• 제목/요약/키워드: High-resolution Satellite imagery

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Matching Performance Analysis of Upsampled Satellite Image and GCP Chip for Establishing Automatic Precision Sensor Orientation for High-Resolution Satellite Images

  • Hyeon-Gyeong Choi;Sung-Joo Yoon;Sunghyeon Kim;Taejung Kim
    • 대한원격탐사학회지
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    • 제40권1호
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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.

An Implementation of Change Detection System for High-resolution Satellite Imagery using a Floating Window

  • Lim, Young-Jae;Jeong, Soo;Kim, Kyung-Ok
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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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.

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VARIOGRAM-BASED URBAN CHARACTERIZATION USING HIGH RESOLUTION SATELLITE IMAGERY

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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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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3D BUILDING INFORMATION EXTRACTION FROM A SINGLE QUICKBIRD IMAGE

  • Kim, Hye-Jin;Han, Dong-Yeob;Kim, Yong-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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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.

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Automatic Road Extraction by Gradient Direction Profile Algorithm (GDPA) using High-Resolution Satellite Imagery: Experiment Study

  • Lee, Ki-Won;Yu, Young-Chul;Lee, Bong-Gyu
    • 대한원격탐사학회지
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    • 제19권5호
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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.

REAL-TIME 3D SIMULATION INFRASTRUCTURE FOR PRACTICAL APPLICATION OF HIGH-RESOLUTION SATELLITE IMAGERY

  • Yoo, Byoung-Hyun;Brotzman, Don;Han, Soon-Hung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.155-158
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    • 2008
  • The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain, and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.

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고해상도 정사위성영상을 이용한 임상도 수정에 관한 연구 (A Study of on the Forest Map Update Using Orthorecified High Resolution Satellite Imagery Data)

  • 성천경;조정호
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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    • pp.571-577
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    • 2004
  • 다중분광 해상도를 가진 고해상도 위성영상의 이용으로 인해, 임상도 제작 부분에 있어 기존 전통적인 방법의 단점을 보완할 수 있어 고해상도 위성영상을 이용함으로써 효과적으로 임상도 수정이 이루어질 것으로 판단된다 본 연구에서는 1m 공간해상도와 4밴드의 분광해상도를 가진 고해상도 인공위성 영상 데이터를 이용하여 제작된 임상도에 있어 일부 수정 부분이 가능하였다. 따라서 고해상도 위성영상이 차후 효과적인 임상도 수정에 사용될 수 있으리라 판단된다.

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고해상도위성영상에서 도로 경계 검출을 위한 고주파와 저주파 필터링 비교분석에 관한 연구 (Comparative Analysis of LPF and HPF for Roads Edge Detection from High Resolution Satellite Imagery)

  • 최현;강인준
    • 대한공간정보학회지
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    • 제14권3호
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    • pp.3-11
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    • 2006
  • 최근 고해상도 위성영상이 다양한 분야에서 활발하게 이용하게 됨에 따라 지형자료의 정확한 경계검출에 대한 필요성이 대두되고 있다. 위성영상을 이용한 도로 경계 검출은 교통정보시스템을 포함한 도로계획, 도시계획 등의 지형 공간정보의 필수 연구로 인식되고 있다. 본 연구는 IKONOS 영상에서 도로 경계 검출을 위한 고주파와 저주파 필터링 비교분석에 관한 연구이다. 분석결과 저주파 필터링과 고주파 필터링은 입력영상의 경계부분에서 영상을 선택적으로 강조할 수 있었다. 저주파 필터링과 같은 영상강화 기법에서는 추출 가능한 경계부의 위치를 변화시키거나 영상의 화소값이 전체영상을 대상으로 변화시켜 비교적 도로 폭이 넓은 경우 효과적이었다. 고주파 필터링은 세부적인 영상정보를 선택적으로 강조할 수 있었다.

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Development of Feature-based Classification Software for High Resolution Satellite Imager

  • Jeong, Soo;Kim, Kyung-Ok;Jeong, Sang-Yong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1111-1113
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    • 2003
  • In this paper, we investigated a method for feature - based classification to develop software which is suitable to the classification of high resolution satellite imagery . So, we developed related algorithm and designed user interfaces of convenience, considering various elements require for the feature - based classification. The software was tested with eCognition software which is unique commercial software for feature - based classification.

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A building roof detection method using snake model in high resolution satellite imagery

  • Ye Chul-Soo;Lee Sun-Gu;Kim Yongseung;Paik Hongyul
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.241-244
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    • 2005
  • Many building detection methods mainly rely on line segments extracted from aerial or satellite imagery. Building detection methods based on line segments, however, are difficult to succeed in high resolution satellite imagery such as IKONOS imagery, for most buildings in IKONOS imagery have small size of roofs with low contrast between roof and background. In this paper, we propose an efficient method to extract line segments and group them at the same time. First, edge preserving filtering is applied to the imagery to remove the noise. Second, we segment the imagery by watershed method, which collects the pixels with similar intensities to obtain homogeneous region. The boundaries of homogeneous region are not completely coincident with roof boundaries due to low contrast in the vicinity of the roof boundaries. Finally, to resolve this problem, we set up snake model with segmented region boundaries as initial snake's positions. We used a greedy algorithm to fit a snake to roof boundary. Experimental results show our method can obtain more .correct roof boundary with small size and low contrast from IKONOS imagery. Snake algorithm, building roof detection, watershed segmentation, edge-preserving filtering

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