Retrieval and analysis of coal fire temperature in Wuda coalfield,Inner Mongolia,China

Coal fire burning around the world is an environmental catastrophe characterized by the emission of noxious gases, particulate matter, and condensation by-products. In this study, coal fire temperature is retrieved based on Landsat 5 TM images and Generalized Single-Channel Algorithm (GSCA), in Wuda coalfield, Inner Mongolia, China. Then coal fire zones are extracted by Jenks′ natural breaks and threshold methods based on temperature images. Changes of coal fire zones are analyzed from 1989 to 2008. The results are summarized as follows: 1) The coal fire temperature retrieval method based on Landsat 5 TM and the GSCA model is effective and feasible, because the temperature error is relatively small (from –2.9℃ to +2.6℃) between the measured temperature and the retrieved temperature. 2) The accuracy is relatively high to extract coal fire zones through the Jenks′ natural breaks and threshold methods, because 83.56% of surveyed area is located in the coal fire zones extracted in 2005. 3) The coal fire area increased 9.81 × 10 5 m 2 from 1989 to 2005, and the annual growth is about 6.1 × 10 4 m 2 , with an annual increasing rate of 2.48%. The area of coal fire decreased by 8.1 × 10 5 m 2 from 2005 to 2008.     

Vegetation recovery after fire in mountain grasslands of Argentina

Fire is a natural disturbance occurring every few years in many grasslands ecosystems. However, since European colonization, fire has been highly reduced or even suppressed in Argentinean grasslands, fostering ignitable material accumulation. This has led to occasional catastrophic controldemanding fire events, extended for larger areas. The aims of this work are to study vegetation recovery and change after a non-natural fire event in mountain grasslands. The study area is located in the Ventania mountain system, mid-eastern Argentina. We studied vegetation recovery after fire(January 2014) in two different communities: grass-steppes(grasslands) and shrub-steppes(open low shrublands). We measured vegetation cover, species richness and bare ground percentage in burned and unburned areas 1, 4, 8, 11 and 23 months after fire. Vegetation surveys were also performed at the end of the growing season(December) 11 and 23 months after fire. Data were analyzed using regression analysis, ANOVA and multivariate analysis(NMS, PERMANOVA). Both communities increased their vegetation cover at the same rate, without differences between burned and unburned areas after two years. Species richness was higher in shrublands and their recovery was alsofaster than in grasslands. Considering functional composition, besides transient changes during the first year after fire, there were no differences in abundance of different functional vegetation groups two years after fire. At the same time, shrublands showed no differences in species composition, while grasslands had a different species composition in burned and unburned plots. Also, burned grassland showed a higher species richness than unburned grassland. Data shown mountain vegetation in Pampas grassland is adapted to fire, recovering cover and richness rapidly after fire and thus reducing soil erosion risks. Vegetation in mountain Pampas seems to be well adapted to fire, but in grasslands species composition has changed due to fire. Nonetheless, these changes seem to be not permanent since prefire species are still present in the area.     

Study on forest fire danger model with remote sensing based on GIS

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RS AND GIS-BASED FOREST FIRE RISK ZONE MAPPING IN DA HINGGAN MOUNTAINS

1INTRODUCTIONForests are one of the major natural resources that per-form important environmental and recreational func-tions (COSTANZA and GROOT, 1997). It is well known that forests can absorb atmospheric carbon, maintain a certain degree of humidity in atmosphere, regulate rainfall, moderate temperature, and restrain soil erosion, etc. (AURELIA, 2003). So, the health of a forest in any given area is a very important indicator of the ecological conditions. But fire is the great…     

Estimation of non-CO2 GHGs emissions by analyzing burn severity in the Samcheok fire, South Korea

