• Journal of Internet Computing and Services
• /
• v.21 no.5
• /
• pp.31-37
• /
• 2020

Last year's Goseong-Sokcho forest fires have highlighted the limitations of extinguishing work for night-time forest fire and the importance of quick identification for information on the spread of forest fire. However, it is not easy to find services that take into account the characteristics of forest fires, as most existing disaster-related mobile applications and research assume various disaster situations rather than just forest fire situations. Therefore, a system that can provide information quickly is needed, taking into account the characteristics of forest fires and the limitations of extinguishing work. In this paper, we propose evacuation route guidance services that bypass areas where fire has already spread, supplement existing methods of extinguishing work, and provide general information on forest fire situations in real time, by putting drones into forest fire situations. It has been implemented to automate image analysis using the Rekognition service of Amazon Web Service (AWS), and the results of fire detection and the T Map API guide the evacuation path. It is expected that the results of this paper will allow efficient and rapid rescue and extinguishing work to be carried out, and further reduce the damage of human life caused by forest fires.

• Journal of Environmental Science International
• /
• v.23 no.4
• /
• pp.595-603
• /
• 2014

Jeju Island, a volcanic island, is the region that shows the biggest rainfall and has a big elevation-specific deviation of precipitation, but Jeju Island River Maintenance Plan doesn't reflect the characteristics of Jeju Island as it only calculates probable precipitation from four weather stations with elevation less than 100m. Therefore, this study uses AWS observational data in four Jeju Island weather stations and other regions to calculate location-specific probable precipitation, review the elevation-probable precipitation correlation in southern and northern regions, and create a probable precipitation map for all regions of Jeju Island, in order to produce better outcomes. This study is expected to be the most basic data to establish a safe Jeju island from flood disaster in preparation for the future climate changes and widely used for Jejudo Basin Dimension Planning, River Maintenance Plan, Pre-Disaster Impact Review, etc.

• Journal of the Korean GEO-environmental Society
• /
• v.22 no.11
• /
• pp.5-13
• /
• 2021

The interest of expecting the liquefaction damage is increasing due to the liquefaction in Pohang in 2017. Liquefaction is defined as a phenomenon that the ground can not support the superstructure due to loss of the strength of the ground. As an alternative against this, many studies are being conducted to increase the precision and to compose a liquefaction hazard map for the purpose of identifying the scale of liquefaction damage using the liquefaction potential index (LPI). In this research, in order to analyze the degree of precision with regard to spatial interpolation objects such as LPI value and geotechnical information for LPI determination, liquefaction hazard map were made for the target area. Furthermore, based on the trend of precision, probability value was analyzed using probability maps prepared through qualitative characteristics. Based on the analysis results, the precision of the liquefaction hazard map setting the spatial interpolation object as geotechnical information is higher than that as LPI value. Furthermore, the precision of the liquefaction hazard map does not affect the distribution of the probability value.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.26 no.5
• /
• pp.506-513
• /
• 2020

Due to climate change, there is an increasing risk of complex (hybrid) disasters, comprising rising sea-levels, typhoons, and torrential rains. This study focuses on Marine City, Busan, a new residential city built on a former landfill site in Suyeong Bay, which recently suffered massive flood damage following a combination of typhoons, storm surges, and wave overtopping and run-up. Preparations for similar complex disasters in future will depend on risk impact assessment and prioritization to establish appropriate countermeasures. A framework was first developed for this study, followed by the collection of data on flood prediction and socioeconomic risk factors. Five socioeconomic risk factors were identified: (1) population density, (2) basement accommodation, (3) building density and design, (4) design of sidewalks, and (5) design of roads. For each factor, absolute criteria were determined with which to assess their level of risk, while expert surveys were consulted to weight each factor. The results were classified into four levels and the risk level was calculated according to the sea-level rise predictions for the year 2100 and a 100-year return period for storm surge and rainfall: Attention 43 %, Caution 24 %, Alert 21 %, and Danger 11 %. Finally, each level, indicated by a different color, was depicted on a complex disaster risk map.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.19 no.5
• /
• pp.11-17
• /
• 2016

The purposes of this research are to estimate area of greenable roof and to monitor maintaining of green roofs using World-View 2 images. The contents of this research are development of World-View 2 application technologies for estimation of green roof area and development of monitoring and maintaining of green roofs using World-View 2 images. The available green roof areas in Gwangjin-gu Seoul, a case for this study, were estimated using digital maps and World-View 2 images. The available green roof area is approximately 12.17% ($2,153,700m^2$) of the total area, and the roof vegetation accounts for 0.46% ($80,660m^2$) of the total area. For verification of the extracted roof vegetation, Vworld 3D Desktop map service was applied. The study results may be used as a decision-making tool by the government and local governments in determining the feasibility of green roof projects. In addition, the project implementer may periodically monitor to see whether roof greening has maintained for efficient management of projects, and a vast amount of World-View 2 images may be regularly used before and after the projects to contribute to sharing of satellite images information.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.275-279
• /
• 2002

