Automated extraction of fire line parameters from multispectral infrared images

Remotely sensed infrared images are often used to assess wildland fire conditions. Separately, fire propagation models are in use to forecast future conditions. In the Dynamic Data-Driven Application System (DDDAS) concept, the fire propagation model will react to the image data, which should produce more accurate predictions of fire propagation. In this study we describe a series of image processing tools that can be used to extract fire propagation parameters from multispectral infrared images so that the parameters can be used to drive a fire propagation model built upon the DDDAS concept. The method is capable of automatically determining the fire perimeter, active fire line, and fire propagation direction. A multi-band image gradient calculation, the Normalized Difference Vegetation Index, and the Normalized Difference Burn Ratio along with several standard image processing techniques are used to identify and constrain the fire propagation parameters. These fire propagation parameters can potentially be used within the DDDAS modeling framework for model update and adjustment.     

森林场景可视化和林火模拟仿真技术研究综述

森林是生态环境系统的重要组成部分。随着气候变暖,恶劣气候气象条件造成全球森林火灾频繁发生,给国民经济和消防救援带来巨大挑战,森林火灾已成为全球主要的自然灾害。因此,森林场景可视化建模、3维场景仿真、林火模拟仿真、火场复现、预测和灾害评估成为林业虚拟仿真研究热点。本文对树木形态结构建模技术、森林场景大规模重建和实时渲染、森林场景可视化、林火模型和林火模拟仿真等前沿技术和算法进行综述。对相关的林木、植被的形态结构表达和真实感可视化建模方法进行归纳分类,并对不同可视化方法的算法优劣、复杂度、实时渲染效率和适用场景进行讨论。基于规则的林木建模方法和基于林分特征的真实场景重建方法对大规模森林场景重建技术进行分类,基于物理模型、经验模型和半经验模型对森林火灾的林火模型、单木林火、多木林火模拟和蔓延进行总结,对影响林火蔓延的不同环境气象因子（如地形地貌、湿度、可燃物等）和森林分布对林火发生、扩散和蔓延的影响进行分析,对不同算法的优劣进行对比、分析和讨论,对森林场景可视化和林火模拟仿真技术未来的发展方向、存在问题和挑战进行展望。本文为基于森林真实场景的森林火灾模拟仿真和数字孪生沉浸式互动模拟系统的构建提供了理论方法基础,该平台可以实现森林场景快速构建、不同火源林火模拟、火场蔓延模拟仿真以及不同气象影响条件的火场预测,可对森林火场救援指挥、火场灾害评估和火场复原提供可视化决策支持。     

Deriving forest fire ignition risk with biogeochemical process modelling

Climate impacts the growth of trees and also affects disturbance regimes such as wildfire frequency. The European Alps have warmed considerably over the past half-century, but incomplete records make it difficult to definitively link alpine wildfire to climate change. Complicating this is the influence of forest composition and fuel loading on fire ignition risk, which is not considered by purely meteorological risk indices. Biogeochemical forest growth models track several variables that may be used as proxies for fire ignition risk. This study assesses the usefulness of the ecophysiological model BIOME-BGC's ‘soil water’ and ‘labile litter carbon’ variables in predicting fire ignition. A brief application case examines historic fire occurrence trends over pre-defined regions of Austria from 1960 to 2008. Results show that summer fire ignition risk is largely a function of low soil moisture, while winter fire ignitions are linked to the mass of volatile litter and atmospheric dryness.     

Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread

Environmental conditions, such as fuel load and moisture levels, can influence the behaviour of wildfires. These factors are subject to natural small-scale variation which is usually spatially or temporally averaged for modelling fire propagation. The effect of including this variation in propagation models has not previously been fully examined or quantified. We investigate the effects of incorporating three types of variation on the shape and rate of propagation of a fire perimeter: variation in combustion conditions, wind direction and wind speed. We find that increasing the variation of combustion condition decreases the overall rate of propagation. An analytical model, based on the harmonic mean, is presented to explain this behaviour. Variation in wind direction is found to cause the development of rounded flanks due to cumulative chance of outward fluctuations at the sides of the perimeter. Our findings may be used to develop improved models for fire spread prediction.     

