• Economic and Environmental Geology
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• v.54 no.4
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• pp.475-482
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• 2021

This study proposed a strategy with literature review on effective monitoring of dispersion of the particulate matters (PM) emitted from domestic open pit lime mines. The mines generally produced a large amount of PM through the mine processes such as crushing and transportation of raw or crushed ores. The PM emission from mine facilities or transportation can be assessed using empirical equations which was prepared through the experimental tests to produce PM from ores. For effective monitoring of mine PM dispersion, this study showed a preliminary application of the monitoring network with multiple low-cost sensors around a main PM emission source for each mine site. Therefore, two domestic limestone mine sites were selected for this study, and install the monitoring network with low-cost PM sensors and LTE (Long-term evolution) data communication. Then, preliminary resultant PM data plotted according to monitoring duration showed typical PM dispersion patterns. The quantification of the PM dispersion patterns should be roughly prepared by a PM size-dependent dispersion modeling.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.6
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• pp.385-391
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• 2022

This paper presents to develop a path planning algorithm combining gradient descent-based path planning (GBPP) and particle swarm optimization (PSO) for considering prohibited flight areas, terrain information, and characteristics of fixed-wing unmmaned aerial vehicle (UAV) in 3D space. Path can be generated fast using GBPP, but it is often happened that an unsafe path can be generated by converging to a local minimum depending on the initial path. Bio-inspired swarm intelligence algorithms, such as Genetic algorithm (GA) and PSO, can avoid the local minima problem by sampling several paths. However, if the number of optimal variable increases due to an increase in the number of UAVs and waypoints, it requires heavy computation time and efforts due to increasing the number of particles accordingly. To solve the disadvantages of the two algorithms, hierarchical path planning algorithm associated with hierarchical particle swarm optimization (HPSO) is developed by defining the initial path, which is the input of GBPP, as two variables including particles variables. Feasibility of the proposed algorithm is verified by software-in-the-loop simulation (SILS) of flight control computer (FCC) for UAVs.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.140-150
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• 2022

This paper focuses on introducing the concept of the multi-scale study on the Ulleungdo-Dokdo Volcanic Group in the East Sea and recent new findings from it. Multi-channel seismic reflection data reveals that the major volcanic activities of the Ulleungdo-Dokdo Volcanic Group took place between 5 and 2.5 Ma, which were propagated from Isabu Tablemount on the eastern end to the Ulleung Island on the western end. The terrestrial Ulleung Island was built via 5 stages, which eventually formed a 3 km-wide caldera, named Nari Caldera, and a volcanic dome, named Albong, within the caldera. The Albong and the unit N-1, the earliest phreatomagmatic explosive phase of the Albong volcano, were generated from a new magma injected into the existing phonolitic body. The generally trachyandesitic bulk rock composition of the pumice in unit N-1 and Albong is attributed to the contamination of the new magma by mafic cumulates at the base of the existing phonolitic chamber. The lines of evidence of a new magma injection point toward that Ulleung Island is an active volcano with a live subvolcanic magma plumbing system.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.88-99
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• 2022

The river network is one of the essential topographical characteristics in river management. The river network which as previously constructed by the ground surveying method has recently begun to be efficiently constructed using the remote sensing datasets. Since it is difficult to remove these obstacles such as bridges in the urban rivers, it is rare to construct the urban river networks with the various obstacles. In this study, the Sentinel-2 satellite imagery was used to develop the automatic method for detecting the urban river networks without the obstacles and with the preserved boundaries as follows. First, the normalized difference water index image was generated using the multispectral bands of the given Sentinel-2 satellite imagery, and the binary image that could classify the water body and other regions was generated. Next, the morphological operations were employed for detecting the complete river networks with the obstacles removed and the boundaries preserved. As a result of applying the proposed methodology to Han River in Seoul, the complete river networks with the obstacles removed and the boundaries preserved were well constructed.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.1
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• pp.47-61
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• 2022

In this study, We developed VR (Virtual Reality) geological resources based on the Geo Big Data of the Big Data platform that provided by the Korea Institute of Geoscience and Mineral Material (KIGAM). So students selected the theme of lessons by using these resources and we operated Remote classes using the materials that developed as to Virtual Reality. Therefore, the geological theme maps provided by the Geo Big Data Open Platform were reconstructed and produced materials were created for Study about Real Korean geological outcrops grounded in Virtual Reality. And Topographic information data was used to produce class materials for Remote classes. Twenty students were selected by Random sampling, and data were collected by conducting a survey including interviews to confirm the change in students' perception of remote classes in virtual reality geological data development and the effect of the classes, so data were analyzed through inductive categorization. The results of this study are as follows. First, students showed positive responses in terms of interest, utilization, and knowledge utilization as taking remote classes for developing geological data in virtual reality geological data. This is the result of showing the adaptability of diverse and flexible learning getting away from a fixed framework by motivating and encouraging students and inducing cooperation for communication. Second, students recognized distance education in the development of Virtual Reality geological data as 'Realistic hands-on learning process', 'Immersive learning process by motivation', and 'Learning process of acquiring knowledge in the field of earth science'.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.227-237
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• 2022

