• Title/Summary/Keyword: Ground control points (GCP)

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Extraction of Ground Control Point (GCP) from SAR Image

  • Hong, S.H.;Lee, S.K.;Won, J.S.;Jung, H.S.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1058-1060
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    • 2003
  • A ground control point (GCP) is a point on the surface of Earth where image coord inates and map coordinates can be identified. The GCP is useful for the geometric correction of systematic and unsystematic errors usually contained in a remotely sensed data. Especially in case of synthetic aperture radar (SAR) data, it has serious geometric distortions caused by inherent side looking geometry. In addition, SAR images are usually severely corrupted by speckle noises so that it is difficult to identify ground control points. We developed a ground point extraction algorithm that has an improved capability. An application of radargrammetry to Daejon area in Korea was studied to acquire the geometric information. For the ground control point extraction algorithm, an ERS SAR data with precise Delft orbit information and rough digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map and GPS survey data.

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GCP Placement Methods for Improving the Accuracy of Shoreline Extraction in Coastal Video Monitoring

  • Changyul Lee;Kideok Do;Inho Kim;Sungyeol Chang
    • Journal of Ocean Engineering and Technology
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    • v.38 no.4
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    • pp.174-186
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    • 2024
  • In coastal video monitoring, the direct linear transform (DLT) method with ground control points (GCPs) is commonly used for geo-rectification. However, current practices often overlook the impact of GCP quantity, arrangement, and the geographical characteristics of beaches. To address this, we designed scenarios at Chuam Beach to evaluate how factors such as the distance from the camera to GCPs, the number of GCPs, and the height of each point affect the DLT method. Accuracy was assessed by calculating the root mean square error of the distance errors between the actual GCP coordinates and the image coordinates for each setting. This analysis aims to propose an optimal GCP placement method. Our results show that placing GCPs within 200 m of the camera ensures high accuracy with few points, whereas positioning them at strategic heights enhances shoreline extraction. However, since only fixed cameras were used in this study, factors like varying heights, orientations, and resolutions could not be considered. Based on data from a single location, we propose an optimal method for GCP placement that takes into account distance, number, and height using the DLT method.

The Operational Comparison of SPOT GCP Acquisition and Accuracy Evaluation

  • Kim, Kam-Lae;Kim, Uk-Nam;Chun, Ho-Woun;Lee, Ho-Nam
    • Korean Journal of Geomatics
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    • v.1 no.1
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    • pp.1-5
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    • 2001
  • This paper presents an investigation into the operational comparison of SPOT triangulation to build GCP library by analytical plotter and DPW (digital photogrammetric workstation). GCP database derived from current SPOT images can be used to other image sensors of satellite, if any reasons, such as lack of topographic maps or GCPs. But, general formulation of a photogrammetric process for GCP measurement has to take care of the scene interpretation problem. There are two classical methods depending on whether an analytical plotter or DPW is being used. Regardless of the method used, the measurement of GCPs is the weakest point in the automation of photogrammetric orientation procedures. To make an operational comparison, five models of SPOT panchromatic images (level 1A) and negative films (level 1AP) were used. Ten images and film products were used for the five GRS areas. Photogrammetric measurements were carried out in a manual mode on P2 analytical plotter and LH Systems DPW770. We presented an approach for exterior orientation of SPOT images, which was based on the use of approximately eighty national geodetic control points as GCPs which located on the summit of the mountain. Using sixteen well-spaced geodetic control points per model, all segments consistently showed RMS error just below the pixel at the check points in analytical instrument. In the case of DPW, half of the ground controls could not found or distinguished exactly when we displayed the image on the computer monitor. Experiment results showed that the RMS errors with DPW test was fluctuated case by case. And the magnitudes of the errors were reached more than three pixels due to the lack of image interpretation capability. It showed that the geodetic control points is not suitable as the ground control points in DPW for modeling the SPOT image.

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Three-Dimensional Positional Accuracy Analysis of UAV Imagery Using Ground Control Points Acquired from Multisource Geospatial Data (다종 공간정보로부터 취득한 지상기준점을 활용한 UAV 영상의 3차원 위치 정확도 비교 분석)

  • Park, Soyeon;Choi, Yoonjo;Bae, Junsu;Hong, Seunghwan;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1013-1025
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    • 2020
  • Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

AUTOMATIC PRECISION CORRECTION OF SATELLITE IMAGES

  • Im, Yong-Jo;Kim, Tae-Jung
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.40-44
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    • 2002
  • Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

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Bundle Adjustment of Aerial Photographs using GCP Image Chip (영상칩 지상기준점을 이용한 항공사진 번들조정)

  • 김기홍;손홍규;김호성;백종하;이재원
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.11a
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    • pp.239-243
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    • 2004
  • Recently various thematic maps and image maps using aerial photograph and satellite imagery are frequently made. The geo-referencing is essential to make image map and topographic map using aerial photograph and satellite imagery. For this geo-referencing, Ground Control Points (GCPs) are needed. In this paper, we used GPS relative positioning to measure GCP ground coordinate and the accuracy of 8cm level was achieved. We made GCP image chips for the efficiency of geo-referencing and carried out the bundle adjustment of aerial photographs using GCP image chips to acquire the GCP photo coordinate with image matching technique. Finally we analyzed the accuracy of bundle adjustment compared to the accuracy of the case in using digital maps to acquire GCP photo coordinate.

