• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.534-545
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• 2010

To examine 1) rainfall pattern (i.e., type and intensity) regulating surface erosion on hillslopes in postwildfire area and 2) its effect on variation in sediment yield along the gradient of severity wildfire regimes and elapsed years, we surveyed the amount of sediment yield with respect to daily or net-effective rainfall in 9 plots in eastern coastal region, Republic of Korea. Before field investigation, all plots classified into three groups: low-, mixed- and high-severity wildfire regimes (3 plots in each group). We found that, with decreasing wildfire regimes and increasing elapsed years, the rainfall type regulating surface erosion changed from daily rainfall to net-effective rainfall (considering rainfall continuity) and its intensity increased continuously. In general, wildfires can destroy the stabilized forest floors, and thus rainfall interception by vegetation and litter layer should be reduced. Wildfires can also decrease soil pores in forest floors, and thus infiltration rates of soil are reduced. These two processes lead to frequent occurrence of overland flows required to surface erosion, and sediment yields in post-wildfire areas should increase linearly with increasing rainfall events. With the decreasing severity wildfire regimes and the increasing elapsed years, these processes should be stabilized, and therefore their sediment yields also decreased. Our findings on variations in sediment yields caused by the wildfire regimes and the elapsed years suggest understanding of hydrogeomorphic and ecologic diversities in post-wildfire areas, and these should be carefully examined for both watershed management and disaster prevention.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1389-1403
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• 2021

Disaster management using VHR (very high resolution) satellite images supports rapid damage assessment and also offers detailed information of the damages. However, the acquisition of pre-event VHR satellite images is usually limited due to the long revisit time of VHR satellites. The absence of the pre-event data can reduce the accuracy of damage assessment since it is difficult to distinguish the changed region from the unchanged region with only post-event data. To address this limitation, in this study, we conducted the wildfire-induced change detection on national wildfire cases using post-fire VHR satellite images and GIS (Geographic Information System) data. For GIS data, a national land cover map was selected to simulate the pre-fire NIR (near-infrared) images using the spatial information of the pre-fire land cover. Then, the simulated pre-fire NIR images were used to analyze bi-temporal NDVI (Normalized Difference Vegetation Index) correlation for unsupervised change detection. The whole process of change detection was performed on a superpixel basis considering the advantages of superpixels being able to reduce the complexity of the image processing while preserving the details of the VHR images. The proposed method was validated on the 2019 Gangwon wildfire cases and showed a high overall accuracy over 98% and a high F1-score over 0.97 for both study sites.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.2
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• pp.114-124
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• 2014

For classifying fire damaged areas and analyzing burn severity of two large-fire areas damaged over 100 ha in 2011, three methods were employed utilized supervised classification, unsupervised classification and Normalized Difference Vegetation Index (NDVI). In this paper, the post-fire imageries of SPOT were used to compute the Maximum Likelihood (MLC), Minimum Distance (MIN), ISODATA, K-means, NDVI and to evaluate large-scale patterns of burn severity from 1 m to 5 m spatial resolutions. The result of the accuracy verification on burn severity from satellite images showed that average overall accuracy was 88.38 % and the Kappa coefficient was 0.8147. To compare the accuracy between burn severity and field survey at Uljin and Youngduk, two large fire sites were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. The burn severities of the study areas were estimated by analyzing burn severity (BS) classes from SPOT images taken one month after the occurrence of the fire. The applicability of composite burn index (CBI) was validated with a correlation analysis between field survey data and burn severity classified by SPOT5, and by their confusion matrix. The result showed that correlation between field survey data and BS by SPOT5 were closely correlated in both Uljin (r = -0.544 and p<0.01) and Youngduk (r = -0.616 and p<0.01). Thus, this result supported that the proposed burn severity analysis is an adequate method to measure burn severity of large fire areas in Korea.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.684-693
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• 2021

Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.542-549
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• 2022

Purpose: Pipes are widely used as applied devices in many industrial fields such as machinery, electronics, electricity, and plants, and are also widely used in safety-related fields such as firefighting and chemistry. With the diversification of products, the importance of technology in the piping field is also increasing. In particular, when changing the existing copper pipe to stainless steel, it is necessary to evaluate safety and flow characteristics through structural analysis or flow analysis. Method: This study investigated the structural stability of the 6.35 and 15.88 socket models, which are integrated insert type connectors developed by a company, using FEM. For structural analysis, HyperMesh as pre-processor, HYPER VIEW as post-processor, and LS-DYNA as solver were used. Result: In the case of 6.35 socket, the maximum stresses at hook, holder and hinge were 95.02MPa, 19.59MPa and 44.01MPa, respectively, and in case of 15.88 socket, it was 127.7 MPa, 40.09MPa and 45.23MPa, respectively. Conclusion: Comparing the stress distribution of the two socket models, the stress in the 15.88 socket, which has a relatively large outer diameter, appears to be large overall, but it is significantly lower than the yield stress of each material, indicating that there is no problem in structural safety in both models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.119-129
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• 2023

