Forest fire risk indices and zoning of hazardous areas in Sorocaba,S?o 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,S?o 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.     

The choices of the fire — Debating socioeconomic determinants of the fires observed at Portuguese municipalities

Forest fires have been an important source of economic losses in Portuguese municipalities. This work is one of the first studies to test a large range of socioeconomic determinants to explain the differences in the burnt forest areas observed in 278 Portuguese municipalities between 2000 and 2011. Using Classification and Regression Trees, the amount of municipal burnt area per forest fire was observed to depend on the economic dynamism of each locality, the population density of a municipality, the availability of trained teams of forest firefighters, and the presence of relatively high municipal expenditures on environment outlays. We also studied the number of forest fires, concluding that the frequency of forest fires depends on the aging index, the economic dynamism and the average altitude of a municipality.     

Forest fuel mapping and evaluation of LANDFIRE fuel maps in Boulder County,Colorado, USA

A key challenge in modern wildfire mitigation and forest management is accurate mapping of forest fuels in order to determine spatial fire hazard, plan mitigation efforts, and manage active fires. This study quantified forest fuels of the montane zone of Boulder County, CO, USA in an effort to aid wildfire mitigation planning and provide a metric by which LANDFIRE national fuel maps may be compared. Using data from 196 randomly stratified field plots, pre-existing vegetation maps, and derived variables, predictive classification and regression tree models were created for four fuel parameters necessary for spatial fire simulation with FARSITE (surface fuel model, canopy bulk density, canopy base height, and stand height). These predictive models accounted for 56–62% of the variability in forest fuels and produced fuel maps that predicted 91.4% and 88.2% of the burned area of two historic fires simulated in the FARSITE model. Simulations of areas burned based on LANDFIRE national fuel maps were less accurate, burning 77.7% and 40.3% of the historic fire areas. Our results indicate that fuel mapping efforts that utilize local area information and biotic as well as abiotic predictors will more accurately simulate fire spread rates and reflect the inherent variability of forested environments than do current LANDFIRE data products.     

基于地理加权回归模型与林火遥感数据估算森林年龄

【目的】通过地理加权回归(GWR)模型估算非干扰林龄,利用遥感数据和林火发生历史数据,获取过火区域信息,进而对林火烈度分级,讨论林火烈度与森林类型的交互作用,估算干扰林龄,最终获得黑龙江省森林年龄的空间分布。【方法】以黑龙江森林为研究区域,基于研究区域的多光谱数据结合地面森林资源清查数据,通过逐步回归方法提取了包括遥感因子绿度指数(Greeness)、湿度指数(Wetness)、林分平均胸径(ADBH)、林分平均树高(ASH)及海拔(Altitude)在内的5个显著因子作为自变量,采用GWR模型建立非干扰林龄估算模型。采用全局Moran I来描述模型残差的空间自相关性。绘制研究区非干扰林龄空间分布图并探究林龄的空间分布状态。[JP+1]结合林火位置与面积记录对多光谱数据目视解译提取过火区域,根据dNBR将过火区域火烈度分级。将火烈度图与植被类型图叠加分析,讨论不同森林类型在不同火烈度下的演替情况。定义干扰林龄时,未发生树种更替的森林林龄不变,树种发生更替的森林在林火发生年将其林龄归为0,并在新的优势树种萌发时从1开始累加,以此类推干扰后森林的林龄。【结果】黑龙江省非干扰森林平均林龄为48年,标准差为16年。GWR模型的 Radj^2 为0.68,RMSE为16.171 7。使用Moran I来检验模型的残差,发现GWR模型可很好地消除残差的空间自相关性。研究区林龄整体空间分布状态不均匀,大兴安岭地区林龄普遍高于黑龙江林区。黑龙江省2000―2010年林火主要发生在大兴安岭及小兴安岭地区,根据dNBR将已提取的过火区域林火烈度分为:未过火、轻度过火、中度过火和重度过火4类,总过火面积为527 932 hm^2,其中重度29 157 hm^2、中度180 268 hm^2、轻度318 507 hm^2。兴安落叶松林和蒙古栎林在整个研究区中过火面积最大,分别占总过火面积的28.63%和47.23%。根据不同森林类型在不同火烈度下的演替情况,估算干扰森林的林龄并绘制干扰林龄空间分布图。【结论】 GWR模型能较有效地估算黑龙江省非干扰林龄,成功地降低了残差的空间自相关性。在估算林龄的过程中加入林火干扰因素,以获取更真实的林龄空间分布数据,可为黑龙江地区森林NPP、NEP以及森林碳储量、森林生物量等相关研究提供数据支持。     

