Spatial fuel data products of the LANDFIRE Project

2009 ◽  
Vol 18 (3) ◽  
pp. 250 ◽  
Author(s):  
Matthew C. Reeves ◽  
Kevin C. Ryan ◽  
Matthew G. Rollins ◽  
Thomas G. Thompson
Keyword(s):  
Bulk Density ◽  
Vegetation Structure ◽  
Fire Regime ◽  
Fire Behavior ◽  
The United States ◽  
Surface Fire ◽  
Spatial Coverage ◽  
Data Products ◽  
Fuel Models ◽  
Canopy Bulk Density

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50 states. Here we describe development of the LANDFIRE wildland fuels data layers for the conterminous 48 states: surface fire behavior fuel models, canopy bulk density, canopy base height, canopy cover, and canopy height. Surface fire behavior fuel models are mapped by developing crosswalks to vegetation structure and composition created by LANDFIRE. Canopy fuels are mapped using regression trees relating field-referenced estimates of canopy base height and canopy bulk density to satellite imagery, biophysical gradients and vegetation structure and composition data. Here we focus on the methods and data used to create the fuel data products, discuss problems encountered with the data, provide an accuracy assessment, demonstrate recent use of the data during the 2007 fire season, and discuss ideas for updating, maintaining and improving LANDFIRE fuel data products.

Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA

2005 ◽  
Vol 35 (12) ◽  
pp. 2981-2995 ◽  
Author(s):  
Crystal L Raymond ◽  
David L Peterson
Keyword(s):  
Tree Mortality ◽  
Fire Regime ◽  
Fire Severity ◽  
Fire Behavior ◽  
Evergreen Forest ◽  
Fire Intensity ◽  
Crown Fire ◽  
Fuel Loading ◽  
Fuel Treatments ◽  
Surface Fire

We had the rare opportunity to quantify the relationship between fuels and fire severity using prefire surface and canopy fuel data and fire severity data after a wildfire. The study area is a mixed-evergreen forest of southwestern Oregon with a mixed-severity fire regime. Modeled fire behavior showed that thinning reduced canopy fuels, thereby decreasing the potential for crown fire spread. The potential for crown fire initiation remained fairly constant despite reductions in ladder fuels, because thinning increased surface fuels, which contributed to greater surface fire intensity. Thinning followed by underburning reduced canopy, ladder, and surface fuels, thereby decreasing surface fire intensity and crown fire potential. However, crown fire is not a prerequisite for high fire severity; damage to and mortality of overstory trees in the wildfire were extensive despite the absence of crown fire. Mortality was most severe in thinned treatments (80%–100%), moderate in untreated stands (53%–54%), and least severe in the thinned and underburned treatment (5%). Thinned treatments had higher fine-fuel loading and more extensive crown scorch, suggesting that greater consumption of fine fuels contributed to higher tree mortality. Fuel treatments intended to minimize tree mortality will be most effective if both ladder and surface fuels are treated.

Development and testing of models for predicting crown fire rate of spread in conifer forest stands

2005 ◽  
Vol 35 (7) ◽  
pp. 1626-1639 ◽  
Author(s):  
Miguel G Cruz ◽  
Martin E Alexander ◽  
Ronald H Wakimoto
Keyword(s):  
Bulk Density ◽  
Fire Behavior ◽  
Fire Regimes ◽  
Management Decision ◽  
Crown Fire ◽  
Conifer Forest ◽  
Data Set ◽  
Rate Of Spread ◽  
Spread Model ◽  
Canopy Bulk Density

The rate of spread of crown fires advancing over level to gently undulating terrain was modeled through nonlinear regression analysis based on an experimental data set pertaining primarily to boreal forest fuel types. The data set covered a significant spectrum of fuel complex and fire behavior characteristics. Crown fire rate of spread was modeled separately for fires spreading in active and passive crown fire regimes. The active crown fire rate of spread model encompassing the effects of 10-m open wind speed, estimated fine fuel moisture content, and canopy bulk density explained 61% of the variability in the data set. Passive crown fire spread was modeled through a correction factor based on a criterion for active crowning related to canopy bulk density. The models were evaluated against independent data sets originating from experimental fires. The active crown fire rate of spread model predicted 42% of the independent experimental crown fire data with an error lower then 25% and a mean absolute percent error of 26%. While the models have some shortcomings and areas in need of improvement, they can be readily utilized in support of fire management decision making and other fire research studies.

scholarly journals Estimating Canopy Fuel Attributes from Low-Density LiDAR

Fire ◽  
2019 ◽  
Vol 2 (3) ◽  
pp. 38 ◽  
Author(s):  
Peder S. Engelstad ◽  
Michael Falkowski ◽  
Peter Wolter ◽  
Aaron Poznanovic ◽  
Patty Johnson
Keyword(s):  
Bulk Density ◽  
Spatial Data ◽  
Nearest Neighbor ◽  
Wildland Fire ◽  
Fire Behavior ◽  
Stand Age ◽  
Low Density ◽  
K Nearest Neighbor ◽  
Local Conditions ◽  
Canopy Bulk Density

