• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.1
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• pp.17-33
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• 2023

Disasters in coastal regions are a constant source of damage due to their uncertainty and complexity, leading to the proposal of green infrastructure as a nature-based solution that incorporates the concept of resilience to address the limitations of traditional grey infrastructure. This study analyzed trends in research related to coastal disasters and green infrastructure by conducting a co-occurrence keyword analysis of 2,183 articles collected from the Web of Science (WoS). The analysis resulted in the classification of the literature into four clusters. Cluster 1 is related to coastal disasters and tsunamis, as well as predictive simulation techniques, and includes keywords such as surge, wave, tide, and modeling. Cluster 2 focuses on the social system damage caused by coastal disasters and theoretical concepts, with keywords such as population, community, and green infrastructure elements like habitat, wetland, salt marsh, coral reef, and mangrove. Cluster 3 deals with coastal disaster-related sea level rise and international issues, and includes keywords such as sea level rise (or change), floodplain, and DEM. Finally, cluster 4 covers coastal erosion and vulnerability, and GIS, with the theme of 'coastal vulnerability and spatial technique'. Keywords related to green infrastructure in cluster 2 have been continuously appearing since 2016, but their focus has been on the function and effect of each element. Based on this analysis, implications for planning and management processes using green infrastructure in response to coastal disasters have been derived. This study can serve as a valuable resource for future research and policy in responding to and managing various disasters in coastal regions.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.28-33
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• 2023

In this study, computational fluid dynamics was used to analyze the flow bias generated as air supplied by a fan passes through ducts, piping, and a coal separation screen. The flow bias of the air flow is mostly caused by the spatial characteristics of the fan volute and duct, and the internal baffle and the coal separation screen at the outlet cause strong pressure losses that dampen the flow bias. ANSYS CFX was used for computational fluid dynamics, and since the baffle and the coal separation screen are shaped like perforated plates with many small holes uniformly distributed, actual modeling for analysis was not possible. Therefore, the Porous Loss Model was applied. The evaluation of the flow bias was analyzed based on the velocity distribution of the Porous Loss Model at the outlet surface of the coal separation screen obtained from the computational fluid dynamics results.

• Design Convergence Study
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• v.15 no.2
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• pp.169-184
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• 2016

Using geospatial information in the early design phase is crucial because it requires considerable time, money, and effort. We use VWorld, part of the National Spatial Information Distribution system provided by the Korean Ministry of Land, Infrastructure and Transportation, for providing geospatial information to building designers. We provide methods to adopt VWorld geospatial information to building design and develop plugins for a BIM authoring tool to transform and construct necessary BIM data in a user-friendly format. BIM users are benefitted from extra design information supplied from sibling disciplines such as urban design. GIS users are benefited by feedback building information continuously supplied from building projects based upon standard GIS coordinates. It is clear that an architectural designer with BIM tool can save time and efforts to obtain the geospatial information related a project using the developed system as result of this research.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.336-336
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• 2021

기후변화와 도시화로 인한 집중 호우와 불투수층 증가로 도시 홍수의 발생 빈도와 규모가 증가하고 있다. 인적, 물적 자원이 집중되어 있는 도시유역의 특성상 침수가 발생하면 이로 인한 직접적 피해 뿐만 아니라 사회경제적 2차 피해를 발생한다. 도시 홍수로 인한 피해를 줄이고 도시의 재해에 대한 회복력을 키우기 위해서는 관측과 더불어 정확한 모의 기술이 중요하다. 한편, 격자 기반 도시 홍수 모의는 집중 호우에 따른 침수의 시공간적 발생 양상을 물리적으로 해석하는 방법으로, 지표수-우수관거 이중배제 통합 모의, 수치기법, 병렬컴퓨팅, 수질 연계 모의 등의 측면에서 지금까지 많은 발전이 이루어져 왔다. 최근들어 원격탐사 기술의 발달로 공간해상도 1미터 수준 혹은 그 이상의 초고해상도 지형자료가 많은 지역에서 대해 가용해지고 있으며, 도시 홍수 해석에 이와 같은 초고해상도 자료를 적용하기 위한 연구가 활발히 진행되고 있다. 본 연구에서는 초고해상도 지형 및 토지 피복 자료의 공간해상도가 침수해석에 미치는 영향을 분석한다. 도시침수의 두가지 주요 요인인 내수침수와 외수범람 중에서 극한 강우에 의한 내수침수해석 사례만을 주요 연구 범위로 한다. 초고해상도 입력자료의 격자기반 도수 해석 모형으로는 운동파 기반의 2차원 지표 흐름 해석 모형을 적용하고, 초고해상도 모의의 효율적 계산을 위해 하이브리드 병렬 컴퓨팅 기술을 이용한다. 초고해상도 입력자료 적용 사례 대비, 공간해상도 저하에 따라 침수 면적이나 깊이 등에서 어떤 변화가 있는지 정량적으로 검토한다. 또한, 강우의 강도 및 공간분포가 초고해상도 도시 홍수 해석에 미치는 영향에 대해서 분석한다. 모의 결과로부터 도시 홍수 해석시 거리 단위(street-level) 정확도의 재현을 위해 적정한 공간해상도를 분석하고, 초고해상도 도시 홍수 모의를 이용한 기후변화에 따른 극한 홍수의 도시지역 영향 분석 및 회복력 개선 관련 연구의 가능성에 대해 논의한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.481-488
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• 2006