Comparative analysis of multi-criteria probabilistic FR and AHP models for forest fire risk(FFR) mapping in Melghat Tiger Reserve(MTR) forest

A comparative study of Frequency Ratio(FR)and Analytic Hierarchy Process(AHP)models are performed for forest fire risk(FFR)mapping in Melghat Tiger Reserve forest,central India.Identification of FFR depends on various hydrometeorological parameters altitude,slope,aspect,topographic position index,normalized differential vegetation index,rainfall,air temperature,land surface temperature,wind speed,distance to settlements,and distance by road are integrated using a GIS platform.The results from FR and AHP show similar trends.The FR model was significantly higher accurate(overall accuracy of 81.3%,kappa statistic 0.78)than the AHP model(overall accuracy 79.3%,kappa statistic 0.75).The FR model total forest fire risk areas were classified into five classes:very low(7.1%),low(22.2%),moderate(32.3%),high(26.9%),and very high(11.5%).The AHP fire risk classes were very low(6.7%),low(21.7%),moderate(34.0%),high(26.7%),and very high(10.9%).Sensitivity analyses were performed for AHP and FR models.The results of the two different models are compared and justified concerning the forest fire sample points(Forest Survey of India)and burn images(2010-2016).These results help in designing more effective fire management plans to improve the allocation of resources across a landscape framework.     

基于地理加权回归模型与林火遥感数据估算森林年龄

【目的】通过地理加权回归(GWR)模型估算非干扰林龄,利用遥感数据和林火发生历史数据,获取过火区域信息,进而对林火烈度分级,讨论林火烈度与森林类型的交互作用,估算干扰林龄,最终获得黑龙江省森林年龄的空间分布。【方法】以黑龙江森林为研究区域,基于研究区域的多光谱数据结合地面森林资源清查数据,通过逐步回归方法提取了包括遥感因子绿度指数(Greeness)、湿度指数(Wetness)、林分平均胸径(ADBH)、林分平均树高(ASH)及海拔(Altitude)在内的5个显著因子作为自变量,采用GWR模型建立非干扰林龄估算模型。采用全局Moran I来描述模型残差的空间自相关性。绘制研究区非干扰林龄空间分布图并探究林龄的空间分布状态。[JP+1]结合林火位置与面积记录对多光谱数据目视解译提取过火区域,根据dNBR将过火区域火烈度分级。将火烈度图与植被类型图叠加分析,讨论不同森林类型在不同火烈度下的演替情况。定义干扰林龄时,未发生树种更替的森林林龄不变,树种发生更替的森林在林火发生年将其林龄归为0,并在新的优势树种萌发时从1开始累加,以此类推干扰后森林的林龄。【结果】黑龙江省非干扰森林平均林龄为48年,标准差为16年。GWR模型的 Radj^2 为0.68,RMSE为16.171 7。使用Moran I来检验模型的残差,发现GWR模型可很好地消除残差的空间自相关性。研究区林龄整体空间分布状态不均匀,大兴安岭地区林龄普遍高于黑龙江林区。黑龙江省2000―2010年林火主要发生在大兴安岭及小兴安岭地区,根据dNBR将已提取的过火区域林火烈度分为:未过火、轻度过火、中度过火和重度过火4类,总过火面积为527 932 hm^2,其中重度29 157 hm^2、中度180 268 hm^2、轻度318 507 hm^2。兴安落叶松林和蒙古栎林在整个研究区中过火面积最大,分别占总过火面积的28.63%和47.23%。根据不同森林类型在不同火烈度下的演替情况,估算干扰森林的林龄并绘制干扰林龄空间分布图。【结论】 GWR模型能较有效地估算黑龙江省非干扰林龄,成功地降低了残差的空间自相关性。在估算林龄的过程中加入林火干扰因素,以获取更真实的林龄空间分布数据,可为黑龙江地区森林NPP、NEP以及森林碳储量、森林生物量等相关研究提供数据支持。     

