scholarly journals Generation of a global fuel data set using the Fuel Characteristic Classification System

2016 ◽  
Vol 13 (7) ◽  
pp. 2061-2076 ◽  
Author(s):  
M. Lucrecia Pettinari ◽  
Emilio Chuvieco
Keyword(s):  
Classification System ◽  
Boreal Forests ◽  
Fire Behavior ◽  
Data Set ◽  
Spatial Variables ◽  
Carbon Biomass ◽  
Varied Range ◽  
Emissions Inventories ◽  
Fuel Characteristic ◽  
Good Agreement

Abstract. This study presents the methods for the generation of the first global fuel data set, containing all the parameters required to be input in the Fuel Characteristic Classification System (FCCS). The data set was developed from different spatial variables, both based on satellite Earth observation products and fuel databases, and is comprised by a global fuelbed map and a database that includes the parameters of each fuelbed that affect fire behavior and effects. A total of 274 fuelbeds were created and parameterized, and can be input into FCCS to obtain fire potentials, surface fire behavior and carbon biomass for each fuelbed. We present a first assessment of the fuel data set by comparing the carbon biomass obtained from our FCCS fuelbeds with the average biome values of four other regional or global biomass products. The results showed a good agreement both in terms of geographical distribution and biomass loads when compared to other biomass data, with the best results found for tropical and boreal forests (Spearman's coefficient of 0.79 and 0.77). This global fuel data set may be used for a varied range of applications, including fire danger assessment, fire behavior estimations, fuel consumption calculations and emissions inventories.

scholarly journals Generation of a global fuel dataset using the Fuel Characteristic Classification System

2015 ◽  
Vol 12 (20) ◽  
pp. 17245-17284 ◽  
Author(s):  
M. L. Pettinari ◽  
E. Chuvieco
Keyword(s):  
Classification System ◽  
Boreal Forests ◽  
Reasonable Agreement ◽  
Fire Behavior ◽  
Earth Observation ◽  
Spatial Variables ◽  
Carbon Biomass ◽  
Varied Range ◽  
Emissions Inventories ◽  
Fuel Characteristic

Abstract. This study presents the methods for the generation of the first global fuel dataset, containing all the parameters required to be input in the Fuel Characteristic Classification System (FCCS). The dataset was developed from different spatial variables, both based on satellite Earth observation products and fuel databases, and is comprised by a global fuelbed map and a database that includes the parameters of each fuelbed that affect fire behavior and effects. A total of 274 fuelbeds were created and parameterized, and can be input into FCCS to obtain fire potentials, surface fire behavior and carbon biomass for each fuelbed. To assess the results, FCCS was used to calculate the carbon biomass of each fuelbed, and the results were compared to the values obtained for four other regional or global biomass products. The results showed reasonable agreement both in terms of geographical distribution and biomass loads when compared to other biomass data, with the best results found for Tropical and Boreal forests (Spearman's coefficient of 0.79 and 0.77). This global fuel dataset could be used for a varied range of applications, including fire danger assessment, fire behavior estimations, fuel consumption calculations and emissions inventories.

An overview of the Fuel Characteristic Classification System — Quantifying, classifying, and creating fuelbeds for resource planningThis article is one of a selection of papers published in the Special Forum on the Fuel Characteristic Classification System.

2007 ◽  
Vol 37 (12) ◽  
pp. 2383-2393 ◽  
Author(s):  
Roger D. Ottmar ◽  
David V. Sandberg ◽  
Cynthia L. Riccardi ◽  
Susan J. Prichard
Keyword(s):  
United States ◽  
Classification System ◽  
Treatment Effectiveness ◽  
Fire Hazard ◽  
Fire Behavior ◽  
The United States ◽  
Carbon Accounting ◽  
Support Surface ◽  
Fire Emissions ◽  
Fuel Characteristic

We present an overview of the Fuel Characteristic Classification System (FCCS), a tool that enables land managers, regulators, and scientists to create and catalogue fuelbeds and to classify those fuelbeds for their capacity to support fire and consume fuels. The fuelbed characteristics and fire classification from this tool will provide inputs for current and future sophisticated models for the quantification of fire behavior, fire effects, and carbon accounting and enable assessment of fuel treatment effectiveness. The system was designed from requirements provided by land managers, scientists, and policy makers gathered through six regional workshops. The FCCS contains a set of fuelbeds representing the United States, which were compiled from scientific literature, fuels photo series, fuels data sets, and expert opinion. The system enables modification and enhancement of these fuelbeds to represent a particular scale of interest. The FCCS then reports assigned and calculated fuel characteristics for each existing fuelbed stratum including the canopy, shrubs, nonwoody, woody, litter–lichen–moss, and duff. Finally, the system classifies each fuelbed by calculating fire potentials that provide an index of the intrinsic capacity of each fuelbed to support surface fire behavior, support crown fire, and provide fuels for flaming, smoldering, and residual consumption. The FCCS outputs are being used in a national wildland fire emissions inventory and in the development of fuelbed, fire hazard, and treatment effectiveness maps on several national forests. Although the FCCS was built for the United States, the conceptual framework is applicable worldwide.

