• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.775-788
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• 2006

Many disaster monitoring systems are constantly studied to prevent disasters such as environmental pollution, the breaking of a tunnel and a building, flooding, storm earthquake according to the progress of wireless telecommunication, the miniaturization of terminal devices, and the spread of sensor network. A disaster monitoring system can extract information of a remote place, process sensor data with rules to recognize disaster situation, and provide work for preventing disaster. However existing monitoring systems are not enough to predict and prevent disaster, because they can only process current sensor data through utilizing simple aggregation function and operators. In this paper, we design and implement a disaster prevention system to predict near future dangerous area through using outside sensor network and spatial Information. The provided prediction technique considers the change of spatial information over time with current sensor data, and indicates the place that could be dangerous in near future. The system can recognize which place would be dangerous and prepare the disaster prevention. Therefore, damage of disaster and cost of recovery would be reduced. The provided disaster prevention system and prediction technique could be applied to various disaster prevention systems and be utilized for preventing disaster and reducing damages.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.373-383
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• 2006

The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

• Journal of Marine Bioscience and Biotechnology
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• v.5 no.4
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• pp.46-50
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• 2011

Phytoplankton forms the base of sea ecosystems. Various environmental factors and anthropogenic pollution, primarily, affect the concentration and photosynthetic activity algal cells, and the changes in the phytoplankton photosynthesis influence other elements of aquatic ecosystems. The increase in anthropogenic pollution markedly damages natural aquatic ecosystems, particularly, in the coastal zones, where an intense blooming of microalgae occurs, including the release of highly dangerous ecotoxic substances of various chemical natures (red tides). In this study, we tried to apply as a parameter for the algal blooming prediction in the ocean from fluorescence values in the taken samples around Busan coastal area. F0 value was almost constant but Fv/Fm value showed the irregular pattern. We presume that these results are due to the changes of the ocean environment and climate. To predict or give early warning the algal blooming, we need to investigate the specific area or fixed area through real-time monitoring. Especially, algal blooming prediction or warning can be achieved via continuously monitoring and interpretation of fluorescence changes.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.17-20
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• 2004

The purpose of this study is to arrange the digital maps of Hamamatsu City and to construct the map information system to support the prediction and restoration of Tokai earthquake disasters. The authors arrange the land condition map and compute the populations of each land surface conditions and revealed that $37\%$ of the whole population lives in the safe land, but $63\%$ lives in the rather unsafe surface condition. The authors also arrange the digital map of the main lines of water supply pipe lines in corporation with the Hamamatsu City Water Supply Department and revealed the rather dangerous pipe line area in case of Tokai earthquake.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.33-40
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• 2011

This paper presents the prediction and evaluation of landslide using LRA(logistic regression analysis) and ANN (Artificial Neural Network) methods. In order to assess the landslide, we selected Sarabong, Byeoldobong area and Mt. Song-ak in Jeju Island. Five factors which affect the landslide were selected as: slope angle, elevation, porosity, dry density, permeability. So as to predict and evaluate the landslide, firstly the weight value of each factor was analyzed by LRA(logistic regression analysis) and ANN(Artificial Neural Network) methods. Then we got two prediction maps using AcrView software through GIS(Geographic Information System) method. The comparative analysis reveals that the slope angle and porosity play important roles in landslide. Prediction map generated by LRA method is more accurate than ANN method in Jeju. From the prediction map, we found that the most dangerous area is distributed around the road and path.

• Journal of Environmental Science International
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• v.1 no.1
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• pp.35-43
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• 1992

Handling the emergency problems such as Chemobyl accident require real time prediction of pollutants dispersion. One-point real time sounding at pollutant source and simple model including turbulent-radiation process are very important to predict dispersion at real time. The stability categories obtained by one-dimensional numerical model (including PBL dynamics and radiative process) are good agreement with observational data (Golder, 1972). Therefore, the meteorological parameters (thermal, moisture and momentum fluxes; sensible and latent heat; Monin-Obukhov length and bulk Richardson number; vertical diffusion coefficient and TKE; mixing height) calculated by this model will be useful to understand the structure of stable boundary layer and to handling the emergency problems such as dangerous gasses accident. Especially, this simple model has strong merit for practical dispersion models which require turbulence process but does not takes long time to real predictions. According to the results of this model, the urban area has stronger vertical dispersion and weaker horizontal dispersion than rural area during daytime in summer season. The maximum stability class of urban area and rural area are "A" and "B" at 14 LST, respectively. After 20 LST, both urban and rural area have weak vertical dispersion, but they have strong horizontal dispersion. Generally, the urban area have larger radius of horizontal dispersion than rural area. Considering the resolution and time consuming problems of three dimensional grid model, one-dimensional model with one-point real sounding have strong merit for practical dispersion model.al dispersion model.

