sensor line like aerial images with central perspective geometry. So the occlusion by buildings, terrain or other objects exist in the image. It is difficult to detect the occlusion with RPCs(rational polynomial coefficients) for ortho-rectification of image. Therefore, in this study, we detected the occlusion areas in IKONOS images using the nominal collection elevation/azimuth angle and restored the hidden areas using another stereo images, from which the rue ortho image could be produced. The algorithm's validity was evaluated using the geometric accuracy of the generated ortho image.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.253-259
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• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat + ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by National Geographic Information based on aerial photograph and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The classification result by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.331-338
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• 2004

This paper describes capability of utilizing ground control points(GCPs) obtained from 1:1,000 and 1:5,000 digital vector maps to correct image coordinates which have errors due to bais rational polynomial coefficient(RPC) of IKONOS Geo-level stereo images. The accuracy of the bias-corrected images was improved to approximately 4m and 2m in planimetry and height, respectively. The accuracy was also compared with results from using GCPs obtained by GPS surveying. In consequence, bias-compensated IKONOS sereo imagery was evaluated to satisfy generating topographic map 1:10,000.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.221-231
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• 2002

In this study we applied a DEM generation algorithm developed in-house to satellite images at various resolution and discussed the results. We tested SPOT images at l0m resolution, EOC images at 6.6m and IKONOS images at 1m resolution. These images include the same urban area in Daejeon city. For camera model, we used Gupta & Hartley's(1997) DLT model for all three image sets. We carried out accuracy assessment using USGS DTED for SPOT and EOC and 23 check points for IKONOS. The assessment showed that SPOT DEM had about 38m RMS error, EOC DEM 12m RMS error and IKONOS DEM 6.5m RMS error. In terms of image resolution, SPOT and EOC DEM error corresponds to 2∼4 pixels where as IKONOS DEM error 6∼7pixels. IKONOS DEM contains more errors in pixels. However, in IKONOS DEM, individual buildings, apartments and major roads are identifiable. All three DEMs contained errors due to height discontinuity, occlusion and shadow. These experiments show that our algorithm can generate urban DEM from 1m resolution and that, however, we need to improve the algorithm to minimize effects of occlusion and building shadows on DEMs.

• The Korean Journal of Ecology
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• v.26 no.2
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• pp.75-81
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• 2003

This study was performed to prove if the high resolution satellite imagery of IKONOS is suitable for preparing digital vegetation map which is becoming increasingly important in ecological science. Seven classes for forest area and five classes for non-forest area were taken for classification. Three methods, such as the pixel based classification, the segment based classification with majority principle, and the segment based classification with maximum likelihood, were applied to classify IKONOS imagery taken in April 2000. As a whole, the segment based classification shows better performance in classifying the high resolution satellite imagery of IKONOS. Through the comparison of accuracies and kappa values of the above 3 classification methods, the segment based classification with maximum likelihood was proved to be the best suitable for preparing the vegetation map with the help of IKONOS imagery. This is true not only from the viewpoint of accuracy, but also for the purpose of preparing a polygon based vegetation map. On the basis of the segment based classification with the maximum likelihood, a digital vegetation map in which each vegetation class is delimitated in the form of a polygon could be prepared.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.305-309
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• 2009

The object of image fusion is to integrate information from multiple images as the same scene. In the satellite image fusion, many image fusion methods have been proposed for combining a high resolution panchromatic(PAN) image with low resolution multispectral(MS) images and it is very important to preserve both the spatial detail and the spectral information of fusion result. The image fusion method using wavelet transform shows good result compared with other fusion methods in preserving spectral information. This study proposes a modified a'trous algorithm based wavelet image fusion method using IKONOS image. Based on the result of experiment using IKONOS image, we confirmed that proposed method was more effective in preserving spatial detail and spectral information than existing fusion methods using a'trous algorithm.

• 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.