Spatially explicit assessment of forest road suitability for timber extraction and hauling in Switzerland

Efficient forest management, and wood production in particular, requires a forest road network of appropriate density and bearing capacity. The road network affects the choice of a suitable extraction method and the length of the transport route from the forest, while the road standard defines the truck type that can be used.

We evaluate the forest road network’s economic suitability for harvesting operations in the entire Swiss forest, an area of about 13,000 km² covering a range of topographies, based on the Swiss National Forest Inventory’s (NFI) forest road dataset. This dataset is based on information from an interview survey with the local forest services and includes all forest roads in Switzerland capable of carrying trucks. Extraction options and hauling routes are analysed together; thus, the entire logging process is examined.

Model results include maps of the most suitable extraction method; extraction costs; hauling costs; and a suitability map based on a combination of the results. While the larger part of the Swiss forest is classified as “suitable” for economic harvesting operations, significant portions also fall into the “limited suitability” and “not suitable” categories. Our analysis provides an objective, country-wide, spatially explicit assessment of timber accessibility. The resulting suitability map helps identify areas where timber harvesting is economic using the current forest road network, and where it is not. The model results can be used in road network planning and management, for example, by comparing road-network re-design scenarios, and compared to the spatial distribution of available wood volume.

     

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 culti- vation 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 sens- ing 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 influ- ence 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.     

Land cover analysis in wildland-urban interfaces according to wildfire risk: A case study in the South of France

Each year, forest fires destroy about 500,000 ha of vegetation in Europe, predominantly in the Mediterranean region. Many large fires are linked to the land transformations that have taken place in the Mediterranean region in recent decades that have increased the risk of forest fires. On the one hand, agricultural fallows and orchards are slowly being colonized by vegetation, and on the other hand, the forest is not sufficiently used, both of which result in increased accumulation of fuel. In addition, urbanization combined with forest extension results in new spatial configurations called “wildland-urban interfaces” (WUI). WUI are commonly defined as “areas where urban areas meet and interact with rural lands, wildland vegetation and forests”. Spatial analyses were performed using a WUI typology based on two intertwined elements, the spatial organization of homes and the structure of fuel vegetation. The organization of the land cover in terms of representativeness, complexity or road density was evaluated for each type of WUI. Results showed that there were significant differences between the types of WUI in the study area. Three indicators (i) “fire ignition density”, derived from the distribution of fire ignition points, (ii) “wildfire density”, derived from the distribution of wildfire area and (iii) “burned area ratio”, derived from the proportion of the burned area to the total study area were then compared with each type of WUI. Assuming that the three indicators correspond to important aspects of fire risk, we showed that, at least in the south of France, WUI are at high risk of wildfire, and that of the different types of wildland-urban interfaces, isolated and scattered WUI were the most at risk. Their main land cover characteristics, i.e. low housing and road densities but a high density of country roads, and the availability of burnable vegetation such as forested stands and shrubland (garrigue) explain the high fire risk. Improving our knowledge of relationships between WUI environments and fire risk should increase the efficiency of wildfire prevention: to this end, suitable prevention actions and communication campaigns targeting the types of WUI at the highest risk are recommended.     

