STUDY ON FOREST FIRE DANGER MODEL WITH REMOTE SENSING BASED ON GIS

Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.

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.

Modelling of Environment Vulnerability to Forests Fires and Assessment by GIS Application on the Forests of Djelfa (Algeria)

Risk management of forest fires starts from its assessment. This assessment has been subject of several research works and many models of fire risk have been developed. One of them has been developed by ourselves, for the Mediterranean areas. However environmental vulnerability to forest fires is an important part of risk;it represents, in fact, the exposed challenge to this scourge and therefore it worths particular attention by decision makers. Thus and due to the importance of socio-economic potential of forest and the negative influence of fire on this one, we propose in this work, a model for vulnerability assessment to forest fires based on the principle of the weighted sum. Application of the proposed model suggested to use of geomatics technologies to the spatialize level of vulnerability. Within this framework, a GIS was developed and applied to the forests of Djelfa in the Saharian Atlas, as originality, it will allow the understanding of the concept of vulnerability and risk associated the steppes area scale to reach a good space control.

Mathematical Modeling of Crown Forest Fire Spread

Mathematical model of forest fire was based on an analysis of known experimental data and using concept and methods from reactive media mechanics. In this paper the assignment and theoretical investigations of the problems of crown forest fire spread in windy condition were carried out. In this context, a study—mathematical modeling—of the conditions of forest fire spreading that would make it possible to obtain a detailed picture of the change in the temperature and component concentration fields with time, and determine as well as the limiting condition of fire propagation in forest with fire break.

The Mathematical Model of Short-Term Forest Fire Spread

In this paper, we establish a mathematical model of the forest fire spread process based on a partial differential equation. We describe the distribution of time field and velocity field in the whole two-dimensional space by vector field theory. And we obtain a continuous algorithm to predict the dynamic behavior of forest fire spread in a short time. We use the algorithm to interpolate the fire boundary by cubic non-uniform rational B-spline closed curve. The fire boundary curve at any time can be simulated by solving the Eikonal equation. The model is tested in theory and in practice. The results show that the model has good accuracy and stability, and it’s compatible with most of the existing models, such as the elliptic model and the cellular automata model.

Forest fire risk assessment in parts of Northeast India using geospatial tools

Forest fire is a major cause of changes in forest structure and function. Among various floristic regions, the northeast region of India suffers maximum from the fires due to age-old practice of shifting cultivation and spread of fires from jhum fields. For proper mitigation and management, an early warning of forest fires through risk modeling is required. The study results demonstrate the potential use of remote sensing and Geographic Information System （GIS） in identifying forest fire prone areas in Manipur, southeastern part of Northeast India. Land use land cover （LULC）, vegetation type, Digital elevation model （DEM）, slope, aspect and proximity to roads and settlements, factors that influence the behavior of fire, were used to model the forest fire risk zones. Each class of the layers was given weight according to their fire inducing capability and their sensitivity to fire. Weighted sum modeling and ISODATA clustering was used to classify the fire zones. TO validate the results, Along Track Scanning Radiometer （ATSR）, the historical fire hotspots data was used to check the occurrence points and modeled forest fire locations. The forest risk zone map has 55-63% of agreement with ATSR dataset.

Efficient Application of the Radiance Enhancement Method for Detection of the Forest Fires Due to Combustion-Originated Reflectance

The existing methods for detection of the cloud scenes are applied at relatively small spectral range within shortwave upwelling radiative wavelength flux. We have reported a new method for detection of the cloud scenes based on the Radiance Enhancement (RE). This method can be used to cover a significantly wider spectral range from 1100 nm to 1700 nm by using datasets from the space-orbiting micro-spectrometer Argus 1000. Due to high sunlight reflection of the smoke originated from the forest or field fires the proposed RE method can also be implemented for detection of combustion aerosols. This approach can be a promising technique for efficient detection and continuous monitor of the seasonal forest and field fires. To the best of our knowledge this is the first report showing how a cloud method can be generalized for efficient detection of the forest fires due to combustion-originated reflectance.