In many cases, trauma is overcome in a short periodtime, but for some, trauma results in long-term mental health issues such as in the form of post-traumatic stress disorder (PTSD). Natural disasters cause different types and extent of damage, meaning the degree of stress experienced also varies. In the case of damage to a house, the impact can be considerable. Therefore, this study examined the trauma experienced by households whose homes were damaged by natural disasters and to confirm the characteristics of psychological trauma. It was confirmed that traumas was greater when a house was damaged, compared with damage to other types of items. In addition, even in the case of trauma occurring, factors that affect the pattern of change to someone's mental state vary depending on the state's classification. And In addition, health services is significantly analyzed in all variables, and it was considered that the provision of basic services related to safety after a disaster is paramount. However, while psychological counseling has a positive effect on short-term traumas that manifests as anxiety and depression, it has an adverse effect on PTSD because of the depth and complexity of the suffering in PTSD, meaning the type of psychological support needs changing.

• Journal of Digital Convergence
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• v.21 no.3
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• pp.49-62
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• 2023

Due to social and cultural changes and the growth of aging people living as a single because of aging, lonely deaths are steadily increasing, and each local government has begun to define them as a social problem. The legal basis began to be established. In order to explore policy measures to prevent lonely deaths, this study examined cases of lonely death prevention policies using smart digital information technology (AI, IOT), which is being promoted by Daegu Metropolitan City to promote non-face-to-face policies to prevent lonely deaths. Policies related to lonely deaths are divided into two axes: lonely death prevention projects and post-excavation support projects. In order to operate these businesses efficiently, the provision of non-face-to-face services through artificial intelligence and the Internet of Things is recognized as a new service delivery system, so the importance and necessity of non-face-to-face services is increasing. It is time that multifaceted changes and preparations are needed, such as establishing a system to expand the non-face-to-face industry at the national level. In order to respond to another national disaster situation in the future, the non-face-to-face smart care system is being expanded in various welfare policies such as preventing lonely deaths. It will have to be activated.

• Journal of Korean Society of Forest Science
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• v.113 no.3
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• pp.339-348
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• 2024

Debris flow is a typical type of mountainous sediment disaster that can cause widespread damage to both lives and property, making it essential to understand its behavioral characteristics for effective prevention. In this study, pre- and post-event Light Detection And Ranging(LiDAR) data from the Dosan-ri area in Bonghyeon-myeon, Yeongju-si, Gyeongsangbuk-do, Republic of Korea where debris flows occurred in 2023, were used to calculate the actual affected area and terrain change volume caused by the debris flow. These calculated values were then compared with those derived from the numeric simulation model, Morpho2DH, based on field surveys and laboratory investigation data. Additionally, the model's applicability was assessed by conducting cross-sectional elevation analyses based on the extent of the affected area and comparisons of the results. The findings indicate that the debris flow affected area and terrain change volume estimated by the Morpho2DH model were approximately 152% and 178% higher, respectively, compared to the LiDAR-based results. Pearson correlation analysis of the cross-sectional elevation changes showed a positive correlation, with Pearson Correlation Coefficients(PCC) of at least 0.65

• Journal of the Korean Society of Earth Science Education
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• v.12 no.3
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• pp.291-301
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• 2019

The purpose of this study is to develop HTE-STEAM program using natural disasters for high school students and to verify their attitude and satisfaction with STEAM. We developed the HTE-STEAM program utilizing natural disasters and tested the effectiveness of 243 students from G High School and N High School. For data analysis, a single group pretest and post response t-test were conducted to verify the effects on attitudes and satisfaction with STEAM. The research results are as follows. First, we developed STEAM education programs for high school students by selecting the topic of "natural disasters" in the area of earth science and flying drones as lifesaving drones. The six-hour program was designed to give students the experience to solve problems by applying essential knowledge related to natural disasters and drones, and what they learned in other situations. Second, there was a significant statistical test result in the t-test of the corresponding sample by the difference between the pre and post score of the STEAM attitude test (p <.05). The drone-based HTE-STEAM program had a significant improvement in the overall attitude toward STEAM education, which consists of seven subfactors. Third, in the HTE-STEAM satisfaction test, the average value of the lower job offer was 3.64 ~ 3.76, which showed a positive response overall. It is judged that the students' satisfaction is improved through the students' understanding of the problem situation and the design of creative convergence and production process.