• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.63-68
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• 2004

Since 20th century, the rapid growth in economy development and ill-advisable construction of infrastructure which causing injury of nature has generated an El Nino phenomenon problems. For this reason, establishment of heritage preservation plan is being required to prevent damages of important cultural assets from natural disaster. In this study, we obtained both 3D-dxf and VRML-wrl(which support 3D image) files from stone pagodas(stone cultural heritages) by using the digital photogrammetric program. Then database are formed by these two files with other attribute informations. And we made existing cultural heritages management information data format to be unified using JAVA, HTML, and Cosmo Player. Thus, we could construct the web-server for Cultural Heritages Management Information System to contribute not only effective management but also ease of use for expert or amateur user in using of cultural assets informations. And, in virtual reality system, we could make texture presented like as actual texture by using the VRML program.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.47-59
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• 2007

Efficiency and limitations of HAZUS-MH, a GIS based systematic and informative system developed by FEMA and NIBS for natural hazard loss estimations, are discussed by means of a pilot study in the Korean Peninsula. Gyeongsang-do has been selected for the test after careful reviews of previous studies including historical and modern seismicity in the peninsula. A ShakeMap for the selected scenario earthquake with magnitude 6.7 in Gyeongju area is prepared. Then, any losses due to the scenario event have been estimated using HAZUS. Results of the pilot test show that the study area may experience significant physical, economic, and social damages. Detailed study in the future will provide efficient and crucial information to the decision makers and emergency agents to mitigate any disaster posed by natural hazards.

• Journal of the Korea Institute of Building Construction
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• v.15 no.5
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• pp.515-525
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• 2015

Currently, according to the climate change, serious damage by typhoon has been occurred in the world. In this respect, the research on the prediction model to minimize the damage from various natural disaster has been conducted in several developed countries. In the case of U.S, various models to predict building damage costs have been used widely in many organizations such as insurance companies and governments. In South Korea, although studies regarding damage prediction model according to typhoon have been conducted, the scope has been only limited to consider the property of typhoon. However, it is necessary to consider various factors such as typhoon information, geography, construction environment, and socio-economy factors to predict the damages. Therefore, to address this issue, first, correlation analysis is conducted between various variables based on the data of typhoon from 2003 to 2012. Second, the damage prediction model by using regression analysis is developed based on suggested influence factors. The findings of this study can be utilized to develop the model for predicting the damage costs of buildings by typhoon like HAZUS-MH of US.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.217-229
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• 2020

Recently, weather changes in Korea have intensified due to global warming, and the five major natural disasters that occur mostly include heavy rains, typhoons, storms, heavy snow, and earthquakes. Busan is vulnerable to snow disaster, given that the amount of natural disaster damage in Busan accounts for more than 50% of the total amount in the entire metropolitan cities in Korea, and that the Busan area includes many hilly mountains. In this study, we attempted to identify vulnerable areas for snowfall disasters in Busan areas using the geographic information system (GIS) with the data for both geographical and anthropogenic characteristics. We produced the maps of vulnerable areas for evaluating factors that include altitude, slope, land cover, road networks, and demographics, and overlapped those maps to rank the vulnerability to snowfall disasters as the 5th levels finally. To weight each evaluating factor, we used an entropy method. The riskiest areas are characterized by being located in mountainous areas with roads, including Sansung-ro in Geumjeong-gu, Mandeok tunnel in Buk-gu, Hwangnyeongsan-ro in Suyeong-gu, and others, where road restrictions were actually enforced due to snowfall events in the past. This method is simple and easy to be updated, and thus we think this methodology can be adapted to identify vulnerable areas for other environmental disasters.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.610-621
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• 2021

The soil creep, primarily caused by earthquakes and torrential rainfall events, has widely occurred across the country. The Korea Forest Service attempted to quantify the soil creep susceptible areas using a discriminant value table to prevent or mitigate casualties and/or property damages in advance. With the advent of advanced computer technologies, machine learning-based classification models have been employed for managing mountainous disasters, such as landslides and debris flows. This study aims to quantify the soil creep susceptibility using several classifiers, namely the k-Nearest Neighbor (k-NN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) models. To develop the classification models, we downscaled 292 data from 4,618 field survey data. About 70% of the selected data were used for training, with the remaining 30% used for model testing. The developed models have the classification accuracy of 0.727 for k-NN, 0.750 for NB, 0.807 for RF, and 0.750 for SVM against test datasets representing 30% of the total data. Furthermore, we estimated Cohen's Kappa index as 0.534, 0.580, 0.673, and 0.585, with AUC values of 0.872, 0.912, 0.943, and 0.834, respectively. The machine learning-based classifications for soil creep susceptibility were RF, NB, SVM, and k-NN in that order. Our findings indicate that the machine learning classifiers can provide valuable information in establishing and implementing natural disaster management plans in mountainous areas.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.261-275
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• 2023