This study was performed to estimate the emission of non-CO 2 greenhouse gases(GHGs) from biomass burning at a large fire area.The extended methodology adopted the IPCC Guidelines(2003) equation for use on data from the Samcheok forest fire gathered using 30 m resolution Landsat TM satellite imagery,digital forest type maps,and growing stock information per hectare by forest type in 1999.Normalized burn ratio(NBR) technique was employed to analyze the area and severity of the Samcheok forest fire that occurred in 2000.The differences between NBR from pre-and post-fire datasets are examined to determine the extent and degree of change detected from burning.The results of burn severity analysis by dNBR of the Samcheok forest fire area revealed that a total of 16,200 ha of forest were burned.The proportion of the area characterized by a ’Low’ burn severity(dNBR below 152) was 35%,with ’Moderate’(dNBR 153-190) and ’High’(dNBR 191-255) areas were at 33% and 32%,respectively.The combustion efficiency for burn severity was calculated as 0.43 for crown fire where burn severity was ’High’,as 0.40 for ’Moderate’ severity,and 0.15 for ’Low’ severity surface fire.The emission factors for estimating non-CO 2 GHGs were separately applied to CO 130,CH 4 9,NO x 0.7 and N 2 O 0.11.Non-CO 2 GHGs emissions from biomass burning in the Samcheok forest fire area were estimated to be CO 44.100,CH 4 3.053,NO x 0.238 and N 2 O 0.038 Gg.     

A MODIS time series data based algorithm for mapping forest fire burned area

Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and climate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter (MODIS) time series data in Heilongjiang Province, China. The algorithm is divided into two steps: Firstly, the ‘core’ pixels were extracted to represent the most possible burned pixels based on the comparison of the temporal change of Global Environmental Monitoring Index (GEMI), Burned Area Index (BAI) and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ‘core’ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the highest accuracy of 96.61%.     

Driving factors for forest fire occurrence in Durango State of Mexico: A geospatial perspective

Forest fire is one of the major causes of forest loss and therefore one of the main constraints for sustainable forest management worldwide. Identifying the driving factors and understanding the contribution of each factor are essential for the management of forest fire occurrence. The objective of this study is to identify variables that are spatially related to the occurrence and incidence of the forest fire in the State of Durango, Mexico. For this purpose, data from forest fire records for a five-year period were analyzed. The spatial correlations between forest fire occurrence and intensity of land use, susceptibility of vegetation, temperature, precipitation and slope were tested by Geographically Weighted Regression (GWR) method, under an Ordinary Least Square estimator. Results show that the spatial pattern of the forest fire in the study area is closely correlated with the intensity of land use, and land use change is one of the main explanatory variables. In addition, vegetation type and precipitation are also the main driving factors. The fitting model indicates obvious link between the variables. Forest fire was found to be the consequence of a particular combination of the environmental factors, and when these factors coexist with human activities, there is high probability of forest fire occurrence. Mandatory regulation of human activities is a key strategy for forest fire prevention.     

A time-dependent stochastic grassland fire ignition probability model for Hulun Buir Grassland of China

Grassland fire is one of the most important disturbance factors in the natural ecosystems.This paper focuses on the spatial distribution of long-term grassland fire patterns in the Hulun Buir Grassland located in the northeast of Inner Mongolia Autonomous Region in China.The density or ratio of ignition can reflect the relationship between grassland fire and different ignition factors.Based on the relationship between the density or ratio of ignition in different range of each ignition factor and grassland fire events,an ignition probability model was developed by using binary logistic regression function and its overall accuracy averaged up to 81.7%.Meanwhile it was found that daily relative humidity,daily temperature,elevation,vegetation type,distance to county-level road,distance to town are more important determinants of spatial distribution of fire ignitions.Using Monte Carlo method,we developed a time-dependent stochastic ignition probability model based on the distribution of inter-annual daily relative humidity and daily temperature.Through this model,it is possible to estimate the spatial patterns of ignition probability for grassland fire,which will be helpful to the quantitative evaluation of grassland fire risk and its management in the future.     