Discrete-event modelling of fire spreading

We deal here with the application of discrete-event System Specification (DEVS) formalism to implement a semi-physical fire spread model. Currently, models from physics finely representing forest fires are not efficient and still under development. If current softwares are devoted to the simulation of simple models of fire spread, nowadays there is no environment allowing us to model and simulate complex physical models of fire spread. Simulation models of such a type of models require being easily designed, modified and efficient in terms of execution time. DEVS formalism can be used to deal with these problems. This formalism enables the association of object-oriented hierarchical modelling with discrete-event techniques. Object-oriented hierarchical programming facilitates construction, maintenance and reusability of the simulation model. Discrete-events reduce the calculation domain to the active cells of the propagation domain (the heated ones).     

Temperature heterogeneity during travelling fire on experimental building

In order to follow modern trends in contemporary building architecture which is moving off the limits of current fire design models, assumption of homogeneous temperature conditions used for structural fire analysis needs to be validated. In this paper it is described, how temperature distribution in a medium-size fire compartment has been investigated experimentally by conducting fire test in two-storey experimental building in September 2011 in the Czech Republic. In the upper floor, a scenario of travelling fire was prepared. It has been observed that as flames were spreading across the compartment, considerable temperature gradients appeared. Numerical simulation of the travelling fire test conducted using FDS (Fire Dynamics Simulator) has been compared with simulation of compartment fire under uniform temperature conditions to highlight the potential impact of the gas temperature heterogeneity on structural behaviour. The temperature measurements from the fire test have been used for validation of the numerical simulation of travelling fire. The fire test has provided important data for design model of travelling fire and shown that its impact on structural behaviour is not in agreement with the assumption of homogenous temperature conditions.     

Skeletonization via the realization of the fire front's propagationand extinction in digital binary shapes

A sequential method of skeletonization for digital binary images is proposed. The method realizes in a discrete plane prairie-fire propagation model. The techniques of contour following is adopted to simulate the simultaneous fire spreading off of the grass perimeter. The algorithm contains two steps: (1) find and mark all of the contours of the input image during a conventional scan. Then, after the borders a `lighted', (2) repeatedly examine the borders and strip deletable edge points until no more can be removed. In this way only the successive contours, but not the whole image, will be processed. The second step is subdivided as follows: first, the contours representing the current fire fronts are traced, all the edge points are memorized, and the next fire fronts are marked. Second, the algorithm verifies the memorized edge points and those marked only once are removed. Although no neighborhood's test is needed during this stage of peeling, the connectedness of objects to thinning is conserved. Insignificant spurs can, optionally, be removed during thinning     

基于视频的改进的火焰目标分割方法

本文提出了一种改进的基于RGB与HSI颜色模型的火焰目标分割方法,能完整地提取出火焰目标。这种方法是在实时视频流中,采用对抽取出的两帧图像进行帧间差;然后根据RGB与HSI火焰颜色模型进行筛选,获取火焰目标边缘部分像素作为火焰种子;进行以火焰种子遍历八邻域区域生长的方式,提取出完整的火焰。相比以往的火焰分割方法,改进后的方法能更完整地对火焰目标实现分割,也更满足实时视频监控的要求。实验结果证实,提出的改进方法能完整地分割出火焰目标。     

隧道火灾疏散模型实时仿真算法的实现

由于隧道火灾的人员疏散难题,提出一种基于网格选择的隧道火灾人员疏散模型算法,设计了人员类型、奔跑速度、奔跑方向、人员所在环境等疏散属性参数,建立基于网格化离散场变量和坐标值的仿真模型。该算法克服了常用的元胞自动机算法计算量大,实时仿真比较困难的缺点。最后,利用Open Inventor进行了计算机仿真,并应用该仿真模型进行了分析,从逃生通道对疏散时间的影响及诱导标志设计对疏散时间的影响两方面验证了模型的有效性,并可直观地为安全疏散设计提供理论依据。     