Model-Based Forecasts of North American Forest Growth: A Review

In the context of climate change, planning for forest management goals becomes more complicated. Possible changes in precipitation, temperature, and CO2 can affect tree growth substantially and potential effects differ by species and region. However, integration of potential forest growth responses to these factors can be achieved using models. Because of the need to understand the range of forest growth forecasts and the strengths and limitations of different modeling approaches, I summarized results from 25 studies of forecasted forest responses over coming decades. Some models used statistical relationships between tree rings and climate to forecast growth responses to future climate, some simulated net photosynthesis of a standard forest canopy, and many used tree or stand growth models at various levels of mechanistic detail. In general, models that included CO2 responses predicted enhanced forest growth by 2100 across most of the commercial timberland areas of the US and Canada. For modest warming, most models showed growth enhancement in most regions. For hotter scenarios, many models and regions showed even more growth enhancement, but some regions such as the Southwest, mountain West, and southwestern Canada were predicted to experience drought stress and increased fire incidence, although projections in these regions were variable. Young stands, angiosperms, and early-successional species were predicted to exhibit the most positive responses. As a result, commercial harvest ages might be accelerated by several years, depending on species. Some simulations for the Midwest and Northeast US predicted a doubling or more of net primary productivity although other studies show a lesser response. Model runs that did not include mechanisms of CO2 fertilization showed positive growth responses in only limited cases and generally showed growth declines. There also was some evidence indicating the potential spread of forest into woodland at shrub or prairie ecotones.

Estimated Carbon Sequestration in a Temperate Forest in Idaho of USA

Assessing carbon (C) sequestration in forest ecosystems is fundamental to supply information to monitoring, reporting and verification (MRV) for reducing deforestation and forest degradation (REDD). The spatially-explicit version of Forest-DNDC (FDNDC) was evaluated using plot-based observations from Nez Perce-Clearwater National Forest (NPCNF) in Idaho of United States and used to assess C stocks in?about 16,000 km2. The model evaluation indicated that the FDNDC can be used to assess C stocks with disturbances in this temperate forest with a proper model performance efficiency and small error between observations and simulations. Aboveground biomass in this forest was 85.1 Mg C ha-1 in 2010. The mean aboveground biomass in the forest increased by about 0.6 Mg C ha-1 yr-1 in the last 20 years from 1990 to 2010 with spatial mean stand age about 98 years old in 2010. Spatial differences in distributions of biomass, net primary production and net ecosystem product are substantial. The spatial divergence in C sequestration is mainly associated with the spatial disparities in stand age due to disturbances, secondly with ecological drivers and species. Climate variability and change can substantially impact C stocks in the forest based on the climatic variability of spatial climate data for a 33-year period from 1981 to 2013. Temperature rise can produce more biomass in NPCNF, but biomass cannot increase with an increase in precipitation in this forest. The simulation with disturbances using observations and estimates for the time period from 1991 to 2011?showed the effects of disturbances on C stocks in forests. The impacts of fires and insects on C stocks in this forest are highly dependent on the severity, the higher, the more C loss to atmosphere due to?fires, and the more dead woods produced by fires and insects. The rates of biomass increase with an increase in stand age are different among the species. The changes in forest C stocks?in the forest are almost species specific, non-linear and complex. The increase in aboveground biomass with an increase in stand age can be described by a high-order polynomial.

森林火灾中使用细水雾进行灭火仿真方法研究

森林火灾作为一种极具危害性的自然灾害,其发生和蔓延过程通常受到气候、地形、植被、可燃物等多种复杂因素的影响,导致很难准确地对森林火灾的蔓延与灭火过程进行仿真。对森林火灾的蔓延和细水雾灭火过程进行物理建模,蔓延模型采用树形模块结构来模拟树木燃烧的热解反应,并考虑了温度、风场、质量损失率等因素对树木燃烧蔓延的影响。在使用细水雾进行灭火仿真实验时,重点关注细水雾穿透火焰区域形成水膜以及水分蒸发导致的灭火作用,从而阻止森林火灾的蔓延,成功实现了交互灭火的仿真平台,可以让用户沉浸式地体验森林火灾的蔓延过程,并通过水枪、消防车和无人机进行细水雾灭火仿真实验。该研究成果对消防仿真领域方面的应用具有重要意义。