Reformulation of Rothermel’s wildland fire behaviour model for heterogeneous fuelbedsThis article is one of a selection of papers published in the Special Forum on the Fuel Characteristic Classification System.

2007 ◽  
Vol 37 (12) ◽  
pp. 2438-2455 ◽  
Author(s):  
David V. Sandberg ◽  
Cynthia L. Riccardi ◽  
Mark D. Schaaf
Keyword(s):  
Wind Speed ◽  
Environmental Conditions ◽  
Classification System ◽  
Fire Behavior ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Spread Model ◽  
Fuel Characteristic ◽  
Fire Spread Model

The Fuel Characteristic Classification System (FCCS) includes equations that calculate energy release and one-dimensional spread rate in quasi-steady state fires in heterogeneous but spatially-uniform wildland fuelbeds, using a reformulation of the widely used Rothermel fire spread model. This reformulation provides an automated means to predict fire behavior under any environmental conditions in any natural, modified, or simulated wildland fuelbed. The formulation may be used to compare potential fire behavior between fuelbeds that differ in time, space, or as a result of management, and provides a means to classify and map fuelbeds based on their expected surface fire behavior under any set of defined environmental conditions (i.e., effective wind speed and fuel moisture content). Model reformulation preserves the basic mathematical framework of the Rothermel fire spread model, reinterprets data from two of the original basic equations in his model, and offers a new conceptual formulation that allows the direct use of inventoried fuel properties instead of stylized fuel models. Alternative methods for calculating the effect of wind speed and fuel moisture, based on more recent literature, are also provided. This reformulation provides a framework for the incremental improvement in quantifying fire behaviour parameters in complex fuelbeds and for modeling fire spread.

Fire potential rating for wildland fuelbeds using the Fuel Characteristic Classification SystemThis article is one of a selection of papers published in the Special Forum on the Fuel Characteristic Classification System.

2007 ◽  
Vol 37 (12) ◽  
pp. 2456-2463 ◽  
Author(s):  
David V. Sandberg ◽  
Cynthia L. Riccardi ◽  
Mark D. Schaaf
Keyword(s):  
Classification System ◽  
Fire Behavior ◽  
Flame Length ◽  
Crown Fire ◽  
Policy Makers ◽  
Reaction Intensity ◽  
Fuel Characteristic ◽  
Intensity Spread ◽  
Classification Tool ◽  
Moisture Conditions

The Fuel Characteristic Classification System (FCCS) is a systematic catalog of inherent physical properties of wildland fuelbeds that allows land managers, policy makers, and scientists to build and calculate fuel characteristics with complete or incomplete information. The FCCS is equipped with a set of equations to calculate the potential of any real-world or simulated fuelbed to spread fire across the surface and in the crowns, and consume fuels. FCCS fire potentials are a set of relative values that rate the intrinsic physical capacity of a wildland fuelbed to release energy and to spread, crown, consume, and smolder under known or benchmark weather and fuel moisture conditions. The FCCS reports eight component fire potentials for every fuelbed, arranged in three categories: surface fire behaviour (reaction intensity, spread rate, and flame length), crown fire potential (torching and active crown fire), and available fuel potential (flaming, smouldering, and residual smouldering). FCCS fire potentials may be used to classify or compare fuelbeds that differ because of location, structure, passage of time, or management action, based on expected fire behavior or effect outcomes. As a classification tool, they are offered as an objective alternative to categorizing bulk properties of fuelbeds or stylized model inputs.

Fuel Characteristic Classification System (FCCS) field sampling and fuelbed development guide

2019 ◽  
Author(s):  
Susan J. Prichard ◽  
Anne G. Andreu ◽  
Roger D. Ottmar ◽  
Ellen Eberhardt
Keyword(s):  
Classification System ◽  
Field Sampling ◽  
Fuel Characteristic

Agreement and reliability of magnetic, angular rate, and gravity (MARG) sensors to assess multiple body segment’s external loads during off-road running

2021 ◽  
pp. 175433712199698
Author(s):  
Daniel Rojas-Valverde ◽  
José Pino-Ortega ◽  
Rafael Timón ◽  
Randall Gutiérrez-Vargas ◽  
Braulio Sánchez-Ureña ◽  
...  
Keyword(s):  
Vastus Lateralis ◽  
Angular Rate ◽  
Wearable Sensors ◽  
Intraclass Correlation ◽  
Principal Component ◽  
Test Reliability ◽  
Data Set ◽  
Body Segments ◽  
External Loads ◽  
Good Agreement