基于元胞自动机的林火蔓延三维模拟仿真研究

为了在虚拟三维环境中模拟出森林火灾的发展蔓延状态,利用三维引擎进行仿真研究。说明了三维元胞的定义、状态、邻域和转换规则函数;通过求得林火蔓延公式的参数在在8个邻域方向上的分量,得到林火蔓延公式在相应方向上的分量公式。利用Unity3D三维引擎建立野外三维地形,通过不断调整其自带粒子系统的参数,建立适用于不同条件的火焰库和烟雾库,输入气象因素后即可实现林火在三维环境下的模拟蔓延。将野外实地点烧数据与模拟效果进行对比,可以看出模拟的效果与实地点烧相近,模拟效果符合要求。     

雾天条件下基于机器视觉的森林火灾监测

基于机器视觉的森林火灾监测已成为森林火灾监测的一个重要发展方向。烟雾是森林火灾监测的重要指标。然而,诸如云雾和类似烟雾的诸多干扰物降低了火灾识别精度,为此提出了一种结合去云雾和烟雾检测的基于机器视觉的森林火灾监测方法。首先,提取视频中若干帧图像作为样本图像,采用基于Haze-Line的去雾算法对样本图像进行去雾处理。然后,利用基于Horn-Schunck光流法的烟雾检测算法进行烟雾检测,并利用最大类间方差法去除相邻2帧图像间像素质量差异对烟雾检测的影响。最后,利用扩散性分析进行火灾判断。仿真实验及对比分析结果表明,本文方法能够检测出烟雾区域随时间逐渐增加的趋势,从而有效地进行雾天条件下的森林火灾监测,具有更高的准确性和鲁棒性。     

基于元胞自动机的普通超市火灾疏散模型的构建

通过分析已有的元胞自动机理论,结合人员疏散的特点,构建了考虑出口吸引力、火灾排斥力、摩擦力、排斥力和从众吸引力的普通超市火灾疏散模型。该模型充分考虑了多个因素对疏散过程的影响,对影响因素进行归一化处理,以综合影响因素建立的元胞转移强度作为行人移动规则。针对超市疏散人数、出口宽度及相隔距离、从众心理对疏散时间的影响进行了研究,并采用仿真疏散软件Pathfinder+FDS对模型进行验证,说明疏散模型具有一定可信性。研究表明行人疏散时间随人数呈线性正相关,人数存在临界值;出口宽度越宽或出口越多疏散时间相对越短,当达到出口阈值时对疏散时间影响不大;在陌生疏散环境或紧急情况下适当的从众行为会提高疏散效率。     

Numerical simulation of forest fire propagation based on modified two-dimensional model

A modified two-dimensional two-phase mathematical model of forest wildfires propagation is considered. The model is based on the averaging of three-dimensional equations of two-phase medium over the height of the forest fuel (FF) layer and it includes the (k?ε)-turbulence model with additional turbulence production and dissipation terms in the forest layer and the Eddy Break-up Model for the combustion rate in the gas phase. The developed model can be used to carry out numerical simulation of the forest fire-front propagation under the conditions of a heterogeneous FF distribution, the presence of obstacles to the fire propagation, and the wind effects. This model can be used for real-time computation of the fire propagation, for expert assessments of emergency situations, and for assessments of the damage caused by forest fires.     

