• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.2
• /
• pp.263-272
• /
• 2022

As a result of climate change, the heatwave and urban heat island phenomena have become more common, and the frequency of heatwaves is expected to increase by two to six times by the year 2050. In particular, the heat sensation index felt by workers at construction sites during a heatwave is very high, and the sensation index becomes even higher if the urban heat island phenomenon is considered. The construction site environment and the situations of construction workers vulnerable to heat are not improving, and it is now imperative to respond effectively to reduce such damage. In this study, satellite imagery, land surface temperatures (LST), and long short-term memory (LSTM) were applied to analyze areas above 33 ℃, with the most vulnerable areas with increased synergistic damage from heat waves and the urban heat island phenomena then predicted. It is expected that the prediction results will ensure the safety of construction workers and will serve as the basis for a construction site early-warning system.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.6B
• /
• pp.561-569
• /
• 2010

In this study, the impact of climate change on extreme drought events is investigated by comparing drought severity-area-duration curves under present and future climate. The depth-area-duration analysis for characterizing an extreme precipitation event provides a basis for analysing drought events when storm depth is replaced by an appropriate measure of drought severity. In our climate-change impact experiments, the future monthly precipitation time series is based on a KMA regional climate model which has a $27km{\times}27km$ spatial resolution, and the drought severity is computed using the standardized precipitation index. As a result, agricultural drought risk is likely to increase especially in short duration, while hydrologic drought risk will greatly increase in all durations. Such results indicate that a climate change vulnerability assessment for present water resources supply system is urgent.

• Journal of the Society of Disaster Information
• /
• v.9 no.3
• /
• pp.266-275
• /
• 2013

New paradigm to the advancement of disaster management is required for building resilient and safe society. In these circumstances, the importance of local government disaster management capacity has been emphasized through experiencing a series of accidents including 2012 september Gumi fluorosilicic acid diffusion accident. The increase of people's disaster awareness has emerged the public demands on disaster management information of local area. In this study, the disaster management capacity analysis program is developed for self-assessment of local government. The program is designed for disaster managers to database the categorized index of disaster management capacity and recognize the capacity level. For the public announcement of disaster management capacity, the analysis results are shown for citizens in the understandable format. It is expected that the enhancement of emergency management capacity of local society can be achieved by the efforts of local government analyzing and improving the vulnerability as well as the participation of local society.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.303-313
• /
• 2019

After a disaster happens in urban areas, many people need support for a quick evacuation. This work aims to develop a method for the calculation of the most feasible evacuation route inside buildings. In the methodology we simplify the geometry of the structural and non structural elements from the BIM (Building Information Modeling) to store them in a spatial database which follows standards to support vector data. Then, we apply the multicriteria analysis with the allocation of prioritization values and weight factors validated through the AHP (Analytic Hierarchy Process), in order to obtain the Importance Index S(n) of the elements. The criteria consider security conditions and distribution of the building's facilities. The S(n) is included as additional heuristic data for the calculation of the evacuation route through an algorithm developed as a variant of the $A^*$ pathfinding, The experimental results in the simulation of evacuation scenarios for vulnerable people in healthy physical conditions and for the elderly group, shown that the conditions about the wide of routes, restricted areas, vulnerable elements, floor roughness and location of facilities in the building applied in the multicriteria analysis has a high influence on the processing of the developed variant of $A^*$ algorithm. The criteria modify the evacuation route, because they considers as the most feasible route, the safest instead of the shortest, for the simulation of evacuation scenarios for people in healthy physical conditions. Likewise, they consider the route with the location of facilities for the movement of the elderly like the most feasible in the simulation of evacuation route for the transit of the elderly group. These results are important for the assessment of the decision makers to select between the shortest or safest route like the feasible for search and rescue activities.

