• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.197-202
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• 2004

Recent researches have shown that IKONOS Geo imagery is capable of pixel-level geopositioning accuracy. However, a large number of ground control points(GCPs) are required in this case. For reducing the number of GCPs, users try to use the vender-supplied RPCs with Geo imagery. But, the biases included in RPCs give rise to absolute positioning error of about 25m as well known. In this paper, a method for the compensation of biases in rational polynomial coefficients(RPCs) for IKONOS Geo imagery is developed. the method requires provision of one or two GCPs to generate the compensated RPCs, and the analysis result of practical testing represents two or three pixels accuracy from IKONOS Geo imagery in case of using only compensated RPCs without GCPs.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1143-1145
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• 2003

Some of satellites such as IKONOS don't provide the orbital elements so that we can’ utilize the physical sensor model. Therefore, Rational Function Model(RFM) which is one of mathematical models could be a feasible solution. In order to improve 3D geopositioning accuracy of IKONOS stereo imagery, Rational Polynomial Coefficients(RPCs) of the RFM need to be updated with Ground Control Points(GCPs). In this paper, a method to improve RPCs of RFM using GCPs and 3D cube is proposed. Firstly, the image coordinates of GCPs are observed. And then, using offset values and scale values of RPC provided, the image coordinates and ground coordinates of 3D cube are initially determined and updated RPCs are computed by the iterative least square method. The proposed method was implemented and analyzed in several cases: different numbers of 3D cube layers and GCPs. The experimental results showed that the proposed method improved the accuracy of RPCs in great amount.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.344-346
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• 2004

IKONOS 1m satellite imagery is particularly well suited for 3-D feature extraction and 1 :5,000 scale topographic mapping. Because the image line and sample calculated by given RPCs have the error of more than 11m, in order to be able to perform feature extraction and topographic mapping, rational polynomial coefficients(RPCs) camera model that are derived from the very complex IKONOS sensor model to describe the object-image geometry must be refined by several Ground Control Points(GCPs). This paper presents a quantitative evaluation of the geometric accuracy that can be achieved with IKONOS imagery by refining the offset and scaling factors of RPCs using several GCPs. If only two GCPs are available, the offsets and scale factors of image line and sample are updated. If we have more than three GCPs, four parameters of the offsets and scale factors of image line and sample are refined first, and then six parameters of the offsets and scale factors of latitude, longitude and height are updated. The stereo images acquired by IKONOS satellite are tested using six ground points. First, the RPCs model was refined using 2 GCPs and 4 check points acquired by GPS. The results from IKONOS stereo images are reported and these show that the RMSE of check point acquired from left images and right are 1.021m and 1.447m. And then we update the RPCs model using 4 GCPs and 2 check points. The RMSE of geometric accuracy is 0.621 m in left image and 0.816m in right image.

• Spatial Information Research
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• v.18 no.5
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• pp.37-45
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• 2010

AT(Aerial Triangulation) is the essential procedure for creating orthophoto and transforming coordinates on the photographs into the real world coordinates utilizing GCPs (Ground Control Point) which is obtained by field survey and the external orientation factors from GPS/INS as a reference coordinates. In this procedure, all of the GCPs can be collected from field survey using GPS and Total Station, or obtained from digital maps. Collecting GCPs by field survey is accurate than GCPs from digital maps; however, lots of manpower should be put into the collecting procedure, and time and cost as well. On the other hand, in the case of obtaining GCPs from digital maps, it is very difficult to secure the required accuracy because almost things at each stage in the collecting procedure should rely on the subjective judgement of the performer. In this study, the results from three methods have been compared for the accuracy assessment in order to know if the results of each case is within the allowance error: for the perceivable objects such as road boarder, speed bumps, constructions etc., 1) GCPs selection utilizing the unique LiDAR intensity value reflected from such objects, 2) using LiDAR DSM and 3) GCPs from field survey. And also, AT and error analysis have been carried out w ith GCPs obtained by each case.

