• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.173-182
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• 2024

In recent, there has been a trend toward primarily utilizing data-driven models employing artificial intelligence technologies, such as machine learning, for flood prediction. These data-driven models offer the advantage of utilizing pre-training results, significantly reducing the required simulation time. However, it remains that a considerable amount of flood data is necessary for the pre-training in data-driven models, while the available observed data for application is often insufficient. As an alternative, validated simulation results from physically-based models are being employed as pre-training data alongside observed data. In this context, we developed a flood mapping accelerator to generate flood maps for pre-training. The proposed accelerator automates the entire process of flood mapping, i.e., estimating flood discharge using HEC-1, calculating water surface levels using HEC-RAS, simulating channel overflow and generating flood maps using RAS Mapper. With the accelerator, users can easily prepare a database for pre-training of data-driven models from hundreds to tens of thousands of rainfall scenarios. It includes various convenient menus containing a Graphic User Interface(GUI), and its practical applicability has been validated across 26 test-beds.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1076-1076
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• 2005

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.203-222
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• 2011

The characteristics of flood damages have been increasingly strengthened and take the form of unpredictable and unusual weather phenomena caused by climate change and climate anomalies. To prevent inundation damage caused by breach of hydraulic structure such as dam or levee, and trouble of drainage of inner basin, the prediction necessity of flood inundation area, flood risk analysis, and drawing flood risk maps have been on the rise, and the national flood risk maps have been produced. In this study, the quantitative flood vulnerability analysis was performed, which represents population living within flood-affected areas, types of economic activities, facilities affected by flood, in order to extend flood risk mapping from simple hazard concept into risk based idea. By applying it to Nakdong River basin, the flood vulnerability indices were estimated to draw flood risk maps subdivided into administrative districts. The result of this study can be applied to establish the disaster prevention measures and priority decision of disaster prevention project.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.117-126
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• 2018

This study aims to evaluate the usability of polarimetric SAR measurements for discriminating water-covered area from other land cover types and to propose polarimetric parameters showing the better response to the flood. Flood-related changes in the polarimetric parameters were studied using the L-band PALSAR-2 quad-pol mode data acquired before and after the severe flood events occurred in Joso city, Japan. The experimental results showed that, among various polarimetric parameters, the HH-polarization intensity, the Shannon entropy, and the surfaces scattering component of model-based decomposition were found to be useful to discriminate water-covered areas from other land cover types. Particularly, an unsupervised change detection with the Shannon entropy provides the best result for an automated mapping of flood extents.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.287-290
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• 2002

Real-time flood submerged area map provides important scientific basis for the decision-making of flood control and relieving disaster. Taking the Wuhan area as an example, this article gives out a image interpretation method under influence of flood, and describes real-time or quasi-real-time flood submerged area map by using the integration of ERS-2 SAR image and LANDSAT TM image in support of remote sensing images process software ERDAS.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.375-386
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• 2022

The city of Khartoum, the capital of Sudan, was heavily damaged by the flood of the Nile in 2020. Classification using satellite images can define the damaged area and help emergency response. As Synthetic Aperture Radar (SAR) uses microwave that can penetrate cloud, it is suitable to use in the flood study. In this study, Random Forest classifier, one of the supervised classification algorithms, was applied to the flood event in Khartoum with various sizes of the training dataset and number of images using Sentinel-1 SAR. To create a training dataset, we used unsupervised classification and visual inspection. Firstly, Random Forest was performed by reducing the size of each class of the training dataset, but no notable difference was found. Next, we performed Random Forest with various number of images. Accuracy became better as the number of images in creased, but converged to a maximum value when the dataset covers the duration from flood to the completion of drainage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.691-702
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• 2019

Flood inundation map has various important roles in terms of municipal planning, timely dam operation, economic levee design, and building flood forecasting systems. Considering that the riparian areas adjacent to national rivers with high potential flood vulnerability conventionally imposed special cares to justify applications of recently available two- or three-dimensional flood inundation numerical models on top of digital elevation models of dense spatial resolution such as LiDAR irrespective of their high costs. On the contrary, local streams usually could not have benefits from recent technological advances, instead they inevitably have relied upon time-consuming manual drawings or have accepted DEMs with poor resolutions or inaccurate 1D numerical models for producing inundation maps due mainly to limited budgets and suitable techniques. In order to efficiently and cost-effectively provide a series of flood inundation maps dedicatedly for the local streams, this study proposed an OpenGIS-based flood mapping tool named Open Flood Mapper (OFM). The spatial accuracy of flood inundation map derived from the OFM was validated throughout comparison with an inundation trace map acquired after typhoon Nari in Hancheon basin located in Jeju Island. Also, a series of inundation maps from the OFM were comprehensively investigated to track the burst of flood in the extreme flood events.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.181-196
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• 2019

Floods can be caused by a variety of factors, and the main cause of floods is the exceeding of urban drainage system or river capacity. In addition, rainfall frequently occurs that causes large watershed runoff. Since the existing methodology of preparing for flood risk map is based on hydraulic and hydrological modeling, it is difficult to analyse for a large area because it takes a long time due to the extensive data collection and complex analysis process. In order to overcome this problem, this study proposes a methodology of mapping for flood vulnerable area that considered the surface runoff mechanism. This makes it possible to reduce the time and effort required to estimate flood vulnerabilities and enable detailed analysis of large areas. The target area is Seoul, and it was confirmed that flood damage is likely to occur near selected vulnerable areas by verifying using 2×2 confusion matrix and ROC curve. By selecting and prioritizing flood vulnerable areas through the surface runoff mechanism proposed in this study, the establishment of systematic disaster prevention measures and efficient budget allocation will be possible.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.71-84
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• 2022

The objective of this study is to develop a two-dimensional (2D) flood model that can perform accurate flood analysis with simple input data. The 2D flood inundation models currently used to create flood forecast maps require complex input data and grid generation tools. This sometimes requires a lot of time and effort for flood modeling, and there may be difficulties in constructing input data depending on the situation. In order to compensate for these shortcomings, in this study, a grid-based model that can derive accurate and rapid flood analysis by reflecting correct topography as simple input data was developed. The calculation efficiency was improved by extending the existing 2×2 sub-grid model to a 5×5. In order to examine the accuracy and applicability of the model, it was applied to the Gamcheon Basin where both urban and river flooding occurred due to Typhoon Rusa. For efficient flood analysis according to user's selection, flood wave propagation patterns, accuracy and execution time according to grid size and number of sub-grids were investigated. The developed model is expected to be highly useful for flood disaster mapping as it can present the results of flooding analysis for various situations, from the flood inundation map showing accurate flooding to the flood risk map showing only approximate flooding.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.63-71
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• 2017

Recently, there has been growing interest in public participation GIS (Geographic Information System) technology that enables spontaneous public response to increasingly frequent flood and drought events. Accordingly, social and economic demands are increasing on portal services that are designed to help cope with natural hazards such as earthquakes. By focusing on a specific hazard, urban flood, this study designed a prototype of a disaster response portal and its service system. The community map developed in this study is focused on prevention and mitigation of the urban flood damage by analyzing the vulnerable areas, and providing effective means to inspect the roads and sewer systems. By considering the compatibility with VGI (Volunteered Geographic Information) portals, the study created a system environment by employing universally used open-source software programs such as Apache Tomcat, GeoServer, GeoNetwork, and PostgreSQL/PostGIS.