新一代气象雷达回波探测在输电线路防山火中的应用

为有效弥补传统山火监测方法的不足,准确研判火场发生发展态势,将新一代气象雷达应用于山火监测之中,开辟了火灾监测领域的一个新天地,该气象雷达能对周边120公里范围内的地形环境进行扫描,基于多普勒原理技术对着火点进行判别与判定,能在火灾发生后的6分钟内迅速识别着火点经纬度坐标,同时开发出手机客户端APP软件,当接收到雷达系统传送来的着火点经纬度时,软件进行检索查询出着火点附近一定范围内的杆塔和护线员线路巡视人员能及时根据预警信息进行应对处理。同时,该雷达探测对闷烧型火灾的监测效果比其它方法要好,具有全天候监测、监测连续性好、发现早、预警早、定位更精准等特点,更能检测到其它监测系统不能预警的火灾。通过应用案例表明,在清明节、冬季等山火易发时节,极大的促进山火防治工作,有助于减少因山火造成的跳闸事故。     

Development of a virtual active fire product for Africa through a synthesis of geostationary and polar orbiting satellite data

We explore the ability to enhance landscape fire detection and characterization by constructing a ‘virtual’ fire product from a synthesis of geostationary and polar orbiting satellite data. Active fire pixels detected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) were spatially and temporally collated across Africa between February 2004 and January 2005. Coincident fire pixels detected by SEVIRI and MODIS were used to populate an empirical database of frequency density (f-D) distributions of fire radiative power (FRP). Frequency density distributions of FRP measured by SEVIRI at 5.0° grid cell resolution and 15-minute temporal resolution were then cross referenced in the database to a set of counterpart f-D distributions of FRP measured by MODIS. This procedure resulted in the first generation of a ‘virtual’ fire product that exhibits the full continental coverage and high temporal resolution of SEVIRI whilst quantifying fire pixel counts and FRP with accuracies approaching those of MODIS. Diurnal cycles extracted from the virtual fire product indicate that SEVIRI measures a greater proportion of the active fire pixels and FRP potentially detectable by MODIS during the day due to the increased prevalence and stronger radiant contribution of highly energetic fire pixels. On a daily basis (sample size n = 365) the peak magnitude in the diurnal cycle of the virtual FRP occurred within the same 15-minute timeslot as in the native SEVIRI fire product. Continental-scale ignition and extinction events, however, were detected on average 44 min earlier (standard deviation s.d. = 40 min) and 137 min later (s.d. = 92 min), respectively. It is anticipated that the methodology developed here can be used to cross-calibrate active fire products between a variety of different satellite platforms.     

基于改进Yolov5s的无人机火灾图像检测算法

为了解决现有火灾检测算法模型复杂,实时性差,难以部署在无人机平台的问题,通过改进Yolov5s算法对无人机火灾图像目标检测进行分析研究。利用搭载高清摄像头的无人机设备获取的火灾图像、公开数据集、互联网航拍视频自主建立无人机火灾图像数据集;采用轻量化模型Yolov5s为基础模型,MobileNetV3作为特征提取主干网络,降低模型参数和计算量,解决实时性差和模型部署的问题;模型颈部引入注意力模块CBAM,综合了通道和空间信息,加强网络对高层次语义信息的传递;修改模型检测头部结构,增强小目标检测能力。通过消融试验对比分析各个模块对模型的影响,与常见火灾模型进行对比分析,分析本文算法的优劣。算法在自建数据上的平均精度达到78.2%,模型大小为6.7M,单帧（640×640）图像处理时间为15.2ms。实验结果表明,本文算法模型简单、实时性好,为火灾检测算法部署在无人机平台奠定技术基础。     

Integrating fire spread patterns in fire modelling at landscape scale

Fire spread modelling in landscape fire succession models needs to improve to handle uncertainty under global change processes and the resulting impact on forest systems. Linking fire spread patterns to synoptic-scale weather situations are a promising approach to simulating fire spread without fine-grained weather data. Here we present MedSpread—a model that evaluates the weights of five landscape factors in fire spread performance. We readjusted the factor weights for convective, topography-driven and wind-driven fires (n = 123) and re-assessed each fire spread group's performance against seven other control simulations. Results show that for each of the three fire spread patterns, some landscape factors exert a higher influence on fire spread simulation than others. We also found strong evidence that separating fires by fire spread pattern improves model performances. This study shows a promising link between relevant fire weather information, fire spread and fire regime simulation under global change processes.     

