• The Journal of Engineering Geology
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• v.32 no.4
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• pp.547-558
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• 2022

In August 2020, a debris flow occurred in Gokseon, Jeollanam-do, that resulted in the death of five residents. In this study area, high-resolution 0.03 m topographic information was generated through photogrammetry, and the amount of soil movement/loss was measured. In addition, sensitivity analysis was performed for flow depth, flow velocity, and debris flow area with the program Flo-2D using the difference in simulation parameter that discharge and topographic information. Wth increasing debris flow input discharge, increases were seen in flow depth, flow velocity, and debris flow area, as ell as in the gap in results from high-resolution topographic information and low-resolution topographic information. Also, when high-resolution topographic information was used, the results were similar to the actual (measured) flow direction of the debris flow. Therefore, the application of high-resolution topographic information increases the accuracy of the debris flow analysis results compared with low-resolution information. Results could be further imporved in the future by considering geological information such as yield stress and viscosity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.5 no.1
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• pp.49-58
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• 1987

The use of digital terrain model has been enlarged in calculating the earthwork due to the development of aerial photogrammetry. The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advance the accuracy of earthwork calculation. In this study, I have made an analysis of influences which DTM makes on the height accuracy of data ; on the basis of the analysis, we can develop the predictive model formula of profile shape coefficients by which the accuracy of earthwork can he preestimated in practical design according to data density of terrain, making thereby good contribution to the calculation of both earthwork amount and its expenses. This study shows that the accuracy of earthwork is more affected by the distances of cross-sections than by data density and that the effects by the standard errors of height decrease in proportion as the distances of cross-sections are great It also shows that when the prediction model formula of profile shape coefficients is applied to ordinary cases, the differences between the predicted earthwork errors and the errors by ordinary est imation are at 0.8374~3.1437$cm^3$/m, on flat terrain and 1.5628~6.967$cm^3$/m, on mountainous terrain-so little as to be ignored ; thus it can be safely ascertained that the accurate earthwork errors can be predicted applying the prediction model formula made in this study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.327-336
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• 2007

The 3D building modeling is one of crucial components in building 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes by stereoplotter compiler, which indeed take great amount of time and efforts. In addition, some automatic methods that were proposed in research papers and experimental trials have limitations of describing the details of buildings with lack of geometric accuracy. It is essential in automatic fashion that the boundary and shape of buildings should be drawn effortlessly by a sophisticated algorithm. In recent years, airborne LiDAR data representing earth surface in 3D has been utilized in many different fields. However, it is still in technical difficulties for clean and correct boundary extraction without human intervention. The usage of airborne LiDAR data will be much feasible to reconstruct the roof tops of buildings whose boundary lines could be taken out from existing digital maps. The paper proposed a method to reconstruct the roof tops of buildings using airborne LiDAR data with building boundary lines from digital map. The primary process is to perform octree-based segmentation to airborne LiDAR data recursively in 3D space till there are no more airborne LiDAR points to be segmented. Once the octree-based segmentation has been completed, each segmented patch is thereafter merged based on geometric spatial characteristics. The experimental results showed that the proposed method were capable of extracting various building roof components such as plane, gable, polyhedric and curved surface.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.3-12
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• 2010

In previous studies, the digital measurement systems and analysis algorithms were developed by using the related techniques, such as the aerial photograph detection and high resolution satellite image process. However, these studies were limited in 2-dimensional geo-processing. Therefore, it is necessary to apply the 3-dimensional spatial information and coordinate system for higher accuracy in recognizing and locating of geo-features. The objective of this study was to develop a stochastic algorithm for the optimal sensor placement using the 3-dimensional spatial analysis method. The 3-dimensional information of the LiDAR was applied in the sensor field algorithm based on 2- and/or 3-dimensional gridded points. This study was conducted with three case studies using the optimal sensor placement algorithms; the first case was based on 2-dimensional space without obstacles(2D-non obstacles), the second case was based on 2-dimensional space with obstacles(2D-obstacles), and lastly, the third case was based on 3-dimensional space with obstacles(3D-obstacles). Finally, this study suggested the methodology for the optimal sensor placement - especially, for ground-settled sensors - using the LiDAR data, and it showed the possibility of algorithm application in the information collection using sensors.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.307-317
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were 8.1cm, 24.7cm, 35.9cm, respectively.

• 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.

• Journal of the Korean Geosynthetics Society
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• v.19 no.3
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• pp.1-8
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• 2020

In this study, numerical analysis of debris flow was performed using the SPH (Smoothed Particle Hydrodynamics) technique to analyze the mechanism of debris flow, and the applicability of soil parameters was verified by comparison with previous studies. In addition, after performing aerial photographic survey using a drone, a topographic model was created based on this survey to check the applicability of the site to the valley part of Jagul Mountain basin. And after numerical analysis of debris flow was performed using NFLOW, and the result was compared and analyzed with the existing satellite image based method. As a result of this study, the numerical analysis method using drone image and NFLOW was found to have a higher applicability to predicting the impact of debris flow, because it can reflect the actual topography better than the existing method based on satellite imagery. Therefore, it is considered that this study can be used as basic data to establish the preventive measures for debris flow such as location selection of the eruption control dam.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.1
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• pp.97-108
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• 2018

The purpose of this study is to propose the construction of a visibility analysis model, which is the basis of the analysis for landscape management on the heritage sites such as historic villages and scenic sites. Results of the visibility analysis using DEM and the visibility analysis of DSM based on 3D mapping data are compared as follows: Precision level of the extracted data was confirmed to be less than 6.5cm, based on RTK survey results produced by constructing orthoimage data and DSM from the digital data of 2cm-class GSD(Ground Sample Distance) obtained by using a small UAV(Unmanned Aerial Vehicle). As a result of comparing the visibility analysis data of Digital Surface Model (DSM) using a small UAV with Digital Elevation Model(DEM) applying the height of the building to the Digital Topographic Map, it was confirmed that more realistic visibility analysis can be accomplished by applying DSM, as the structures such as fences, trees, and houses are reflected in the topographic data. The visibility analysis model using the 3D mapping technique can efficiently obtain the constantly changing topographic information when needed, by immediately constructing the data by utilizing a small UAV. It seems to be possible to propose a reasonable analysis result for preservation management such as landscape evaluation of cultural property.

• Journal of the Korean association of regional geographers
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• v.1 no.1
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• pp.61-68
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• 1995

The writers study on the development and the prospect of computer map based on the most recent computer mapping technical aspects. We also study domestic prospect of computer map in connection with the present condition of domestic GIS. The main results are as follows: (1) Computer map has rapidly developed in spite of its short history. We expect that computer map will be improved more in the future owing to the development of computer hardware and software. Most mapping processes will be possible sooner or later owing to Artificial Intelligence(AI) and more improved scanner without human effort. (2) Computer map can be used for various industrial fields and its development can give a great help for technical advance in correlated industries. (3) Computer map has really developed in the country since 1980, when GIS was introduced. Especially, government planned to digitalize all the basic topographical maps covering the whole country between 1996-1998. We think that there is an epoch-making change in the development history of computer map in the future. (4) The development of GIS is closely connected with one of computer map, but the recent technical levels of GIS is not perfect. So there is an urgent need for technical supplement to produce good computer maps. (5) The government had better construct GIS database in order to cut down expenses derived from overlapping input of data by individual users and there is a need for data standard.