• Journal of Korean Society of Forest Science
• /
• v.99 no.3
• /
• pp.259-266
• /
• 2010

Forest fire occurrence in Korea is highly related to human activities and its spatial distribution shows a strong spatial dependency with cluster pattern. In this study, we analyzed spatial distribution pattern of forest fire with point pattern analysis considering spatial dependency. Distributional pattern was derived from Ripley's K-function according to causes and distances. Spatially clustered intensity was found out using Kernel intensity estimation. As a result, forest fires in Korea show clustered pattern, although the degrees of clustering for each cause are different. Furthermore, spatial clustering pattern can be classified into two groups in terms of degrees of clustering and distance. The first group shows the national-wide cluster pattern related to the human activity near forests, such as human-induced accidental fire in mountain and field incineration. Another group shows localized cluster pattern which is clustered within a short distance. It is associated with the smoker fire, arson, accidental by children. The range of localized clustering was 30 km. Beyond of this range, the patterns of forest fire became random distribution gradually. Kernel intensity analysis showed that the latter group, which have localized cluster pattern, was occurred in near Seoul with high densed population.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2012.07a
• /
• pp.137-138
• /
• 2012

• The KIPS Transactions:PartD
• /
• v.9D no.6
• /
• pp.1119-1126
• /
• 2002

In this paper, we propose two predictive spatial data mining based on spatial statistics and apply for predicting the forest fire hazardous area. These are conditional probability and likelihood ratio methods. In these approaches, the prediction models and estimation procedures are depending un the basic quantitative relationships of spatial data sets relevant forest fire with respect to selected the past forest fire ignition areas. To make forest fire hazardous area prediction map using the two proposed methods and evaluate the performance of prediction power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively. In comparison of the prediction power of the two proposed prediction model, the likelihood ratio method is mort powerful than conditional probability method. The proposed model for prediction of forest fire hazardous area would be helpful to increase the efficiency of forest fire management such as prevention of forest fire occurrence and effective placement of forest fire monitoring equipment and manpower.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.2_2
• /
• pp.301-306
• /
• 2020

In this study, analyzed national forest fire statistics by cause, year, region, and damage scale based on the National Fire Data System. as a result, the main cause of forest fires was the most frequent human error. forest fires occurred in areas with high population density. and it was confirmed that the Widest area of forest damage was Gang-Won province, which is rich in forestry resources. by season, it occurred a lot in spring because of the warm temperature and strong wind and low humidity. such disasters directly damage forest facilities such as house and cultural properties as well as destruction of natural resources. therefore in this study, made a suggestion plan for prevention from forest fire with forest fire prevention comprehensive plan of MFOA.

• Journal of The Geomorphological Association of Korea
• /
• v.28 no.1
• /
• pp.83-99
• /
• 2021

Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2012.07a
• /
• pp.120-124
• /
• 2012

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.12 no.5
• /
• pp.28-41
• /
• 2009

Because fire has significant impacts on fauna and flora in forest ecosystems, as well as socioeconomic influences to local community, it has been an important field of study for decades. One of the most common ways to reduce fire risk is to enhance fire-resilience of forest through fuel treatments including thinning and prescribed burning. Since fuel treatment can't be practiced over all forested areas, appropriate and effective strategies are needed. The present study aims to look at the relationship between spatial characteristics of forest structure measured with landscape pattern metrics and burn severity to provide guidelines for effective fuel treatments. Samchuck fire was selected for the study, and 232 grids covering the study areas were generated, and the grid size was 1km. The burn severity is measured with dNBR derived from satellite imagery, and spatial characteristics of forest structure were measured using FRAGSTATS for both landscape and class levels for each 1km grid. The results of this study strongly indicated that heterogeneity in composition and configuration of forests may significantly reduce burn severity. By enhancing heterogeneity of forests, fuel treatments for fire-resilience forest could be more effective.

• The Korean Journal of Ecology
• /
• v.28 no.1
• /
• pp.55-61
• /
• 2005

Fire, usually a detrimental factor makes changes in commonly structure and functions when it is practiced properly. In countries like Australia, South Africa, Japan and Texas in USA etc., fire is used as a tool to manage the natural ecosystems in productive condition on the basis of ecological approach. However, in developing countries like India there is effective measure to use and control fire in rangelands. This review provides knowledge on changes in sociological characters of plants, biomass profile, cycling of materials and strategy to use fire for the shaping of communities in different rangelands located in India and other countries. Further, the informations furnished in this article will be more useful for the forest managers, planners of rangelands and administrators in countries like India and tropical countries with similar bioclimatic conditions to prepare appropriate management plans where the fire is an integral factor.

• Fire Science and Engineering
• /
• v.23 no.5
• /
• pp.96-102
• /
• 2009

Forest fire ignition and spread characteristics are needed as basic data in fire management. Slope aspect of ignition point, spread direction, and wind direction at that time were analyzed and regression equations were proposed for predicting burned area, fire perimeter, head spread rate, and flank spread rate using combustion time using 101 forest fires broken out between 2007 and 2009 spring. 57% forest fires of investigated numbers were ignited in south, southwest, and southeast aspects and 68% of forest fires were spreaded to east, southeast, and northeast influenced by westerly wind. About 11.8ha forest was burned and 0.5km fire perimeter increase was predicted per hour. Head and flank spread rate were calculated 0.13km and 0.05km, respectively.

• Journal of the Society of Disaster Information
• /
• v.13 no.3
• /
• pp.296-304
• /
• 2017

In order to predict about forest fire behavior we constructed a database for combustion characteristic of forest fuels in Samcheok, Gangwon-do and prepared fire risk map and fire risk rating using GIS method in this study. For the mapping autoignition temperature, ignition time, flame duration time, total heat release and total smoke release are selected as the standardized parameters and the overall risk rating was made up of the ignition risk parameters(autoignition temperature, ignition time) and the spread risk parameters(flame duration time, total heat release, total smoke release). Forest fire risk was classified into 5 grades and lower grade of fire risk rating mean to correspond to more dangerous forest fire. As a result, the overall risk rating of Samcheok was classified into three grades from 1 to 3 and Nogok-myeon and Miro-myeon were turned out the most dangerous areas for forest fire. Because of the colony of pine and oak trees and the higher fire loads, the flame propagation will be carried out quickly in these areas.