• 대한토목학회논문집
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• 제42권2호
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• pp.263-272
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• 2022

폭염과 도시열섬현상은 기후변화가 진행됨에 따라 피해가 더욱 커지고 있으며, 2050년까지 폭염 발생빈도는 2~6배가 증가될 것으로 예측된다. 특히, 폭염기간동안 건설공사현장에서의 근로자가 느끼는 더위체감지수는 매우 높으며, 도시열섬현상까지 고려하게 되면 체감지수는 더욱 높아진다. 열에 취약한 건설현장 환경과 건설근로자의 상황은 나아지지 않고 있으며, 피해를 줄이기 위해서는 효과적인 대응이 필요한 시점이다. 본 연구에서는 인공위성영상 이미지와 Land Surface Temperature (LST)와 Long Short Term Memory (LSTM) 딥러닝 모델 기법을 적용하여 33℃ 이상 온도가 되는 지역을 분석하고, 폭염에 취약한 건설공사현장을 식별하여 폭염 및 도시열섬현상의 복합적인 피해를 가중시킬 수 있는 가장 취약한 지역을 예측하여 도출하였다. 예측 결과를 통해 건설근로자의 안전을 보장하고, 건설현장 경보시스템의 기반이 될 수 있기를 기대한다.

• 대한토목학회논문집
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• 제30권6B호
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• pp.561-569
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• 2010

본 연구에서는 현재 및 미래 기후에서의 가뭄심도-영향면적-지속기간 곡선의 비교를 통하여 극한 가뭄 사상에 대한 기후변화의 영향을 살펴보았다. 가뭄심도-영향면적-지속기간 곡선은 극한 호우사상을 특성화하기 위한 일반적으로 적용되는 우량깊이-영향면적-지속기간 곡선에서 우량깊이를 가뭄심도를 대표할 수 있는 적절한 지수로 대체함으로써 가뭄사상을 분석할 수 있는 도구를 제공한다. 미래 월 강수량 시계열은 $27km{\times}27km$의 공간적인 해상도를 가지는 기상청 지역기후모형으로부터 획득되었으며, 가뭄심도는 표준강수지수를 이용하여 산출하였다. 분석 결과, 농업가뭄에 대한 위험성은 특히 단기간의 지속기간의 경우에 현재보다 심화될 수 있는 것으로 분석되었으며, 수문학적 가뭄의 경우는 가뭄지속기간에 상관없이 모두 현재보다는 미래에 가뭄심도가 더 깊어질 가능성이 있는 것으로 예측되었다. 이에 따라 현재의 수자원 공급 시스템에 대한 기후변화 취약성 평가가 시급함을 제시하고 있다.

• 한국재난정보학회 논문집
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• 제9권3호
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• pp.266-275
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• 2013

최근 복합재난 환경 속에서 지역 방재력을 구축하기 위한 재난안전관리의 선진화에 대한 새로운 패러다임이 요구되어지고 있다. 이러한 상황속에서 2012년 9월 구미 불산 유출사고를 겪으면서 지방자치단체의 재난안전 역량의 중요성 및 필요성이 부각되었다. 이와 함께 안전 확보에 대한 국민의 관심도 증대는 지역 주민들의 재난안전정보에 대한 권리를 가시화하였고 사회적 이슈로 나타났다. 본 연구에서는 지방자치단체의 재난관리 업무역량을 평가 분석 할 수 있는 프로그램을 개발하였다. 재난관리 역량강화 지표를 데이터베이스화하여 재난관리담당자 중심의 웹 기반 체계를 구축하여 지방자치단체가 자체적으로 재난안전관리 역량 수준을 파악하도록 하였다. 또한, 재난안전관리 정보를 지역주민들이 이해하기 용이하게 지표화하여 공개하도록 하였다. 지방자치단체의 재난관리 역량강화를 위해서는 지역의 취약성을 분석하여 개선사항을 도출하는 노력과 함께 이를 지역주민에게 공시함으로서 지역사회의 참여를 바탕으로 최적의 효과를 거둘 수 있을 것이라 기대한다.

• 한국측량학회지
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• 제37권5호
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• pp.303-313
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• 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.

• 한국지형학회지
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• 제27권3호
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• pp.87-103
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• 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
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• 제15권3호
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• pp.1227-1232
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• 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.

• 한국지형학회지
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• 제27권2호
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• pp.65-80
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• 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.

• 한국재난정보학회 논문집
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• 제17권4호
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• pp.864-881
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• 2021

연구목적: 본 연구는 빅데이터와 인공지능 기술을 기반으로 다양한 위험 특성과 개개인의 상황을 고려한 맞춤형 예방 솔루션을 제공하는 생활안전 예방서비스 연구개발의 일환으로, 일상 생활안전과 관련하여 개인의 현재 안전수준을 정량적 수치로 나타내는 생활안전지수를 산출하는 방안을 제시하여, 안전사고를 예방하고 대응하기 위한 맞춤형 종합지수 서비스를 제공하는 데 목적이 있다. 연구방법: 본 연구의 핵심이 되는 모델은 AHP(Analysis Hierarchy Process)와 리커트 척도(Likert Scale)를 혼용하는 방법으로, 전문가 그룹의 합의형성 모델을 기반으로 산출된다. 생활안전 예방서비스를 평가할 수 있는 평가항목을 위험지표, 취약지표, 예방지표 등으로 구분하고, 이를 AHP 의사결정 방법론에 따라 AHP 계층구조로 정의하여 각 레벨 항목의 쌍대비교를 통해 평가항목 간 상대적 가중치를 산출하는 방법을 제안한다. 또한 평가항목을 적용한 개별 예방서비스에 대한 평가는 향후 생활안전 예방서비스의 확대를 고려하여 AHP 쌍대비교를 대신하여 리커트 척도 기반으로 절대평가하고 그 결과를 상대비교하는 방법으로 개별서비스 간 가중치를 산출하는 방안도 함께 제시한다. 연구결과: 생활안전 예방서비스에 대한 서비스 가중치를 도출하고, 이를 생활안전 예방서비스의 인공지능 예측모델을 통해 산출된 개별위험지수에 반영하여 종합지수를 산출하였다. 결론: 구현한 모델의 적용을 위하여 생활안전 예방서비스 앱과 플랫폼으로 구성된 테스트 환경을 구축하고, 사용자 시나리오를 바탕으로 기능에 대한 효능을 평가하였다. 이를 통해 본 연구에서 제시된 생활안전지수는 사용자에게 현재 자신의 안전수준을 종합하여 나타냄으로써 안전 위험에 진단과 대응 및 예방 골든타임을 지원하는 것으로 기대된다.

• 한국측량학회지
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• 제35권2호
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• pp.113-122
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• 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
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• 제45권4호
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• pp.211-218
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• 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.