scholarly journals Improving silvicultural practices for Mediterranean forests through fire behaviour modelling using LiDAR-derived canopy fuel characteristics

2019 ◽  
Vol 28 (11) ◽  
pp. 823 ◽  
Author(s):  
Brigite Botequim ◽  
Paulo M. Fernandes ◽  
José G. Borges ◽  
Eduardo González-Ferreiro ◽  
Juan Guerra-Hernández
Keyword(s):  
Bulk Density ◽  
Forest Type ◽  
Classification Tree ◽  
Airborne Lidar ◽  
Fuel Load ◽  
Mediterranean Forests ◽  
Fire Behaviour ◽  
Fuel Loading ◽  
Fuel Characteristics ◽  
Stand Height

Wildfires cause substantial environmental and socioeconomic impacts and threaten many Spanish forested landscapes. We describe how LiDAR-derived canopy fuel characteristics and spatial fire simulation can be integrated with stand metrics to derive models describing fire behaviour. We assessed the potential use of very-low-density airborne LiDAR (light detection and ranging) data to estimate canopy fuel characteristics in south-western Spain Mediterranean forests. Forest type-specific equations were used to estimate canopy fuel attributes, namely stand height, canopy base height, fuel load, bulk density and cover. Regressions explained 61–85, 70–85, 38–96 and 75–95% of the variability in field estimated stand height, canopy fuel load, crown bulk density and canopy base height, respectively. The weakest relationships were found for mixed forests, where fuel loading variability was highest. Potential fire behaviour for typical wildfire conditions was predicted with FlamMap using LiDAR-derived canopy fuel characteristics and custom fuel models. Classification tree analysis was used to identify stand structures in relation to crown fire likelihood and fire suppression difficulty levels. The results of the research are useful for integrating multi-objective fire management decisions and effective fire prevention strategies within forest ecosystem management planning.

Using visual obstruction to estimate heathland fuel load and structure

2008 ◽  
Vol 17 (3) ◽  
pp. 380 ◽  
Author(s):  
G. M. Davies ◽  
A. Hamilton ◽  
A. Smith ◽  
C. J. Legg
Keyword(s):  
Vertical Distribution ◽  
Canopy Structure ◽  
Fuel Load ◽  
Vegetation Density ◽  
Fire Behaviour ◽  
Fuel Loading ◽  
Simple Method ◽  
Visual Obstruction ◽  
Non Destructive ◽  
The Vertical Distribution

We present a simple non-destructive technique for assessing fuel load and critical aspects of vegetation structure that play important roles in determining fire behaviour. The method is tested in a Scottish Calluna vulgaris (L.) Hull heathland but could be applied to any vegetation up to ~1 m high. Visual obstruction of a banded measurement stick (the FuelRule) placed vertically through a stand of vegetation is governed by a combination of the height of the vegetation and its density. The vertical distribution of visual obstruction is calibrated to give estimates of total fuel loading, the loading of separate size categories and the vertical distribution and horizontal heterogeneity of fuels. The present paper provides a quick and simple method for estimating total aboveground biomass and structure that may be useful not just in studies of fire behaviour but where non-destructive assessment of biomass, vegetation density or canopy structure is needed. Calibration equations can be rapidly created for use in other vegetation or fuel types.

Modelling canopy fuel variables for Pinus radiata D. Don in NW Spain with low-density LiDAR data

2014 ◽  
Vol 23 (3) ◽  
pp. 350 ◽  
Author(s):  
Eduardo González-Ferreiro ◽  
Ulises Diéguez-Aranda ◽  
Felipe Crecente-Campo ◽  
Laura Barreiro-Fernández ◽  
David Miranda ◽  
...  
Keyword(s):  
Pinus Radiata ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Low Density ◽  
Crown Fire ◽  
Fire Behaviour ◽  
Fuel Characteristics ◽  
Fire Initiation ◽  
Behaviour Simulation ◽  
Simulation Systems