基于INFORM模型与GEE的根河火烧迹地冠层含水量反演研究

【目的】提出一种结合辐射传输模型与遥感云平台反演火烧迹地冠层含水量(Canopy water content,CWC)的新方法,弥补目前对火烧迹地恢复阶段植被含水量的监测,为定量监测植被水分与火灾预警提供理论参考。【方法】以内蒙古自治区根河市火烧迹地为研究对象,基于INFORM辐射传输模型,使用查找表的方法反演森林冠层含水量,并结合Google Earth Engine(GEE)大数据遥感平台与Mann-kendall模型分析了火烧迹地的冠层含水量时序性变化,最后绘制根河2018年8月森林冠层含水量分布图。【结果】1)基于样地的CWC反演精度较高(R2为0.79);2)大范围的归一化水分指数(Normalized difference water index, NDWI)和CWC呈指数关系(R2为0.77),但CWC比NDWI的饱和点更高;3)CWC可作为火烧迹地恢复的生态指标,获得了34 a的CWC时序性反演结果,表明火灾后CWC明显降低,并基于Mann-kendall模型得到各样地CWC和LAI的恢复速率。【结论】联合INFORM模型与GEE反演并监测火烧迹地冠层含水量,方法通用且高效。火烧迹地在恢复过程中面临再次发生火烧和虫害病害的风险,研究结果可为森林防火和森林病虫害监测提供技术支持,对该区域森林火灾与森林虫害的预警有一定意义。     

Historic and current fire regimes in the Great Xing’an Mountains,northeastern China: Implications for long-term forest management

Understanding both historic and current fire regimes is indispensable to sustainable forest landscape management. In this paper, we use a spatially explicit landscape simulation model, LANDIS, to simulate historic and current fire regimes in the Great Xing’an Mountains, in northeastern China. We analyzed fire frequency, fire size, fire intensity, and spatial pattern of burnt patches. Our simulated results show that fire frequency under the current fire scenario is lower than under the historic fire scenario; total area burnt is larger with lower fire intensity under the historic fire scenario, and smaller with higher fire intensity under the current fire scenario. We also found most areas were burned by high intensity fires under the current fire scenario, but by low to moderate fires under the historic fire scenario. Burnt patches exhibit a different pattern between the two simulation scenarios. Large patches burnt by high intensity class fires dominate the landscape under the current fire scenario, and under historic fire scenario, patches burnt by low to moderate fire intensity fires have relatively larger size than those burnt by high intensity fires. Based on these simulated results, we suggest that prescribed burning or coarse woody debris reduction should be incorporated into forest management plans in this region, especially on north-facing slopes. Tree planting may be a better management option on these severely burned areas whereas prescribed burning after small area selective cutting, retaining dispersed seed trees, may be a sound forest management alternative in areas except for the severely burned patches.     

Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China

A forest fire can be a real ecological disaster regardless of whether it is caused by natural forces or human activities, it is possible to map forest fire risk zones to minimize the frequency of fires, avert damage, etc. A method integrating remote sensing and GIS was developed and applied to forest fire risk zone mapping for Baihe forestry bureau in this paper. Satellite images were interpreted and classified to generate vegetation type layer and land use layers （roads, settlements and farmlands）. Topographic layers （slope, aspect and altitude） were derived from DEM. The thematic and topographic information was analyzed by using ARC/INFO GIS software. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the layers （vegetation type, slope, aspect, altitude and distance from r3ads, farmlands and settlements） according to their sensitivity to fire or their fire-inducing capability. Five categories of forest fire risk ranging from very high to very low were derived automatically. The mapping result of the study area was found to be in strong agreement with actual fire-affected sites.     

