• Journal of Korean Society of Water Science and Technology
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• v.26 no.6
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• pp.133-142
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• 2018

Increasing localized torrential rainfall caused by abnormal climate are making higher damage to human and property through urban inundation So The need of preventive measures is being highlighted. In this study, the methodology for calculating flood depth in domestic water map using an interpolation method in order to utilizing the results of flood analysis provided only in the form of a report is suggested. In the Incheon Metropolitan City S area as the test-bed, the flood depth was calculated using the interpolating the actual flood analysis by image and verification was performed. Verification results showed that the error rate was 5.2% for the maximum flooding depth, and that the water depth value was compared to 10 random points, which showed a difference of less than 0.030 m. Also, as the results of the flood analysis were presented in various ways, the flood depth was extracted from the image of the result of the flood analysis, which changed the presentation method, and then compared and analyzed. The results of this study could be available for the use of basic data from the research on the urban penetration of domestic consumption and for decision-making of policy.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.442-448
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• 2009

Recently, the natural disaster has occurred as a heavy snow fall, drought and flood by abnormal weather. The damage of human and property by flood is most serious problem among those natural disaster. In order to prepare structural or non-structural measure, to estimate exact flood discharge is important element. This study analyze frequency of hour-unit rainfall data and estimate probability flood discharge by HEC-HMS as changing method of runoff analysis. Also, this study analyze the peak flood discharge sensibility according to Curve Number(CN) with the return period. As a result of estimation of probability flood discharge with the variety CN, to select Antecedent Moisture To select suitable condition(AMC) is important parameter because flood discharge is estimated 40% gap according to AMC.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.4
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• pp.13-22
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• 2020

Recent abnormal climate has increased the frequent of heavy rains and floods, and over 100 people have been killed in the last decade caused by these. In the midst of severe flood disasters, safety education to learn how to respond and evacuate them has become important. The purpose of this study was to analyze the needs and effective education types for the flood disaster school safety education. This study shows Analysis the current state of school safety education based on the 7 standards of school safety education, especially in disaster safety categories through the survey of secondary school teachers and students. And a desirable form of flood safety education was derived by analysis of awareness of flood disaster safety education and their educational needs. More than 70% of teachers and students hoped for a experience-based flood disaster safety education, they wanted to learn once a year, one hour from a safety education specialist in experience facilities. As for the contents of the training, they wanted to experience evacuation in the event of flood disaster, and also wanted education related to survival swimming. The most necessary thing for the establishment of experience-based disaster safety education was the expansion of experience facilities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.299-309
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• 2006

In recent years, a large natural disasters have occurred due to worldwide abnormal weather and the amount of damage has been increased more resulting from high density population and a large-sized buildings of the urbanized area. In this study. we estimate the flooded area according to rainfall probability intensify and sea level in Woreong dong, Masan occurred flood damages by typhoon Maemi using SWMM, a dynamic rainfall-runoff simulation model in urban area, and then analyze the damage of flood expected area through connecting with GIS database. In result, we can predict accurately expected area of inundation according to the rainfall intensity and sea level rise through dividing the study area into sub-area and estimating a flooded area and height using SWMM. We provide also the shelter information available for urban planning and flood risk estimation by landuse in expected flood area. Further research for hazard management system construction linked with web or wireless communication technology expects to increase its application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.341-346
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• 2022

Due to global warming and abnormal climate, the frequency and damage of floods are increasing, and the number of people exposed to flood-prone areas has increased by 25% compared to 2000. Floods cause huge financial and human losses, and in order to reduce the losses caused by floods, it is necessary to predict the flood in advance and decide to evacuate quickly. This paper proposes a flood risk determination model using a CNN-based classification model so that timely evacuation decisions can be made using rainfall and water level data, which are key data for flood prediction. By comparing the results of the CNN-based classification model proposed in this paper and the DNN-based classification model, it was confirmed that it showed better performance. Through this, it is considered that it can be used as an initial study to determine the risk of flooding, determine whether to evacuate, and make an evacuation decision at the optimal time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.216-218
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• 2022

Natural disasters caused by abnormal climates are continuously increasing, and the types of natural disasters that cause the most damage are flood damage caused by heavy rains and typhoons. Therefore, in order to reduce flood damage, this paper proposes a system that can predict the water level, a major parameter of flood, in real time using LSTM and GRU. The input data used for flood prediction are upstream and downstream water levels, temperature, humidity, and precipitation, and real-time prediction is performed through the pre-trained LSTM-GRU model. The input data uses data from the past 20 hours to predict the water level for the next 3 hours. Through the system proposed in this paper, if the risk determination function can be added and an evacuation order can be issued to the people exposed to the flood, it is thought that a lot of damage caused by the flood can be reduced.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.49-56
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• 2017

In this study, flood analysis was conducted to prepare for damage caused by typhoons and heavy rain due to abnormal climate and climate change. Two - dimensional flooding analysis using the FLUMEN model, which is widely used for national and international flood risk mapping, was conducted for the Nam River Basin, which is the tributary of the Nakdong River. This study divides the topography into $5m{\times}5m$ DEM by ArcView, so that the accuracy of river repair and hydrological characterization and flood area identification can be maximized. As a result of simulation of water flooding, 163.3ha in section 1, 227.7ha in section 2 and 59.9ha in section 3 were simulated.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.74-89
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• 2015

The objective of this study is to present countermeasures for mitigation of flood damage with inundation analysis considering the effect of inland and river flood and prediction of flood inundation area, depth and time against emergencies caused by abnormal flood and local torrential rainfall. In this study, 2-D inundation analysis was fulfilled on the basis of river flood analysis applying to HEC-HMS and FLDWAV model and inundation analysis applying to SWMM model for the area of Shineum-dong, Gimcheon-si. Also expected inundation depth and area about probable rainfall of 100 and 200 years frequency were suggested. If expected inundation depth and flooding area is presented on the basis of this inundation analysis considering the effect of inland and river flood, it would be an important preliminary data to establish structural and nonstructural countermeasures for flood prevention. Also if flood risk map is prepared based on the result of inundation analysis, it would be useful to evacuate residents in high-risk area and regulate road and vehicle.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.655-666
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• 2013

Lately, intensity and frequency of natural disasters such as flood are increasing because of abnormal climate. Casualties and property damages due to large-scale floods such as Typhoon Rusa in 2002 and Typhoon Maemi in 2003 rapidly increased, and these show the limits of the existing disaster prevention measures and flood forecasting systems regarding irregular climate changes. In order to efficiently respond to extraordinary flood, it is important to provide effective countermeasures through an inundation model that can accurately simulate flood inundation patterns. However, the existing flood inundation analysis model has problems such as excessive take of analysis time and accuracy of the analyzed results. Therefore, this study conducted a flood inundation analysis by using the Gerris flow solver that uses quadtree grid, targeting the Baeksan Levee in the Nakdong River Basin that collapsed because of a concentrated torrential rainfall in August, 2002. Through comparisons with the FLUMEN model that uses unstructured grid among the existing flood inundation models and the actual flooded areas, it determined the applicability and efficiency of the quadtree grid-based flood inundation model of the Gerris flow solver.