• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.236-236
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• 2015

Flood is one of the major natural disasters affecting millions of people. Thailand also, frequently faces with this type of disaster. Especially, 2011 mega flood in Central Thailand, inundated highway severely attributed to the failure of national economic and risk to life. Lesson learned from such an extreme event caused flood monitoring and warning becomes one of the sound mitigations. The highway flood hazard mapping accomplished in this research is one of the strategies. This is due to highway flood is the potential risk to life and limb, and potential damage to property. Monitoring and warning therefore help reducing live and property losses. In this study, degree of highway flood hazard was assessed by weighting factors for each cause of the highway flood using Multi Criteria Analysis (MCA) based Analytic Hierarchy Process (AHP). These weighting factors are the essential information to classify the degree of highway flood hazard to enable pinpoint on flood monitoring and flood warning in hazard areas. The highway flood causes were then investigated. It was found that three major factors influence to the highway flood are namely the highway characteristics, the hydrological characteristics and the land topography characteristics. The weight of importance for each cause of the highway flood in the whole country was assessed by weighting 3 major factors influence to the highway flood. According to the result of MCA analysis, the highway, the hydrological and the land topography characteristics were respectively weighted as 35, 35 and 30 percent influence to the cause of highway flood. These weighting factors were further utilized to classify the degree of highway flood hazard. The Weight Linear Combination (WLC) method was used to compute the total score of all highways according to each factor. This score was later used to categorize highway flood as high, moderate and low degree of hazard levels. Highway flood hazard map accomplished in this research study is applicable to serve as the handy tool for highway flood warning. However, to complete the whole warning process, flood water level monitoring system for example the camera gauge should be installed in the hazard highway. This is expected to serve as a simple flood monitor as part of the warning system during such extreme or critical event.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.797-808
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• 2019

This study evaluated the applicability of spacebourne datasets to the flood analysis in an ungauged watershed where is no discharge measurements. The Duman River basin of North Korea was selected as a target area which was flooded by recent Typhoon Lionrock. Topographical parameters for flood analysis were estimated from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM). GDEM includes the shortcomings of information on river cross-section, and conducted 2 dimensional flood analysis when considering virtual river cross-section and not considering it. As a result of comparative analysis, an error occurs in the inundation area and depth, but when used carefully, it is considered that the satellite image can be used for creating flood hazard map and utilizing information for response and preparation.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.278-278
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• 2018

현재 우리나라에서는 행정안전부의 풍수해저감종합계획, 사전재해영향성검토협의, 재해위험지구개선사업 등에 해외에서 개발된 상용프로그램이 사용돼 접근성 저하로 인해 지자체 방재담당자의 실무나 대학에서 연구용으로 다루기에는 한계가 있다. 이에 본 연구에서는 내수침수, 외수침수, 2차원 침수해석으로 구성하여 GUI 기능을 강화한 통합침수재해지도 작성시스템(i-FIM, Integrated Flood Inundation Modeling system)을 개발하여 입력자료의 구성 및 매개변수의 수정이 용이하게 함으로써 하수관망 등에 부분적인 설계 변경이 있는 경우 지자체 방재담당자가 간단한 작업을 통해 침수영향 변화를 쉽게 파악할 수 있도록 하였다. 또한, 상세한 지형의 반영이 필요한 도시지역의 2차원 침수해석의 경우 계산격자 망의 크기가 작아질수록 소요되는 계산시간이 기하급수적으로 증가하는 한계가 있어 i-FIM에서는 계산격자를 $2{\times}2$, $3{\times}3$, $5{\times}5$ Subgrid 형태의 격자를 적용하고, 병렬프로그래밍과 계산시간조정 기능을 추가하여 2차원 침수해석 모형의 계산 속도를 향상시켰다. 이를 실무에 적용하기 앞서 2006년 집중호우로 인해 안성시에서 발생한 제방 붕괴사상, 2016년 태풍 차바로 인해 울산시에서 발생한 제방 월류 사상을 통해 침수흔적도와 비교하여 검증을 실시하였다. i-FIM에서 최종적인 2차원 침수해석 결과는 2017년에 개정된 '재해지도 작성 기준 등에 관한 지침'의 침수심 등급 구분의 색채 설정에 따라 각 격자별 침수심을 표출함으로써 표준화된 재해지도 작성이 가능하도록 하였다. 또한, 포털사이트의 지도 및 위성지도에 표출함으로써 침수 위험이 발생할 수 있는 지역의 현재 이용 용도를 파악하여 침수재해에 대한 상세한 대책을 마련할 수 있을 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.617-623
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• 2019

Numerous water disasters have recently occurred all over the world, including South Korea, due to global climate change in recent years. As water-related disasters occur extensively and their sites are difficult for people to access, it is necessary to monitor them using satellites. The Ministry of Environment and K-water plan to launch the next-generation medium satellite No. 5 (water resource/water disaster satellite) equipped with C-band synthetic aperture radar (SAR) in 2025. C-band SAR has the advantage of being able to observe water resources twice a day at a high resolution both day and night, regardless of weather conditions. Currently, RADARSAT-2 and Sentinel-1 equipped with C-band SAR achieve the purpose of their launch and are used in various environmental fields such as forest structure detection and coastline change monitoring, as well as for unique purposes including the detection of flooding, drought and soil moisture change, utilizing the advantages of SAR. As such, this study aimed to analyze the characteristics of the next-generation medium satellite No. 5 and its application in environmental fields. Our findings showed that it can be used to improve the degree of precision of existing environmental spatial information such as the classification accuracy of land cover map in environmental field works. It also enables us to observe forests and water resources in North Korea that are difficult to access geographically. It is ultimately expected that this will enable the monitoring of the whole Korean Peninsula in various environmental fields, and help in relevant responses and policy supports.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.211-218
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• 2019

