scholarly journals Georeferencing Oblique Aerial Wildfire Photographs: An Untapped Source of Fire Behaviour Data

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 81
Author(s):  
Henry Hart ◽  
Daniel D. B. Perrakis ◽  
Stephen W. Taylor ◽  
Christopher Bone ◽  
Claudio Bozzini
Keyword(s):  
Fire Behavior ◽  
Fire Spread ◽  
Behavior Prediction ◽  
Empirical Relationships ◽  
Rate Of Spread ◽  
Front Position ◽  
Fire Front ◽  
Initial Work ◽  
The Mean ◽  
Behaviour Data

In this study, we investigate a novel application of the photogrammetric monoplotting technique for assessing wildfires. We demonstrate the use of the software program WSL Monoplotting Tool (MPT) to georeference operational oblique aerial wildfire photographs taken during airtanker response in the early stages of fire growth. We located the position of the fire front in georeferenced pairs of photos from five fires taken 31–118 min apart, and calculated the head fire spread distance and head fire rate of spread (HROS). Our example photos were taken 0.7 to 4.7 km from fire fronts, with camera angles of incidence from −19 to −50° to image centre. Using high quality images with detailed landscape features, it is possible to identify fire front positions with high precision; in our example data, the mean 3D error was 0.533 m and the maximum 3D error for individual fire runs was less than 3 m. This resulted in a maximum HROS error due to monoplotting of only ~0.5%. We then compared HROS estimates with predictions from the Canadian Fire Behavior Prediction System, with differences mainly attributed to model error or uncertainty in weather and fuel inputs. This method can be used to obtain observations to validate fire spread models or create new empirical relationships where databases of such wildfire photos exist. Our initial work suggests that monophotogrammetry can provide reproducible estimates of fire front position, spread distance and rate of spread with high accuracy, and could potentially be used to characterize other fire features such as flame and smoke plume dimensions and spotting.

Testing the Effect of Fuel Consumption on Fire Spread Rate

1995 ◽  
Vol 5 (3) ◽  
pp. 143 ◽  
Author(s):  
RS McAlpine
Keyword(s):  
Fuel Consumption ◽  
Fire Behavior ◽  
Fire Spread ◽  
Data Sets ◽  
Behavior Prediction ◽  
Spread Rate ◽  
Data Set ◽  
Weak Relationship ◽  
Rate Of Spread ◽  
Fire Front

It has been theorized that the amount of fuel involved in a fire front can influence the rate of spread of the fire. Three data sets are examined in an attempt to prove this relationship. The first, a Canadian Forest Service database of over 400 experimental, wild, and prescribed fires showed a weak relationship in some fuel complexes. The second, a series of field experimental fires conducted to isolate the relationship, showed a small effect. The final data set, from a series of 47 small plots (3m x 3m) burned with a variety of fuel loadings, also show a weak relationship. While a relationship was shown to exist, it is debatable whether it should be included in a fire behavior prediction system. Inherent errors associated with predicting fuel consumption can be compounded, causing additional, more critical, errors with the derived fire spread rate.

Fine-Scale Fire Spread in Pine Straw

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 69
Author(s):  
Daryn Sagel ◽  
Kevin Speer ◽  
Scott Pokswinski ◽  
Bryan Quaife
Keyword(s):  
Fire Spread ◽  
Small Scale ◽  
Natural Setting ◽  
Fine Scale ◽  
Prescribed Burn ◽  
Fire Dynamics ◽  
Rate Of Spread ◽  
Scale Models ◽  
Fire Front ◽  
Visible Images

Most wildland and prescribed fire spread occurs through ground fuels, and the rate of spread (RoS) in such environments is often summarized with empirical models that assume uniform environmental conditions and produce a unique RoS. On the other hand, representing the effects of local, small-scale variations of fuel and wind experienced in the field is challenging and, for landscape-scale models, impractical. Moreover, the level of uncertainty associated with characterizing RoS and flame dynamics in the presence of turbulent flow demonstrates the need for further understanding of fire dynamics at small scales in realistic settings. This work describes adapted computer vision techniques used to form fine-scale measurements of the spatially and temporally varying RoS in a natural setting. These algorithms are applied to infrared and visible images of a small-scale prescribed burn of a quasi-homogeneous pine needle bed under stationary wind conditions. A large number of distinct fire front displacements are then used statistically to analyze the fire spread. We find that the fine-scale forward RoS is characterized by an exponential distribution, suggesting a model for fire spread as a random process at this scale.

Laboratory fire spread analysis using visual and infrared images

2006 ◽  
Vol 15 (2) ◽  
pp. 179 ◽  
Author(s):  
J. Ramiro Martínez-de Dios ◽  
Jorge C. André ◽  
João C. Gonçalves ◽  
Begoña Ch. Arrue ◽  
Aníbal Ollero ◽  
...  
Keyword(s):  
Graphical Model ◽  
Fire Spread ◽  
Rate Of Spread ◽  
Virtual View ◽  
Fire Front ◽  
Computer Based ◽  
Front Shape ◽  
Processing Techniques ◽  
Spread Analysis ◽  
Base Width

This paper presents an experimental method using computer-based image processing techniques of visual and infrared movies of a propagating fire front, taken from one or more cameras, to supply the time evolutions of the fire front shape and position, flame inclination angle, height, and base width. As secondary outputs, it also provides the fire front rate of spread and a 3D graphical model of the fire front that can be rendered from any virtual view. The method is automatic and non-intrusive, has space–time resolution close to continuum and can be run in real-time or deferred modes. It is demonstrated in simple laboratory experiments in beds of pine needles set upon an inclinable burn table, with point and linear ignitions, but can be extended to open field situations.