The purpose of this study was to analyze the conceptual understanding of carbon neutrality among secondary school science pre-service teachers, as well as to identify gaze patterns in visual materials. For this study, gaze tracking data of 20 pre-service secondary school science teachers were analyzed. Through this, the levels of conceptual understanding of carbon neutrality were categorized for the participants, and differences in gaze patterns were analyzed based on the degree of conceptual understanding of carbon neutrality. The research findings are as follows. First, as a result of performing modeling activities to predict carbon emissions and removals until 2100 using the concept of '2050 carbon neutrality,' 50% of the participants held a conception that carbon emissions would continue to increase. Additionally, 25% of the participants did not properly understand the causal relationship between net carbon dioxide emissions and cumulative concentrations. Second, the gaze movements of the participants regarding visual materials related to carbon neutrality were significantly influenced by the information presented in the text area, and in the case of graphs, the focus was mainly on the data area. Moreover, when visual data with the same function and category were arranged, participants showed the most interest in materials explaining concepts or visual data placed on the left side. This implies a preference for specific positions or orders. Participants with lower levels of conceptual understanding and inadequate grasp of causal relationships among elements exhibited notably reduced concentration and overall gaze flow. These findings suggest that conceptual understanding of carbon neutrality including climate change and natural disaster significantly influences interest in and engagement with visual materials.

• Land and Housing Review
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• v.15 no.2
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• pp.57-71
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• 2024

This study aims to develop an evaluation method for solar power facilities considering disaster impacts and to analyse the vulnerabilities of existing facilities. Haenam-gun in Jeollanam-do, where the reassessment of existing facilities is urgent, was selected as the study area. To evaluate the vulnerability from a more objective perspective, principal component analysis and entropy methods were utilised. Seven vulnerability assessment indicators were selected: maximum hourly rainfall, maximum wind speed, number of typhoon occurrence days, number of rainfall days lasting more than five days, maximum daily rainfall, impermeable area ratio, and population density. Among these, maximum hourly rainfall, maximum wind speed, maximum daily rainfall, and number of rainfall days lasting more than five days were found to have the highest weights. The overlay of the derived weights showed that the southeastern regions of Haenam-eup and Bukil-myeon were classified as Grade 1 and 2, whereas the northern regions of Hwawon-myeon, Sani-myeon, and Munnae-myeon were classified as Grade 4 and 5, indicating differences in vulnerability. Of the 2,133 facilities evaluated, 91.1% were classified as Grade 3 or higher, indicating a generally favourable condition. However, there were more Grade 1 facilities than Grade 2, highlighting the need for countermeasures. This study is significant in that it evaluates solar power facilities considering urban disaster resilience and is expected to be used as a basic resource for the installation of new facilities or the management and operation of existing ones.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.655-662
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• 2005

The objective of this thesis is to develop a prediction system of potential landslide sites to apply to the prevention of landslide disaster which occurred during the heavy rainfall in the rainy season. The system was developed by combining a modified slope stability analysis model and a hydrological model. The modified slope stability analysis model, which was improved from 1-D infinite slope stability analysis model, has been taken into consideration of the flexion of the hill slopes. To evaluate its applicability to the prediction of landslides, the data of actual landslides were plotted on the predicted areas on the GIS map. The matching rate of this model to the actual data was 92.4%. And the relations between wetness index and landform factors and potential landslide were analyzed.

• Journal of the Korean Institute of Rural Architecture
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• v.14 no.3
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• pp.121-128
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• 2012

In recent years, the number of returnfarmer is increasing in Korea, interlinked with baby boomer's retirement. One of the returnfarmer's serious problems is the decision making for his returnfarm place. This study intends to get information about a ideal returnfarm place by interpreting Jung-Hwan Lee's written in the Choseon Dynasty, and to use it for returnfarmer's decision making as a lesson in the present age. In the results, this study could finds 8 evaluation criteria in his book except his 4 requirements for a ideal place to live : Ji-ri(地理, geographic), Saeng-ri(生理, physiology), In-sim(人心, popular mind), and San-su(山水, landscape), which are (1) distance from seoul, (2)multi-habitation, (3)convenient transportation, (4)a natural disaster, (5)thief(public order), (6)refuge from a war & escaping from a troubled society, (7)feeling from a place, and (8)Jang-gi(poison coming from earth).

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1209-1212
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• 2007

Urban flooding with surcharges in sewer system was investigated because of unexpected torrential storm events these days, causing significant amounts of human and economic damages. Although there are limitations in forecasting and preventing natural disasters, integrated urban flooding management system using the SWMM(Storm Water Management Model) engine and Web technology will be an effective tool in securing safety in operating rubber-tired transportation system. In this study, the study area, located in Chuncheon, Kangwon province, was selected to evaluate the applicability of the SWMM model in forecasting urban flooding due to surcharges in sewer system The catchment are 21.10 ha in size and the average slope is 2% in lower flat areas. Information of subcatchment, conjunctions, and conduits was used as the SWMM interface to model surface runoff generation, water distribution through the sewer system and amount of water overflow. Through this study, the applicability of the SWMM for urban flooding forecasting was investigated and probability distribution of storm events module was developed to facilitate urban flooding prediction with forecasted rainfall amounts. In addition, this result can be used to the establishment of disaster management system for rainfall safety of rubber-tired tram in the future.