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Acquiring Precise Coordinates of Ground Targets through GCP Geometric Correction of Captured Images in UAS (무인 항공 시스템에서 촬영 영상의 GCP 기하보정을 통한 정밀한 지상 표적 좌표 획득 방법)

  • Namwon An;Kyung-Mee Lim;So-Young Jeong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.2
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    • pp.129-138
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    • 2023
  • Acquiring precise coordinates of ground targets can be regarded as the key mission of the tactical-level military UAS(Unmanned Aerial System) operations. The coordinates deviations for the ground targets estimated from UAV (Unmanned Aerial Vehicle) images may depend on the sensor specifications and slant ranges between UAV and ground targets. It has an order of several tens to hundreds of meters for typical tactical UAV mission scenarios. In this paper, we propose a scheme that precisely acquires target coordinates from UAS by mapping image pixels to geographical coordinates based on GCP(Ground Control Points). This scheme was implemented and tested from ground control station for UAS. We took images of targets of which exact location is known and acquired the target coordinates using our proposed scheme. The experimental results showed that errors of the acquired coordinates remained within an order of several meters and the coordinates accuracy was significantly improved.

Quality Assessment of Digital Surface Model Vertical Position Accuracies by Ground Control Point Location (지상기준점 선점 위치에 따른 DSM 높이 정확도 분석)

  • Lee, Jong Phil
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.1
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    • pp.125-136
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    • 2021
  • Recently, Unmanned Aerial Vehicle utilization and image processing technology for remote sensing have diversified remarkably with Orthophoto and Digital Surface Model. In particular, It uses more application fields such as spatial information analysis and hazardous areas as well as land surveying. This study analyses the accuracy of the coordinate on Orthophoto and DSM height on slope area with high and low differences by using UAV images. As the result of this study, in the case of GCP on 2D orthophoto, the location error was not produced significantly. The vertical position of the DSM showed the highest accuracy when the height difference between GCPs is under 30m(RMSEZ=0.07m). The location of the GCPs was divided into approximately 10m, 20m, 30m, and 40m with analysis for each of the eight points of GCP and inspection points in general. This study expects that producing both horizontal accuracy of Orthophoto and vertical accuracy of DSM using UAV on the sloped area which similar to this research area will help in spatial information fields.

A STUDY ON DEM GENE]RATON USING POLYNOMIAL CAMERA MODEL IN SATELLITE IMAGERY

  • Jeon, Seung-Hun;Kim, Sung-Chai;Lee, Heung-Jae;Lee, Kae-hei
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.518-523
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    • 2002
  • Nowadays the Rational Function Model (RFM), an abstract sensor model, is substituting physical sensor models for highly complicated imaging geometry. But RFM is algorithm to be required many Ground Control Points (GCP). In case of RFM of the third order, At least forty GCP are required far RFM generation. The purpose of this study is to research more efficient algorithm on GCP and accurate algorithm similar to RFM. The Polynomial Camera Model is relatively accurate and requires a little GCP in comparisons of RFM. This paper introduces how to generate Polynomial Camera Model and fundamental algorithms for construction of 3-D topographic data using the Polynomial Camera Model information in the Kompsat stereo pair and describes how to generate the 3-D ground coordinates by manual matching. Finally we tried to extract height information for the whole image area with the stereo matching technique based on the correlation.

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TIN Based Geometric Correction with GCP

  • Seo, Ji-Hun;Jeong, Soo;Kim, Kyoung-Ok
    • Korean Journal of Remote Sensing
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    • v.19 no.3
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    • pp.247-253
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    • 2003
  • The mainly used technique to correct satellite images with geometric distortion is to develop a mathematical relationship between pixels on the image and corresponding points on the ground. Polynomial models with various transformations have been designed for defining the relationship between two coordinate systems. GCP based geometric correction has peformed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The Region with highly variant height is rectified with distortion on overall plane mapping. To consider locally variable region in satellite image, TIN-based rectification on a satellite image is proposed in this paper. This paper describes the relationship between GCP distribution and rectification model through experimental result and analysis about each rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.