森林火灾污染物质释放及其影响研究进展

森林火灾是大气中气体污染物和颗粒物的重要来源,可对全球气候系统、大气环境以及生态系统产生重要影响,对全球温室气体和含碳颗粒物释放具有重要的贡献,是推动全球气候变化的重要因素。森林火灾释放污染物已成为区域乃至全球范围内重要污染源之一,这些污染物质与辐射、能见度以及温室效应等问题直接相关。准确地描述森林火灾释放的气体和颗粒污染物释放机理、释放总量、时空分布特征、不同尺度的扩散过程模拟,以及对区域大气环境的影响,对于量化森林火灾释放污染物总量及区域影响具有重要意义。基于森林火灾污染物质释放方面的国内外文献,从火灾释放的污染物质对环境的影响、森林火灾释放污染物定量化和传输路径监测的研究方法、污染物质的扩散和运输模型以及跨区域影响等几个方面进行了综述。森林火灾释放的CO、PM_(10)和PM_(2.5)对环境和人的生命安全造成巨大威胁,而且森林火灾释放的污染物质能够随气流长距离传输,不仅对当地的空气造成污染,污染物也能够随着气团进行长距离传输,并在传输过程与当地气溶胶混合,形成跨区域污染。森林火灾释放污染物扩散、传输模拟通过不同模型相互耦合完成,包括可燃物载量估算模型、可燃物消耗和释放模型、污染物扩散传输模型,以及污染物预测和可视化模型等。总结了国内外森林火灾释放污染物质主要研究方法,并展望了今后研究重点:目前我国关于森林火灾释放物质相关的研究尚不足以支撑我国森林火灾温室气体释放、污染物释放等方面的研究,并且我国目前还没有发展出适合于我国的森林火灾污染物释放模型,以及污染物扩散、传输系统。森林火灾排放因子库大多数引用国外研究结果,在一定程度上增加不确定性,缺乏森林火灾对区域大气环境影响的定量化研究。因此,今后我国应加强对森林火灾污染物质释放与影响的研究,尤其是污染物质扩散和传输模型的预测和可视化研究以及排放因子的测量。

基于观测与预报数据融合的森林火险预报

针对气象因子日变化波动大容易引起森林火险气象等级预报变动大这一问题,参考布龙-戴维斯方案森林火险气象预报模型的构建思路,利用2016—2020年广西1785个森林火灾样本和气象观测数据,建立森林火险气象指数模型(简称“模型”)。将气象观测数据输入模型,计算出每日森林火险气象监测指数,同时,将智能网格预报数据输入模型,计算出每日森林火险气象预报指数,然后利用加权算法将每日森林火险气象监测指数和每日森林火险气象预报指数进行融合计算,得到森林火险气象融合预报指数。利用2021年6月—2023年6月789个火灾样本,对林火险气象融合预报指数进行验证,结果表明:融合后未来1~7 d森林火险等级预报准确率从82%~56%,较融合前预报准确率提升1%~3%,基本满足目前广西森林火险气象等级预报业务应用。

基于虚拟现实的森林灭火指挥训练系统研究

森林消防队伍日常训练和考评主要以森林灭火应急预案进行实装演练,针对训练中成本高、环境受限、内容不足等问题,迫切需要采用虚拟现实、人工智能等先进技术实现森林灭火指挥训练与考评系统。本文自主研发了一套基于定制化的Unity3D渲染引擎的虚拟仿真训练教学考评系统。对比国外主流虚拟仿真软件,本系统中场景细节更逼真,能进行实景虚拟仿真训练,更加贴近灭火实战;同时系统具有自主可控性、可扩展性,为用户提供简单编辑方式,支持火环境设计制作等森林消防专业应用逻辑。本文研究结果对于探索建立规范化、信息化森林灭火指挥员训练考评体系具有重要的现实意义。

