An easy,accurate and efficient procedure to create forest fire risk maps using the SEXTANTE plugin Modeler

To prevent, detect, and protect against forest fires, forest personnel need to define rules for determining forest fire risk. In Portugal, all municipalities must annually produce forest fire risk （FFR） maps. To produce more reliable FFR maps more easily, we developed an open source model using the Modeler plugin of SEXTANTE in the program QGIS version 2.0 Dufour. The model provides all the maps involved in the FFR model （susceptibility map, hazard map, vulnerability map, economic value map, and potential loss map） and was produced according to Portuguese Forest Authority＇s （AFN, Autoridade Florestal Nacional） rules for determining the FFR. This model was tested for the Portuguese municipality Santa Maria da Feira, where 40 % of the total municipality area falls in the category ＂very high＂ or ＂high＂ fire risk. The ＂very high＂ fire risk area is mainly classified as broad-leaved forest and has the steepest slopes （〉15 %）. The distance of burned areas to roads was also analyzed; the proportion of burned areas increased with increasing distance to the main roads. In addition, 92.6 % of the ＂high＂ and ＂very high＂ risk zones were located in areas with lower elevation. These results confirmed that forest fire is strongly influenced not only by environmental factors but also by anthropogenic factors. The procedure implemented here was compared with our open source application already available in QGIS and also to the same procedure implemented in GIS pro- prietary software. Although the results were obviously the same, the model developed here presents several advan- tages over the other two approaches. Besides being faster, it is easy to change the model parameters according to user needs （i.e., to the rules of different countries）, and can be modified and adapted to other variables and other areas to create risk maps for different natural phenomena （e.g., floods, earthquakes, landslides）. The model is easy to use and to create risk and hazard maps rapidly in a free, open source environment that does not require any programming knowledge.

Forest fire risk indices and zoning of hazardous areas in Sorocaba,Sao Paulo state,Brazil

This study compares the performance of three fire risk indices for accuracy in predicting fires in semideciduous forest fragments,creates a fire risk map by integrating historical fire occurrences in a probabilistic density surface using the Kernel density estimator(KDE)in the municipality of Sorocaba,Sao Paulo state,Brazil.The logarithmic Telicyn index,Monte Alegre formula(MAF)and enhanced Monte Alegre formula(MAF+)were employed using data for the period 1 January 2005 to 31 December 2016.Meteorological data and numbers of fire occurrences were obtained from the National Institute of Meteorology(INMET)and the Institute for Space Research(INPE),respectively.Two performance measures were calculated:Heidke skill score(SS)and success rate(SR).The MAF+index was the most accurate,with values of SS and SR of 0.611%and 62.8%,respectively.The fire risk map revealed two most susceptible areas with high(63 km^2)and very high(47 km^2)risk of fires in the municipality.Identification of the best risk index and the generation of fire risk maps can contribute to better planning and cost reduction in preventing and fighting forest fires.

基于机器学习的流域尺度森林火灾灾害风险预测

森林是碳库,具有强大的固碳增汇功能,在应对气候变化中发挥着重要作用。然而,由于极端高温的影响,频繁发生可燃物自燃而引发森林火灾,除了影响区域水文大气循环过程以外,也给人类带来严重的人员伤亡和经济损失。现有森林火灾预测研究主要侧重可燃物研究和火灾监测等方面,较少关注大尺度地形、气象和人类活动对森林火灾的影响,但这些也是除可燃物外导致森林火灾发生的主要因素。以嘉陵江流域重庆段为研究区,区域内山地受自然火灾影响严峻。基于地理信息系统叠加地理空间因子与火灾分布点获得数据集,构建4种机器学习模型,测试模型性能,评价最优模型进行森林火灾灾害风险制图。研究结果表明,模型评估指标受试者工作曲线下面积(area under the curve,AUC)平均值为95.0%,模型性能梯度提升决策树最优,AUC值为98.3%。利用梯度提升决策树(gradient boosting decision tree,GBDT)模型预测森林火灾风险对防范大尺度森林火灾具有一定的可行性,对山城避灾规划起到借鉴作用,规划引导降低森林火灾风险,从而维护生态平衡和生态系统碳汇能力。

基于改进相互作用矩阵-模糊认知图的矿井火灾风险评价

针对多因素耦合作用下矿井火灾风险评价中影响因素模糊性与动态解释能力不足的问题,基于人、机、环境、管理4个维度构建矿井火灾风险评价指标体系;运用组合数有序加权(combination ordered weighted averaging,C-OWA)算子削弱主观因素影响建立相互作用矩阵,进而识别关键风险因素;将矩阵元素融入模糊认知图推理模型,预测火灾风险演化趋势;最后通过组合评价系数确定风险评价等级,并将所提方法应用到矿井实例予以验证。结果表明:该矿井火灾风险为一般风险,与实际情况相符,验证了该方法的可行性与适用性,同时该方法既能对风险因素进行耦合分析,又能实现对风险趋势的定量化预测,具有一定的优越性。

