• Title/Summary/Keyword: Disaster information

Search Result 3,479, Processing Time 0.027 seconds

A Real-time Correction of the Underestimation Noise for GK2A Daily NDVI (GK2A 일단위 NDVI의 과소추정 노이즈 실시간 보정)

  • Lee, Soo-Jin;Youn, Youjeong;Sohn, Eunha;Kim, Mija;Lee, Yangwon
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.6_1
    • /
    • pp.1301-1314
    • /
    • 2022
  • Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.

Development of web-based system for ground excavation impact prediction and risk assessment (웹기반 굴착 영향도 예측 및 위험도 평가 시스템 개발)

  • Park, Jae Hoon;Lee, Ho;Kim, Chang Yong;Park, Chi Myeon;Kim, Ji Eun
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.23 no.6
    • /
    • pp.559-575
    • /
    • 2021
  • Due to the increase in ground excavation work, the possibility of ground subsidence accidents is increasing. And it is very difficult to prevent these risk fundamentally through institutional reinforcement such as the special law for underground safety management. As for the various cases of urban ground excavation practice, the ground subsidence behavior characteristics which is predicted using various information before excavation showed a considerable difference that could not be ignored compared to the results real construction data. Changes in site conditions such as seasonal differences in design and construction period, changes in construction methods depending on the site conditions and long-term construction suspension due to various reasons could be considered as the main causes. As the countermeasures, the safety management system through various construction information is introduced, but there is still no suitable system which can predict the effect of excavation and risk assessment. In this study, a web-based system was developed in order to predict the degree of impact on the ground subsidence and surrounding structures in advance before ground excavation and evaluate the risk in the design and construction of urban ground excavation projects. A system was built using time series analysis technique that can predict the current and future behavior characteristics such as ground water level and settlement based on past field construction records with field monitoring data. It was presented as a geotechnical data visualization (GDV) technology for risk reduction and disaster management based on web-based system, Using this newly developed web-based assessment system, it is possible to predict ground excavation impact prediction and risk assessment.

Application of Artificial Intelligence Technology for Dam-Reservoir Operation in Long-Term Solution to Flood and Drought in Upper Mun River Basin

  • Areeya Rittima;JidapaKraisangka;WudhichartSawangphol;YutthanaPhankamolsil;Allan Sriratana Tabucanon;YutthanaTalaluxmana;VarawootVudhivanich
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2023.05a
    • /
    • pp.30-30
    • /
    • 2023
  • This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

  • PDF

Physical Model Experiment for Estimating Wave Overtopping on a Vertical Seawall under Regular Wave Conditions for On-Site Measurements (현장 월파계측을 위한 규칙파 조건에서 직립식 호안의 월파량 추정에 관한 모형실험)

  • Dong-Hoon Yoo;Young-Chan Lee;Do-Sam Kim;Kwang-Ho Lee
    • Journal of Korean Society of Coastal and Ocean Engineers
    • /
    • v.35 no.4
    • /
    • pp.75-83
    • /
    • 2023
  • Apart from implementing hardware solutions like raising the crest freeboard of coastal structures to efficiently counter wave-overtopping, there is a simultaneous requirement for software-driven disaster mitigation strategies. These tactics involve the swift and accurate dissemination of wave-overtopping information to the inland regions of coastal zones, enabling the regulation of evacuation procedures and movement. In this study, a method was proposed to estimate wave-overtopping by utilizing the temporal variation of wave heights exceeding the structure's crown level, with the aim of developing an on-site wave measurement system for providing wave-overtopping information in the field. Laboratory model experiments were conducted on vertical seawall structures to measure wave-overtopping volumes and wave runup heights under different wave conditions and structural freeboard variations. By assuming that the velocity of water inundation on the top of the structure during wave-overtopping events is equivalent to the long-wave velocity, an overtopping discharge coefficient was introduced. This coefficient was utilized to estimate the rate of wave-overtopping based on the temporal changes in wave runup heights measured at the top of the structure. Upon reasonably calculating the overtopping discharge coefficient, it was verified that the estimation of wave-overtopping could be achieved solely based on the wave runup heights.