Tradeoff between the number of firefighting resources and the level of fire ignition prevention efforts in the Republic of Korea

This study explores the tradeoff relationship between the number of initial attack firefighting resources and the level of fire ignition prevention efforts mitigating the probability of human-made fires in the Republic of Korea, where most fires are caused by human activities. To examine this tradeoff relationship, we develop a hybrid model that combines a robust optimization model with a stochastic simulation model. The robust optimization minimizes the expected number of fires not receiving a pre-defined response, such as the number of firefighting resources that must arrive at the fire within half an hour, subject to budget constraints and uncertainty about the daily number and location of fires. The simulation model produces a set of fire scenarios in which a combination of number, location, ignition time, and intensity of fires occur. Results show that fire ignition prevention is as cost-effective as initial attack firefighting resources given the current budget in the Republic of Korea for reducing the expected number of fires not covered by the predefined response. The mixed policy of fire suppression and fire prevention may produce some gains in efficiency relative to the dominant policy of strong fire suppression strategies.     

Simulating impact of larch caterpillar (<Emphasis Type="Italic">Dendrolimus superans</Emphasis>) on fire regime and forest landscape in Da Hinggan Mountains,Northeast China

Larch caterpillar (Dendrolimus superans) is very common in the Da Hinggan Mountains, Northeast China, affecting fire regime and forest ecosystem change at large spatio-temporal scales. In this study, we used a spatially explicit landscape model, LANDIS, to simulate the changes of fire regime and forest landscape under four larch caterpillar disturbance intensity levels scenarios in Huzhong forest area, northern of Da Hinggan Mountains. The results indicate that larch caterpillar disturbances would decrease ...     

Crown fuel characteristics and carbon emission from Japanese red pine stands burned by crown fire in Mt. Palgong, South Korea

Carbon emissions from forest fires are considered an important factor of ecosystem carbon balance and global climate change. Carbon emissions from Japanese red pine stands (Pinus densiflora S. et Z.) burned by crown fire were estimated at Mt. Palgong in Daegu Metropolitan City, and crown fuel characteristics, including crown bulk density, crown base height, and fuel moisture content of Japanese red pine, were analyzed. Total biomass combusted was calculated by subtracting the biomass of burned stands from that of unburned stands exhibiting similar stand structures and site environments. Ten trees in the unburned area and five trees in the burned area were cut by using direct harvesting techniques to estimate crown layer biomass. All biomass sampled was oven-dried and weighed. The dry weight ratios of stems, branches, and needles were 70%, 21%, and 9%, respectively. The available fuel load susceptible to combustion during the crown fire spread was equivalent to 55% of the crown layer biomass. The crown bulk density was 0.24 kg/ m 3 on average. The estimated amount of CO 2 was 23,454 kg CO 2 /ha for the crown layer. These results will be useful for calculating the amount of CO 2 emitted from forest fires and for developing a forest carbon model in P. densiflora forests.     

Exploring seven hundred years of transhumance,climate dynamic,fire and human activity through a historical mountain pass in central Spain

A high-altitude peat sequence from the heart of the Spanish Central System (Gredos range) was analysed through a multi-proxy approach to determine the sensitivity of high-mountain habitats to climate, fire and land use changes during the last seven hundred years, providing valuable insight into our understanding of the vegetation history and environmental changes in a mountain pass close to a traditional route of transhumance. The pollen data indicate that the vegetation was dominated by shrublands and grasslands with scattered pines in high-mountain areas, while in the valleys cereals, chestnut and olive trees were cultivated. Strong declines of high-mountain pines percentages are recorded at 1540, 1675, 1765, 1835 and 1925 cal AD, which may be related to increasing grazing activities and/or the occurrence of anthropogenic fires. The practice of mountain summer farming and transhumance deeply changed and redesigned the landscape of the high altitudes in central Spain (Gredos range) since the Middle Ages, although its dynamics was influenced in some way by climate variability of the past seven centuries.     