The Ministry of Land, Infrastructure and Transport is planning to launch CAS-500 (Compact Advanced Satellite 500) 1 and 2 in 2019 and 2020. Satellite image information collected through CAS-500 can be used in various fields such as global environmental monitoring, topographic map production, analysis for disaster prevention. In order to utilize in various fields like this, it is important to get the location accuracy of the satellite image. In order to establish the precise geometry of the satellite image, it is necessary to establish a precise sensor model using the GCP (Ground Control Point). In order to utilize various fields, step - by - step automation for orthoimage construction is required. To do this, a database of satellite image GCP chip should be structured systematically. Therefore, in this study, we will analyze various techniques for automatic GCP extraction for precise geometry of satellite images.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.593-603
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• 2018

The most of groundwater with high U-concentration occur in the Jurassic granite of Gyeonggi massif and Ogcheon belt, and some of them occur in the Cretaceous granite of Ogcheon belt. On the contrary, they do not occur in the Jurassic granite of Yeongnam massif and the Cretaceou granite of Gyeongsang basin. The Jurassic and Cretacous granite, the host rock of high U-groundwater, were resulted from parental magma with high ratio of crustal material and highly differentiated product of fractional crystalization. These petrogenetic characteristics explain the geological evidence for preferential distribution of uraniferous groundwater in each host rock. It were reported recently that high U-content, low Th/U ratio and soluble mineral occurrence of uraninite in the two-mica granite of Daejeon area which have characteristics of S-type peraluminous and highly differntiated product. It is the mineralogical-geochemical evidences supporting the fact that the two-mica granite is the effective source of uranium in groundwater. The biotite granite and two-mica granite of Jurassic age were reported as biotite granite in many geological map even though two-mica granite occur locally. This fact suggest that the influence of two-mica granite can not be ignored in uraniferous groundwater hosted by biotite granite.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.345-352
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• 2020

Securing the lead time for evacuation is crucial to minimize flood damage. In this study, downstream water levels for heavy rainfall were predicted using measured water level observation data. Multiple regression analysis and artificial neural networks were applied to the Seom River experimental watershed to predict the water level. Water level observation data for the Seom River experimental watershed from 2002 to 2010 were used to perform the multiple regression analysis and to train the artificial neural networks. The water level was predicted using the trained model. The simulation results for the coefficients of determination of the artificial neural network level prediction ranged from 0.991 to 0.999, while those of the multiple regression analysis ranged from 0.945 to 0.990. The water level prediction model developed using an artificial neural network was better than the multiple-regression analysis model. This technique for forecasting downstream water levels is expected to contribute toward flooding warning systems that secure the lead time for streams.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.39-47
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• 2022

This study aims at evaluating the stability of disaster risks, such as schools, apartments, and geotechnical structures located around slopes in urban areas. The research conducted an aerial photography analysis on where the slope of the retaining wall behind 𐩒𐩒 High School in Gwangju collapsed in August 2018 due to heavy rain. In general, the overflow of rainwater has been managed through drainage channels around slopes during the rainy season, and the surface flow of rainfall was limited due to the presence of dense forests in the area. However, when the slope collapsed, a lot of water flowed out of the ground, and the saturated surface layer ground was destroyed. To analyze the cause, the changed terrain of the upper slope area, which could not be directly identified, was photographed using unmanned aerial vehicles. Digital Elevation Model by unmanned aerial vehicle shooting was performed by analyzing the slope map, calculating the direction of rainfall and the length and width of water-logged areas. The change in the instability of the slope over time due to a 10-day rainfall was also analyzed through numerical analysis.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.425-440
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• 2023

Monitoring water surface has become one of the most prominent areas of research in addressing environmental challenges.Accurate and automated detection of watersurface in remote sensing imagesis crucial for disaster prevention, urban planning, and water resource management, particularly for a country where water plays a vital role in human life. However, achieving precise detection poses challenges. Previous studies have explored different approaches,such as analyzing water indexes, like normalized difference water index (NDWI) derived from satellite imagery's visible or infrared bands and using k-means clustering analysis to identify land cover patterns and segment regions based on similar attributes. Nonetheless, challenges persist, notably distinguishing between waterspectralsignatures and cloud shadow or terrain shadow. In thisstudy, our objective is to enhance the precision of water surface detection by constructing a comprehensive water database (DB) using existing digital and land cover maps. This database serves as an initial assumption for automated water index analysis. We utilized 1:5,000 and 1:25,000 digital maps of Korea to extract water surface, specifically rivers, lakes, and reservoirs. Additionally, the 1:50,000 and 1:5,000 land cover maps of Korea aided in the extraction process. Our research demonstrates the effectiveness of utilizing a water DB product as our first approach for efficient water surface extraction from satellite images, complemented by our second and third approachesinvolving NDWI analysis and k-means analysis. The image segmentation and binary mask methods were employed for image analysis during the water extraction process. To evaluate the accuracy of our approach, we conducted two assessments using reference and ground truth data that we made during this research. Visual interpretation involved comparing our results with the global surface water (GSW) mask 60 m resolution, revealing significant improvements in quality and resolution. Additionally, accuracy assessment measures, including an overall accuracy of 90% and kappa values exceeding 0.8, further support the efficacy of our methodology. In conclusion, thisstudy'sresults demonstrate enhanced extraction quality and resolution. Through comprehensive assessment, our approach proves effective in achieving high accuracy in delineating watersurfaces from satellite images.