This paper suggests a novel approach of integrating the quasi-distributed watershed model SWAT with the fully-distributed groundwater model MODFLOW. Since the SWAT model has semi distributed features, its groundwater components hardly considers distributed parameters such as hydraulic conductivity and storage coefficient. Generating a detailed representation of groundwater recharge, head distribution and pumping rate is equally difficult. To solve these problems, the method of exchanging the characteristics of the hydrologic response units (HRUs) in SWAT with cells in MODFLOW by fully combined manner is proposed. The linkage is completed by considering the interaction between the stream network and the aquifer to reflect boundary flow. This approach is provisionally applied to Gyungancheon basin in Korea. The application demonstrates a combined model which enables an interaction between saturated zones and channel reaches. This interaction plays an essential role in the runoff generation in the Gyungancheon basin. The comprehensive results show a wide applicability of the model which represents the temporal-spatial groundwater head distribution and recharge.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.3
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• pp.29-42
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• 2023

As the destruction of habitats due to recent development continues, there is also increasing interest in endangered species. Mankyua chejuense is a vulnerable species that is sensitive to changes in population and habitat, and it has recently been upgraded from Endangered Species II to Endangered Species I, requiring significant management efforts. So in this study, we analyzed the potential habitats of Mankyua chejuense using MaxEnt(Maximum Entropy) modeling. We developed three models: one that considered only environmental characteristics, one that considered artificial factors, and one that reflected the habitat of dominant tree species in the overstory. Based on previous studies, we incorporated environmental and human influence factors for the habitats of Mankyua chejuense into spatial information, and we also used the habitat distribution models of dominant tree species, including Ulmus parvifolia, Maclura tricuspidata, and Ligustrum obtusifolium, that have been previously identified as major overstory species of Mankyua chejuense. Our analysis revealed that rock exposure, elevation, slope, forest type, building density, and soil type were the main factors determining the potential habitat of Mankyua chejuense. Differences among the three models were observed in the edges of the habitats due to human influence factors, and results varied depending on the similarity of the habitats of Mankyua chejuense and the dominant tree species in the overstory. The potential habitats of Mankyua chejuense presented in this study include areas where the species could potentially inhabit in addition to existing habitats. Therefore, these results can be used for the conservation and management planning of Mankyua chejuense.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.891-907
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• 2023

Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.4
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• pp.159-176
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• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

• Journal of Aerospace System Engineering
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• v.18 no.2
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• pp.12-20
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• 2024

The application of reinforcement design to ensure the structural safety of electronics in small satellites is limited by the spatial constraints of the satellite structure during launch vibrations. Additionally, a reliable evaluation approach is needed for mounting highly integrated devices that are susceptible to fatigue failure. Although the Steinberg fatigue failure theory has been used to assess the structural integrity of electronic devices, recent studies have highlighted its theoretical limitations. In this paper, we propose a structural methodology based on the critical strain theory to design the digital control unit (DCU) of the X-band SAR payload component for the small SAR technology experimental project (S-STEP), a small satellite constellation. To validate the design, we conducted modal and random analyses using simplified modeling techniques. Based on our methodology, we ultimately demonstrated the structural safety of the electronics through analysis results, safety margin derivation, and functional tests conducted both before and after the launch test.