Forward simulation of coal fire model by transient electromagnetic method with electrical source

Uncontrolled coal fires are natural disasters that may cause mineral loss and environmental damage. The traditional loop source transient electromagnetic method can effectively detect the low-resistivity region of coal fires, but its detection efficiency is not so good for high-resistivity regions. In view of this limitation, a technique based on electrical source transient electromagnetics is proposed in this paper to detect high-resistivity regions in the spontaneous combustion process of coal. Considering the complex geometry of the coal fire area, an unstructured tetrahedral grid is used in this study to realize the spatial discretization of the model, and solve the electromagnetic field based on a vector finite element algorithm. Numerical analysis is used to investigate methods for detecting coal fires and the characteristics of effective anomalies are further examined to provide guidance for practical detection.     

火险等级评估方法与应用分析

森林草原火灾不仅严重危害到社会和人民财产安全,还危及到我国生态安全。火险等级评估作为科学防火的一个重要方法,可以为森林草原防火提供科学有效的决策支持信息。本文在已有相关研究总结的基础之上,针对火险等级评估方法和应用进行了如下分析。并定义阐述了火险等级评估研究中的相关概念;对火灾危险评估已使用过的指标进行了总结,简要分析了各类评估指标对火灾的影响;总结和分析了已有的火险等级评估方法;并介绍了针对我国北方四省森林草原生态环境特点简要分析了遥感反演指标的火险等级评估应用。     

Drought and Spatiotemporal Variability of Forest Fires Across Mexico

Understanding the spatiotemporal links between drought and forest fire occurrence is crucial for improving decision-making in fire management under current and future climatic conditions. We quantified forest fire activity in Mexico using georeferenced fire records for the period of 2005–2015 and examined its spatial and temporal relationships with a multiscalar drought index, the Standardized Precipitation-Evapotranspiration Index(SPEI). A total of 47975 fire counts were recorded in the 11-year long study period, with the peak in fire frequency occurring in 2011. We identified four fire clusters, i.e., regions where there is a high density of fire records in Mexico using the Getis-Ord G spatial statistic. Then, we examined fire frequency data in the clustered regions and assessed how fire activity related to the SPEI for the entire study period and also for the year 2011. Associations between the SPEI and fire frequency varied across Mexico and fire-SPEI relationships also varied across the months of major fire occurrence and related SPEI temporal scales. In particular, in the two fire clusters located in northern Mexico(Chihuahua, northern Baja California), drier conditions over the previous 5 months triggered fire occurrence. In contrast, we did not observe a significant relationship between drought severity and fire frequency in the central Mexico cluster, which exhibited the highest fire frequency. We also found moderate fire-drought associations in the cluster situated in the tropical southern Chiapas where agriculture activities are the main causes of forest fire occurrence. These results are useful for improving our understanding of the spatiotemporal patterns of fire occurrence as related to drought severity in megadiverse countries hosting many forest types as Mexico.     

实时路况支持下的南京市消防救援覆盖率时空模式分析

快速城镇化导致我国城市消防应急服务基础设施与城市发展不同步的问题日益凸显,城市消防救援覆盖率评估是提升消防服务质量与优化消防资源配置的重要手段。本文提出一种基于实时路况的城市消防救援覆盖率评估模型,通过考虑消防站管辖区域的空间限制,在2020年9月连续三周时间内利用高德地图API获取消防站到达历史火灾事件的实时出行救援时间,对南京市消防救援覆盖率的时空模式进行分析与挖掘。结果显示：① 南京城市火灾密集区域（简称火灾密集区）消防站的平均出行救援时间约10 min,非火灾密集区约16 min,均比国家规定的5 min到达时间标准明显要长,导致南京市消防站在5 min到达标准下的覆盖率仅为8.2%;② 由于南京火灾密集区消防站的平均行车救援距离仅为非火灾密集区的37%,导致火灾密集区火灾事件等待救援时间明显低于非火灾密集区,尤其火灾密集区西南部、东北部及部分消防站周边火灾事件等待救援时间相对较短,但南京全区火灾事件等待救援时间在5 min以内的比例不足7%,且等待救援时间在5~10 min之间的短距离火灾事件受早晚交通出行高峰期交通拥堵影响最大;③ 南京市消防站救援覆盖率受早晚交通出行高峰影响呈现早晚交通出行高峰期明显低于其他时段的“W”形变化模式,火灾密集区消防站在5 min到达标准下的救援覆盖率从非交通出行高峰期的11.5%降低到交通出行高峰期的8.4%,而非火灾密集区从6.1%降低到5%,火灾密集区东南部石门坎与东山交界区域和北部汉中门与迈皋桥周边区域早晚交通出行高峰时段等待救援时间超过15 min的火灾事件比非交通出行高峰时段明显增多;④ 在5 min到达标准下,南京市消防站救援覆盖率“W”形模式波动最小,10 min到达标准下的平均覆盖率为43.5%且波动最明显,15 min到达标准下的平均覆盖率达到75%。最后根据分析结果给出了南京市消防未来建设发展意见。     

