• Title/Summary/Keyword: forest fire risk rating

Search Result 7, Processing Time 0.031 seconds

A Study on Mapping Forest Fire Risk Using Combustion Characteristic of Forest Fuels : Focusing on Samcheok in Gangwon-do (산불연료의 연소특성을 활용한 산불위험지도 작성에 관한 연구 : 강원도 삼척 시를 중심으로)

  • Lee, Haepyeong;Park, Youngju
    • 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.

Analysis of forest fire danger rating on the forest characteristic of thinning area and non-thinning area (숲 가꾸기 실행 및 미실행지의 임분특성에 따른 산불위험도 분석)

  • Lee, Si-Young;Lee, Myung-Woog;Chae, Hee-Min;Won, Myoung-Soo;Yeom, Chan-Ho
    • 한국방재학회:학술대회논문집
    • /
    • 2007.02a
    • /
    • pp.217-222
    • /
    • 2007
  • Since 1973, we attain a successful achievement of nation-wide afforestation such as a thick forest and heaped-up leaves. However, the higher of the formation density in forest, the more dangerous to be a large-scale forest fire whenever fire occurs. According to the type of forest in the country, 42% of the forest is occupied by conifer forest that are highly flammable, and the distribution of forest age is in a transition period from immature forest to mature one. And the structure is too weak to the forest fire for the occurrence and spread because there are too many scrub and shrub trees in the forest. As a matter of course, it is on the increase of the thinning-forest that can shift the forest structure from a weak on forest fire to a strong one nowaday. In other words, thinning-forest has primary purposes such as the promotion of producing forest trees, production of excellent timbers, and build-up of public forest area. Furthermore, in some reports, the reduction of ladder fuel by eliminating the vertical/horizontal fuel in a forest and ensuring spaces in the forest can decrease the occurrence of forest fire and the risk of spread of burning as by-effect. Therefore, this study is designed to clarify the relation with the risk of forest fire by an on-spat-investigation of the characteristics of forest composition on the thinning and the non-thinning area.

  • PDF

Developing the Forest Fire Occurrence Probability Model Using GIS and Mapping Forest Fire Risks (공간분석에 의한 산불발생확률모형 개발 및 위험지도 작성)

  • An, Sang-Hyun;Lee, Si Young;Won, Myoung Soo;Lee, Myung Bo;Shin, Young-Chul
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.7 no.4
    • /
    • pp.57-64
    • /
    • 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.

  • PDF

Developing Fire-Danger Rating Model (산림화재예측(山林火災豫測) Model의 개발(開發)을 위(爲)한 연구(硏究))

  • Han, Sang Yeol;Choi, Kwan
    • Journal of Korean Society of Forest Science
    • /
    • v.80 no.3
    • /
    • pp.257-264
    • /
    • 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.

  • PDF

Comparative Analysis of Forest Fire Danger Rating on the Forest Characteristics of Thinning Area and Non-thinning Area (숲 가꾸기 실행 및 미 실행지의 임분특성에 따른 산불위험성 비교분석)

  • Lee, Si-Young;Lee, Myung-Woog
    • Fire Science and Engineering
    • /
    • v.21 no.4
    • /
    • pp.52-58
    • /
    • 2007
  • The effect of stand-growing-stock characteristics of thinning area and non-thinning area on forest fire was studied in this work. 14 spots were selected from 3 counties such as Yangyang, Injae, and Gapyeong and on-the-spot investigations were performed to evaluate the effect of forest fire. The stand-growing-stock characteristics on the spots were analyzed through the height of tree, breast height diameter, clear length, mortality of branch, forest tree standing crop density, degree of closure, and shrub and grass cover degree. The relation between forest fire and the risk of spread of forest fire were analyzed from the analysis of the stand-growing-stock characteristics. It is considered from this work that the possibility of forest fire is decreased on the thinning area compared to the non-thinning area because of higher clearlength, lower number of tree, lower mortality of branch and higher shrub and grass cover degree.

Comparative Analysis of Forest Fire Danger Rating on Accumulation Types of the Leaving of Thinning Slash (숲가꾸기 산물의 적재형태에 따른 산불위험성 비교 분석)

  • Lee, Si-Young;Lee, Myung-Woog;Lee, Hae-Pyeong
    • Fire Science and Engineering
    • /
    • v.22 no.1
    • /
    • pp.45-53
    • /
    • 2008
  • The effect of thinned trees which are produced from forest thinning on forest fire was studied in this work. To investigate the effect of thinning slash, Yang-yang, In-je, and Ga-pyeong-gun were selected as thinning-areas and non-thinning areas. The research was carried out with the variations of tree's types, area's characteristics, thinning strength, thinning types, and pile types of thinned tree. The survey areas of 14 areas were selected at Yangyang-gun(5 areas), Gapyeong-gun(4 areas), and Inje-gun(5 areas), and on-the-spot investigations were carried out at the thinning areas of 9 and the non-thinning areas of 5, respectively. Non-thinning areas of 5, which are adjacent to thinning areas, were selected for the comparison with thinning areas and for the analysis of risk of forest fire. It is considered that forest fire have no chance to diffuse to a tree trunk because the height of thinned trees was lower than 1 m. However, it is considered that forest fire may affect directly to a tree trunk if it spread to piled thinned tree because there was no space between thinned trees and trees. Furthermore, it was found that re-ignition had a chance to occur due to lots of piled thinning trees.

District-Level Seismic Vulnerability Rating and Risk Level Based-Density Analysis of Buildings through Comparative Analysis of Machine Learning and Statistical Analysis Techniques in Seoul (머신러닝과 통계분석 기법의 비교분석을 통한 건물에 대한 서울시 구별 지진취약도 등급화 및 위험건물 밀도분석)

  • Sang-Bin Kim;Seong H. Kim;Dae-Hyeon Kim
    • Journal of Industrial Convergence
    • /
    • v.21 no.7
    • /
    • pp.29-39
    • /
    • 2023
  • In the recent period, there have been numerous earthquakes both domestically and internationally, and buildings in South Korea are particularly vulnerable to seismic design and earthquake damage. Therefore, the objective of this study is to discover an effective method for assessing the seismic vulnerability of buildings and conducting a density analysis of high-risk structures. The aim is to model this approach and validate it using data from pilot area(Seoul). To achieve this, two modeling techniques were employed, of which the predictive accuracy of the statistical analysis technique was 87%. Among the machine learning techniques, Random Forest Model exhibited the highest predictive accuracy, and the accuracy of the model on the Test Set was determined to be 97.1%. As a result of the analysis, the district rating revealed that Gwangjin-gu and Songpa-gu were relatively at higher risk, and the density analysis of at-risk buildings predicted that Seocho-gu, Gwanak-gu, and Gangseo-gu were relatively at higher risk. Finally, the result of the statistical analysis technique was predicted as more dangerous than those of the machine learning technique. However, considering that about 18.9% of the buildings in Seoul are designed to withstand the Seismic intensity of 6.5 (MMI), which is the standard for seismic-resistant design in South Korea, the result of the machine learning technique was predicted to be more accurate. The current research is limited in that it only considers buildings without taking into account factors such as population density, police stations, and fire stations. Considering these limitations in future studies would lead to more comprehensive and valuable research.