基于深度学习的内蒙古大兴安岭林区火灾预测建模研究

[目的]对内蒙古大兴安岭地区的森林火灾进行预测,为森林防火工作的开展提供重要支持。[方法]以内蒙古大兴安岭林区为研究对象,结合MCD64 A1月度火点产品、地形、气候等数据,构建森林火灾潜在影响因子数据集,分别利用卷积神经网络、随机森林、支持向量机模型对研究区森林火灾的发生概率进行预测与可视化,在此基础上对模型效果进行评价并分析森林火灾空间分布特征。[结果]大兴安岭的主要林火驱动因子按重要性值由高到低排序为海拔、平均气温、总降水量、与水域的距离等;CNN、RF、SVM预测森林火灾发生概率的AUC值分别为0.838、0.794、0.788,CNN的精度最高;CNN能够有效划分出森林火灾易感性极高、极低的区域,有利于划分森林火灾的警示区。[结论]CNN模型比RF、SVM模型更适用于大兴安岭林火发生概率的预测;大兴安岭林火风险的空间分布有明显的区域性,主要发生在东南地区。

云南顶瓶梗霉对森林地表凋落物的降解效果

【目的】探究云南顶瓶梗霉GZUIFR 22.409对不同类型森林地表凋落物的降解效果,以期利用该真菌促进森林地表凋落物的降解,减少森林地表凋落物的载量,从而降低森林火险等级,并为利用微生物降解法降低贵州林区森林可燃物载量提供理论依据和基础数据。【方法】采集林地的针叶和阔叶地表凋落物,利用云南顶瓶梗霉活菌和粗酶分别处理凋落物,并按照野外调查地表凋落物床层参数设置床层后,于25 ℃温度和80%相对湿度条件下测定两类地表凋落物的失重动态,分析云南顶瓶梗霉活菌和粗酶对两类地表凋落物的降解效果。【结果】云南顶瓶梗霉活菌和粗酶对两类地表凋落物均具有降解作用且都在第16天降解率最大。对于针叶凋落物,粗酶的降解率为9.74%,菌的降解率为13.14%;经降解模型拟合,粗酶的降解系数k为0.004,降解t_(0.5)为165 d、t_(0.95)为740 d,菌的降解系数k为0.005,降解t_(0.5)为131 d、t_(0.95)为588 d;对于阔叶凋落物,粗酶的降解率为15.76%,菌的降解率为15.37%;经降解模型拟合,粗酶的降解系数k为0.007,降解t_(0.5)为93 d、t_(0.95)为422 d,菌的降解系数k为0.006,降解t_(0.5)为103 d、t_(0.95)为487 d。【结论】云南顶瓶梗霉活菌及其粗酶对针阔叶地表凋落物都有降解效果,对阔叶凋落物的降解效果优于针叶凋落物,应用该菌可在一定程度上能够达到减少森林地表可燃物载量的效果。因此云南顶瓶梗霉在调控森林地表凋落物载量方面具有较好的应用前景。

基于改进的王正非模型结合元胞自动机的林火蔓延预测

【目的】针对当前我国林火蔓延预测仍存在预测精度不高、普适性差等问题,基于王正非速度模型结合多维元胞自动机的林火蔓延预测模型进行改进,研究了不同区域和分辨率下该模型的有效性,增强了该模型对于不同分辨率数据的适应能力,从而更好地对森林火灾蔓延进行预测,并为林区的火灾蔓延预测和管理提供一种科学合理的技术手段。【方法】使用黑龙江省大兴安岭地区2011年10月28日发生的森林火灾(分辨率500 m)与四川省凉山地区2022年3月29日发生的森林火灾(分辨率30 m)作为数据源,提取发生火灾时刻以及蔓延过程的火线。引入归一化植被指数(NDVI)对王正非模型进行改进,并利用反卷积算法对元胞自动机算法进行改进,将改进后模型输出的结果与实际结果进行精度对比,并比较不同分辨率下的模型精度表现。【结果】改进后的模型精度有明显的提升,其中,黑龙江省大兴安岭试验改进后模型的kappa系数提高了0.0297,面积误差率降低了21.33%,火场预测火点170个,平均过火速度0.75 m/min。四川省木里县试验改进后模型的kappa系数提高了0.1165,面积误差率降低了37.08%,火场预测火点1795个,平均过火速度为4.00 m/min。【结论】改进后的林火蔓延预测模型可以更有效地预测火灾蔓延并计算出最可能过火的火点位置,其预测结果具有高度的一致性和准确性,提高了林火蔓延模拟预测的实用性。与原始模型相比,改进后的模型很好地提高了在不同分辨率数据下的预测精度,能为林火预防和管理提供科学依据。

