• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.765-779
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• 2022

This study evaluates the accuracy in identifying the burned area in South Korea using multi-temporal data from Sentinel-2 MSI and Landsat 8/9 OLI. Spectral indices such as the Difference Normalized Burn Ratio (dNBR), Relative Difference Normalized Burn Ratio (RdNBR), and Burned Area Index (BAI) were used to identify the burned area in the March 2022 forest fire in Uljin. Based on the results of six indices, the accuracy to detect the burned area was assessed for four satellites using Sentinel-2 and Landsat 8/9, respectively. Sentinel-2 and Landsat 8/9 produce images every 16 and 10 days, respectively, although it is difficult to acquire clear images due to clouds. Furthermore, using images taken before and after a forest fire to examine the burned area results in a rapid shift because vegetation growth in South Korea began in April, making it difficult to detect. Because Sentinel-2 and Landsat 8/9 images from February to May are based on the same date, this study is able to compare the indices with a relatively high detection accuracy and gets over the temporal resolution limitation. The results of this study are expected to be applied in the development of new indices to detect burned areas and indices that are optimized to detect South Korean forest fires.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.212-222
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• 2021

In this study, the flow resistance coefficient was calculated considering the physical properties and distribution characteristics of floodplain vegetation, and the effect of floodplain vegetation distribution on flow characteristics was analyzed by reflecting it in a two-dimensional numerical simulation. The three-dimensional point clouds of vegetation acquired using ground lidar were analyzed to apply floodplain vegetation's physical properties to the existing formula for vegetation flow resistance calculation. The floodplain vegetation distribution in the modeling was divided into locally distributed and fully distributed conditions in the floodplain. As a result of the simulation of the study site, the flow resistance coefficient of floodplain vegetation was found to have a value of about five times or more compared to the flow resistance coefficient of the main channel bed when the design flood occurs based on Manning's n coefficient. Also, it affected the hydraulic characteristics in the main channel and floodplain.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.829-838
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• 2022

This study conducts Hypervelocity Impact(HVI) simulations considering space objects with various shapes and different impact angles. A commercial nonlinear structural dynamics analysis code, LS-DYNA, is used for the present simulation study. The Smoothed Particle Hydrodynamic(SPH) method is applied to represent the impact phenomena with hypervelocity. Mie-Grüneisen Equation of State and Johnson-Cook material model are used to consider nonlinear structural behaviors of metallic materials. The space objects with various shapes are modeled as a sphere, cube, cylinder, and cone, respectively. The space structure is modeled as a thin plate(200 mm×200 mm×2 mm). HVI simulations are conducted when space objects with various shapes with 4.119 km/s collide with the space structures, and the impact phenomena such as a debris cloud are analyzed considering the space objects with various shapes having the same mass at the different impact angles of 0°, 30° and 45° between the space object and space structure. Although space objects have the same kinetic energy, different debris clouds are generated due to different shapes. In addition, it is investigated that the size of the debris cloud is decreased by impact angles.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.954-966
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• 2021

With regards to the marine spatial plannings of the world, the spaces are being managed through the integration of various uses and the establishment of systems and laws in the perspective of the utilization of spaces. In the perspective of policy establishment, the policy readiness level is applied to analyze the trends in the studies on South Korea's marine spatial plans. The scope of the study included analyzing marine spatial plan as a keyword in articles published over the period from 2010 to 2020. The methods of analysis included the analyses of the frequency of word appearance, word clouds, and appearance intensity, which were used to identify key issues. Five keywords that were related to the topics were identified, and were again used to identify the key themes. The core themes were changing in all phases, such as the principles development phase, institutionalization phase, policy verification phase. For future benefit, this requires more research in South Korean public organizations and universities.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.548-560
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• 2022

Video based Point Cloud Compression (V-PCC) is one of the compression methods for compressing point clouds, and shows high efficiency in dynamic point cloud compression with movement due to the feature of compressing point cloud data using an existing video codec. Accordingly, V-PCC is drawing attention as a core technology for immersive content services such as AR/VR. In order to effectively service these V-PCC contents through a media streaming platform, it is necessary to encapsulate them in the existing media file format, ISO based Media File Format (ISOBMFF). However, in order to service through an adaptive streaming platform such as Dynamic Adaptive Streaming over HTTP (DASH), it is necessary to encode V-PCC contents of various qualities and store them in the server. Due to the size of the 2D media, it causes a great burden on the encoder and the server compared to the existing 2D media. As a method to solve such a problem, it may be considered to configure a streaming platform based on content obtained through V-PCC content encoding based on SHVC. Therefore, this paper encapsulates the SHVC-based V-PCC bitstream into ISOBMFF suitable for DASH service and proposes a configuration method to service it. In addition, in this paper, we propose ISOBMFF encapsulation and DASH configuration method to effectively service SHVC-based V-PCC contents, and confirm them through verification experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.160-174
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• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.3-20
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• 2022

The origins of the world-recognized Korean gat can be traced back to Gojoseon, and the jades for the sangtu and gwanja come from Hongshan culture. This study examines the etymology of the hat, the symbolism of the gat and the jade comb, and the history of the development of the accessories for the hat. The research methods of literature review, investigation of relics and murals, and analysis of cases of pronunciation changes were used. Most of the relics excavated from the Hongshan are identical to those excavated from Korea. The Byun-Khan people wore a triangle-shaped conical hat (the byun), which was shaped to fit the protruding sangtu hairstyle, with a foldable brim that, if pulled downward, changed the hat to a gat. The Chu sangtu, a pointed top-knot hairstyle, is uniquely found among Northeast Asian peoples, and it is an ethnic symbol for Koreans. Until the modern period, many Koreans wore their hair in the sangtu style, indicating their descent from the sky. Jade combs shaped like birds and clouds from the Hongshan period emphasized the religious nature and ceremony of hair styling at that period. The word hat is widely used to refer to gat all over the world. The pronunciation of ㄱg, ㅎh. and ㅋq/kh are closely related to each other, and the ancient pronunciation ㄱg gradually evolved to ㅎh or ㅋq/kh. The English 'Hat' and Korean 'Gat' were transformed from the middle-ancient sound 'gasa > gosa > got' of the crown 'gwan, gokkal'. This creative hair style culture that started from the Hongshan culture continued to be fashionable during the Gojoseon Dangun period, and the decoration techniques for hats and accessories were inherited over time and continuously developed. Along with the method of making gat, creative hair-related parts, such as manggeons, donggot pins, gwanja buttons, and fine combs were developed over the course of a thousand years.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.47-63
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• 2023

The Seoul Metropolitan Government is building and operating digital twin-based urban spatial information to solve various problems in the city and provide public services. Two essential factors to ensure the stable utilization of spatial information for the implementation of such a digital twin city are the latest and quality of the data. However, it is time-consuming and costly to maintain continuous updating of high-quality urban spatial information. To overcome this problem, we studied efficient urban spatial information construction technology and the operation, management, and update procedures of construction data. First, we demonstrated and applied automatic 3D building construction technology centered on point clouds using the latest hybrid sensors, confirmed that it is possible to automatically construct high-quality building models using high-density airborne lidar results, and established an efficient data management plan. By applying differentiated production methods by region, supporting detection of urban change areas through Seoul spatial feature identifiers, and producing international standard data by level, we strengthened the utilization of urban spatial information. We believe that this study can serve as a good precedent for local governments and related organizations that are considering activating urban spatial information based on digital twins, and we expect that discussions on the construction and management of spatial information as infrastructure information for city-level digital twin implementation will continue.