Analysis of the seasonal characteristics of forest fires in South Korea using the multivariate analysis approach

For efficient forest fire management, special precautions are required in dry and strong-wind seasons vulnerable to severe forest fires. To extract the seasonal characteristics of forest fires in South Korea, the statistics over the past 16 years, 1991 through 2005, were investigated. The daily records of the number of fire occurrences, the total area burned and the average burned area per occurrence were examined to identify the seasonal patterns of forest fires using cluster analysis and principal component analysis; the risk of daily fires was also assessed using the ordered logit model. As a result, the fire patterns were classified into five clusters and a general danger index for forest fires was derived from the first principal component, showing relatively large-scaled fire regimes in spring, and frequent small-scaled fire regimes in autumn and winter. In connection with the ordered logit model, the probability for the five ranks of forest fire risk was calculated and the threshold for high-risk fires was detected. As an implementation of the results above, the proper forest fire precautionary period in South Korea was estimated, and consequently October 21 through May 17 was recognized as a dry season at a high risk of forest fires. This period began 10 days earlier in autumn and extended into midwinter (late December and January) as opposed to the existing precautionary period, indicating the need of more cautious forest fire management earlier in autumn and continuing through midwinter.     

Assessing fire risk using Monte Carlo simulations of fire spread

Understanding the spatial pattern of fire is essential for Mediterranean vegetation management. Fire-risk maps are typically constructed at coarse resolutions using vegetation maps with limited capacity for prescribing prevention activities. This paper describes and evaluates a novel approach for fire risk assessment that may produce a decision support system for actual fire management at fine scales. FARSITE, a two-dimensional fire growth and behavior model was activated, using ArcView VBA code, to generate Monte Carlo simulations of fire spread. The study area was 300 km² of Mt. Carmel, Israel. FARSITE fuel models were adjusted for Mediterranean conditions. The simulation session consisted of 500 runs. For each simulation run, a calendar date, fire length, ignition location, climatic data and other parameters were selected randomly from known distributions of these parameters. Distance from road served as a proxy for the probability of ignition. The resulting 500 maps of fire distribution (the entire area burnt in a specific fire) were overlaid to produce a map of ‘hotspots’ and ‘cold spots’ of fire frequency. The results revealed a clear pattern of fires, with high frequency areas concentrated in the northwestern part. The spatial pattern of the fire frequency map bears partial resemblance to the fuel map, but seems to be affected by several other factors as well, including the location of urban areas, microclimate, topography and the distribution of ignition locations (which is affected by road pattern). These results demonstrate the complexities of fire behavior, showing a very clear pattern of risk level even at fine scales, where neighboring areas have different risk levels due to combinations of vegetation cover, topography, microclimate and other factors.     

中国森林火灾发生规律及预测模型研究

量化分析森林火灾发生规律能为预测和防治森林火灾提供科学依据。文中采用四参数Weibull分布描述了我国森林火灾发生次数和火场面积分布规律,运用Spearman相关系数分析承灾主体因子、灾害管理因子、孕灾环境因子与森林火灾发生次数、面积间关系,基于全国森林火灾数据分别建立灰色系统理论模型、BP人工神经网络模型和时间序列ARIMA模型,并采用Markov随机过程改进已建立模型。结果表明,我国森林火灾发生次数分布呈左偏正态分布,火场面积呈倒J型分布,火灾次数和火场面积分布模型拟合决定系数分别为0.63和0.66;承灾主体、孕灾环境和灾害管理对森林火灾次数和火场面积影响程度依次减小,人工林面积、累年年平均气温、年降雨量平均差值、年最低气温平均日数与森林火灾发生具有明显相关性,影响森林火灾的因子与森林火灾发生次数、火场面积间存在指数型关系;不同模型对森林火灾发生次数和火场面积拟合优度次序为BP模型、GM（1,1）-Markov模型、BP-Markov模型、GM（1,1）模型、ARIMA模型、ARIMA-Markov模型,采用Markov过程能显著改进GM（1,1）预测模型对火灾随机性的预测效果,可以更好地反映森林火灾发生规律。     

Post-fire analysis of pre-fire mapping of fire-risk: A recent case study from Mt. Carmel (Israel)