GIS-based Debris Flow Risk Assessment (GIS 기반 토석류 위험도 평가)

  • Lee, Hanna;Kim, Gihong
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.43 no.1
    • /
    • pp.139-147
    • /
    • 2023
  • As heavy precipitation rates have increased due to climate change, the risk of landslides has also become greater. Studies in the field of disaster risk assessment predominantly focus on evaluating intrinsic importance represented by the use or role of facilities. This work, however, focused on evaluating risks according to the external conditions of facilities, which were presented via debris flow simulation. A random walk model (RWM) was partially improved and used for the debris flow simulation. The existing RWM algorithm contained the problem of the simulation results being overly concentrated on the maximum slope line. To improve the model, the center cell height was adjusted and the inertia application method was modified. Facility information was collected from a digital topographic map layer. The risk level of each object was evaluated by combining the simulation result and the digital topographic map layer. A risk assessment technique suitable for the polygon and polyline layers was applied, respectively. Finally, by combining the evaluated risk with the attribute table of the layer, a system was prepared that could create a list of objects expected to be damaged, derive various statistics, and express the risk of each facility on a map. In short, we used an easy-to-understand simulation algorithm and proposed a technique to express detailed risk information on a map. This work will aid in the user-friendly development of a debris flow risk assessment system.

Establishing meteorological drought severity considering the level of emergency water supply (비상급수의 규모를 고려한 기상학적 가뭄 강도 수립)

  • Lee, Seungmin;Wang, Wonjoon;Kim, Donghyun;Han, Heechan;Kim, Soojun;Kim, Hung Soo
    • Journal of Korea Water Resources Association
    • /
    • v.56 no.10
    • /
    • pp.619-629
    • /
    • 2023
  • Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

Research on Farmer's Response to the Farm-customized Early Warning Service for Weather Risk Management in Korea (농장맞춤형 기상재해 조기경보서비스의 농업인 반응조사)

  • Soo Jin Kim;Sangtaek Seo;Kyo-Moon Shim
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.25 no.3
    • /
    • pp.151-171
    • /
    • 2023
  • This study analyzed farmer's responses to the pilot project in advance of the nationwide expansion of the farm-customized early warning service for weather risk management by conducting a survey among all farmers who received text messages of this service. We analyzed not only the satisfaction of farmers with the early warning service, but also the effectiveness of the service in preventing agrometeorological disasters through cross-tabulation analysis of survey results. More than 330 farmers participated in the survey, and more than 60% of the respondents said that they had prevented or mitigated crop disasters by using the early warning service. The cross-tabulation analysis showed that farmers who perceived the field-specific weather information of the early warning service to be more accurate than the weather forecast were statistically significantly more likely to prevent crop disasters than those who did not. According to our case study, farmers who grew open field fruit crops were particularly sensitive to weather information and confirmed that early warning services, along with disaster prevention facilities, were effective in preparing for freezing and frost injury that had been occurring frequently under the influence of climate change. This study is significant in that it is the first to systematically analyze the effectiveness of the farm-customized early warning service for weather risk management based on extensive surveys. It is expected to contribute to exploring ways to develop the service ahead of the nationwide expansion of the early warning service in the near future.

