• 대한원격탐사학회지
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• 제24권5호
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• pp.483-496
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• 2008

Qualified ground control points (GCPs) are required to construct a digital elevation model (DEM) from a pushbroom stereo pair. An inverse geolocation algorithm for extracting GCPs from ERS SAR data and the SRTM DEM was recently developed. However, not all GCPs established by this method are accurate enough for direct application to the geometric correction of pushbroom images such as SPOT, IRS, etc, and thus a method for selecting and removing inaccurate points from the sets of GCPs is needed. In this study, we propose a method for evaluating GCP accuracy and winnowing sets of GCPs through orientation modeling of pushbroom image and validate performance of this method using SPOT stereo pair of Daejon City. It has been found that the statistical distribution of GCP positional errors is approximately Gaussian without bias, and that the residual errors estimated by orientation modeling have a linear relationship with the positional errors. Inaccurate GCPs have large positional errors and can be iteratively eliminated by thresholding the residual errors. Forty-one GCPs were initially extracted for the test, with mean the positional error values of 25.6m, 2.5m and -6.1m in the X-, Y- and Z-directions, respectively, and standard deviations of 62.4m, 37.6m and 15.0m. Twenty-one GCPs were eliminated by the proposed method, resulting in the standard deviations of the positional errors of the 20 final GCPs being reduced to 13.9m, 8.5m and 7.5m in the X-, Y- and Z-directions, respectively. Orientation modeling of the SPOT stereo pair was performed using the 20 GCPs, and the model was checked against 15 map-based points. The root mean square errors (RMSEs) of the model were 10.4m, 7.1m and 12.1m in X-, Y- and Z-directions, respectively. A SPOT DEM with a 20m ground resolution was successfully constructed using a automatic matching procedure.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.275-278
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• 2004

The geo-referencing of satellite imagery is a key task in remote sensing. GCPs are points the position of which is known both in the image and in the supporting maps. Mapping function makes the determination of map coordinates of all image pixels possible. Generally manual operations are done to identify image points corresponding to the points on a digital topographic map. In order to accurately measure ground coordinates of GCPs, differential global positioning system (DGPS) surveying are used. To acquire the sufficient number of well distributed GCPs is one of the most time-consuming and cost-consuming tasks. This paper describes the procedure of automatically extracting GCOs using GCP database. GCP image chips and image matching technique are used for automatic extraction of GCPs. We developed image processing tool for making image chip GCPs and Web Server for management of GCPs.

• 한국측량학회지
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• 제21권4호
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• pp.301-308
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• 2003

본 논문은 IKONOS 입체영상과 RPC(Rational Polynomial Coefficients) 모델을 이용하여 3차원 지형자료를 추출할 경우, 추출되는 3차원 지형자료의 정확도를 향상시키기 위하여 RPC모델의 위치정확도를 보정하는 연구를 수행하였다. 이를 위하여 지상기준점을 활용하여 RPC 모델의 보정을 시도할 경우, 지상기준점의 지역적인 분포 및 사용되는 개수가 보정되는 RPC 모델의 위치정확도 향상에 어떠한 영향을 미치는지를 검증하였다. 실험결과 사용되는 지상기준점의 개수보다는 지상기준점의 분포상태가 보정되는 RPC 모델의 위치정확도에 미치는 영향이 더 크다는 것을 확인할 수 있었다. 또한, 분포상태가 고른 지상기준점을 사용하여 본 연구에서 사용한 알고리즘을 적용할 경우에 안정적으로 위치정확도가 향상된 RPC 모델을 획득할 수 있음을 알 수 있었다. 수행된 연구결과를 토대로 지상기준점의 분포가 좋지 않거나 사용 가능한 지상기준점의 개수가 부족한 경우, 이를 극복하기 위해 의사지상기준점을 활용하는 알고리즘에 관한 연구도 수행하였다. 실험 결과에 따르면 지역적으로 좋지 않은 분포를 보이는 지상기준점들을 활용한 경우에도 의사지상기준점을 활용하면 원래의 RPC 모델보다 위치정확도가 향상된 RPC 모델을 얻을 수 있었다. 그리고 적은 수의 의사지상기준점을 활용할수록 즉, 지상기준점에 대한 가중치를 더 높일수록 정확도가 높은 RPC 모델을 획득할 수 있었다. 마지막으로, 본 연구에서 개발된 알고리즘들을 적용하여 RPC 모델의 위치정확도를 보정하고 이를 이용하여 3차원 지형좌표를 추출하였다. 정확도평가 결과 원래의 RPC 모델을 사용하여 추출된 3차원 지형좌표보다 정확도가 향상된 3차원 지형좌표의 취득이 가능하였다. 이는 본 연구에서 개발한 알고리즘들의 효용성을 입증하는 결과라 사료된다.

