• Spatial Information Research
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• v.22 no.1
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• pp.75-84
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• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.545-553
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• 2009

Digital Elevation Models (DEM) is widely used in establishing the topographic profile in nation spatial information. Aerial Light Detection And Ranging (LiDAR) system is one of the well-known means to produce DEM. The system has fast data acquisition procedures and less weather-dependent restrictions compared to photogrammetric approaches. In this regards, LiDAR has been widely utilized and accepted in the process of nation spatial information generation due to its sufficient positional accuracy. However, the investigation of the accuracy of aerial LiDAR data over the area of forestation with various kinds of vegetations has been barely implemented in Korea. Hence, this research focuses on the investigation of the accuracy of aerial LiDAR data over the area of forestation and the evaluation of the acquired accuracy according to the characteristics of the vegetations. The study areas include land with shrubs and its adjacent forest area with mixed tree species. The spots for the investigation have been selected to be well-distributed over the whole study areas and their coordinates are surveyed by Global Positioning Systems (GPS). Then, the surveyed information and aerial LiDAR data have been compared with each other and the result accuracy has been evaluated. Conclusively, it is recommended that LiDAR data collection to be conducted after defoliation period, especially over the areas with broadleaf trees due to the possibility of significant outliers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.125-134
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• 2012

In this paper, we propose a method to analyze M:N corresponding relations in semantic matching, especially focusing on feature class matching. Similarities between any class pairs are measured by spatial objects which coexist in the class pairs, and corresponding classes are obtained by clustering with these pairwise similarities. We applied a graph embedding method, which constructs a global configuration of each class in a low-dimensional Euclidean space while preserving the above pairwise similarities, so that the distances between the embedded classes are proportional to the overall degree of similarity on the edge paths in the graph. Thus, the clustering problem could be solved by employing a general clustering algorithm with the embedded coordinates. We applied the proposed method to polygon object layers in a topographic map and land parcel categories in a cadastral map of Suwon area and evaluated the results. F-measures of the detected class pairs were analyzed to validate the results. And some class pairs which would not detected by analysis on nominal class names were detected by the proposed method.

• Economic and Environmental Geology
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• v.48 no.6
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• pp.537-543
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• 2015

In Korea, the use of world geodetic system(WGS) has been mandated in year 2010. Accordingly, the national geographic information institute(NGIS) provides the digital maps according to the WGS. Nevertheless, most of the digital geological maps are still based on the Tokyo Datum(TD). Therefore, users should conduct 2D/3D geological spatial analysis after converting the coordinates of digital geological maps to WGS. The conversion process is often tedious and troublesome for certain users. Therefore, in this study, the method to transform coordinate from TD to WGS using ArcToolbox is introduced for users not familiar with the process. For a better appreciation, the Chungju and Hwanggang-ri digital sheets of 1:50,000 scale was chosen as an example. Here, Chungju and Hwanggang-ri sheets were defined based on the TD-central origin and TD-east origin, respectively. The two sheets were merged after the transformation of TD-east origin of Hwanggang-ri to the TD-central origin, and eventually transformed to WGS-central origin. The merged map was found to match exactly with the digital map(Daeso 367041). The problem of coordinate determination in previous digital geological maps was solved effectively. The proposed method is believed to be helpful to 2D/3D geological spatial analysis of various geological thematic maps.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.195-206
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• 1993

As the first step in developing the urban information system it is very important to identify the location of the street, and the feature of objects on it Also it is necessary to understand the relationship between objects concerned. In order to manage these information efficiently, the road information should be well organized and standardized for digital data. Because the road is the base place under which most urban utilities are buried. However, the present real situation is that even if we have unique numbers authorized by law for some parts of the road it is too ambiguous to figure out the spatial location of the specific area because the assigned area is so large and incoherent. Therefore, the purpose of this study is to propose a road location identication scheme, to apply this scheme at Kangnam-ku Seoul, and finally to propose the guideline in developing the road management information system in Korea. The road identification scheme developed in this study are as follows: (1) The road is defined as a fixed factor, and was given the identification number which repressents the funtion, relationship, and direction of the road without the road section and absolute coordinates. (2) The parcel identification nutter was given to each route to understand it possible to understand the location of the road itself and surroundings. (3) To update the md information using the scheme developed in this study relative coordinate method(Dynamic Segmentation) based on the road centerline was applied.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.111-124
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• 2021