The FireFlux II experiment: a model-guided field experiment to improve understanding of fire–atmosphere interactions and fire spread

2019 ◽  
Vol 28 (4) ◽  
pp. 308 ◽  
Author(s):  
Craig B. Clements ◽  
Adam K. Kochanski ◽  
Daisuke Seto ◽  
Braniff Davis ◽  
Christopher Camacho ◽  
...  
Keyword(s):  
Fire Spread ◽  
Model Systems ◽  
Large Set ◽  
Tall Grass ◽  
Combustion Gases ◽  
Tall Grass Prairie ◽  
Fire Front ◽  
Air Chemistry ◽  
Atmosphere Model ◽  
Behaviour Data

The FireFlux II experiment was conducted in a tall grass prairie located in south-east Texas on 30 January 2013 under a regional burn ban and high fire danger conditions. The goal of the experiment was to better understand micrometeorological aspects of fire spread. The experimental design was guided by the use of a coupled fire–atmosphere model that predicted the fire spread in advance. Preliminary results show that after ignition, a surface pressure perturbation formed and strengthened as the fire front and plume developed, causing an increase in wind velocity at the fire front. The fire-induced winds advected hot combustion gases forward and downwind of the fire front that resulted in acceleration of air through the flame front. Overall, the experiment collected a large set of micrometeorological, air chemistry and fire behaviour data that may provide a comprehensive dataset for evaluating and testing coupled fire–atmosphere model systems.

scholarly journals Meteorological Conditions Conducive to the Rapid Spread of the Deadly Wildfire in Eastern Attica, Greece

2019 ◽  
Vol 100 (11) ◽  
pp. 2137-2145 ◽  
Author(s):  
K. Lagouvardos ◽  
V. Kotroni ◽  
T. M. Giannaros ◽  
S. Dafis
Keyword(s):  
Fire Behavior ◽  
Fire Spread ◽  
High Rate ◽  
Contributing Factors ◽  
Suburban Areas ◽  
Rate Of Spread ◽  
Rapid Spread ◽  
Westerly Flow ◽  
Downslope Flow ◽  
Extreme Fire

AbstractOn 23 July 2018, Attica, Greece, was impacted by a major wildfire that took place in a wildland–urban interface area and exhibited extreme fire behavior, characterized by a very high rate of spread. One-hundred civilian fatalities were registered, establishing this wildfire as the second-deadliest weather-related natural disaster in Greece, following the heat wave of July 1987. On the day of the deadly wildfire, a very strong westerly flow was blowing for more than 10 h over Attica. Wind gusts up to 30–34 m s−1 occurred over the mountainous areas of Attica, with 20–25 m s−1 in the city of Athens and surrounding suburban areas. This strong westerly flow interacted with the local topography and acted as downslope flow over the eastern part of Attica, with temperatures rising up to 39°C and relative humidity dropping to 19% prior to the onset of the wildfire. These weather elements are widely acknowledged as the major contributing factors to extreme fire behavior. WRF-SFIRE correctly predicted the spatiotemporal distribution of the fire spread and demonstrated its utility for fire spread warning purposes.

scholarly journals Improvement of fire danger rating and vegetation fire behaviour prediction on protected areas

2019 ◽  
Vol 16 ◽  
pp. 00040
Author(s):  
Aleksandra Volokitina ◽  
Dina Nazimova ◽  
Tatiana Sofronova ◽  
Mikhail Korets
Keyword(s):  
Protected Areas ◽  
Biological Diversity ◽  
Fire Behavior ◽  
Fire Spread ◽  
Fire Effects ◽  
Nature Reserves ◽  
Fire Danger ◽  
Behavior Prediction ◽  
Forest Fire Danger ◽  
Economic Use

Protected areas (PAs) are established to conserve biological diversity, to maintain nature complexes and objects in their natural condition. Strict nature reserves prevail in Russia by their total area. The whole nature complex is forever extracted from economic use in nature reserves. Here it is prohibited to pursue any activity which might disturb or damage the nature complexes. Even under the existing strict protection from anthropogenic ignition sources, vegetation fires do occur on their territory. Besides, lightnings − these natural ignition sources − are impossible to exclude. Since large destructive fires are impermissible in nature reserves, the later especially need vegetation fire behavior prediction for fire management. Fire behavior prediction includes fire spread rate, development (from surface fire into crown or ground one) and fire effects. All this is necessary for taking optimal decisions on how to control each occurring fire and how to suppress it. The Sukachev Institute of Forest SB RAS has developed a method to improve forest fire danger rating and a technique of vegetation fire behavior prediction using vegetation fuel maps (VF maps).