应用机器学习算法分析广西林火发生驱动因素及林火预测

森林火灾对生态环境和人类社会构成了严重威胁,当前全球气候不断变化、人类活动日益频繁,森林火灾的影响也日益凸显。以广西壮族自治区为研究区,根据2006—2020年研究区的卫星监测森林火点数据,结合气象数据、地形数据、植被数据和人为活动数据,应用反向传播神经网络(BPNN)、梯度增强决策树(GBDT)、随机森林(RF)、支持向量机(SVM)和极限梯度提升模型(XGBoost)等机器学习算法对广西地区的森林火灾建模,对林火发生概率进行预测;利用最优模型绘制了季节性森林火险区域图,分析森林火灾发生的驱动因素和潜在的森林火灾风险。结果表明:(1)XGBoost模型在预测广西地区森林火灾风险方面表现最佳,其准确率为92.33%,精确度为92.89%,召回率为91.88%,F_(1)值为92.38%,A_(UC)值为97.68%。(2)广西地区森林火灾的主要驱动因素为气象条件与植被因素,主要因素为潜在蒸发量(Pes)、大气压(Sfp)、总初级生产力(GPP)和增强型植被指数(Evi)等。(3)广西地区的春季和冬季是森林火灾的高发季节,中高风险区主要集中在桂东、桂中南和桂西地区。

吉林省延边地区森林火灾发生概率预测模型

对于森林火灾这种严重危害森林生态系统的自然灾害而言,预防大于扑救。为实现对吉林省延边地区的森林火灾进行预测,根据历史火灾资料、气象数据、地形地貌数据、植被数据和人为与社会经济数据建立了延边地区森林火灾发生概率预测模型。研究结果表明:建立的4个林火发生概率预测模型均具有较高的拟合度(模型精度值>0.9)和准确率(>80%);经最优模型筛选,随机森林模型(RF)的综合得分最高,最适用于延边地区的林火发生概率预测模型;最优模型中,最小相对湿度和人口密度的变量重要性最大;延边地区南部的林火发生概率明显高于北部,IV级和V级林火发生风险区也多分布于南部。

虚拟环境中面向灭火指挥的火场信息可视分析

针对森林火灾现场指挥的需求,综合分析地理环境、气象条件、森林资源和林火行为等灭火指挥所需信息,设计实现了在虚拟林火环境中的数据可视化可视分析方法。使用王正非-3D混合元胞自动机模型模拟林火蔓延过程;采取差时方法预测林火蔓延行为;实时捕捉不同兴趣域内环境数据的变化,结合多视图面板及图层叠加的方法,构建火场信息可视分析模块。通过调整虚拟林场的环境参数,对不同场景下的林火蔓延过程进行模拟仿真,并对火场信息进行可视化可视分析。实验结果表明:该方法能够在一定条件下较准确地预测林火蔓延行为,还可以较全面地描述火场信息。

Influences of finite-size effects on the self-organized critical-ity of forest-fire model

The influences of finite-size effects on the self-organized criticality (SOC) of the traditional forest-fire model are investigated by means of a new method. The forest size is originally set to a value much greater than the correla-tion length of the forest. Finite-size effects are then studied by equally dividing the forest into more and more separate subsystems on condition that the forest size, igniting prob-ability and planting probability are invariant. A new phe-nomenon, i.e. the finite-size effects with one-side frequency peak, is observed. The boundary between two neighboring subsystems can be regarded as a firebreak. The concept of ’separation ability’ is introduced to represent the probability for the firebreak to block off the fire successfully. Restrain-ing effects of separation ability on finite-size effects are ana-lyzed. Finite-size effects and separation ability, as well as their relations are found to have practical importance to the actual forest-fire protection.