scholarly journals Daily burned area and carbon emissions from boreal fires in Alaska

2015 ◽  
Vol 12 (11) ◽  
pp. 3579-3601 ◽  
Author(s):  
S. Veraverbeke ◽  
B. M. Rogers ◽  
J. T. Randerson
Keyword(s):  
Land Cover ◽  
Carbon Emissions ◽  
Environmental Variables ◽  
Black Spruce ◽  
Tree Cover ◽  
Burned Area ◽  
Carbon Consumption ◽  
Fire Emissions ◽  
Spruce Stands ◽  
Belowground Carbon

Abstract. Boreal fires burn into carbon-rich organic soils, thereby releasing large quantities of trace gases and aerosols that influence atmospheric composition and climate. To better understand the factors regulating boreal fire emissions, we developed a statistical model of carbon consumption by fire for Alaska with a spatial resolution of 450 m and a temporal resolution of 1 day. We used the model to estimate variability in carbon emissions between 2001 and 2012. Daily burned area was mapped using imagery from the Moderate Resolution Imaging Spectroradiometer combined with perimeters from the Alaska Large Fire Database. Carbon consumption was calibrated using available field measurements from black spruce forests in Alaska. We built two nonlinear multiplicative models to separately predict above- and belowground carbon consumption by fire in response to environmental variables including elevation, day of burning within the fire season, pre-fire tree cover and the differenced normalized burn ratio (dNBR). Higher belowground carbon consumption occurred later in the season and for mid-elevation forests. Topographic slope and aspect did not improve performance of the belowground carbon consumption model. Aboveground and belowground carbon consumption also increased as a function of tree cover and the dNBR, suggesting a causal link between the processes regulating these two components of carbon consumption. Between 2001 and 2012, the median carbon consumption was 2.54 kg C m-2. Burning in land-cover types other than black spruce was considerable and was associated with lower levels of carbon consumption than for pure black spruce stands. Carbon consumption originated primarily from the belowground fraction (median = 2.32 kg C m-2 for all cover types and 2.67 kg C m-2 for pure black spruce stands). Total carbon emissions varied considerably from year to year, with the highest emissions occurring during 2004 (69 Tg C), 2005 (46 Tg C), 2009 (26 Tg C), and 2002 (17 Tg C) and a mean of 15 Tg C year-1 between 2001 and 2012. Mean uncertainty of carbon consumption for the domain, expressed as 1 standard deviation (SD), was 0.50 kg C m-2. Uncertainties in the multiplicative regression model used to estimate belowground consumption in black spruce stands and the land-cover classification were primary contributors to uncertainty estimates. Our analysis highlights the importance of accounting for the spatial heterogeneity of fuels and combustion when extrapolating emissions in space and time, and the need for of additional field campaigns to increase the density of observations as a function of tree cover and other environmental variables influencing consumption. The daily emissions time series from the Alaskan Fire Emissions Database (AKFED) presented here creates new opportunities to study environmental controls on daily fire dynamics, optimize boreal fire emissions in biogeochemical models, and quantify potential feedbacks from changing fire regimes.

scholarly journals Daily burned area and carbon emissions from boreal fires in Alaska

2014 ◽  
Vol 11 (12) ◽  
pp. 17579-17629
Author(s):  
S. Veraverbeke ◽  
B. M. Rogers ◽  
J. T. Randerson
Keyword(s):  
Fuel Consumption ◽  
Carbon Emissions ◽  
Black Spruce ◽  
Total Carbon ◽  
Tree Cover ◽  
Burned Area ◽  
Organic Soils ◽  
Carbon Consumption ◽  
Fire Emissions ◽  
Spruce Stands

Abstract. Boreal fires burn carbon-rich organic soils, thereby releasing large quantities of trace gases and aerosols that influence atmospheric composition and climate. To better understand the factors regulating boreal fire emissions, we developed a statistical model of carbon consumption by fire for Alaska with a spatial resolution of 500 m and a temporal resolution of one day. We used the model to estimate variability in carbon emissions between 2001 and 2012. Daily burned area was mapped using imagery from the Moderate Resolution Imaging Spectroradiometer combined with perimeters from the Alaska Large Fire Database. Carbon consumption was calibrated using available field measurements from black spruce forests in Alaska. We built two nonlinear multiplicative models to separately predict above- and belowground carbon consumption by fire in response to environmental variables including elevation, day of burning within the fire season, pre-fire tree cover and the differenced normalized burn ratio (dNBR). Higher belowground consumption occurred later in the season and for mid-elevation regions. Aboveground and belowground consumption also increased as a function of tree cover and the dNBR, suggesting a causal link between the processes regulating these two components of consumption. Between 2001 and 2012, the median fuel consumption was 2.48 kg C m-2 and the median pixel-based uncertainty (SD of prediction error) was 0.38 kg C m-2. There were considerable amounts of burning in other cover types than black spruce and consumption in pure black spruce stands was generally higher. Fuel consumption originated primarily from the belowground fraction (median = 2.30 kg C m-2 for all cover types and 2.63 kg C m-2 for pure black spruce stands). Total carbon emissions varied considerably from year to year, with the highest emissions occurring during 2004 (67 Tg C), 2005 (44 Tg C), 2009 (25 Tg C), and 2002 (16 Tg C) and a mean of 14 Tg C per year between 2001 and 2012. Our analysis highlights the importance of accounting for the spatial heterogeneity within fuels and consumption when extrapolating emissions in space and time. This data on daily burned area and emissions may be useful for in understanding controls and limits on fire growth, and predicting potential feedbacks of changing fire regimes.