Development of a model to generate a risk map in a building fire

Fire simulations and sensors are widely used in building fires,various data such as temperature,CO and CO2 concentration,visibility can be obtained by sensors and sensor-based simulation. It is important to generate a risk map based on such data so that we can use it to estimate safety of the building. In this paper,we propose a method to generate a dynamical,integrated risk map using sensor readings in a building fire. Such risk evaluation model is developed using similarity comparison between the space state and dangerous state by a likelihood distance calculating and data grouping from a two-step cluster method. The risk evaluation model considers the integrated influence on the occupants in the zone from high temperature,lack of oxygen,toxic and harmful gases and shows the relative fire risk map at certain time. Based on the simulation study,it is proved that multi-factor fire risk analysis would be more objective and accurate than single factor and two-factor risk analysis and the fire risk evaluation model can generate a risk map and provide the classification information and the whole building risk statistic results to support evacuation command and control.

LY1063—92行业标准应用于国有林场火险区划方法的研究

应用 LY1063—92行业区划标准系统,对平利县千家坪林场诸火险柯关因子分析并进行区划研究,得出安康地区国营林业单位参与地区森林火险区划诸因子的量化确定标准和区划原则。指出在区划过程中以林班组作为区划分区的基本单位。结合秦巴山区的植被条件和不同林分的燃烧性差异给出火险重要值—优势树种组的得分确定方法。

基于CiteSpace的火灾风险评估研究知识图谱分析

为了解火灾风险评估领域的全局概况,对CNKI和Web of Science数据库进行检索,借助CiteSpace软件分析了1999-2020年间的共1 250篇文献数据,并绘制了知识图谱。结果表明:火灾风险评估发文量呈稳定上升趋势;高产核心作者是田玉敏和THOMPSON P M;核心机构是中国人民武装警察部队学院(现中国人民警察大学)和中国科学技术大学;高产核心国家是中国和美国;对关键词综合分析,得出未来研究的热点是:理论研究方面,继续研究火灾发生的随机性与不确定性;评估方法方面,构建基于火灾双重属性规律的火灾风险评估方法;评估实践方面,开发智能化的评估软件。

东莞大屏嶂森林火险等级评价与区划

针对广东省东莞大屏嶂森林公园的森林资源环境特点,选取植被类型、坡度、坡向、海拔、居民区距离、道路距离6个火险影响因子,利用GIS空间分析功能对大屏嶂森林公园进行森林火险等级的评价与区划。区划方案表明,该区可以划分为无、低、中、高和极高5个等级火险区,其面积分别占研究区的1.67%、2.19%、33.16%、55.3%和7.68%。森林火险等级的空间分异较明显,极高火险主要出现在西北部,中部和北部火险等级较高,东部与南部火险稍低。森林火险较高等级主要受植被类型、坡向及海拔这3个因素影响。

基于模糊逻辑和网络层次分析法的森林火险区划

林火对人类生命财产安全和生态环境产生重要影响,编制高质量的森林火险图对预防林火的发生、指导扑救资源配置、辅助火灾扑灭和支持决策制定均有积极意义。本研究采用基于地理信息系统的多准则决策分析(MCDA)方法以及查阅文献确定影响福建省尤溪县林火发生的主要因子,每个火险因子的重要性利用网络层次分析法(ANP)确定,得出权重,次标准的权重由模糊逻辑评估,使用ArcGIS的聚合函数生成森林火灾风险图,结合卫星火点验证准确度。结果表明:尤溪县4级及以上火险等级区域占比大,中部和北部林火发生风险较高,该县整体火险情况严峻;模糊ANP模型的准确性较高,达85.8%。引入新的MCDA方法有效地提高了小尺度范围森林火险制图的准确度,可为早期林火预警、扑灭资源规划和分配工作提供依据。

Development and prospects of the fire space monitoring system in Kazakhstan

This article provides a brief description of the fire space monitoring system in Kazakhstan, including the GIS-technology incorporated in its structure. The system performs operative space monitoring of fire areas and burnt areas, mapping of large fire areas, analysis of seasonal and long-term dynamics of burnt areas, and estimation of fire risk zones. Examples of output information obtained from space monitoring of fires are given. Possible directions of development of fire space monitoring in Kazakhstan are specified.

危险度图方法在建筑工程消防性能化设计评估中的应用

消防安全性评估是建筑工程消防性能化设计的重要步骤。为使消防安全性评估方法更具有科学性,该文将火场中多重危险因素如高温、毒气和缺氧等的综合效果定义成统一的危险度,并结合火场模拟直观地给出了火场危险度图。通过有机耦合危险度图和考虑低能见度影响的疏散模拟,经过大样本统计得到伤害概率分布、区域危险度和区域疏散时间等。结合示例建筑,从对危险度图的分析中优化了疏散路径,并对上述火灾危险指标比较分析验证了优化路径策略的有效性。该危险度图方法综合考虑了建筑火场中多重危险和人员疏散等性能化设计中涉及的多项复杂分散因素,在规范火灾危险指标和标准评估过程方面为建筑工程消防性能评估和设计提供了一套切实可行的思路和方法。