• Proceedings of the Korea Air Pollution Research Association Conference
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• 2006.04a
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• pp.135-137
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• 2006

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.161.2-161.2
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• 2009

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.367-367
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• 2006

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2005.04a
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• pp.161-163
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• 2005

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.117-118
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• 2022

본 논문에서는 재난 및 안전관리 기본법에서 정의하는 사회재난의 산불발생시 인원과 장비를 효율적으로 활용하기 위해 드론에 부착 가능한 열화상카메라, 소화탄, AI기능 등 활용에 관한 연구이다

• Applied Chemistry for Engineering
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• v.21 no.6
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• pp.664-669
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• 2010

The forest area of domestic is 6370304 ha, which covers 70% of the whole country, and especially Gangwon-do is remarkably larger than other Province. A thick forest of the country has the most basic component among other natural environments as well as it has invaluable worth to human being such as scientific research and educational value. However due to the breakout of forest fire since 1990s, the loss of trees, destruction of natural environment and ecology, economic damage have been occurring and its scale also has become larger. The causes of becoming larger in scale are resulted from forest components which mainly consist of needle leaf trees, wide leaf trees, fallen leaves, herbaceous plants so that it has been a direct cause for forest fire. However, few research on combustion and pyrolysis characteristics has been done in domestic and abroad. The study on the combustion and pyrolysis for Pinus densiflora which are typical needle leaf trees has been tried using TGA. Pinus desiflora started to being ignited at around $162^{\circ}C$ and pyrolysis was done at around $197^{\circ}C$. Differential method was applied to calculate activation energy and frequency factor according to the variation of conversion. Activation energy in pyrolysis was increased from 79 kJ/mol to 487 kJ/mol with increasing conversion and average activation energy was 195 kJ/mol. The activation energy in combustion was decreased from 148 kJ/mol to 133 kJ/mol.

• Journal of Korean Society of Disaster and Security
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• v.14 no.3
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• pp.17-27
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• 2021

In this study, classification models were built using machine learning techniques that can classify the soil creep risk into three classes from A to C (A: risk, B: moderate, C: good). A total of six machine learning techniques were used: K-Nearest Neighbor, Support Vector Machine, Logistic Regression, Decision Tree, Random Forest, and Extreme Gradient Boosting and then their classification accuracy was analyzed using the nationwide soil creep field survey data in 2019 and 2020. As a result of classification accuracy analysis, all six methods showed excellent accuracy of 0.9 or more. The methods where numerical data were applied for data training showed better performance than the methods based on character data of field survey evaluation table. Moreover, the methods learned with the data group (R1~R4) reflecting the expert opinion had higher accuracy than the field survey evaluation score data group (C1~C4). The machine learning can be used as a tool for prediction of soil creep if high-quality data are continuously secured and updated in the future.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.687-698
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• 2022

Purpose: This study was conducted to understand the public awareness of landslide and check dams in 2015-2020 using the big data platform 'Hyean' and to confirm the utilization of this platform in disaster prevention areas. Method: The total amount, number of detection by period by media, and affirmative and negative trends of a search for 'landslide' and 'check dam' in 2015-2020 were analyzed using a keyword search of 'Hyean.' Result: There is significant lack of public awareness of check dam compared to landslide, and the trend is more noticeable in the conspicuous gap of data amount between the news and SNS media. The number and the timing of the search for 'landslide' coincided with the actual occurrence of landslide, while the detection of 'check dam' was less related to it. Relatively affirmative preception for the check dam is inferred, but it was difficult to confirm accurate statistical affirmative and negative trends in the disaster prevention field using 'Hyean.' Conclusion: Unlike the experts who expect positive public awareness of check dam, the statistic results show that the public awareness of the check dam as an effective countermeasure against landslide was extremely low. Active promotion of erosion control projects should be carried out first, and a balanced sample survey should accompany online and periodic field surveys. Since there is a limit to grasping the effective perception in the field of disaster prevention area using 'Hyean', it should be very cautious to establish local/governmental policies using it.

• Journal of Conservation Science
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• v.5 no.1 s.5
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• pp.87-93
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• 1996

This study was carried out to Identify wood and charcoal segments, which were excavated in 1994 at the Seohaean highway construction site along the western coast of Korea ; Tuntaeri, Hwasunggun. We identified the objects excavated at the fire places of the Tuntaeri dwelling sites (early Koryo period ; A. D. $11\~12C$) ; charcoal pieces and 1 wood segment, which was used for the handle of a metal hook. Chestnut(Castanea crenata), deciduous oaks(Quercus spp.) and maple(Acer app.) were identified from the charcoals, whereas the wood segment as willow species(Salix spp.). These species seem to represent warm and wet climate in the middlewest Korea during $11\~12C$.

• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.1
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• pp.43-66
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• 1985

Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.