• Fire Science and Engineering
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• v.3 no.2
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• pp.61-76
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• 1989

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.146-156
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• 2016

In this study, we developed a large fire forecasting system using critical weather conditions, such as strong winds and effective humidity. We incorporated information on forest type prior to large fires using an incident case study. The case study includes thirty-seven large fires covering more than 100 ha of damaged area over the last 20 years. Dangerous large fire regions were identified as areas of more than 30 ha of Korean red pine and the surrounding two kilometers. Large fires occur when wind speeds average 5.3 m/s with a maximum of 11.6 m/s and standard deviation of 2.5 m/s. Effective humidity for large fires average 30% with a minimum of 13% and standard deviation of 14.5%. In dangerous Korean red pine stand areas, the large fire 'Watch' level is issued when effective humidity is 30-45% for more than two days and average wind speed is 7-10 m/s. The 'Warning' level is issued when effective humidity is less than 30% for more than two days and average wind speed is more than 11 m/s. Therefore, from now on, the large fire forecasting system can be used effectively for forest fire prevention activities based on a selection and concentration strategy in dangerous large fire regions using severe weather conditions.

• Journal of agriculture & life science
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• v.45 no.4
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• pp.29-35
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• 2011

A forest fire was one of the huge disasters and damaged human lifes and a properties. Therefore, many countries operated forest fire forecasting systems which developed from forest fire records, weather data, fuel models and etc. And many countries also estimated future state of forest fire using a long-term climate forecasting like GCMs and prepared resources for future huge disasters. In this study, we analyzed relationships between forest fire occurrence and meteorological factors (the minimum temperature ($^{\circ}C$), the relative humidity (%), the precipitation (mm), the duration of sunshine (hour) and etc.) for developing a estimating tools, which could forecast forest fire regime under future climate change condition. Results showed that forest fires in this area were mainly occurred when the maximum temperature was $10{\sim}200^{\circ}C$, when the relative humidity was 40~60%, and when the average wind speed was under 2m/s. And forest fires mainly occurred at 2~3 day after rainfall.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.80-88
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• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.39-55
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• 2019

In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2004.06a
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• pp.39-46
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• 2004

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.29-37
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• 2011

Forest fire in Korea has been controlled by local government, so that it is required to understand the characteristics of regional forest fire occurrences for the effective management. In this study, to analyze the patterns of regional forest fire occurrences, we divided South Korea into nine zones based on administrative boundaries and performed spatial statistical analysis using the location data of forest fire occurrences for 1991-2008. The spatial distributions of forest fire were analyzed by the variogram, and the risk of forest fire was predicted by kriging analysis. As a result, forest fires in metropolitan areas showed strong spatial correlations, while it was hard to find spatial correlations of forest fires in local areas without big city as Gangwon-do, Chungcheongbuk-do and Jeju island.

• Applied Chemistry for Engineering
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• v.21 no.5
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• pp.575-580
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• 2010

Forest fires in Korea, having forest coverage of 70%, have kept increasing in number and scale since the middle of 1990's. Although deposited fallen leaves in forests such as herbaceous plants, conifers, and broadleaf trees are used as a medium for forest fires, the pyrolysis and combustion characteristics of the various species of trees are hardly studied. Oriental oak is the representative broadleaf tree in domestic forests, and pyrolysis and combustion of oriental oak leaf were carried out by thermogravimetic analysis (TGA). The leaf of oriental oak was ignited at $239^{\circ}C$ whereas pyrolysis started at $250^{\circ}C$. The corresponding kinetic parameters including activation energy and pre-exponential factor were determined by differential method over the degree of conversions. The values of activation energies for pyrolysis were increased as the conversion increases from 10% to 80%, whereas those of values were decreased during combustion.

• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.182-188
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• 2012

In this study we analyzed carbon emissions of leaves of a Pinus densiflora which is vulnerable to a forest fire using the cone calorimeter in order to analyze greenhouse gas emissions from forest fires depending on region and altitude. Fuels were collected from 9 regions[Hongcheon(Gangwon-do), Chungsong(Gyeongbuk-do), Yanhpyeong (Gyeonggi-do), Jecheon(Chungchongbuk-do), Gongju(Chungcheongnam-do), Wuju(Jeollabuk-do), Youngam(Jeollanam-do), Busan and Jeju-do)] and 9 altitudes(80 m, 450 m, 900 m, 1000 m, 1100 m, 1200 m, 1300 m, 1400 m and 1500 m) and then, carbon dioxide and carbon monoxide emissions contained in a weight of 50 g of fuel were analyzed. According to the results, there were differences in carbon emissions by regional groups, as the average carbon dioxide and carbon monoxide emissions in 9 regions were nearly 43.5929 g to 52.8868 g, and 0.8842 g to 3.6422 g, respectively. Busan and Jecheon had relatively higher carbon dioxide emissions and especially, Busan had 1.23 times higher carbon dioxide emissions than Jeju-do. Also, Gongju, Chungcheongnamo Province and Busan had relatively higher carbon monoxide emissions and especially, Gongju and Pusan had relatively higher carbon monoxide emissions and especially, Gongju had 4.12 higher carbon monoxide emissions than Hongcheon. In addition, there were differences in carbon emissions too depending on altitude, since carbon dioxide and carbon monoxide emissions in 9 altitudes were respectively, 40.7015 g to 68.9297 g and 1.3923 g to 12.2918 g. At the altitude of 80m, carbon dioxide and carbon monoxide emissions were respectively, 68.9297 g and 12.2918 g, and at the altitude of 450m, carbon dioxide and carbon monoxide emissions were respectively, 65.5115 g and 11.2497 g. These results show that pine trees at the lower altitude discharge relatively more carbon. It is considered that this analysis on carbon emissions depending on region and altitude can be effectively used for predicting greenhouse gas emissions and establishing statistical data from forest fires in each region and altitude.

• Fire Science and Engineering
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• v.30 no.1
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• pp.57-62
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• 2016

This study evaluated the risk of forest fires due to climate change in Jeju using the VESTAP. The study primarily aimed at assessing the risks posed to Jeju city and Seogwipo city, and uses actual and projected date from the period of 2000's to 2040's based on RCP 8.5 scenario. Forest fire vulnerability throughout Jeju-do was determined through the standardization of vulnerability index. The highest vulnerability was determined for the towns of Chuja-myeon, Udo-myeon, two downtown areas in Jeju city, Daejeong-eup, and five downtown areas in Seogwipo city, respectively.