• 한국측량학회지
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• 제35권4호
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• pp.241-248
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• 2017

GCPs (Ground Control Points) are needed to correct the DEM (Digital Elevation Model) produced from high-resolution satellite images and the RPC (Rational Polynomial Coefficient). It is difficult to acquire the GCPs through field surveys such as GPS surveys and to read the image coordinates corresponding to the GCPs. In addition, GCPs cannot cover the entire image of the test site, and the RPC correction results may be influenced by the arrangement and distribution of the GCPs in the image. Therefore, a new method for the RPC correction is needed. In this study, an LHD (Least-squares Height Difference) DEM matching method was applied using previous DEMs: SRTM DEM, digital map DEM, and corrected IKONOS DEM. This was carried out to correct the DEM produced from KOMPSAT-3 satellite images and the provided RPC without GCPs. The IKONOS DEM had the highest accuracy, and the height accuracy was about ${\pm}3m$ RMSE in a mountainous area and about ${\pm}2m$ RMSE in an area with only low heights.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.328-331
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• 2008

It is possible to extract qualified ground control points (GCPs) solely from SAR data without published maps. TerraSAR-X is now in orbit and provides valuable data that have one of the highest spatial resolutions among civilian SAR systems. In this study, a sophisticated method for GCP coordinate extraction from TerraSAR-X stripmap mode data with a 3 m resolution was tested and the quality of the extracted GCPs was evaluated. An inverse-geolocation algorithm was applied to obtain GCPs from TerraSAR-X data. SRTM 90m DEM was used as an auxiliary data set for azimuth time correction of the SAR data. Mean values of the distance errors were 0.11 m and -3.96 m with standard deviations of 6.52 m and 5.11 m in easting and northing, respectively. The result is one of the best among GCPs possibly extracted from current civilian remote sensing systems. The extracted GCPs were used for geo-rectification of an IKONOS image, which demonstrated the applicability of the GCPs to geo-rectification of high resolution optic image. The method used in this study can be applied to KOMPSAT-5 for geo-rectification of high-resolution optic images acquired by KOMPSAT-2 or follow-up missions.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.186-191
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• 1998

The first step in change detection in any SAR monitoring, including SAR interferometry, is the co-registration of the images. CCPs (Ground Control Points) for co-registration are usually detected manually, but for qualitative analyses of enormous volumes of data, some automation of the process will become necessary. An automated determination of common CCPs for the same path/row data is especially desirable. We selected the intersections of linear features as the candidates of common GCPs Very bright point targets, which are commonly used as GCPs, have the drawback of appearing and disappearing depending on the conditions of the observation. But in the case of linear features, some detailed elements may appear differently in some case, but the overall line-likeness will remain. In this study, we selected 18 common GCPs for a single-look JERS-1 SAR image of Omaezaki area in central Japan. Although the GCPs in the first image had to be selected either interactively or semi-automatically, the same GCPs in all other images were successively detected automatically using a tiny sub-image around each GCP and a dilated mask of each linear feature in the first image as the reference data.

• 대한공간정보학회지
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• 제15권4호
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• pp.103-109
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• 2007