• Journal of The Geomorphological Association of Korea
• /
• v.27 no.3
• /
• pp.87-103
• /
• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.3
• /
• pp.1227-1232
• /
• 2014

Background: Given that there are many Iranian women who have never had a Pap smear, this study was designed to develop and validate a measurement tool based on the Protection Motivation Theory to assess factors influencing the Iranian women's intention to perform first Pap testing. Materials and Methods: In this psychometric research, to determine the Content Validity Index (CVI) and the Content Validity Ratio (CVR), a panel of experts (n=10) reviewed scale items. Reliability was estimated through the Intraclass Correlation Coefficient (n=30) and internal consistency (n=240). Also, factor analysis (exploratory and conformity) was performed on the data of the sample women who had never had a Pap smear test (n=240). Results: A 26-item questionnaire was developed. The CVI and CVR scores of the scale were 0.89 and 0.90, respectively. Exploratory factor analysis loaded a 26-item with seven factors questionnaire (perceived vulnerability and severity, fear, response costs, response efficacy, self-efficacy, and protection motivation (or intention)) that jointly accounted for 72.76% of the observed variance. Confirmatory factor analysis indicated a good fit for the data. Internal consistency (range 0.70-0.93) and test-retest reliability (range 0.72-0.96) of sub-scales were acceptable. Conclusions: This study showed that the designed instrument was a valid and reliable tool for measuring the factors influencing the women's intention to perform their first Pap testing.

• Journal of The Geomorphological Association of Korea
• /
• v.27 no.2
• /
• pp.65-80
• /
• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• Journal of the Society of Disaster Information
• /
• v.17 no.4
• /
• pp.864-881
• /
• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.2
• /
• pp.113-122
• /
• 2017

Natural disasters caused by climate change are increasing globally. There are few studies on the quantitative analysis methods for predicting damages in the island area due to sea level rise. Therefore, it is necessary to study the damage prediction analysis method using the GIS which can quantitatively analyze. In this paper, we analyze the cause and status of sea level rise, quantify the vulnerability index, establish an integrated terrestrial modeling method of the ocean and land, and establish a method of analyzing the damage area and damage scale due to sea level rise using GIS and the method of making the damage prediction figure was studied. In order to extract the other affected areas to sea level rise are apart of the terrain model is generated by one requires a terrain modeling of target areas are offshore and vertical reference system differences in land, found the need for correction by a tidal observations and geoid model there was. Grading of terrain, coastline erosion rate, coastal slope, sea level rise rate, and even average by vulnerable factors due to sea level rise indicates that quantitative damage prediction is possible due to sea level rise in the island area. In the case of vulnerable areas extracted by GIS, residential areas and living areas are concentrated on the coastal area due to the nature of the book area, and field survey shows that coastal changes and erosion are caused by sea level rise or tsunami.

• Journal of Preventive Medicine and Public Health
• /
• v.45 no.4
• /
• pp.211-218
• /
• 2012

Objectives: The objective of this study was to identify the differences in obesity rates among people with and without disabilities, and evaluate the relationship between obesity rates and the existence of disabilities or characteristics of disabilities. Methods: Mass screening data from 2008 from the National Disability Registry and National Health Insurance (NHI) are used. For analysis, we classified physical disability into three subtypes: upper limb disability, lower limb disability, and spinal cord injury. For a control group, we extracted people without disabilities by each subtype. To adjust for the participation rate in the NHI mass screening, we calculated and adopted the weight stratified by sex, age, and grade of disability. Differences in obesity rates between people with and without disabilities were examined by a chi-squared test. In addition, the effect of the existence of disabilities and grade of disabilities on obesity was examined by multiple logistic regression analysis. Results: People with disabilities were found to have a higher obesity rate than those without disabilities. The obesity rates were 35.2% and 35.0% (people with disabilities vs. without disabilities) in the upper limb disability, 44.5% and 34.8% in the lower limb disability, 43.4% and 34.6% in the spinal cord injury. The odds for existence of physical disability and grade of disability are higher than the nondisabilities. Conclusions: These results show that people with physical disability have a higher vulnerability to obesity.