• Journal of The Geomorphological Association of Korea
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• v.28 no.4
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• pp.41-52
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• 2021

With the popularization of drones and the ease of use of the Global Navigation Satellite System (GNSS), drone photogrammetry for terrain information has been widely used. Drone photogrammetry enables the realization of high-accuracy three-dimensional topography for the entire area with less effort and time compared to the past direct survey using GNSS or total station. From 3-D topographic data, various topographical analysis is possible. To improve the accuracy of drone photogrammetry, direct GCP surveying in the field is essential, and the numbers and reasonable positioning of GCPs are very important. In the case of beaches or tidal flats on the west coast of Korea, the numbers and location of GCPs are important factors in efficient drone photogrammetry because of the size of the area, difficulties of movement, and the risk from tides. If the RTK (Real-time kinematic) or PPK (Post-processed kinematic) method is used, the increased accuracy of the drone's location enables high-accuracy photogrammetry with a small number of GCPs. This study presents an efficient drone photogrammetry method in terms of time and economy by comparing and analyzing the results of drone photogrammetry using Non-PPK with low-cost PPK-Kit, based on the tests of various numbers and locations of GCPs in the university field including various slopes and structures like coastal terrain.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.11-18
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• 2006

In this paper, airborne LiDAR data were evaluated in horizontal and vertical accuracy. By using zigzag scanning type of LiDAR, GCPs are not tested directly. So points around GCPs were used in this evaluation. Building corner points were made from LiDAR's building planar and compared with ground surveyed GCPs, in horizontal accuracy test. Its accuracy shows 19cm average and 21cm RMSE and 15 points were within 20cm among 16 points. In vertical accuracy test, 41 GCPs were used and it shows 11cm average and 14cm RMSE and 75% of GCPs were within 15cm. This could be a criterion in topographic map modification and basic geographic DB and 3D data construction using airborne LiDAR data.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.3-9
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• 2016

UAV(unmanned aerial vehicle) can quickly produce orthoimage with high-spatial resolution and DSM(digital surface model) at low cost. However, vertical and horizontal positioning accuracy of orthoimage and DSM, which are obtained by UAV, are influenced by image processing techniques, quality of aerial photo, the number and position of GCPs(ground control points) and overlap in flight plan. In this study, effects of overlap and the number of GCPs are analyzed in orthoimage and DSM. Positioning accuracy are estimated based on RMSE(root mean square error) by using dataset of nine pairs. In the experiments, Overlaps and the number of GCPs have influence on horizontal and vertical accuracy of orthoimage and DSM.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.135-140
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• 2007

Due to the expensiveness of IKONOS Pro and Precision Products, it is attractive to use the low-cost IKONOS Geo Product with vendor-provided RPCs to produce highly accurate mapping products. The imaging geometry of IKONOS high-resolution imagery is described by RFs instead of rigorous sensor models. This paper presents four different models defined respectively in object space and image space to improve the accuracies of the RF-derived ground coordinates. The four models include the offset model, the scale & offset model, the affine model and the 2nd-order polynomial model. Different configurations of ground control points (GCPs) are carefully examined to evaluate the effect of the GCPs arrangement on the accuracy of ground coordinates. The experiment also evaluates the effect of different cartographic parameters such as the number location, and accuracy of GCPs on the accuracy of geopositioning.

• Proceedings of the KSRS Conference
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• v.2
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• pp.578-581
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• 2006

Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.286-288
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• 2003

In this paper, we present our implementation of the direct camera model (image to ground) for SPOT5 and use it to assess the geometric accuracy of SPOT5 imagery. Our assessment confirms the location accuracy of SPOT5 imagery (without use of GCPs) is less than 50m. We further introduce a few attitude parameters to refine the camera model with GCPs. The model is applied to two SPOT5 supermode images, one near vertical, incidence angle of 3 degrees, and one far oblique, incidence angle of 27 degrees. The results show that accuracy (rms of check points) of about one pixel (2.5m) can be achieved with about 4 GCPs by using only 3 parameters to correct the yaw, pitch and roll of the satellite.