• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.213-220
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• 2017

This study examines the limitations of existing crime mapping that relies mainly on reported crime data, suggests a crime mapping method based on experts' and users' assessments of a neighborhood environment as an alternative approach, and conducts a case study on a real-world site by applying the suggested approach. According to the results of the case analysis, while the areas adjoining arterial roads with heavy pedestrian traffic were shown as high crime risk areas in the crime map based on actual reported crime data, the areas adjoining local roads with low pedestrian traffic were high-risk areas in the crime risk area map based on experts' and residents' evaluations. This study makes a contribution to the field in that it demonstrates the detailed application process of crime risk area mapping according experts' and residents' evaluations, compares the results with those of an existing crime map, and finally shows that the former can function as a complement to the latter.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.24-34
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• 2024

Fire, being primarily a natural phenomenon, is impossible to control, although it is feasible to map the forest fire risk zone, minimizing the frequency of fires. The spread of a fire starting in any stand in a forest can be predicted, given the burning conditions. The natural cover of the land and the safety of the population may be threatened by the spread of forest fires; thus, the prevention of fire damage requires early discovery. Satellite data and geographic information system (GIS) can be used effectively to combine different forest-fire-causing factors for mapping the forest fire risk zone. This study mainly focuses on mapping forest fire risk in the Madikhola watershed. The primary causes of forest fires appear to be human negligence, uncontrolled fire in nearby forests and agricultural regions, and fire for pastoral purposes which were used to evaluate and assign risk values to the mapping process. The majority of fires, according to MODIS events, occurred from December to April, with March recording the highest occurrences. The Risk Zonation Map, which was prepared using LULC, Forest Type, Slope, Aspect, Elevation, Road Proximity, and Proximity to Water Bodies, showed that a High Fire Risk Zone comprised 29% of the Total Watershed Area, followed by a Moderate Risk Zone, covering 37% of the total area. The derived map products are helpful to local forest managers to minimize fire risks within the forests and take proper responses when fires break out. This study further recommends including the fuel factor and other fire-contributing factors to derive a higher resolution of the fire risk map.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.497-500
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• 2008

Recently, the urban regeneration project has been performed actively at home and abroad. The stake-holders in urban regeneration project are various and complicated, and has large scale during a long life period. Also they show the characteristics of a mega-project and most mixed-use form. Therefore, the urban regeneration has a lot of potential risk factors from project beginning to completion. It means they need efficient and continuous risk management in terms of performance measurement. But the current domestic construction project does not reflect risk management in view of performance measurement. This study proposes the risk management methodology by mapping risk factors with major performance indexes of the urban regeneration project.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.73-82
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• 2013

The main objective of this study was to evaluate Representative Concentration Pathways (RCP) scenarios-based flood risk at a Si-Gun level. A bias correction using a quantile mapping method with the Generalized Extreme Value (GEV) distribution was performed to correct future precipitation data provided by the Korea Meteorological Administration (KMA). A series of proxy variables including CN80 (Number of days over 80 mm) and CX3h (Maximum precipitation during 3-hr) etc. were used to carry out flood risk assessment. Indicators were normalized by a Z-score method and weighted by factors estimated by principal component analysis (PCA). Flood risk evaluation was conducted for the four different time periods, i.e. 1990s, 2025s, 2055s, and 2085s, which correspond to 1976~2005, 2011~2040, 2041~2070, and 2071~2100. The average flood risk indices based on RCP4.5 scenario were 0.08, 0.16, 0.22, and 0.13 for the corresponding periods in the order of time, which increased steadily up to 2055s period and decreased. The average indices based on RCP8.5 scenario were 0.08, 0.23, 0.11, and 0.21, which decreased in the 2055s period and then increased again. Considering the average index during entire period of the future, RCP8.5 scenario resulted in greater risk than RCP4.5 scenario.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.164-164
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• 2023

This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

• Fire Science and Engineering
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• v.32 no.6
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• pp.141-149
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• 2018

The perception of risk that firefighters have is closely related to their performance and emergency preparedness in nuclear power plant accidents. This study investigated the unique risk perception among firefighters working in nuclear power plants (NPPs) using a concept mapping method. Thirty three firefighters in NPPs participated in this study. Two core axes, "fear and control" and "coping resource", emerged in the firefighters' risk perception. In particular, the risk perception consisted of six clusters: fear of radiation exposure and low controllability; anxiety caused by the lack of control and authority; lack of trust and cooperation; lack of authority and professionals; lack of equipment, manual, and information; and lack of knowledge and training. Catastrophic expectation and a low sense of control caused by the lack of responsive resources were the main factors that increase the risk perception. The theoretical and practical contributions of this study were discussed.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.85-97
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• 2022

In this study, a method for an integrated flood risk mapping was proposed that simultaneously considers the flood inundation map indicating the degree of risk and the disaster vulnerability index. This method creates a new disaster map that can be used in actual situations by providing various and specific information on a single map. In order to consider the human, social and economic factors in the disaster map, the study area was divided into exposure, vulnerability, responsiveness, and recovery factors. Then, 7 indicators for each factor were extracted using the GIS tool. The data extracted by each indicator was classified into grades 1 to 5, and the data was selected as a disaster vulnerability index and used for integrated risk mapping by factor. The risk map for each factor, which overlaps the flood inundatoin map and the disaster vulnerability index factor, was used to establish an evacuation plan by considering regional conditions including population, assets, and buildings. In addition, an integrated risk analysis method that considers risks while converting to a single vulnerability through standardization of the disaster vulnerability index was proposed. This is expected to contribute to the establishment of preparedness, response and recovery plans for providing detailed and diverse information that simultaneously considers the flood risk including social, humanistic, and economic factors.

• Korean Chemical Engineering Research
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• v.52 no.6
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• pp.736-742
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• 2014

If an accident occurs at work places that handle 'the accident preparedness substances', it causes more property damage and casualties than accidents of normal chemical substances. Even though various systems and regulations have been operated in order to prevent accidents, techniques for reducing and removing human error, which is one of the main reasons of accidents, are still inadequate. In this paper, hazardous work digitization, potential hazard verification, and work evaluation based on domestic technical guidelines have been performed through a case study of the accident of hydrofluoric acid leakage in Gumi in September 2012, and development of a new risk mapping method has been studied to supplement existing systems.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1225-1239
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• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.29
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• pp.143-172
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• 2006

This study focuses on the risk management of "Digital Goods" appeared with the progress of information technology(IT) in international transaction. As a result of that digital goods have a lot of uncertainty between the general goods or service which have been deal with object of international transaction broadly because digital goods hold uniqueness. In this study, the author give a definition of "Digital Goods" and make an examination of uniqueness of that in international transaction. Next, six risks are defined base on risk theory and risk analysis matrix applying risk mapping model is made. Conclusionally, risk transfer as insurance is adequate to manage business risk, security risk, credit risk and legal risk. Meanwhile, risk avoidance is adequate to manage reputation risk and market risk. But, this study have following three limits. Firstly, concerning definition of the risk, real case is not applied owing to lack of transaction data. Secondly, measuring of the risk is not based on absolute data but relative data. Lastly, suggesting way of risk management is not concrete and practical to international trader of digital goods.