The importance of fire - atmosphere coupling and boundary-layer turbulence to wildfire spread

2009 ◽  
Vol 18 (1) ◽  
pp. 50 ◽  
Author(s):  
Ruiyu Sun ◽  
Steven K. Krueger ◽  
Mary Ann Jenkins ◽  
Michael A. Zulauf ◽  
Joseph J. Charney
Keyword(s):  
Boundary Layer ◽  
Transient Behavior ◽  
Fire Spread ◽  
Behavior Prediction ◽  
Ambient Flow ◽  
Boundary Layer Turbulence ◽  
Rate Of Spread ◽  
Two Factors ◽  
Wildfire Spread ◽  
Induced Flow

The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire’s environment. The changes in flow are dominated by two factors. The first is the interaction or ‘coupling’ between the fire and the fire-induced flow. The second is the interaction or ‘coupling’ between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire–atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire–atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts.

Modelling logic and the Canadian Forest Fire Behavior Prediction System

1998 ◽  
Vol 74 (1) ◽  
pp. 50-52 ◽  
Author(s):  
C. E. Van Wagner
Keyword(s):  
Forest Fire ◽  
Fire Behavior ◽  
Fire Spread ◽  
Fire Research ◽  
Fire Intensity ◽  
Prediction System ◽  
Behavior Prediction ◽  
Crown Fire ◽  
Fire Modelling ◽  
Semi Empirical

This article outlines the flexible semi-empirical philosophy used throughout six decades of fire research by the Canadian Forest Service, culminating in the development of the Forest Fire Behavior Prediction System. It then describes the principles involved when spread rate and fuel consumption are estimated separately to yield fire intensity, and the anomaly that has resulted from the omission of a foliar-moisture effect on crown-fire spread. Judged on its results so far, this Canadian approach has held its own against any other, and holds full promise for the future as well. Key words: forest fire behavior, Canadian FBP System, fire modelling, crown-fire theory, fire research philosophy

Examining fire behavior in mesquite - acacia shrublands

2005 ◽  
Vol 14 (2) ◽  
pp. 131 ◽  
Author(s):  
Tamara J. Streeks ◽  
M. Keith Owens ◽  
Steve G. Whisenant
Keyword(s):  
Flame Temperature ◽  
Fire Behavior ◽  
Fire Spread ◽  
Flame Length ◽  
South Texas ◽  
Fire Intensity ◽  
Rate Of Spread ◽  
Vegetation Shift ◽  
Naturally Occurring ◽  
Behavior Systems

The vegetation of South Texas has changed from mesquite savanna to mixed mesquite–acacia (Prosopis–Acacia) shrubland over the last 150 years. Fire reduction, due to lack of fine fuel and suppression of naturally occurring fires, is cited as one of the primary causes for this vegetation shift. Fire behavior, primarily rate of spread and fire intensity, is poorly understood in these communities, so fire prescriptions have not been developed. We evaluated two current fire behavior systems (BEHAVE and the CSIRO fire spread and fire danger calculator) and three models developed for shrublands to determine how well they predicted rate of spread and flame length during three summer fires within mesquite–acacia shrublands. We also used geostatistical analyses to examine the spatial pattern of net heat, flame temperature and fuel characteristics. The CSIRO forest model under-predicted the rate of fire spread by an average of 5.43 m min−1 and over-predicted flame lengths by 0.2 m while the BEHAVE brush model under-predicted rate of spread by an average of 6.57 m min−1 and flame lengths by an average of 0.33 m. The three shrubland models did not consistently predict the rate of spread in these plant communities. Net heat and flame temperature were related to the amount of 10-h fuel on the site, but were not related to the cover of grasses, forbs, shrubs, or apparent continuity of fine fuel. Fuel loads were typical of South Texas shrublands, in that they were uneven and spatially inconsistent, which resulted in an unpredictable fire pattern.

scholarly journals A Coupled Atmosphere-Fire Model: Role of the Convective Froude Number and Dynamic Fingering at the Fireline

1996 ◽  
Vol 6 (4) ◽  
pp. 177 ◽  
Author(s):  
TL Clark ◽  
MA Jenkins ◽  
JL Coen ◽  
DR Packham
Keyword(s):  
Forest Fire ◽  
Fire Behavior ◽  
Atmospheric Model ◽  
Fire Spread ◽  
Atmospheric Conditions ◽  
Fire Model ◽  
Eucalyptus Forest ◽  
Fire Front ◽  
Forest Fire Model ◽  
Wildfire Simulation

A numerical atmospheric model is coupled with a simple dry eucalyptus forest fire model to create a wildfire simulation model. This is used to show how certain atmospheric conditions can lead to commonly observed forest fire behavior. Using short line fires, simulations show that with moderate winds, the fire line interacts with the updraft ahead of it causing the fire line to curve forward into a conical shape. Other experiments show that when ambient winds change with height, a pair of rotating updrafts at the curved fire front can touch down within the fire and break up the fire line. We also demonstrate 'dynamic fingering', in which the rotating columns near the fire front intensify to tornado strength and can result in rapid and strong increases in the fire spread rate.

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