Evaluation of Spectral Band Adjustment Factor Applicability for Near Infrared Channel of Sentinel-2A Using Landsat-8 (Landsat-8을 활용한 Sentinel-2A Near Infrared 채널의 Spectral Band Adjustment Factor 적용성 평가)

  • Nayeon Kim;Noh-hun Seong;Daeseong Jung;Suyoung Sim;Jongho Woo;Sungwon Choi;Sungwoo Park;Kyung-Soo Han
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.3
    • /
    • pp.363-370
    • /
    • 2023
  • Various earth observation satellites need to provide accurate and high-quality data after launch. To maintain and enhance the quality of satellite data, it is crucial to employ a cross-calibration process that accounts for differences in sensor characteristics, such as the spectral band adjustment factor (SBAF). In this study, we utilized Landsat-8 and Sentinel-2A satellite imagery collected from desert sites in Libya4, Algeria3, and Mauritania2 among pseudo-invariant calibration sites to calculate and apply SBAF, thereby compensating the uncertainties arising from variations in bandwidths. We quantitatively compared the reflectance differences based on the similarity of bandwidths, including Blue, Green, Red, and both the near-infrared (NIR) narrow, and NIR bands of Sentinel-2A. Following the application of SBAF, significant results with reflectance differences of approximately 1% or less were observed for all bands except NIR. In the case of the Sentinel-2A NIR band, it exhibited a significantly larger bandwidth difference compared to the NIR narrow band. However, after applying SBAF, the reflectance difference fell within the acceptable error range (5%) of 1-2%. It indicates that SBAF can be applied even when there is a substantial difference in the bandwidths of the two sensors, particularly in situations where satellite utilization is limited. Therefore, it was determined that SBAF could be applied even when the bandwidth difference between the two sensors is large in a situation where satellite utilization is limited. It is expected to be helpful in research utilizing the quality and continuity of satellite data.

Establishment of Geospatial Schemes Based on Topo-Climatology for Farm-Specific Agrometeorological Information (농장맞춤형 농업기상정보 생산을 위한 소기후 모형 구축)

  • Kim, Dae-Jun;Kim, Soo-Ock;Kim, Jin-Hee;Yun, Eun-Jeong
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.21 no.3
    • /
    • pp.146-157
    • /
    • 2019
  • One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.

A Review Study on Major Factors Influencing Chlorine Disappearances in Water Storage Tanks (저수조 내 잔류염소 감소에 미치는 주요 영향 인자에 관한 문헌연구)

  • Noh, Yoorae;Kim, Sang-Hyo;Choi, Sung-Uk;Park, Joonhong
    • Journal of Korean Society of Disaster and Security
    • /
    • v.9 no.2
    • /
    • pp.63-75
    • /
    • 2016
  • For safe water supply, residual chlorine has to be maintained in tap-water above a certain level from drinking water treatment plants to the final tap-water end-point. However, according to the current literature, approximately 30-60% of residual chlorine is being lost during the whole water supply pathways. The losses of residual chlorine may have been attributed to the current tendency for water supply managers to reduce chlorine dosage in drinking water treatment plants, aqueous phase decomposition of residual chlorine in supply pipes, accelerated chlorine decomposition at a high temperature during summer, leakage or losses of residual chlorine from old water supply pipes, and disappearances of residual chlorine in water storage tanks. Because of these, it is difficult to rule out the possibility that residual chlorine concentrations become lower than a regulatory level. In addition, it is concerned that the regulatory satisfaction of residual chlorine in water storage tanks can not always be guaranteed by using the current design method in which only storage capacity and/or hydraulic retention time are simply used as design factors, without considering other physico-chemical processes involved in chlorine disappearances in water storage tank. To circumvent the limitations of the current design method, mathematical models for aqueous chlorine decomposition, sorption of chlorine into wall surface, and mass-transfer into air-phase via evaporation were selected from literature, and residual chlorine reduction behavior in water storage tanks was numerically simulated. The model simulation revealed that the major factors influencing residual chlorine disappearances in water storage tanks are the water quality (organic pollutant concentration) of tap-water entering into a storage tank, the hydraulic dispersion developed by inflow of tap-water into a water storage tank, and sorption capacity onto the wall of a water storage tank. The findings from his work provide useful information in developing novel design and technology for minimizing residual chlorine disappearances in water storage tanks.