Change Detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, Change Detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by low- or middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• Journal of Korean Society of societal Security
• /
• v.1 no.4
• /
• pp.57-64
• /
• 2008

Korea has been suffered from serious damages of lives and properties, due to landslides that are triggered by heavy rains in every monsoon season. This study developed the physically based landslide prediction model which consists of 3 parts, such as slope stability analysis model, groundwater flow model and soil depth model. To evaluate its applicability to the prediction of landslides, the data of actual landslides were plotted on the areas predicted on the GIS map. The matching rate of this model to the actual data was 84.8%. The relation between hydrological and landform factors and potential landslide were analyzed.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.3
• /
• pp.102-112
• /
• 2015

In this paper we propose an application that can help you to find a school near you easily using smart phone GPS capabilities and Google map mounted on Android system. We use a shortest path algorithm to search near destinations. You can take advantage of the developed application when finding public places or destinations. Schools have usually been used as places for disaster evacuation, entrance examination, and qualifying examination. Even though you are not the young who use the smart phone easily, anyone can find a destination school easily with the proposed application of this paper.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.376-376
• /
• 2018

수재해 관련 정보를 수집하기 위한 주요 소스로서 위성 정보가 활용되고 있다. 본 연구에서는 그 중 NASA SEDAC과 UNISDR(United Nations International Strategy for Disaster Reduction)의 Global Risk Data Platform, UNESCO의 IHP-WINS를 대상으로 메타정보를 구축하는 [글로벌(위성기반) 수재해 관련정보 수집체계]를 구성하였다. 이때 메타정보를 수신/처리하는 역할의 하비스터는 OGC(Open Geospatial Consortium) 표준 WMS(Web Map Service)서비스의 필수 Operation인 GetCapabilities를 통하여 ISO GML을 획득한 후 이를 처리하도록 구성함으로써 여타표준 준수 DataSource에 대한 적응성을 확보하였다. 수집된 메타데이터를 통하여 검색된 정보는 표준 Map Service를 통하여 구글 지도 기반의 시계열 수재해 주제도 정보 서비스와 WebGL기반 3D 수재해 주제도 서비스로 각각 구성되도록 설계하였다. 국내 수재해 현장정보 수집 체계에 있어서는 사진을 포함한 시민의 현장 정보가 지오태깅기술과 동반되어 수재해 플랫폼으로 업로드 되면, 수집된 시계열 정보는 주제별 카테고리로 그룹화 된 후 클러스터링 가시화 기법으로 지도 공간상에 표출되도록 구성하였다. 이때 공신력 있는 공공 데이터(Data.go.kr)의 대피소 등 관련 시설 정보를 동시에 매핑하여 융합서비스 하도록 모색하였다. 본 연구는 전반적으로 웹서비스를 지향하며 전문가, 기관(부처), 교육기관으로 구분된 서비스를 구상하고 있다.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1303-1322
• /
• 2020

Indonesia is more prone to natural disasters due to its geological condition under the three main plates, making Indonesia experience frequent seismic activity, causing earthquakes, volcanic eruption, and tsunami. Those disasters could lead to other disasters such as landslides, floods, land subsidence, and coastal inundation. Monitoring those disasters could be essential to predict and prevent damage to the environment. We reviewed the application of remote sensing and Geographic Information System (GIS) for detecting natural disasters in the case of Indonesia, based on 43 articles. The remote sensing and GIS method will be focused on InSAR techniques, image classification, and susceptibility mapping. InSAR method has been used to monitor natural disasters affecting the deformation of the earth's surface in Indonesia, such as earthquakes, volcanic activity, and land subsidence. Monitoring landslides in Indonesia using InSAR techniques has not been found in many studies; hence it is crucial to monitor the unstable slope that leads to a landslide. Image classification techniques have been used to monitor pre-and post-natural disasters in Indonesia, such as earthquakes, tsunami, forest fires, and volcano eruptions. It has a lack of studies about the classification of flood damage in Indonesia. However, flood mapping was found in susceptibility maps, as many studies about the landslide susceptibility map in Indonesia have been conducted. However, a land subsidence susceptibility map was the one subject to be studied more to decrease land subsidence damage, considering many reported cases found about land subsidence frequently occur in several cities in Indonesia.