Crown fire initiation and spread are key elements in gauging fire behaviour potential in conifer forests. Crown fire initiation and spread models implemented in widely used fire behaviour simulation systems such as FARSITE and FlamMap require accurate spatially explicit estimation of canopy fuel complex characteristics. In the present study, we evaluated the potential use of very low-density airborne LiDAR (light detection and ranging) data (0.5 first returns m–2) – which is freely available for most of the Spanish territory – to estimate canopy fuel characteristics in Pinus radiata D. Don stands in north-western Spain. Regression analysis indicated strong relationships (R2=0.82–0.98) between LiDAR-derived metrics and field-based fuel estimates for stand height, canopy fuel load, and average and effective canopy base height Average and effective canopy bulk density (R2=0.59–0.70) were estimated indirectly from a set of previously modelled forest variables. The LiDAR-based models developed can be used to elaborate geo-referenced raster files to describe fuel characteristics. These files can be generated periodically, whenever new freely available airborne LiDAR data are released by the Spanish National Plan of Aerial Orthophotography, and can be used as inputs in fire behaviour simulation systems.

Fire Behaviour Modelling in Tasmanian Buttongrass Moorlands .I. Fuel Characteristics

1995 ◽  
Vol 5 (4) ◽  
pp. 203 ◽  
Author(s):  
JB Marsden-Smedley ◽  
WR Catchpole
Keyword(s):  
Vegetation Cover ◽  
Fire Management ◽  
Management Strategies ◽  
Subsequent Paper ◽  
Fire Behaviour ◽  
Fuel Loading ◽  
Wide Range ◽  
Fuel Models ◽  
Fuel Characteristics ◽  
The Dead

As part of a program to develop fire management strategies for Tasmanian buttongrass moorlands fuel characteristics were sampled from a wide range of sites in western and southwestern Tasmania. Equations were developed to predict the total fuel loading and the dead fuel loading. These variables are shown in a subsequent paper to be correlated with fire behaviour. The best predictors of fuel loading were found to be geology, vegetation age (i.e. time since the last fire) and vegetation cover. Vegetation cover is difficult to assess consistently. It is shown that reasonable predictions can be made using age and geology alone. The dead fuel loading of a given age was found to be strongly related to the total fuel loading, independent of geology. Statistical techniques used to develop fuel models are discussed. Other fuel characteristics that could be used as inputs for the Rothermel fire behaviour model are also presented.

Effects of fuel load and moisture content on fire behaviour and heating in masticated litter-dominated fuels

2013 ◽  
Vol 22 (4) ◽  
pp. 440 ◽  
Author(s):  
Jesse K. Kreye ◽  
Leda N. Kobziar ◽  
Wayne C. Zipperer
Keyword(s):  
Moisture Content ◽  
Fuel Load ◽  
Maximum Temperature ◽  
Fire Behaviour ◽  
Fuel Loading ◽  
Pine Flatwoods ◽  
Rate Of Spread ◽  
Soil Temperatures ◽  
Fuel Moisture Content ◽  
In Fire

Mechanical fuels treatments are being used in fire-prone ecosystems where fuel loading poses a hazard, yet little research elucidating subsequent fire behaviour exists, especially in litter-dominated fuelbeds. To address this deficiency, we burned constructed fuelbeds from masticated sites in pine flatwoods forests in northern Florida with palmetto-dominated understoreys and examined the effects of fuel load and fuel moisture content (FMC) on fire behaviour. Flame lengths (49–140 cm) and fireline intensity (183–773 kJ m–1 s–1) increased with loading (10–30 Mg ha–1) and were reduced by 40 and 47% with increasing FMC from 9 to 13%. Rate of spread was not influenced by fuel load, but doubled under drier FMC. Fuel consumption was >90% for all burns. Soil temperatures were influenced by both fuel load and FMC, but never reached lethal temperatures (60°C). However, temperatures of thermocouple probes placed at the fuelbed surface reached 274–503°C. Probe maximum temperature and duration at temperatures ≥60°C (9.5–20.0°C min) both increased with fuel load, but were unaffected by FMC. The fire behaviour observed in these unique litter-dominated fuelbeds provides additional insight into the burning characteristics of masticated fuels in general.