Simulations of wildland fire risk are dependent on the accuracy and relevance of spatial data inputs describing drivers of wildland fire, including canopy fuels. Spatial data are freely available at national and regional levels. However, the spatial resolution and accuracy of these types of products often are insufficient for modeling local conditions. Fortunately, active remote sensing techniques can produce accurate, high-resolution estimates of forest structure. Here, low-density LiDAR and field-based data were combined using randomForest k-nearest neighbor imputation (RF-kNN) to estimate canopy bulk density, canopy base height, and stand age across the Boundary Waters Canoe Area in Minnesota, USA. RF-kNN models produced strong relationships between estimated canopy fuel attributes and field-based data for stand age (Adj. R2 = 0.81, RMSE = 10.12 years), crown fuel base height (Adj. R2 = 0.78, RMSE = 1.10 m), live crown base height (Adj. R2 = 0.7, RMSE = 1.60 m), and canopy bulk density (Adj. R2 = 0.48, RMSE = 0.09kg/m3). These results suggest that low-density LiDAR can help estimate canopy fuel attributes in mixed forests, with robust model accuracies and high spatial resolutions compared to currently utilized fire behavior model inputs. Model map outputs provide a cost-efficient alternative for data required to simulate fire behavior and support local management.

Chaparral shrub bulk density and fire behavior

2016 ◽  
Author(s):  
Jing Li ◽  
Shankar Mahalingam ◽  
David R. Weise
Keyword(s):  
Bulk Density ◽  
Fire Behavior

scholarly journals Comparative Study of the Properties of Wood Flour and Wood Pellets Manufactured from Secondary Processing Mill Residues

Polymers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2487
Author(s):  
Geeta Pokhrel ◽  
Yousoo Han ◽  
Douglas J. Gardner
Keyword(s):  
Moisture Content ◽  
Bulk Density ◽  
Raw Materials ◽  
Wood Flour ◽  
The United States ◽  
Red Maple ◽  
Wood Pellets ◽  
Secondary Processing ◽  
Material Costs ◽  
Mill Residues

The generation of secondary processing mill residues from wood processing facilities is extensive in the United States. Wood flour can be manufactured utilizing these residues and an important application of wood flour is as a filler in the wood–plastic composites (WPCs). Scientific research on wood flour production from mill residues is limited. One of the greatest costs involved in the supply chain of WPCs manufacturing is the transportation cost. Wood flour, constrained by low bulk densities, is commonly transported by truck trailers without attaining allowable weight limits. Because of this, shipping costs often exceed the material costs, consequently increasing raw material costs for WPC manufacturers and the price of finished products. A bulk density study of wood flour (190–220 kg/m3) and wood pellets (700–750 kg/m3) shows that a tractor-trailer can carry more than three times the weight of pellets compared to flour. Thus, this study focuses on exploring the utilization of mill residues from four wood species in Maine to produce raw materials for manufacturing WPCs. Two types of raw materials for the manufacture of WPCs, i.e., wood flour and wood pellets, were produced and a study of their properties was performed. At the species level, red maple 40-mesh wood flour had the highest bulk density and lowest moisture content. Spruce-fir wood flour particles were the finest (dgw of 0.18 mm). For all species, the 18–40 wood flour mesh size possessed the highest aspect ratio. Similarly, on average, wood pellets manufactured from 40-mesh particles had a lower moisture content, higher bulk density, and better durability than the pellets from unsieved wood flour. Red maple pellets had the lowest moisture content (0.12%) and the highest bulk density (738 kg/m3). The results concluded that the processing of residues into wood flour and then into pellets reduced the moisture content by 76.8% and increased the bulk density by 747%. These material property parameters are an important attempt to provide information that can facilitate the more cost-efficient transport of wood residue feedstocks over longer distances.

A generally applicable pedotransfer function that estimates field capacity and permanent wilting point from soil texture and bulk density

2008 ◽  
Vol 88 (5) ◽  
pp. 761-774 ◽  
Author(s):  
J. A. P. Pollacco
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Bulk Density ◽  
Soil Texture ◽  
The United States ◽  
Pedotransfer Functions ◽  
Pedotransfer Function ◽  
Data Set ◽  
Wide Range ◽  
Fitting Parameters