scholarly journals Spatial and temporal variability in the ratio of trace gases emitted from biomass burning

2011 ◽  
Vol 11 (8) ◽  
pp. 3611-3629 ◽  
Author(s):  
T. T. van Leeuwen ◽  
G. R. van der Werf
Keyword(s):  
Temporal Variability ◽  
Field Measurement ◽  
Environmental Variables ◽  
Trace Gases ◽  
Measurement Techniques ◽  
Arithmetic Mean ◽  
Fire Season ◽  
Burned Area ◽  
Spatial And Temporal Variability ◽  
Fire Emissions

Abstract. Fires are a major source of trace gases and aerosols to the atmosphere. The amount of biomass burned is becoming better known, most importantly due to improved burned area datasets and a better representation of fuel consumption. The spatial and temporal variability in the partitioning of biomass burned into emitted trace gases and aerosols, however, has received relatively little attention. To convert estimates of biomass burned to trace gas and aerosol emissions, most studies have used emission ratios (or emission factors (EFs)) based on the arithmetic mean of field measurement outcomes, stratified by biome. However, EFs vary substantially in time and space, even within a single biome. In addition, it is unknown whether the available field measurement locations provide a representative sample for the various biomes. Here we used the available body of EF literature in combination with satellite-derived information on vegetation characteristics and climatic conditions to better understand the spatio-temporal variability in EFs. While focusing on CO, CH4, and CO2, our findings are also applicable to other trace gases and aerosols. We explored relations between EFs and different measurements of environmental variables that may correlate with part of the variability in EFs (tree cover density, vegetation greenness, temperature, precipitation, and the length of the dry season). Although reasonable correlations were found for specific case studies, correlations based on the full suite of available measurements were lower and explained about 33%, 38%, 19%, and 34% of the variability for respectively CO, CH4, CO2, and the Modified Combustion Efficiency (MCE). This may be partly due to uncertainties in the environmental variables, differences in measurement techniques for EFs, assumptions on the ratio between flaming and smoldering combustion, and incomplete information on the location and timing of EF measurements. We derived new mean EFs, using the relative importance of each measurement location with regard to fire emissions. These weighted averages were relatively similar to the arithmetic mean. When using relations between the environmental variables and EFs to extrapolate to regional and global scales, we found substantial differences, with for savannas 13% and 22% higher CO and CH4 EFs than the arithmetic mean of the field studies, possibly linked to an underrepresentation of woodland fires in EF measurement locations. We argue that from a global modeling perspective, future measurement campaigns could be more beneficial if measurements are made over the full fire season, and if relations between ambient conditions and EFs receive more attention.

scholarly journals African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data

2021 ◽  
Vol 118 (9) ◽  
pp. e2011160118
Author(s):  
Ruben Ramo ◽  
Ekhi Roteta ◽  
Ioannis Bistinas ◽  
Dave van Wees ◽  
Aitor Bastarrika ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Spatial Resolution ◽  
Carbon Emissions ◽  
Sub Saharan Africa ◽  
Burned Area ◽  
Fire Emissions ◽  
Coarse Spatial Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sub Saharan ◽  
Sentinel 2