The extensive use of wearable sensors in sport medicine, exercise medicine, and health has increased the interest in their study. That is why it is necessary to test these technologies’ efficiency, effectiveness, agreement, and reliability in different settings. Consequently, the purpose of this article was to analyze the magnetic, angular rate, and gravity (MARG) sensor’s test-retest agreement and reliability when assessing multiple body segments’ external loads during off-road running. A total of 18 off-road runners (38.78 ± 10.38 years, 73.24 ± 12.6 kg, 172.17 ± 9.48 cm) ran two laps (1st and 2nd Lap) of a 12 km circuit wearing six MARG sensors. The sensors were attached to six different body segments: left (MPLeft) and right (MPRight) malleolus peroneus, left (VLLeft) and right (VLRight) vastus lateralis, lumbar (L1-L3), and thorax (T2-T4) using a special neoprene suit. After a principal component analysis (PCA) was performed, the total data set variance of all body segments was represented by 44.08%–70.64% for the 1st PCA factor considering two variables, Player LoadRT and Impacts, on L1-L3, respectively. These two variables were chosen among three total accelerometry-based external load indicators (ABELIs) to perform the agreement and reliability tests due to their relevance based on PCAs for each body segment. There were no significant differences between laps in the Player LoadRT or Impacts ( p > 0.05, trivial). The intraclass correlation and lineal correlation showed a substantial to almost perfect over-time test consistency assessed via reliability in both Player LoadRT and Impacts. Bias and t-test assessments showed good agreement between Laps. It can be concluded that MARGs sensors offer significant test re-test reliability and good agreement when assessing off-road kinematics in the six different body segments.

scholarly journals MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches

2015 ◽  
Vol 8 (2) ◽  
pp. 941-963 ◽  
Author(s):  
T. Vlemmix ◽  
F. Hendrick ◽  
G. Pinardi ◽  
I. De Smedt ◽  
C. Fayt ◽  
...  
Keyword(s):  
Standard Deviation ◽  
A Priori ◽  
Systematic Bias ◽  
Aerosol Extinction ◽  
Data Set ◽  
Near Surface ◽  
Beijing Area ◽  
Least Squares Fit ◽  
Relative Differences ◽  
Good Agreement

Abstract. A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, −23 ± 28 and −8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 and aerosol extinction which on average show quite good agreement for characteristic profile heights below 1.5 km. One of the main advantages of method A is the stability, even under suboptimal conditions (e.g. in the presence of clouds). Method B is generally more unstable and this explains probably a substantial part of the quite large relative differences between the two methods. However, despite a relatively low precision for individual profile retrievals it appears as if seasonally averaged profile heights retrieved with method B are less biased towards a priori assumptions than those retrieved with method A. This gives confidence in the result obtained with method B, namely that aerosol extinction profiles tend on average to be higher than NO2 profiles in spring and summer, whereas they seem on average to be of the same height in winter, a result which is especially relevant in relation to the validation of satellite retrievals.

scholarly journals Global estimation of burned area using MODIS active fire observations

2006 ◽  
Vol 6 (4) ◽  
pp. 957-974 ◽  
Author(s):  
L. Giglio ◽  
G. R. van der Werf ◽  
J. T. Randerson ◽  
G. J. Collatz ◽  
P. Kasibhatla
Keyword(s):  
Vegetation Cover ◽  
Regression Trees ◽  
The United States ◽  
Tree Cover ◽  
Burned Area ◽  
Data Set ◽  
Active Fire ◽  
Terra Modis ◽  
Good Agreement ◽  
Area Data

Abstract. We present a method for estimating monthly burned area globally at 1° spatial resolution using Terra MODIS data and ancillary vegetation cover information. Using regression trees constructed for 14 different global regions, MODIS active fire observations were calibrated to burned area estimates derived from 500-m MODIS imagery based on the assumption that burned area is proportional to counts of fire pixels. Unlike earlier methods, we allow the constant of proportionality to vary as a function of tree and herbaceous vegetation cover, and the mean size of monthly cumulative fire-pixel clusters. In areas undergoing active deforestation, we implemented a subsequent correction based on tree cover information and a simple measure of fire persistence. Regions showing good agreement between predicted and observed burned area included Boreal Asia, Central Asia, Europe, and Temperate North America, where the estimates produced by the regression trees were relatively accurate and precise. Poorest agreement was found for southern-hemisphere South America, where predicted values of burned area are both inaccurate and imprecise; this is most likely a consequence of multiple factors that include extremely persistent cloud cover, and lower quality of the 500-m burned area maps used for calibration. Application of our approach to the nine remaining regions yielded comparatively accurate, but less precise, estimates of monthly burned area. We applied the regional regression trees to the entire archive of Terra MODIS fire data to produce a monthly global burned area data set spanning late 2000 through mid-2005. Annual totals derived from this approach showed good agreement with independent annual estimates available for nine Canadian provinces, the United States, and Russia. With our data set we estimate the global annual burned area for the years 2001-2004 to vary between 2.97 million and 3.74 million km2, with the maximum occurring in 2001. These coarse-resolution burned area estimates may serve as a useful interim product until long-term burned area data sets from multiple sensors and retrieval approaches become available.

