• 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.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1847-1859
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• 2022

Wildfires in North Korea can have a directly or indirectly affect South Korea if they go south to the Demilitarized Zone. Therefore, this study calculates the regional optimized Forest Fire Danger Index (FFDI) based on Local Data Assessment and Prediction System (LDAPS) weather data to obtain forest fire risk in North Korea, and applied it to the cases in Goseong-gun and Cheorwon-gun, North Korea in April 2022. As a result, the suitability was confirmed as the FFDI at the time of ignition corresponded to the risk class Extreme and Severe sections, respectively. In addition, a qualitative comparison of the risk map and the soil moisture map before and after the wildfire, the correlation was grasped. A new forest fire risk index that combines drought factors such as soil moisture, Standardized Precipitation Index (SPI), and Normalized Difference Water Index (NDWI) will be needed in the future.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.187-197
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• 2024

In this study, we aimed to identify the factors influencing post-fire mortality in Korean red pine (Pinus densiflora) using Cox's proportional hazards model and analyze the impact of these factors. We monitored the mortality rate of fire-damaged pine trees for seven years after a forest fire. Our survival analysis revealed that the risk of mortality increased with higher values of the delta normalized difference vegetation index (dNDVI), delat normalized burn ratio (dNBR), bark scorch index (BSI), bark scorch height (BSH) and slope. Conversely, the risk of mortality decreased with higher elevation, greater diameter at breast height (DBH), and higher value of delta moisture stress index (dMSI) (p < 0.01). Verification of the proportional hazards assumption for each variable showed that all factors, except slope aspect, were suitable for the model and significantly influenced fire occurrence. Among the variables, BSI caused the greatest change in the survival curves (p < 0.0001). The environmental change factors determined through remote sensing also significantly influenced the survival rates (p < 0.0001). These results will be useful in establishing restoration plans considering the potential mortality risk of Korean red pine after a forest fire.

• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.37-46
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• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, we are making an effort to improve prevention measures for forest fires. The objective of this study is to classify hazard regions where forest fires occur based on the factors that contribute to the occurrence of forest fires. Forest fire sites in the Uiseong-gun, Gyeongsangbuk-do were surveyed according to the factors of forest type and topographic characteristics where the forest fires occurred. We used a correlation analysis to determine the forest fire occurrence factors and a conditional probability analysis and GIS to determine a forest fire danger index. The resulting forest fire danger index was used in the classification of forest fire occurrence risk regions.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.57-64
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• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, the forest fire danger rating system was developed to estimate forest fire risk by means of weather, topography, and forest type. Forest fires occurrence prediction needs to improve continually. Logistic regression and spatial analysis was used in developing the forest fire occurrence probability model. The forest fire danger index in accordance to the probability of forest fire occurrence was used in the classification of forest fire occurrence risk regions.

• Atmosphere
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• v.28 no.4
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• pp.457-467
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• 2018

This study investigated the variability of spring (March-May) forest fire risk in Korea for the period 1991~2017 and analyzed its relationship with large-scale climate factors. The Forest Weather Index (FWI) representing the meteorological risk for forest fire occurrences calculated based on observational data and its relationship with large-scale climate factors were analyzed. We performed the empirical orthogonal function (EOF) analysis on the spring FWI. The leading EOF mode of FWI accounting for about 70% of total variability was found to be highly correlated with total number of forest fire occurrences in Korea. The high FWI, forest fire occurrence risk, in Korea, is associated with warmer atmosphere temperature in midwest Eurasia-China-Korea peninsula, cyclonic circulation anomaly in northeastern China-Korea peninsula-northwest pacific, westerly wind anomaly in central China-Korea peninsula, and low humidity in Korea. These are further related with warmer sea surface temperature and enhanced outgoing longwave radiation over Western Pacific, which represents a typical condition for a La $Ni\tilde{n}a$ episode. This suggests that large-scale climate factors over East Asia and ENSO could have a significant influence on the occurrence of spring forest fires in Korea.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.257-264
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• 1991

Korea has accomplished the afforestation of its forest land in the early 1980's. To meet the increasing demand for forest products and forest recreation, a development of scientific forest management system is needed as a whole. For this purpose the development of efficient forestfire management system is essential. In this context, the purpose of this study is to develop a theoretical foundation of forestfire danger rating system. In this study, it is hypothesized that the degree of forestfire risk is affected by Weather Factor and Man-Caused Risk Factor. (1) To accommodate the Weather Factor, a statistical model was estimated in which weather variables such as humidity, temperature, precipitation, wind velocity, duration of sunshine were included as independent variables and the probability of forestfire occurrence as dependent variable. (2) To account man-caused risk, historical data of forestfire occurrence was investigated. The contribution of man's activities make to risk was evaluated from three inputs. The first, potential risk class is a semipermanent number which ranks the man-caused fire potential of the individual protection unit relative to that of the other protection units. The second, the risk sources ratio, is that portion of the potential man-caused fire problem which can be charged to a specific cause. The third, daily activity level is that the fire control officer's estimate of how active each of these sources is, For each risk sources, evaluate its daily activity level ; the resulting number is the partial risk factor. Sum up the partial risk factors, one for each source, to get the unnormalized Man-Caused Risk. To make up the Man-Caused Risk, the partial risk factor and the unit's potential risk class were considered together. (3) At last, Fire occurrence index was formed fire danger rating estimation by the Weather Factors and the Man-Caused Risk Index were integrated to form the final Fire Occurrence Index.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.303-321
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• 2023

To develop the Forest Work Load Index (FWLI) for estimating the work intensity of forest workers, a study focused on forest tending was conducted. To estimate the FWLI, we used the Ovako Working Posture Analysis System (OWAS) and the Work Load Index (WLI). The OWAS is a prominent method used for analyzing musculoskeletal load in work tasks, and WLI is a prominent method used for analyzing the work intensity of workers. The PRI values analyzed for each forest tending project were 185.3 (Thinning), 150.6 (Pruning), 181.1 (Thinning for Forest Fire Prevention), and 197.0 (Thinning for Young Trees). The WLI values, calculated on the basis of the measured heart rates, were 59.5% (Thinning), 53.5% (Pruning), 56.2% (Thinning for Forest Fire Prevention), and 62.3% (Thinning for Young Trees). The FWLI was calculated using the analyzed PRI and WLI values. The FWLI values for the forest tending project were 110.2 (Thinning), 80.7 (Pruning), 102.1 (Thinning for Forest Fire Prevention), and 123.0 (Thinning for Young Trees). The FWLI developed in this study can be used to quantitatively compare the workloads of forest workers. In the future, the analyzed FWLI can be used as a basis for improving forest workers' postures and comparing workloads across different forest projects.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.1-11
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• 2022

Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.