Effects of fuel characteristics on horizontal spread rate and ground surface temperatures of smouldering duff

2020 ◽  
Vol 29 (9) ◽  
pp. 820
Author(s):  
Daniel A. Cowan ◽  
Wesley G. Page ◽  
Bret W. Butler ◽  
David L. Blunck
Keyword(s):  
Moisture Content ◽  
Bulk Density ◽  
Ponderosa Pine ◽  
Ground Surface ◽  
Spread Rate ◽  
Fuel Loading ◽  
Surface Temperatures ◽  
Inorganic Content ◽  
Fuel Characteristics ◽  
Horizontal Spread

The slow-moving flameless burning of wildland fuels (i.e. smouldering) can be difficult to detect and challenging to extinguish. Although previous research involving the smouldering of organic fuels (e.g. cotton, cellulose, peat) has investigated the influence of various fuel characteristics (e.g. moisture content, inorganic content, bulk density) on spread rate and surface temperatures, the smouldering behaviour of other common fuels is not well understood. This study expands on previous research to better understand how fuel characteristics influence the smouldering behaviour of duff from coniferous forests. Specifically, horizontal spread rates (0.5–19.5cm h−1) and ground surface temperatures (258–392°C) were measured on 52 duff samples collected from underneath mature ponderosa pine trees (Pinus ponderosa) from sites in the Pacific Northwest, USA, and evaluated in terms of their moisture content (6–113%), inorganic content (3–42%), bulk density (34–130kgm−3) and fuel depth (3.8–16.3cm). The data suggested that horizontal spread rates decrease when inorganic content, inorganic loading and/or moisture loading of the duff increases. Surface temperatures decrease when inorganic bulk density and/or fuel loading increases. Conversely, surface temperatures decrease when moisture content increases for shallow duff. Higher fuel loading increases the likelihood of smouldering below the surface.

Fuel properties and fire behaviour characteristics of prescribed fire in pine-dominated forests at Nam Nao National Park, Thailand

2013 ◽  
Vol 22 (5) ◽  
pp. 615 ◽  
Author(s):  
K. Wanthongchai ◽  
V. Tarusadamrongdet ◽  
K. Chinnawong ◽  
K. Sooksawat
Keyword(s):  
Prescribed Fire ◽  
National Park ◽  
Forest Type ◽  
Pine Forest ◽  
Fuel Load ◽  
Fire Behaviour ◽  
Temperature Changes ◽  
Fuel Loads ◽  
Soil Temperatures ◽  
Fuel Components

Anthropogenic burning has become a common phenomenon throughout Thailand’s pine-dominated ecosystems. This study investigated fuel loads and experimental fire behaviour characteristics in a degraded pine forest (PF) and a pine–oak forest (O-PF), at Nam Nao National Park, Thailand in three replicate 50 × 50-m plots of each forest type. Pre-burn fuel loads, fire behaviour descriptors, fire and soil temperature, the residues left after burning and post-burn fuel recovery for 1 year were investigated. The aboveground fuel load in PF (1.29 kg m–2) was significantly higher than in O-PF (0.87 kg m–2). The main fuel components in the PF stand were grass (45%) and litter (44%), whereas leaf litter was the predominant fuel in the O-PF stand (55%). The fire behaviour characteristics in the PF stand were significantly greater than those in the O-PF stand. Burning at the O-PF and the PF was respectively classified as low (48 kW m–1) and medium intensity (627 kW m–1). During the burning experiment, the surface soil temperatures at all sites were higher than 250°C. However, fire did not cause temperature changes in the deeper soil layers. In the pine forest the post-burn fuel loads 1 year after the fire remained lower than the pre-burn level. These results may imply that a pine forest at Nam Nao National Park requires more than 1 year of fire-free period to recover back to the pre-burn conditions.