scholarly journals Automated Negative Lightning Return Strokes Classification System

2021 ◽  
Vol 2107 (1) ◽  
pp. 012022
Author(s):  
F. Abdul Haris ◽  
M.Z.A. Ab Kadir ◽  
S. Sudin ◽  
D. Johari ◽  
J. Jasni ◽  
...  
Keyword(s):  
Classification System ◽  
Automatic System ◽  
Human Error ◽  
Processing Time ◽  
Visual Inspection ◽  
Automated System ◽  
Graphic User Interface ◽  
Data Comparison ◽  
Good Agreement

Abstract Over the years, many studies have been conducted to measure and classify the lightning-generated electric field waveform for a better understanding of the lightning physics phenomenon. Through measurement and classification, the features of the negative lightning return strokes can be accessed and analysed. In most studies, the classification of negative lightning return strokes was performed using a conventional approach based on manual visual inspection. Nevertheless, this traditional method could compromise the accuracy of data analysis due to human error, which also required a longer processing time. Hence, this study developed an automated negative lightning return strokes classification system using MATLAB software. In this study, a total of 115 return strokes was recorded and classified automatically by using the developed system. The data comparison with the Tenaga Nasional Berhad Research (TNBR) lightning report showed a good agreement between the lightning signal detected from this study with those signals recorded from the report. Apart from that, the developed automated system was successfully classified the negative lightning return strokes which this parameter was also illustrated on Graphic User Interface (GUI). Thus, the proposed automatic system could offer a practical and reliable approach by reducing human error and the processing time while classifying the negative lightning return strokes.

scholarly journals Tropical troposphere to stratosphere transport of carbon monoxide and long-lived trace species in the Chemical Lagrangian Model of the Stratosphere (CLaMS)

2014 ◽  
Vol 7 (4) ◽  
pp. 5087-5139 ◽  
Author(s):  
R. Pommrich ◽  
R. Müller ◽  
J.-U. Grooß ◽  
P. Konopka ◽  
F. Ploeger ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Large Scale ◽  
Lower Stratosphere ◽  
Lagrangian Model ◽  
Quasi Biennial Oscillation ◽  
Data Set ◽  
Model Version ◽  
The Tropics ◽  
The Impact ◽  
Good Agreement

Abstract. Variations in the mixing ratio of trace gases of tropospheric origin entering the stratosphere in the tropics are of interest for assessing both troposphere to stratosphere transport fluxes in the tropics and the impact of these transport fluxes on the composition of the tropical lower stratosphere. Anomaly patterns of carbon monoxide (CO) and long-lived tracers in the lower tropical stratosphere allow conclusions about the rate and the variability of tropical upwelling to be drawn. Here, we present a simplified chemistry scheme for the Chemical Lagrangian Model of the Stratosphere (CLaMS) for the simulation, at comparatively low numerical cost, of CO, ozone, and long-lived trace substances (CH4, N2O, CCl3F (CFC-11), CCl2F2 (CFC-12), and CO2) in the lower tropical stratosphere. For the long-lived trace substances, the boundary conditions at the surface are prescribed based on ground-based measurements in the lowest model level. The boundary condition for CO in the free troposphere is deduced from MOPITT measurements (at ≈ 700–200 hPa). Due to the lack of a specific representation of mixing and convective uplift in the troposphere in this model version, enhanced CO values, in particular those resulting from convective outflow are underestimated. However, in the tropical tropopause layer and the lower tropical stratosphere, there is relatively good agreement of simulated CO with in-situ measurements (with the exception of the TROCCINOX campaign, where CO in the simulation is biased low ≈ 10–20 ppbv). Further, the model results are of sufficient quality to describe large scale anomaly patterns of CO in the lower stratosphere. In particular, the zonally averaged tropical CO anomaly patterns (the so called "tape recorder" patterns) simulated by this model version of CLaMS are in good agreement with observations. The simulations show a too rapid upwelling compared to observations as a consequence of the overestimated vertical velocities in the ERA-interim reanalysis data set. Moreover, the simulated tropical anomaly patterns of N2O are in good agreement with observations. In the simulations, anomaly patterns for CH4 and CFC-11 were found to be consistent with those of N2O; for all long-lived tracers, positive anomalies are simulated because of the enhanced tropical upwelling in the easterly phase of the quasi-biennial oscillation.

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