• Proceedings of the KSRS Conference
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• v.1
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• pp.166-169
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• 2006

Our country's coast is vulnerable area to natural disaster which the repetitive damages occur every year including a loss of lives, the damage of facilities and erosion mostly except for the east coast because of a typhoon, tidal waves, sea water overflowing by topographic structure of low-lying gentle slope and shallow sea. However, as for prevention of natural disaster occurring every year, the situation is that it's centered on the restorationcentered measures and the general disaster prevention research to minimize damages at the time of disaster occurrence is insufficient. This study intendedlop t to devehe techniques possible for real time sampling of damage prediction areas on Web in order to support decision making for damage prevention and establishment of disaster prevention policy. For this, the thematic map was produced related to disaster based on high-resolution satellite picture, and the environmental DB similar to real world was constructed through topographic construction of three-dimension integrating the parts of land and the sea. In addition, the system was developed possible for the expression of damageable regions by real time grasp of dangerous regions at the time of disaster occurrence through over flowing simulation of three-dimension, and it's intended to prepare a basis to minimize damages to disaster situations through it.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.1 no.1
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• pp.35-43
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• 1997

Handling the emergency problems such as Chemobyl accident require real time prediction of pollutants dispersion. One-point real time sounding at pollutant source and simple model including turbulent-radiation process are very important to predict dispersion at real time. The stability categories obtained by one-dimensional numerical model (including PBL dynamics and radiative process) are good agreement with observational data (Golder, 1972). Therefore, the meteorological parameters (thermal, moisture and momentum fluxes; sensible and latent heat; Monin-Obukhov length and bulk Richardson number; vertical diffusion coefficient and TKE; mixing height) calculated by this model will be useful to understand the structure of stable boundary layer and to handling the emergency problems such as dangerous gasses accident. Especially, this simple model has strong merit for practical dispersion models which require turbulence process but does not takes long time to real predictions. According to the results of this model, the urban area has stronger vertical dispersion and weaker horizontal dispersion than rural area during daytime in summer season. The maximum stability class of urban area and rural area are 'A' and 'B' at 14 LST, respectively. After 20 LST, both urban and rural area have weak vertical dispersion, but they have strong horizontal dispersion. Generally, the urban area have larger radius of horizontal dispersion than rural area. Considering the resolution and time consuming problems of three dimensional grid model, one-dimensional model with one-point real sounding have strong merit for practical dispersion model.

• 한국지역지리학회:학술대회
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• 2009.08a
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• pp.108-115
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• 2009

An increase in oil and gas plants caused by development of process industry have brought into the increase in use of flammable and toxic materials in the complex process under high temperature and pressure. There is always possibility of fire and explosion of dangerous chemicals, which exist as raw materials, intermediates, and finished goods whether used or stored in the industrial plants. Since there is the need of efforts on disaster damage reduction or mitigation process, we have been conducting a research to relate explosion model on the background of real 3D terrain model. By predicting the extent of damage caused by recent disasters, we will be able to improve efficiency of recovery and, sure, to take preventive measure and emergency counterplan in response to unprepared disaster. For disaster damage prediction, it is general to conduct quantitative risk assessment, using engineering model for environmentaldescription of the target area. There are different engineering models, according to type of disaster, to be used for industry disaster such as UVCE (Unconfined Vapor Cloud Explosion), BLEVE (Boiling Liquid Evaporation Vapor Explosion), Fireball and so on, among them.we estimate explosion damage through UVCE model which is used in the event of explosion of high frequency and severe damage. When flammable gas in a tank is released to the air, firing it brings about explosion, then we can assess the effect of explosion. As 3D terrain information data is utilized to predict and estimate the extent of damage for each human and material. 3D terrain data with synthetic environment (SEDRIS) gives us more accurate damage prediction for industrial disaster and this research will show appropriate prediction results.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.3-5
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• 2008

An increase in oil and gas plants caused by development of process industry have brought into the increase in use of flammable and toxic materials in the complex process under high temperature and pressure. There is always possibility of fire and explosion of dangerous chemicals, which exist as raw materials, intermediates, and finished goods whether used or stored in the industrial plants. Since there is the need of efforts on disaster damage reduction or mitigation process, we have been conducting a research to relate explosion model on the background of real 3D terrain model. By predicting the extent of damage caused by recent disasters, we will be able to improve efficiency of recovery and, sure, to take preventive measure and emergency counterplan in response to unprepared disaster. For disaster damage prediction, it is general to conduct quantitative risk assessment, using engineering model for environmental description of the target area. There are different engineering models, according to type of disaster, to be used for industry disaster such as UVCE (Unconfined Vapour Cloud Explosion), BLEVE (Boiling Liquid Evaporation Vapour Explosion), Fireball and so on, among them, we estimate explosion damage through UVCE model which is used in the event of explosion of high frequency and severe damage. When flammable gas in a tank is released to the air, firing it brings about explosion, then we can assess the effect of explosion. As 3D terrain information data is utilized to predict and estimate the extent of damage for each human and material. 3D terrain data with synthetic environment (SEDRIS) gives us more accurate damage prediction for industrial disaster and this research will show appropriate prediction results.