• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1999.06a
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• pp.51-59
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• 1999

산불발생 요인으로 캐나다와 미국의 경우에는 자연적인 현상이 대부분을 차지하고 있으나 우리나라의 경우에는 입산 자들의 부주의, 농산폐기물소각 등에서 오는 인위적인 원인들이 대부분을 차지하고 있다. 또한 산불발생시 즉시 진화하기 어려운 이유는 우리나라의 지형특성상 구릉지가 많아 발견되기 어렵고, 산불의 진압을 위한 장비와 인력동원에서 오는 지연시간 및 산불확산에 영향을 미치는 요인들의 변화를 예측하기 어렵다는 점에 있다. (중략)

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2011.11a
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• pp.289-293
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• 2011

대형 산불이 발생했을 경우 인접 마을 등에 대한 피난 연구는 국내에서 아직까지 이루어지지 않고 있으며 대부분의 대피 대상자들이 재해 약자들로 구성되어있어 산불 대피에 관한 연구가 필요한 실정이다. 이에 본 연구에서는 산불 대피지도 알고리즘을 개발하여 산불의 진행경로 및 확산에 따른 적정한 대피경로를 제시함으로서 인적 피해를 저감하는데 그 목적이 있다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.115-116
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• 2022

최근까지 강원도 일대에서는 산불재난으로 큰 곤욕을 치렀다. 본문의 표1의 자료에서 나와 있듯이 2000년대 이후 대한민국은 지속적인 산불재난으로 인해 세대에 걸친 중대한 피해를 입고 있는 실정이다. 이에 따라, 산불재난을 바라보는 인식의 변화가 필요할 것이며, "불가피성의 자연재해"라는 사후조치성 위주의 기존인식을 확장하여 사전조치성 예방 및 준비단계에 관심을 기울일 필요성이 있다고 생각된다.

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.101.1-101.1
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• 2009

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.116-130
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• 2019

In South Korea, forest fire occurrences are increasing in size and duration due to various factors such as the increase in fuel materials and frequent drying conditions in forests. Therefore, it is necessary to minimize the damage caused by forest fires by appropriately providing the probability of forest fire risk. The purpose of this study is to improve the Daily Weather Index(DWI) provided by the current forest fire forecasting system in South Korea. A new Fire Risk Index(FRI) is proposed in this study, which is provided in a 5km grid through the synergistic use of numerical weather forecast data, satellite-based drought indices, and forest fire-prone areas. The FRI is calculated based on the product of the Fine Fuel Moisture Code(FFMC) optimized for Korea, an integrated drought index, and spatio-temporal weighting approaches. In order to improve the temporal accuracy of forest fire risk, monthly weights were applied based on the forest fire occurrences by month. Similarly, spatial weights were applied using the forest fire density information to improve the spatial accuracy of forest fire risk. In the time series analysis of the number of monthly forest fires and the FRI, the relationship between the two were well simulated. In addition, it was possible to provide more spatially detailed information on forest fire risk when using FRI in the 5km grid than DWI based on administrative units. The research findings from this study can help make appropriate decisions before and after forest fire occurrences.

• 산림경영
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• s.193
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• pp.15-15
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• 2009

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.4
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• pp.213-217
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• 2003

Forest fire spread and intensity were modeled as a function of wind and fuel. Spread rate and intensity of forest fire were related to weight and thickness of forest fuel beds and to wind speed. Forest fire spread rate and fire intensity were differentiated according to wind speed. Rapid wind speed causes a faster forest fire spread rate and greater fire intensity than does slow wind speed. Relative burning time of the fire from beginning to end in the model was 161 sec at a wind speed of 0.5 m/sec and 146 sec at 1m/sec on the model. Average forest lire spread rate was 0.014 m/sec at a wind speed of 0.5 m/sec and 0.020 m/sec at 1m/sec. Average fire intensity was 0.183 ㎾/m at a wind speed of 0.5 m/sec, 0.259 ㎾/m at 1m/sec. Fire intensity was greater when forest fire spread rate was rapid.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.781-791
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• 2022

It is crucial to provide forest fire risk forecast information to minimize forest fire-related losses. In this research, forecast models of forest fire risk at a mid-range (with lead times up to 7 days) scale were developed considering past, present and future conditions (i.e., forest fire risk, drought, and weather) through random forest machine learning over South Korea. The models were developed using weather forecast data from the Global Data Assessment and Prediction System, historical and current Fire Risk Index (FRI) information, and environmental factors (i.e., elevation, forest fire hazard index, and drought index). Three schemes were examined: scheme 1 using historical values of FRI and drought index, scheme 2 using historical values of FRI only, and scheme 3 using the temporal patterns of FRI and drought index. The models showed high accuracy (Pearson correlation coefficient >0.8, relative root mean square error <10%), regardless of the lead times, resulting in a good agreement with actual forest fire events. The use of the historical FRI itself as an input variable rather than the trend of the historical FRI produced more accurate results, regardless of the drought index used.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.69-83
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• 2023

Forest fires increase the risk of subsequent soil erosion and mass movement in burned areas, even under rainfall conditions below landslide alert thresholds, by destroying plants and vegetation and causing changes to soil properties. These effects of forest fires can alter runoff in burned areas by altering soil composition, component minerals, soil water repellency, soil mass stability, and soil fabric. Heat from forest fires not only burns shallow organic matter and plants but also spreads below the surface, affecting soil constituents including minerals. This study analyzed X-ray diffraction and physical properties of topsoil and subsoil obtained from both burned and non-burned areas to identify the composition and distribution of clay minerals in the soil. Small amounts of mullite, analcite, and hematite were identified in burned soils. Vermiculite and mixed-layer illite/vermiculite (I/V) were found in topsoil samples from burned areas but not in those from non-burned areas. These findings show changes in soil mineral composition caused by forest fires. Expansive clay minerals increase the volume of soil during rainfall, degrading the structural stability of slopes. Clay minerals generated in soil in burned areas are therefore likely to affect the long-term stability of slopes in mountainous areas.