• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.111-121
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• 2018

RIn this research, digital elevation models, true-ortho image and 3-dimensional digital complied data was generated and evaluated using unmanned aircraft vehicle stereoscopic images by applying photogrammetric principles. In order to implement stereoscopic vision, digital Photogrammetric Workstation should be used necessarily. For conducting this, in this study GEOMAPPER 1.0 is used. That was developed by the Ministry of Trade, Industry and Energy. To realize stereoscopic vision using two overlapping images of the unmanned aerial vehicle, the interior and exterior orientation parameters should be calculated. Especially lens distortion of non-metric camera must be accurately compensated for stereoscope. In this work. photogrammetric orientation process was conducted using commercial Software, PhotoScan 1.4. Fixed wing KRobotics KD-2 was used for the acquisition of UAV images. True-ortho photo was generated and digital topographic map was partially produced. Finally, we presented error analysis on the generated digital complied map. As the results, it is confirmed that the production of digital terrain map with a scale 1:2,500~1:3,000 is available using stereoscope method.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.140-148
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• 2001

The satellite sensor model is typically established using ground control points acquired by ground survey Of existing topographic maps. In some cases where the targeted area can't be accessed and the topographic maps are not available, it is difficult to obtain ground control points so that geospatial information could not be obtained from satellite image. The paper presents several satellite sensor models and satellite image decomposition methods for non-accessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then the behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in 1$^{st}$, 2$^{nd}$ and 3$^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\phi$(phi) correlated highly with positional parameters could be assigned to constant values. For non-accessible area, satellite images were decomposed, which means that two consecutive images were combined as one image. The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1$^{st}$ order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.33-44
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• 2001

The paper presents several satellite models and satellite image decomposition methods for inaccessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in $1^{st}$, $2^{nd}$ and $3^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\Phi$(phi) correlated highly with positional parameters could be assigned to constant values. For inaccessible area, satellite images were decomposed, which means that two consecutive images were combined as one image, The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1st order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.393-398
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• 2004

It is transformed map data of different coordinate system into unique system and We triedto make topographic map on non-accessible area. We transformed Russian map coordinates(Krassovsky, G-K projection) intoWGS-84, TM projection and assessed accuracy. The RMSE(in East and West bearings : ${\pm}$13.67m, in North and South bearings ： ${\pm}$14.67m) using only SCP(Survey Control Point) is more accurate than that(in East and West bearings ： ${\pm}$24.26m, in North and South bearings : ${\pm}$25.32m) using SCP, intersection of road, bridge. Exterior orientation parameters are estimated using rigorous modelling and GCPs are classified with SCP, intersection of road, bridge. Rigorous modelling is performed with each classified GCP. The modelling result usingonly SCP(in East and West bearings : ${\pm}$13.53m, in North and South bearings ： ${\pm}$14.22m) is more accurate than that using intersection of road(in East and West bearings ： ${\pm}$16.l1m, in North and South bearings： ${\pm}$23.85m), bridge(in East and West bearings : ${\pm}$17.21m, in North and South bearings : ${\pm}$21.82m). The results means that SCP is more accurate than intersection of road, bridge because of edit to generate map. therefore, SCP is suitable for object of GCP in paper map(1:50,000). Geographic information on non-accessible area and analysis is performed. The results of stereoscopic plotting is well matched old map data on road, railroad but, many objects are generally editted. It is possible to update on new objects(building, tributary ‥‥etc). Ability of description using SPOT-5(stereo) is more than features and items included in 1:50,000 topographic map. Therefore, it is possible to make large scale map than 1:50,000 topographic map using SPOT-5 imagery. But, there are many problems(accurate GCPs, obtain of high resolution stereoscopic satellite imagery in a period ‥‥ etc) to make topographic map on non-accessible area. It is actually difficult to solve these problems. therefore, it is possible to update 1:50,000 topographic map in part of topographic map generation.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.141-152
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• 1993

This study aims to generate digital elevation model from digital satellite imagery. Digital elevation model is being increasingly used for geo-spatial information system database development and for digital map production. Image matching technique was applied to acquire conjugate image coordinates and the algorithm for digital elevation model generation is presented in this study The exterior orientation parameters of the satellite imagery is determined by bundle adjustment and standard correlation was applied for image matching conjugate of image points. The window as well as the searching area have to be defined in image matching. Different sizes of searching area were tested to study the appropriate size of the searching area. Various coordinate transformation methods were applied to improve the computation speed as well as the geometric accuracy. The results were then statistically analysed after which the searching area is determined with the safety factor. To evaluate the accuracy of digital elevation model, 3-D coordinates were extracted from 1/5000 scale topographic map and this was compared to the digital elevation model generated from satellite imagery. The algorithm for generation of digital elevation model generated from satellite imagery is presented in this study which will prove effective in the database development of geo-spatial information system and in digital elevation modelling of large areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.203-211
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• 2009

With supply of the domestic digital camera, the relative importance of the digital camera is coming to be high gradually on aerial photogrammetry, the image of digital camera is more applied in image map or digital topographic map production. But, there are cases that do not have position information or attitude information of each photograph in digital camera results. Therefore, we wish to present additional method to get more accurate photograph control point result. In this study, One is called A method, which is the case of entering positioning information of principal point from topographic map as default values that are need to extract tie point automatically using by 56 pieces of photography that are photographed by DMC to the extent to 5 courses and 35 GCP points. The other is called B-method, which is the case of entering exterior orientation parameters that are processed by block adjustment for A-method using by 4 control points in method-1 as default values. We have analyzed about results per control points arrangement for two cases using MATCH-AT that is photograph control point measurement S/W of Germany INPHO company. As a result of analysis, accuracy of B-method was better than that of A-method, and we could get more accurate results if block adjustments are executed including self calibration. Also, it is more effective in expense side that using self calibration for photograph survey in B-method because can reduce GCP numbers.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.250-261
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• 1998

The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the results of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation parameters obtained from modeling and conjugate points from matching. In the DEM generation system, matching procedure holds most of a processing time, therefore to reduce the time for matching, a new fast matching algorithm using gradient correlation and fast similarity measure calculation method is proposed. In this paper, the SPOT satellite images, level 1A 6000$\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM extraction with the satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.663-670
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• 2020

In the present study, we assessed the accuracy of aerial triangulation using a UAV (Unmanned Aerial Vehicle) capable of network RTK (Real-Time Kinematic) survey in a disaster situation that may occur in a semi-urban area mixed with buildings. For a reliable survey of check points, they were installed on the roofs of buildings, and static GNSS (Global Navigation Satellite System) survey was conducted for more than four hours. For objective accuracy assessment, coded aerial targets were installed on the check points to be automatically recognized by software. At the instance of image acquisition, the 3D coordinates of the UAV camera were measured using VRS (Virtual Reference Station) method, as a kind of network RTK survey, and the 3-axial angles were achieved using IMU (Inertial Measurement Unit) and gimbal rotation measurement. As a result of estimation and update of the interior and exterior orientation parameters using Agisoft Metashape, the 3D RMSE (Root Mean Square Error) of aerial triangulation ranged from 0.153 m to 0.102 m according to the combination of the image overlap and the angle of the image acquisition. To get higher aerial triangulation accuracy, it was proved to be effective to incorporate oblique images, though it is common to increase the overlap of vertical images. Therefore, to conduct a UAV mapping in an urgent disaster site, it is necessary to acquire oblique images together rather than improving image overlap.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.