• 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.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.275-279
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• 2002

Change Detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, Change Detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by low- or middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• 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.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.103-114
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• 2024

The escalating demands for high-resolution satellite imagery necessitate the dissemination of geospatial data with superior accuracy.Achieving precise positioning is imperative for mitigating geometric distortions inherent in high-resolution satellite imagery. However, maintaining sub-pixel level accuracy poses significant challenges within the current technological landscape. This research introduces an approach wherein upsampling is employed on both the satellite image and ground control points (GCPs) chip, facilitating the establishment of a high-resolution satellite image precision sensor orientation. The ensuing analysis entails a comprehensive comparison of matching performance. To evaluate the proposed methodology, the Compact Advanced Satellite 500-1 (CAS500-1), boasting a resolution of 0.5 m, serves as the high-resolution satellite image. Correspondingly, GCP chips with resolutions of 0.25 m and 0.5 m are utilized for the South Korean and North Korean regions, respectively. Results from the experiment reveal that concurrent upsampling of satellite imagery and GCP chips enhances matching performance by up to 50% in comparison to the original resolution. Furthermore, the position error only improved with 2x upsampling. However,with 3x upsampling, the position error tended to increase. This study affirms that meticulous upsampling of high-resolution satellite imagery and GCP chips can yield sub-pixel-level positioning accuracy, thereby advancing the state-of-the-art in the field.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.547-552
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• 2007

This study presents an approach to reconstruct high-resolution imagery for multispectral imagery of low-resolution using panchromatic imagery of high-resolution. The proposed scheme reconstructs a high-resolution image which agrees with original spectral values. It uses a linear model of high-and low- resolution images and consists of two stages. The first one is to perform a global estimation of the least square error on the basis of a linear model of low-resolution image associated with high-resolution feature, and next local correction then makes the reconstructed image locally fit to the original spectral values. In this study, the new method was applied to KOMPSAT-1 EOC image of 6m and LANDSAT ETM+ of 30m, and an 1m RGB image was also generated from 4m IKONOS multispectral data. The results show its capability to reconstruct high-resolution imagery from multispectral data of low-resolution.

• Proceedings of the KSRS Conference
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• v.1
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• pp.409-412
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.137-139
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• 2008

This study presents an approach to reconstruct high-resolution imagery for multispectral imagery of low-resolution using panchromatic imagery of high-resolution. The proposed scheme reconstructs a high-resolution image which agrees with original spectral values. It uses a linear model of high-and low- resolution images and consists of two stages. In this study, an 1m RGB image was generated from 4m IKONOS multispectral data.

• Korean Journal of Remote Sensing
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• v.18 no.5
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• pp.263-271
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• 2002

Recently, spatial information technologies using remotely sensed imagery and functionality of GIS (Geographic Information Systems) have been widely utilized to various types of transportation-related applications. In this study, extraction programs of some practical indices, to be effectively used in transportation reference planning problem, were designed and implemented as prototyped extensions in GIS development environment: traffic flow estimation (TFL/TFB), urban rural index (URI), and accessibility index (AI). In TFL/TFB, user can obtain quantitative results on traffic flow estimation at link/block using high-resolution satellite imagery. Whereas, URI extension provides urban-rural characteristics related to road system, being considered one of important factors in transportation planning. Lastly, AI extension helps to obtain accessibility index between nodes of road segments and surrounding district areas touched or intersected with the road network system, and it also provides useful information for transportation planning problems. This approach is regarded as one of RS-T (Remote Sensing in Transportation), and it is expected to expand as new application of remotely sensed imagery.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.357-366
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• 2006

A traditional image analysis or classification method using satellite imagery is mostly based on the spectral information. However, the spatial information is more important according as the resolution is higher and spatial patterns are more complex. In this study, we attempted to compare and analyze the variogram properties of actual high resolution imageries mainly in the urban area. Through the several experiments, we have understood that the variogram is various according to a sensor type, spatial resolution, a location, a feature type, time, season and so on and shows the information related to a feature size. With simple modeling, we confirmed that the unique variogram types were shown unlike the classical variogram in case of small subsets. Based on the grasped variogram characteristics, we made a level index map for determining urban complexity or land-use classification. These results will become more and more important and be widely applied to the various fields of high-resolution imagery such as KOMPSAT-2 and KOMPSAT-3 which is scheduled to be launched.