Fires are a major contributor to atmospheric budgets of greenhouse gases and aerosols, affect soils and vegetation properties, and are a key driver of land use change. Since the 1990s, global burned area (BA) estimates based on satellite observations have provided critical insights into patterns and trends of fire occurrence. However, these global BA products are based on coarse spatial-resolution sensors, which are unsuitable for detecting small fires that burn only a fraction of a satellite pixel. We estimated the relevance of those small fires by comparing a BA product generated from Sentinel-2 MSI (Multispectral Instrument) images (20-m spatial resolution) with a widely used global BA product based on Moderate Resolution Imaging Spectroradiometer (MODIS) images (500 m) focusing on sub-Saharan Africa. For the year 2016, we detected 80% more BA with Sentinel-2 images than with the MODIS product. This difference was predominately related to small fires: we observed that 2.02 Mkm2 (out of a total of 4.89 Mkm2) was burned by fires smaller than 100 ha, whereas the MODIS product only detected 0.13 million km2 BA in that fire-size class. This increase in BA subsequently resulted in increased estimates of fire emissions; we computed 31 to 101% more fire carbon emissions than current estimates based on MODIS products. We conclude that small fires are a critical driver of BA in sub-Saharan Africa and that including those small fires in emission estimates raises the contribution of biomass burning to global burdens of (greenhouse) gases and aerosols.

scholarly journals Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)

2010 ◽  
Vol 10 (23) ◽  
pp. 11707-11735 ◽  
Author(s):  
G. R. van der Werf ◽  
J. T. Randerson ◽  
L. Giglio ◽  
G. J. Collatz ◽  
M. Mu ◽  
...  
Keyword(s):  
South America ◽  
Carbon Emissions ◽  
Agricultural Waste ◽  
Trace Gases ◽  
Plant Productivity ◽  
Tropical Deforestation ◽  
Burned Area ◽  
Fire Emissions ◽  
Active Fire ◽  
Peat Fires

Abstract. New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

scholarly journals Global Wildfire Outlook Forecast with Neural Networks

2020 ◽  
Vol 12 (14) ◽  
pp. 2246
Author(s):  
Yongjia Song ◽  
Yuhang Wang
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
South America ◽  
Land Cover ◽  
Southern Africa ◽  
Burned Area ◽  
Good Prediction ◽  
Wildfire Occurrence ◽  
Fire Emissions ◽  
Burned Areas

Wildfire occurrence and spread are affected by atmospheric and land-cover conditions, and therefore meteorological and land-cover parameters can be used in area burned prediction. We apply three forecast methods, a generalized linear model, regression trees, and neural networks (Levenberg–Marquardt backpropagation) to produce monthly wildfire predictions 1 year in advance. The models are trained using the Global Fire Emissions Database version 4 with small fires (GFEDv4s). Continuous 1-year monthly fire predictions from 2011 to 2015 are evaluated with GFEDs data for 10 major fire regions around the globe. The predictions by the neural network method are superior. The 1-year moving predictions have good prediction skills over these regions, especially over the tropics and the southern hemisphere. The temporal refined index of agreement (IOA) between predictions and GFEDv4s regional burned areas are 0.82, 0.82, 0.8, 0.75, and 0.56 for northern and southern Africa, South America, equatorial Asia and Australia, respectively. The spatial refined IOA for 5-year averaged monthly burned area range from 0.69 in low-fire months to 0.86 in high-fire months over South America, 0.3–0.93 over northern Africa, 0.69–0.93 over southern Africa, 0.47–0.85 over equatorial Asia, and 0.53–0.8 over Australia. For fire regions in the northern temperate and boreal regions, the temporal and spatial IOA between predictions and GFEDv4s data in fire seasons are 0.7–0.79 and 0.24–0.83, respectively. The predictions in high-fire months are better than low-fire months. This study illustrates the feasibility of global fire activity outlook forecasts using a neural network model and the method can be applied to quickly assess the potential effects of climate change on wildfires.

scholarly journals Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)

2010 ◽  
Vol 10 (6) ◽  
pp. 16153-16230 ◽  
Author(s):  
G. R. van der Werf ◽  
J. T. Randerson ◽  
L. Giglio ◽  
G. J. Collatz ◽  
M. Mu ◽  
...  
Keyword(s):  
South America ◽  
Carbon Emissions ◽  
Agricultural Waste ◽  
Trace Gases ◽  
Plant Productivity ◽  
Tropical Deforestation ◽  
Burned Area ◽  
Fire Emissions ◽  
Active Fire ◽  
Peat Fires

Abstract. New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used burned area estimates based on Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and Advanced Very High Resolution Radiometer (AVHRR) derived estimates of plant productivity during the same period. Average global fire carbon emissions were 2.0 Pg yr−1 with significant interannual variability during 1997–2001 (2.8 Pg yr−1 in 1998 and 1.6 Pg yr−1 in 2001). Emissions during 2002–2007 were relatively constant (around 2.1 Pg yr−1) before declining in 2008 (1.7 Pg yr−1) and 2009 (1.5 Pg yr−1) partly due to lower deforestation fire emissions in South America and tropical Asia. During 2002–2007, emissions were highly variable from year-to-year in many regions, including in boreal Asia, South America, and Indonesia, but these regional differences cancelled out at a global level. During the MODIS era (2001–2009), most fire carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C yr−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