Risk of fire emergency evacuation in complex construction sites: Integration of 4D-BIM,social force modeling,and fire quantitative risk assessment

Construction industry is claimed to be the fourth most dangerous sector by number of fatalities. In complex construction sites, emergency evacuation risk assessment is a challenging task due to their ever-changing nature. This study developed a model to analyze the risk of fire emergency occurrence, and risks which are associated with evacuation performance (in response to that emergency) through an integrated approach in complex construction sites. To analyze the evacuation scenarios more realistically, we utilized Social Force Model (SFM) simulation engine. Using SFM for simulating the evacuation of complex construction sites has not been adequately addressed in the literature. Microscopically simulating the evacuation scenarios for all workdays of the studied complex project required high computation efforts. To tackle this computation challenge, a parallel computing technique was coupled with SFM simulation engine. More importantly, in this paper site’s evacuation performance was evaluated multi-objectively considering evacuation time and evacuation safety. The construction site’s emergency scenarios were modeled by 4D-BIM, potential for trigger fire emergency was determined by a fire ignition Quantitative Risk Assessment (QRA) module, and site evacuation was simulated by SFM simulation engine. The proposed framework handled the collaboration of 4D-BIM, fire QRA module, and SFM engine. This research study benefited from data driven from a real mega project. The findings demonstrated that analyzing the risk of evacuation through an integrated approach by the proposed model could render more realistic results. The results also provided the project managers with a reliable safety decision-making support.     

Spectral indices and fire behavior simulation for fire risk assessment in savanna ecosystems

The lack of information on the vegetation status before the use of fire as a management tool in protected areas leads to drastic destruction of the natural vegetation and biodiversity. This paper describes the use of spectral indices and simulation of savanna burning to assess risk of intensive fire propagation in a National Park (Niokolo Koba, Senegal, West Africa). Spectral parameters corresponding to thematic information (wetness, brightness, and greenness) were retrieved using an orthogonal transformation, the Tasseled Cap approach on LANDSAT-ETM images. Wetness and brightness indices were normalized (σ=1 and mean=0) and then combined in a simple semi-empirical algorithm of fire risk levels discrimination. These two indices are proven to reflect qualitatively both fuel moisture and its distribution, which constitute the most foreseen determinants of fire propagation in savanna areas. The fire risk assessment algorithm (FIRA algorithm) was used to produce a fire risk map at the beginning of the management fire implement period. In parallel, a fire area simulator (FARSITE) developed by USDA was used with randomly spaced fire sources to determine areas which can be potentially burned in the study site. These simulated burned areas and the FIRA algorithm results were cross-compared to a real fire scars dated at the end of the same burning period and to land cover map. A great consistency was found between the different sources of information. More than 85% of fire prone areas identified by the FIRA algorithm or simulated by FARSITE were located in trees-shrub, woodland, and shrub savannas. These cover types included also 95% of real fire scars. Almost 88% and 84% of real fire scars were found in the risk zones determined by the FIRA algorithm and the simulated burned areas by FARSITE, respectively. The method used is simple and suited for an operational use for management fire implementation in savanna ecosystems.     

Enhancing multi-model forest fire spread prediction by exploiting multi-core parallelism

The Two-Stage forest fire spread prediction methodology was developed to enhance forest fire evolution forecast by tackling the uncertainty of some environmental conditions. However, there are parameters, such as wind, that present a variation along terrain and time. In such cases, it is necessary to couple forest fire propagation models and complementary models, such as meteorological forecast and wind field models. This multi-model approach improves the accuracy of the predictions by introducing an overhead in the execution time. In this paper, different multi-model approaches are discussed and the results show that the propagation prediction is improved. Exploiting multi-core architectures of current processors, we can reduce the overhead introduced by complementary models.