天山西部林区护林防火信息系统构建

天山西部林区护林防火信息系统是综合运用空间信息技术、数据库技术及森林防火专业技术,依托地理基础信息、森林资源信息及护林防火专题信息,在Arc GIS Engine开发平台上,通过VB.NET可视化开发语言的二次开发,构建的专业应用系统。该系统的框架包括数据库及林火预测预报、火灾指挥扑救、灾后损失评估、森林资源管理等子系统,可实现火点智能定位、火场信息查询显示、辅助决策指挥等具体功能。为林区护林防火部门进行宏观管理、分析决策提供多源、及时、科学的空间信息服务,旨在改善林区防灾、减灾及森林安全工作的被动局面,提升林火管理的科学化、信息化水平。     

一种森林火险预报方法研究——以山东省为例

可燃物含水率、空气温度、相对湿度、人口密度是林火预报中重要因子,将这些因子构建综合火险指数模型,该模型包括三个部分:植被火险敏感指数(FSI)、归一化天气火险指数(NWDI)、人口火险概率指数(PDI)。详细介绍模型各部分的计算方法,将该模型与遥感、GIS相结合,开发综合森林火险指数预报系统,制作2010年10月～2011年9月山东省综合火险指数图,并与实际火灾发生情况进行对比,结果表明,该模型能够取得较好的预测结果。     

结合遥感和气象数据的森林火险监测研究——以马来西亚半岛为例

结合遥感和气象数据,基于可燃物引燃能量的物理概念,利用火灾敏感性指数(FSI)进行森林火险监测和评估。计算FSI只需要两个参数,即可燃物的温度和湿度,两者均可以从遥感和气象数据获得。利用遥感数据进行可燃物类型制图,并根据可燃物易燃性对FSI的值进行调整计算。利用MODIS探测的火点数据对马来西亚半岛火灾前9天的FSI进行了比较分析,发现随着火灾发生日期的接近,FSI的值逐渐升高,这个趋势在火灾发生的前4天中表现的尤其明显。结果表明,FSI将遥感数据和气象数据两者紧密结合在一起,能够很好地对森林火险进行监测和预警,是一种性能优越的火险评价指数。FSI可用于计算可燃物的点燃概率以及在不同的生态系统中进行火险的比较,并且因其灵活性和可扩展性,有利于不同类型火险模型的集成和发展。     

欧亚北方森林MODIS 14数据的林火变化分析——以俄罗斯欧洲地区为例

人为或自然因素造成的森林火灾常导致森林覆盖和结构的变化,对森林碳循环产生重大影响。MODIS热异常-火灾产品(MOD14)包含地表火灾位置、可信度、火点辐射能量及其他属性信息,可用于火灾频率、等级及其变化的监测。本研究以俄罗斯欧洲地区的北方森林为研究对象,采用2005-2010年每日MODIS14数据和GIS空间分析方法,对研究区过火像元进行判别提取,分析该地区林火时空变化规律,并探讨驱动因素。结果显示,俄罗斯欧洲地区森林火灾主要分布在中南部。近年来,火灾数量呈上升趋势,2010年的火灾覆盖范围是2005年的1.5倍;年内火灾发生情况随时间波动,火险期为每年的4-10月;极端干旱天气造成的的特大型火灾事件在本研究结果中得以反映。