Fuel accumulation and forest structure change following hazardous fuel reduction treatments throughout California

2015 ◽  
Vol 24 (3) ◽  
pp. 361 ◽  
Author(s):  
Nicole M. Vaillant ◽  
Erin K. Noonan-Wright ◽  
Alicia L. Reiner ◽  
Carol M. Ewell ◽  
Benjamin M. Rau ◽  
...  
Keyword(s):  
Bulk Density ◽  
Prescribed Fire ◽  
Forest Structure ◽  
Fire Regimes ◽  
Post Treatment ◽  
Fuel Load ◽  
Fire Behaviour ◽  
Fuel Treatments ◽  
Minimal Impact ◽  
Canopy Bulk Density

Altered fuel conditions coupled with changing climate have disrupted fire regimes of forests historically characterised by high-frequency and low-to-moderate-severity fire. Managers use fuel treatments to abate undesirable fire behaviour and effects. Short-term effectiveness of fuel treatments to alter fire behaviour and effects is well documented; however, long-term effectiveness is not well known. We evaluated surface fuel load, vegetation cover and forest structure before and after mechanical and fire-only treatments over 8 years across 11 National Forests in California. Eight years post treatment, total surface fuel load returned to 67 to 79% and 55 to 103% of pretreatment levels following fire-only and mechanical treatments respectively. Herbaceous or shrub cover exceeded pretreatment levels two-thirds of the time 8 years after treatment. Fire-only treatments warranted re-entry at 8 years post treatment owing to the accumulation of live and dead fuels and minimal impact on canopy bulk density. In general, mechanical treatments were more effective at reducing canopy bulk density and initially increasing canopy base height than prescribed fire. However, elevated surface fuel loads, canopy base height reductions in later years and lack of restoration of fire as an ecological process suggest that including prescribed fire would be beneficial.

scholarly journals Generating a Baseline Map of Surface Fuel Loading Using Stratified Random Sampling Inventory Data through Cokriging and Multiple Linear Regression Methods

2021 ◽  
Vol 13 (8) ◽  
pp. 1561
Author(s):  
Chinsu Lin ◽  
Siao-En Ma ◽  
Li-Ping Huang ◽  
Chung-I Chen ◽  
Pei-Ting Lin ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Sampling ◽  
Fuel Load ◽  
Estimation Accuracy ◽  
Slope Aspect ◽  
Stratified Random Sampling ◽  
Inventory Data ◽  
Fuel Loading ◽  
Regression Methods

Surface fuel loading is a key factor in controlling wildfires and planning sustainable forest management. Spatially explicit maps of surface fuel loading can highlight the risks of a forest fire. Geospatial information is critical in enabling careful use of deliberate fire setting and also helps to minimize the possibility of heat conduction over forest lands. In contrast to lidar sensing and/or optical sensing based methods, an approach of integrating in-situ fuel inventory data, geospatial interpolation techniques, and multiple linear regression methods provides an alternative approach to surface fuel load estimation and mapping over mountainous forests. Using a stratified random sampling based inventory and cokriging analysis, surface fuel loading data of 120 plots distributed over four kinds of fuel types were collected in order to develop a total surface fuel loading model (lntSFL-BioTopo model) and a fine surface fuel model (lnfSFL-BioTopo model) for generating tSFL and fSFL maps. Results showed that the combination of topographic parameters such as slope, aspect, and their cross products and the fuel types such as pine stand, non-pine conifer stand, broadleaf stand, and conifer–broadleaf mixed stand was able to appropriately describe the changes in surface fuel loads over a forest with diverse terrain morphology. Based on a cross-validation method, the estimation of tSFL and fSFL of the study site had an RMSE of 3.476 tons/ha and 3.384 tons/ha, respectively. In contrast to the average loading of all inventory plots, the estimation for tSFL and fSFL had a relative error of 38% (PRMSE). The reciprocal of estimation bias of both SFL-BioTopo models tended to be an exponential growth function of the amount of surface fuel load, indicating that the estimation accuracy of the proposed method is likely to be improved with further study. In the regression modeling, a natural logarithm transformation of the surface fuel loading prevented the outcome of negative estimates and thus improved the estimation. Based on the results, this paper defined a minimum sampling unit (MSU) as the area for collecting surface fuels for interpolation using a cokriging model. Allocating the MSUs at the boundary and center of a plot improved surface fuel load prediction and mapping.