고해상도 위성영상으로부터 수치고도자료와 정사영상을 생성하기 위해서는 센서모델을 수립해야 한다. 센서모델 수립에 필요한 지상기준점은 실측을 통해서 획득할 수 있지만, 이를 위해서는 많은 시간과 비용이 소요된다. 본 연구에서는 기존의 정사영상과 위성영상 간의 정합을 통해서 얻은 지상좌표와 그에 대응하는 높이를 Digital Terrain Elevation(DTED) Level 2 자료로부터 추출하여 IKONOS 위성영상 센서모델을 수립하기 위한 기준점을 획득하였다. 획득한 기준점으로 IKONOS 센서 모델을 수립하고 그 결과를 분석하여 이로부터 추출한 기준점이 IKONOS 위성영상의 센서모델 수립에 적합한지 여부를 알아보았다. 본 연구를 위해서 사용된 DTED Level 2는 공간해상도가 약30m이고, 절대 수평 정확도는 원형오차로 23m(WGS84 기준)이하이고 절대 수직 정확도가 평균해수면 기준으로 18m 이하인 수치고도모델이다. 정합에 사용된 기존 정사영상의 공간해상도는 1m이다. 본 연구에서는 DTED와 정사영상을 이용해서 추출한 기준점으로 수립한 IKONOS 센서모델의 성능을 분석하였다. 실측 기준점을 검사점으로 했을 때 수립된 모델의 독립적 성능은 약 $4{\sim}5$ 픽셀 정도였다. 또한 수치고도모델을 생성하고 이를 실측 기준점으로 생성한 수치고도모델과 육안으로 비교했을 때 서로 유사함을 알 수 있었으며, DTED 자료를 기준으로 산출한 높이 RMS 오차는 약 9 m였다. 이 결과로 보아 DTED Level 2와 정사영상을 이용해서 추출한 기준점이 IKONOS 센서 모델 수립에 적용될 수 있음을 알 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.667-670
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• 2005

Ground control points(GCPs) can be extracted from SAR data given precise orbit for DTM generation using optic images and other SAR data. In this study, we extract GCPs from ERS SAR data and SRTM DEM. Although it is very difficult to identify GCPs in ERS SAR image, the geometry of optic image and other SAR data are able to be corrected and more precise DTM can be constructed from stereo optic images. Twenty GCPs were obtained from the ERS SAR data with precise Delft orbit information. After the correction was applied, the mean values of planimetric distance errors of the GCPs were 3.7m, 12.1 and -0.8m with standard deviations of 19.9m, 18.1, and 7.8m in geocentric X, Y, and Z coordinates, respectively. The geometries of SPOT stereo pair were corrected by 13 GCPs, and r.m.s. errors were 405m, 705m and 8.6m in northing, easting and height direction, respectively. And the geometries of RADARS AT stereo pair were corrected by 12 GCPs, and r.m.s. errors were 804m, 7.9m and 6.9m in northing, easting and height direction, respectively. DTMs, through a method of area based matching with pyramid images, were generated by SPOT stereo images and RADARS AT stereo images. Comparison between points of the obtained DTMs and points estimated from a national 1 :5,000 digital map was performed. For DTM by SPOT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. For DTM by RADARSAT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. These results met the accuracy of DTED level 2

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.252-256
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• 1998

Accurate mapping of satellite images is one of the most important Parts in many remote sensing applications. Since the position and the attitude of a satellite during image acquisition cannot be determined accurately enough, it is normal to have several hundred meters' ground-mapping errors in the systematically corrected images. The users which require a pixel-level or a sub-pixel level mapping accuracy for high-resolution satellite images must use a number of Ground Control Points (GCPs). In this paper, the performance of two geometric correction algorithms is tested and compared. One is the polynomial warping algorithm which is simple and popular enough to be implemented in most of the commercial satellite image processing software. The other is full camera modelling algorithm using Physical orbit-sensor-Earth geometry which is used in satellite image data receiving, pre-processing and distribution stations. Several criteria were considered for the performance analysis : ultimate correction accuracy, GCP representatibility, number of GCPs required, convergence speed, sensitiveness to inaccurate GCPs, usefulness of the correction results. This paper focuses on the usefulness of the precision correction algorithm for regular image pre-processing operations. This means that not only final correction accuracy but also the number of GCPs and their spatial distribution required for an image correction are important factors. Both correction algorithms were implemented and will be used for the precision correction of KITSAT-3 images.

• 한국측량학회지
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• 제20권2호
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• pp.165-170
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• 2002

다목적 실용위성영상을 이용하여 지리정보를 얻기 위해서는 영상의 기하보정이 필수적이지만 현지접근 불능지역은 지상기준점을 획득하기가 어렵고, 지도 독취를 통하여 획득한 지상기준점은 부정확하다. 일반적으로 시스템기하보정은 위성궤도요소 및 자세요소를 이용하나, 이 방법은 위성영상의 절대위치오차를 크게 향상시키지 못한다. 이러한 단점을 보완하기 위하여 본 논문에서는 가상 접근 불능지역과 접근 가능지역을 포함한 영상을 이용하여 접근 가능지역에서 GPS로부터 획득된 지상기준점만으로 편향적인 기하보정을 수행한 후 오차추이분석을 통한 영상좌표의 상대정확도 향상기법을 제시하였다.