Fire emissions estimates in Siberia: evaluation of uncertainties in area burned, land cover, and fuel consumption

2013 ◽  
Vol 43 (5) ◽  
pp. 493-506 ◽  
Author(s):  
Elena A. Kukavskaya ◽  
Amber J. Soja ◽  
Alexander P. Petkov ◽  
Evgeni I. Ponomarev ◽  
Galina A. Ivanova ◽  
...  
Keyword(s):  
Land Cover ◽  
Fuel Consumption ◽  
Boreal Forests ◽  
Carbon Budget ◽  
Natural Disturbance ◽  
Weather Conditions ◽  
Burned Area ◽  
Data Sets ◽  
Fire Emissions ◽  
Area Burned

Boreal forests constitute the world's largest terrestrial carbon pools. The main natural disturbance in these forests is wildfire, which modifies the carbon budget and atmosphere, directly and indirectly. Wildfire emissions in Russia contribute substantially to the global carbon cycle and have potentially important feedbacks to changing climate. Published estimates of carbon emissions from fires in Russian boreal forests vary greatly depending on the methods and data sets used. We examined various fire and vegetation products used to estimate wildfire emissions for Siberia. Large (up to fivefold) differences in annual and monthly area burned estimates for Siberia were found among four satellite-based fire data sets. Official Russian data were typically less than 10% of satellite estimates. Differences in the estimated proportion of annual burned area within each ecosystem were as much as 40% among five land-cover products. As a result, fuel consumption estimates would be expected to vary widely (3%–98%) depending on the specific vegetation mapping product used and as a function of weather conditions. Verification and validation of burned area and land-cover data sets along with the development of fuel maps and combustion models are essential for accurate Siberian wildfire emission estimates, which are central to balancing the carbon budget and assessing feedbacks to climate change.

scholarly journals Contrasting tree-cover loss and subsequent land cover in two neotropical forest regions: sample-based assessment of the Mexican Yucatán and Argentine Chaco

2018 ◽  
Vol 13 (6) ◽  
pp. 549-564 ◽  
Author(s):  
Alexander Krylov ◽  
Marc K. Steininger ◽  
Matthew C. Hansen ◽  
Peter V. Potapov ◽  
Stephen V. Stehman ◽  
...  
Keyword(s):  
Land Cover ◽  
Tree Cover ◽  
Neotropical Forest ◽  
Forest Regions

scholarly journals Quantifying Tree Cover Loss in Urban Forests within Nairobi City Metropolitan Area from Earth Observation Data

2020 ◽  
Vol 3 (1) ◽  
pp. 78
Author(s):  
Francis Oloo ◽  
Godwin Murithi ◽  
Charlynne Jepkosgei
Keyword(s):  
Land Cover ◽  
Metropolitan Area ◽  
Land Surface ◽  
Urban Forest ◽  
Urban Forests ◽  
Earth Observation ◽  
Tree Cover ◽  
Observation Data ◽  
Vegetation Health ◽  
Earth Observation Data

Urban forests contribute significantly to the ecological integrity of urban areas and the quality of life of urban dwellers through air quality control, energy conservation, improving urban hydrology, and regulation of land surface temperatures (LST). However, urban forests are under threat due to human activities, natural calamities, and bioinvasion continually decimating forest cover. Few studies have used fine-scaled Earth observation data to understand the dynamics of tree cover loss in urban forests and the sustainability of such forests in the face of increasing urban population. The aim of this work was to quantify the spatial and temporal changes in urban forest characteristics and to assess the potential drivers of such changes. We used data on tree cover, normalized difference vegetation index (NDVI), and land cover change to quantify tree cover loss and changes in vegetation health in urban forests within the Nairobi metropolitan area in Kenya. We also used land cover data to visualize the potential link between tree cover loss and changes in land use characteristics. From approximately 6600 hectares (ha) of forest land, 720 ha have been lost between 2000 and 2019, representing about 11% loss in 20 years. In six of the urban forests, the trend of loss was positive, indicating a continuing disturbance of urban forests around Nairobi. Conversely, there was a negative trend in the annual mean NDVI values for each of the forests, indicating a potential deterioration of the vegetation health in the forests. A preliminary, visual inspection of high-resolution imagery in sample areas of tree cover loss showed that the main drivers of loss are the conversion of forest lands to residential areas and farmlands, implementation of big infrastructure projects that pass through the forests, and extraction of timber and other resources to support urban developments. The outcome of this study reveals the value of Earth observation data in monitoring urban forest resources.

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