Recently, Interest in the restoration and 3D reconstruction of cultural properties due to the fire of Notre Dame Cathedral on April 15, 2019 has been focused once again after the 2008 Sungnyemun fire incident in South Korea. In particular, research to restore and reconstruct the actual measurement of cultural properties using LiDAR(Light Detection and ranging) and conventional surveying, which were previously used, using various 3D reconstruction technologies, is being actively conducted. This study acquires data using unmanned aerial imagery of UAV(Unmanned Aerial Vehicle), which has recently established itself as a core technology in the era of the 4th industrial revolution, and the existing CRP(Closed Range Photogrammetry) and terrestrial LiDAR scanning for the Recumbent Buddha of Unju Temple. Then, the 3D reconstruction was performed with three fusion models based on SfM(Structure-from-Motion), and the reproducibility and accuracy of the models were compared and analyzed. In addition, using the best fusion model among the three models, the relationship with the Polar Star(Polaris) was confirmed based on the real world coordinates of the Recumbent Buddha, which contains the astronomical history of Buddhism in the early 11th century Goryeo Dynasty. Through this study, not only the simple external 3D reconstruction of cultural properties, but also the method of reconstructing the historical evidence according to the type and shape of the cultural properties was sought by confirming the historical evidence of the cultural properties in terms of spatial information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.511-519
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• 2020

For camera calibration, a checkerboard is generally used to determine the principal point, focal length, and lens distortions. The checkerboard has a planar and three-dimensional shape, and camera calibration parameters are affected by the size of the checkerboard, the placement of the target, and the number of target points. In this study, the accuracies of the types of checkerboards were compared using checkpoints for stereo camera calibration, and the purpose of this study was to propose the best performance checkerboard. The checkerboard with large flat shape showed comparatively high accuracy through comparison with the check points. However, due to the size of the checkerboard, it was inconvenient to move and rotate, and there was a disadvantage in that it was difficult to shoot so that the target points could all appear in the stereo camera. The checkerboard, which was manufactured in a small size in a flat shape, was easy to move and rotate but had the lowest three-dimensional accuracy. The checkerboard with targets with height values had the hassle of having to determine the three-dimensional coordinates of the target points by using observation equipment for camera calibration, but it was small in size, convenient to move and rotate, and showed the highest three-dimensional accuracy.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.114-125
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• 2023

The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.1-16
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• 2024

Alvin Toffler mentioned that it is important for future society to keep pace with synchronization and that time deviations can hinder social development. As we experience the new normal era of untact, we have experienced an increase in non-face-to-face contact and accelerated digital transformation. Amid these rapid changes, we can maintain the need for synchronization or change in space. Therefore, we would like to study what kind of settlements people create and choose. We looked at the metaverse as an object that could indirectly find out about this, and used the content called "Animal Crossing" to collect data related to the spatial form of the metaverse. Sampling utilized a judgment sampling method during non-probability sampling to alleviate differences due to the progress of the game. The collected data was classified according to floor plan and location type and briefly organized through descriptive statistics. After matching each facility by use, data was constructed by setting coordinates for each cluster and listing them. This data was interpreted graphically on the coordinate plane for each cluster, and Euclidean analysis was performed to analyze the relationships between clusters and residential choice using a Euclidean matrix. As a result of the analysis, it could be interpreted that efficiency was pursued by arranging similar functions in close proximity. Nevertheless, when choosing a residence, it was interpreted that the intention was to create a community through arrangement adjacent to residents rather than efficiency or convenience. Due to the differences between the metaverse and the real world, it is expected that there will be limitations in equating it with reality. However, through the space expressed in the virtual world by people who are far away from the constraints of reality, we can indirectly know the wishes that we have not been able to express due to our lack of awareness.