Fuel and fire characteristics in savanna - woodland of West Africa in relation to grazing and dominant grass type

2007 ◽  
Vol 16 (5) ◽  
pp. 531 ◽  
Author(s):  
Patrice Savadogo ◽  
Didier Zida ◽  
Louis Sawadogo ◽  
Daniel Tiveau ◽  
Mulualem Tigabu ◽  
...  
Keyword(s):  
Prescribed Burning ◽  
Management Tool ◽  
Fuel Load ◽  
Maximum Temperature ◽  
Fire Intensity ◽  
Fire Behaviour ◽  
Savanna Woodland ◽  
Vegetation Height ◽  
Average Maximum ◽  
Dominant Grass

Fuel characteristics, fire behaviour and temperature were studied in relation to grazing, dominant grass type and wind direction in West African savanna–woodland by lighting 32 prescribed early fires. Grazing significantly reduced the vegetation height, total fuel load, and dead and live fuel fractions whereas plots dominated by perennial grasses had higher values for vegetation height, total fuel load and the quantity of live fuel load. Although fire intensity remained insensitive (P > 0.05) to any of these factors, fuel consumption was significantly (P = 0.021) reduced by grazing, rate of spread was faster in head fire (P = 0.012), and flame length was shorter in head fire than back fire (P = 0.044). The average maximum temperature was higher (P < 0.05) on non-grazed plots, on plots dominated by annual grasses, on plots subjected to head fire, and at the soil surface. Lethal temperature residence time showed a nearly similar trend to fire temperature. Wind speed and total fuel load were best predictors of fire behaviour parameters (R2 ranging from 0.557 to 0.862). It can be concluded that grazing could be used as a management tool to modify fire behaviour, back fire should be carried out during prescribed burning to lower fire severity, and the fire behaviour models can be employed to guide prescribed early fire in the study area.

scholarly journals Fuel characteristics, loads and consumption in Scots pine forests of central Siberia

2019 ◽  
Vol 31 (6) ◽  
pp. 2507-2524
Author(s):  
Galina A. Ivanova ◽  
Elena A. Kukavskaya ◽  
Valery A. Ivanov ◽  
Susan G. Conard ◽  
Douglas J. McRae
Keyword(s):  
Scots Pine ◽  
Southern Taiga ◽  
Pine Forest ◽  
Ground Vegetation ◽  
Fuel Loading ◽  
Fire Weather Index ◽  
Central Siberia ◽  
Feather Moss ◽  
Fuel Characteristics ◽  
The Impact

Abstract Forest fuel investigations in central and southern Siberian taiga of Scots pine forest stands dominated by lichen and feather moss ground vegetation cover revealed that total aboveground biomass varied from 13.1 to 21.0 kg/m2. Stand biomass was higher in plots in the southern taiga, while ground fuel loads were higher in the central taiga. We developed equations for fuel biomass (both aerial and ground) that could be applicable to similar pine forest sites of Central Siberia. Fuel loading variability found among plots is related to the impact and recovery time since the last wildfire and the mosaic distribution of living vegetation. Fuel consumption due to surface fires of low to high-intensities ranged from 0.95 to 3.08 kg/m2, that is, 18–74% from prefire values. The total amount of fuels available to burn in case of fire was up to 4.5–6.5 kg/m2. Moisture content of fuels (litter, lichen, feather moss) was related to weather conditions characterized by the Russian Fire Danger Index (PV-1) and FWI code of the Canadian Forest Fire Weather Index System. The data obtained provide a strong foundation for understanding and modeling fire behavior, emissions, and fire effects on ecosystem processes and carbon stocks and could be used to improve existing global and regional models that incorporate biomass and fuel characteristics.

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