The recent devastating wildfire on Mt. Carmel provided a unique opportunity to evaluate a fire-risk map constructed for the region, published two years ago in this journal. This largest forest fire in the history of Israel, occurred during December 2010, covering 2180 ha, burning more than half-million trees and causing the loss of life of 45 people.A study of fire risk in this area was conducted between 2007 and 2009 utilizing a combination of Monte Carlo simulation of spatial spread of fire ignition with fire behavior model (FARSITE). The fire risk map produced in 2009 is assessed here with reference to the area burnt during December 2010. The results showed that most of burnt areas corresponded to high risk levels in the risk map. According to a null model, the five lower risk levels taken together would have corresponded to 50% of the burnt area, while in fact they were presented in only 5.6% of the area. In contrast, the three highest risk levels, for which the null model expectation would be a representation of 30%, were represented in 87% of the area. Comparing the fire risk map against the map of the real recent fire provided support to the general approach, and strengthened the confidence of our fire risk model.     

Herbaceous species diversity in relation to fire severity in Zagros oak forests,Iran

Zagros forests are mainly covered byQuercus brantii L. coppices and oak sprout clumps occupy the forest area like patches. We investigated post-fire herbaceous diversity in the first growing season after fire. For this purpose neighboring burned and unburned areas were selected with the same plant species and ecological conditions. The data were collected from areas subjected to different fire severities. Overall 6 treatments were considered with respect to fire severity and the mi-crosites of inside and outside of oak sprout clumps including： unburned inside and outside of sprout clumps （Ni and No）, inside of sprout clumps that burned with high fire severity （H）, inside of sprout clumps that burned with moderate fire severity （M）, outside of sprout clumps that burned with low fire severity （OH and OM）. Different herbaceous com-position was observed in the unburned inside and outside of oak sprout clumps. The species diversity and richness were increased in treatments burned with low and moderate fire severity. However, in treatment burned with high fire severity （H）, herbaceous cover was reduced, even-ness was increased, and richness and diversity were not significantly changed. We concluded that besides the microsites conditions in forest, fire severity is an inseparable part of the ecological effect of fire on her-baceous composition.     

林火碳排放研究进展

火是森林生态系统主要的干扰因子, 森林火灾的频繁发生不仅使森林生态系统遭到破坏, 同时也造成了含碳温室气体的大量释放。综述了火烧面积、森林可燃物以及燃烧效率等主要因子对森林火灾排放碳量估计的影响, 分析了这一领域未来研究发展趋势。大量研究表明:1)卫星遥感是估测大尺度上森林过火面积的主要手段, 随着高分辨率卫星的应用, 森林火灾面积的估计精度不断得到提高。目前的研究主要集中于大尺度上林火面积的估计和估算方法的改进。2)遥感数据是目前估计大尺度可燃物燃烧量的有效手段, 利用遥感数据的同时结合有效可燃物计算模型, 运用多元线性与非线性分析结合等方法提高对可燃物燃烧量的估计。3)燃烧效率是决定可燃物消耗量的主要因子, 也是估计森林火灾释放含碳气体量的关键。未来的研究是利用高分辨率的遥感数据, 结合复杂的可燃物计算模型, 更精确地估计林火碳排放。     

Evaluating the efficiency of the Dong model in determining fire vulnerability in Iran's Zagros forests

Recent fires in Iran's Zagros forests have inflicted heavy,extensive losses to the environment,forests,villages,and forest inhabitants,resulting in a huge financial loss to the country.With the increasing risk of fire and the resulting losses,it has become ever more necessary to design and develop efficient fire control and prediction procedures.The present study utilizes the Dong model to develop a map of areas vulnerable to fire in the Zarivar lake forests as a representative sample of Zagros forests.The model uses as its inputs some of the most significant factors(such as vegetation,physiographic features,and the human component) that affect the fire occurrence and spread.Having assigned weights to each factor based on the model,all maps were overlapped in the ArcMap and then the region was divided into five zones.The results showed that 74% of the region was located in three classes:highly vulnerable,vulnerable,and medially vulnerable.To validate the proposed zoning map it was compared with a map based on real data obtained from previous fires.The results showed that 81% of fire incidents were located in highly vulnerable,vulnerable and medially vulnerable zones.Furthermore,the findings indicated a medium to a high degree of fire vulnerability in Zarivar Lake forests.