Hydrological models require the determination of fitting parameters that are tedious and time consuming to acquire. A rapid alternative method of estimating the fitting parameters is to use pedotransfer functions. This paper proposes a reliable method to estimate soil moisture at -33 and -1500 kPa from soil texture and bulk density. This method reduces the saturated moisture content by multiplying it with two non-linear functions depending on sand and clay contents. The novel pedotransfer function has no restrictions on the range of the texture predictors and gives reasonable predictions for soils with bulk density that varies from 0.25 to 2.16 g cm-3. These pedotransfer functions require only five parameters for each pressure head. It is generally accepted that the introduction of organic matter as a predictor improves the outcomes; however it was found by using a porosity based pedotransfer model, using organic matter as a predictor only modestly improves the accuracy. The model was developed employing 18 559 samples from the IGBP-DIS soil data set for pedotransfer function development (Data and Information System of the International Geosphere Biosphere Programme) database that embodies all major soils across the United States of America. The function is reliable and performs well for a wide range of soils occurring in very dry to very wet climates. Climatical grouping of the IGBP-DIS soils was proposed (aquic, tropical, cryic, aridic), but the results show that only tropical soils require specific grouping. Among many other different non-climatical soil groups tested, only humic and vitric soils were found to require specific grouping. The reliability of the pedotransfer function was further demonstrated with an independent database from Northern Italy having heterogeneous soils, and was found to be comparable or better than the accuracy of other pedotransfer functions found in the literature. Key words: Pedotransfer functions, soil moisture, soil texture, bulk density, organic matter, grouping

Impact of Ventilation on Fire Behavior in Legacy and Contemporary Residential Construction

2010 ◽  
Author(s):  
Steve Kerber ◽  
Keyword(s):  
Homeland Security ◽  
Fire Behavior ◽  
The United States ◽  
Fire Service ◽  
United States Department ◽  
Department Of Homeland Security ◽  
Front Door ◽  
Fire Environment ◽  
Open Floor ◽  
The Impact

Under the United States Department of Homeland Security (DHS) Assistance to Firefighter Grant Program, Underwriters Laboratories examined fire service ventilation practices as well as the impact of changes in modern house geometries. There has been a steady change in the residential fire environment over the past several decades. These changes include larger homes, more open floor plans and volumes and increased synthetic fuel loads. This series of experiments examine this change in fire behavior and the impact on firefighter ventilation tactics. This fire research project developed the empirical data that is needed to quantify the fire behavior associated with these scenarios and result in immediately developing the necessary firefighting ventilation practices to reduce firefighter death and injury. Two houses were constructed in the large fire facility of Underwriters Laboratories in Northbrook, IL. The first of two houses constructed was a one-story, 1200 ft, 3 bedroom, 
bathroom house with 8 total rooms. The second house was a two-story 3200 ft, 4 bedroom, 2.5 bathroom house with 12 total rooms. The second house featured a modern open floor plan, two- story great room and open foyer. Fifteen experiments were conducted varying the ventilation locations and the number of ventilation openings. Ventilation scenarios included ventilating the front door only, opening the front door and a window near and remote from the seat of the fire, opening a window only and ventilating a higher opening in the two-story house. One scenario in each house was conducted in triplicate to examine repeatability. The results of these experiments provide knowledge for the fire service for them to examine their thought processes, standard operating procedures and training content. Several tactical considerations were developed utilizing the data from the experiments to provide specific examples of changes that can be adopted based on a departments current strategies and tactics.

scholarly journals Grass Canopy Architecture Influences Temperature Exposure at Soil Surface

Fire ◽  
2018 ◽  
Vol 1 (3) ◽  
pp. 35 ◽  
Author(s):  
Xiulin Gao ◽  
Dylan Schwilk
Keyword(s):  
Fire Regime ◽  
Fire Behavior ◽  
Soil Surface ◽  
Grass Species ◽  
Canopy Architecture ◽  
Height Ratio ◽  
Biomass Density ◽  
Litter Flammability ◽  
Temperature Exposure ◽  
Density And Biomass

There is increasing recognition that plant traits contribute to variations in fire behavior and fire regime. Diversity across species in litter flammability and canopy flammability has been documented in many woody plants. Grasses, however, are often considered homogeneous fuels in which any flammability differences across species are attributable to biomass differences alone and therefore are of less ecological interest, because biomass is hugely plastic. We examined the effect of grass canopy architecture on flammability across eight grass species in short grass steppe of New Mexico and Texas. To characterize grass canopy architecture, we measured biomass density and “biomass-height ratio” (the ratio of canopy biomass above 10 cm to that of biomass below 10 cm). Indoor flammability experiments were performed on air-dried individual plants. As expected, plant biomass influenced all flammability measures. However, biomass-height ratio had additional negative effect on temperature exposure at soil surface (accumulation of mean temperature >100 °C) in well-cured grasses, which is an important fire behavior metric predicting soil heating and meristem survival. This canopy architecture effect, however, needs further investigation to be isolated from biomass density due to correlation of these two traits. This result demonstrates the potential for species-specific variation in architecture to influence local fire effects in grasses.

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