The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.403-412
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• 2022

As the 4th industrial revolution is in full swing and next-generation ICT(Information & Communications Technology) convergence technology is being developed, various smart construction technologies are being rapidly introduced in the construction field to respond to technological changes. In particular, since the earth-volume calculation process for site design accounts for a large part of the design cost at the construction site, related researches are being actively conducted to improve the efficiency of the process and accurately calculate the earth-volume. The purpose of this study is to present a method for quickly constructing the topography of a construction site in 3D and efficiently calculating earth-volume using the results. For this purpose, the construction site was constructed as a 3D realistic model using large-scale aerial photos obtained from UAV(Unmanned Aerial Vehicle). At this time, since the constructed 3D realistic model has a surface model structure in which volume calculation is impossible, the structure was converted into a 3D solid model to enable volume calculation. And we devised a methodology to calculate earth-volume based on CAD(Computer-Aided Design and Drafting) using the converted solid model. Automatically calculating earth-volume from the solid model by applying the method. As a result, It was possible to confirm a relative deviation of 1.52% from the calculated earth-volume from the existing survey results. In addition, as a result of comparative analysis of the process time required for each method, it was confirmed that the time required is reduced of 60%. The technique presented in this study is expected to be utilized as a technology for smart construction management, such as periodic site monitoring throughout the entire construction process, as well as cost reduction for earth-volume calculation.

• Journal of Popular Narrative
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• v.26 no.2
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• pp.221-247
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• 2020

This paper examines the meaning of Pyeongsari, the main stage of the novel 'Toji (Land )' and the original experience space engraved in the lives of the characters and suggests the direction of Pyeongsari as a 'Toji (Land )' content platform. Pyeongsa-ri, an imaginary space in the novel, starts from the background of the original work and turns into a representative tourist space for Ha Dong-gun. However, it is necessary to provide cultural experience-type contents that visitors can experience in person. In the original work, Pyeongsari is an ideal community and a symbol of the Korean modern history of suffering and pioneering. Therefore, taking advantage of this meaning, it is necessary to prepare a cultural experience space that shows Confucian culture, women's labor culture, and shamanic culture to draw on visitors' experiences. In addition, the app should be developed in connection with transformed works that have been the driving force behind the reorganization of Pyeongsari, and education and experience spaces using augmented reality are provided on the web. This interaction between digital and reality makes the meaning of the original or transformed works contemporaneous, while contributing to the visitor's own experience. In addition, through this, Pyeongsari can evolve into a cultural experience content platform that reflects the meaning of Korean culture and life. This paper is significant in that it suggests the direction of Pyeongsari's space planning for the 'geography of meaningful places'. In addition, while showing how the imaginary space of the original literary work has reorganized the space of reality, there are implications for the media content of the literary work and the terrain of the culture and arts industry.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.318-329
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• 2022

Plant phenology including flowering, leaf unfolding, and leaf coloring in a forest is important to understand the forest ecosystem. Temperature rise due to recent climate change, however, can lead to plant phenology change as well as snowfall in winter season. Therefore, accurate monitoring of forest environment changes such as plant phenology and snow cover is essential to understand the climate change effect on forest management. These changes can monitor using a digital camera system. This paper introduces the detection methods for plant phenology and snow cover at the mountain region using an unmanned camera system that is a way to monitor the change of forest environment. In this study, the Automatic Mountain Meteorology Stations (AMOS) operated by Korea Forest Service (KFS) were selected as the testbed sites in order to systematize the plant phenology and snow cover detection in complex mountain areas. Multi-directional Internet Protocol (IP) camera system that is a kind of unmanned camera was installed at AMOS located in Seoul, Pyeongchang, Geochang, and Uljin. To detect the forest plant phenology and snow cover, the Red-Green-Blue (RGB) analysis based on the IP camera imagery was developed. The results produced by using image analysis captured from IP camera showed good performance in comparison with in-situ data. This result indicates that the utilization technique of IP camera system can capture the forest environment effectively and can be applied to various forest fields such as secure safety, forest ecosystem and disaster management, forestry, etc.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.346-352
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• 2022

Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.