Global burned area and biomass burning emissions from small fires

In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001–2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia—regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes.

[1]  L. Giglio MODIS Collection 5 Active Fire Product User's Guide Version 2.5 , 2013 .

[2]  J. Randerson,et al.  Global impact of contemporary smoke aerosols from landscape fires on climate and the Hadley circulation , 2012 .

[3]  J. Randerson,et al.  Evaluating greenhouse gas emissions inventories for agricultural burning using satellite observations of active fires. , 2012, Ecological applications : a publication of the Ecological Society of America.

[4]  D. Morton,et al.  Impact of sensor degradation on the MODIS NDVI time series , 2012 .

[5]  Michael Brauer,et al.  Estimated Global Mortality Attributable to Smoke from Landscape Fires , 2012, Environmental health perspectives.

[6]  O. Arino,et al.  Global night-time fire season timing and fire count trends using the ATSR instrument series , 2012 .

[7]  J. Randerson,et al.  Daily and 3‐hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide , 2011 .

[8]  D. Riaño,et al.  Quantifying burned area for North American forests: Implications for direct reduction of carbon stocks , 2011 .

[9]  J. Randerson,et al.  Model comparisons for estimating carbon emissions from North American wildland fire , 2011 .

[10]  Christopher I. Roos,et al.  The human dimension of fire regimes on Earth , 2011, Journal of biogeography.

[11]  J. Randerson,et al.  Forecasting Fire Season Severity in South America Using Sea Surface Temperature Anomalies , 2011, Science.

[12]  James T. Randerson,et al.  The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN , 2011 .

[13]  P. Friedlingstein,et al.  Modeling fire and the terrestrial carbon balance , 2011 .

[14]  A. Arneth,et al.  Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations , 2011 .

[15]  G. Roberts,et al.  Integration of geostationary FRP and polar-orbiter burned area datasets for an enhanced biomass burning inventory , 2011 .

[16]  M. Razinger,et al.  Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power , 2011 .

[17]  R. DeFries,et al.  Mapping canopy damage from understory fires in Amazon forests using annual time series of Landsat and MODIS data , 2011 .

[18]  David J. Diner,et al.  Dynamics of fire plumes and smoke clouds associated with peat and deforestation fires in Indonesia , 2011 .

[19]  J. Randerson,et al.  The impacts and implications of an intensifying fire regime on Alaskan boreal forest composition and albedo , 2011, Global Change Biology.

[20]  G. Roberts,et al.  Addressing the spatiotemporal sampling design of MODIS to provide estimates of the fire radiative energy emitted from Africa , 2011 .

[21]  Yiqi Luo,et al.  Dynamic disequilibrium of the terrestrial carbon cycle under global change. , 2011, Trends in ecology & evolution.

[22]  E. Kasischke,et al.  Recent acceleration of biomass burning and carbon losses in Alaskan forests and peatlands , 2011 .

[23]  J. G. Borges,et al.  Characterization of wildfires in Portugal , 2011, European Journal of Forest Research.

[24]  J. Randerson,et al.  Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009) , 2010 .

[25]  G. Roberts,et al.  New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America , 2010 .

[26]  Y. Shimabukuro,et al.  The Incidence of Fire in Amazonian Forests with Implications for REDD , 2010, Science.

[27]  Damien Sulla-Menashe,et al.  MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .

[28]  J. Randerson,et al.  Assessing variability and long-term trends in burned area by merging multiple satellite fire products , 2009 .

[29]  D. Roy,et al.  Strategies for the fusion of satellite fire radiative power with burned area data for fire radiative energy derivation , 2009 .

[30]  C. Justice,et al.  The spatial and temporal distribution of crop residue burning in the contiguous United States. , 2009, The Science of the total environment.

[31]  Gareth Roberts,et al.  An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power , 2009 .

[32]  Sundar A. Christopher,et al.  Global Monitoring and Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions (FLAMBE) Program , 2009, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[33]  Mikhail Zhizhin,et al.  A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data , 2009 .

[34]  B. Malamud,et al.  Development of a virtual active fire product for Africa through a synthesis of geostationary and polar orbiting satellite data , 2009 .

[35]  E. Vermote,et al.  Estimating biomass consumed from fire using MODIS FRE , 2009 .

[36]  David P. Roy,et al.  Southern Africa Validation of the MODIS, L3JRC, and GlobCarbon Burned-Area Products , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[37]  Samuel S. P. Shen,et al.  Human amplification of drought-induced biomass burning in Indonesia since 1960 , 2009 .

[38]  D. Roy,et al.  An active-fire based burned area mapping algorithm for the MODIS sensor , 2009 .

[39]  R. Betts,et al.  Fire risk in Amazonia due to climate change in the HadCM3 climate model: Potential interactions with deforestation , 2008 .

[40]  G. Roberts,et al.  Annual and diurnal african biomass burning temporal dynamics , 2008 .

[41]  J. Randerson,et al.  Climate controls on the variability of fires in the tropics and subtropics , 2008 .

[42]  J. Townshend,et al.  Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data , 2008, Proceedings of the National Academy of Sciences.

[43]  C. Justice,et al.  Global characterization of fire activity: toward defining fire regimes from Earth observation data , 2008 .

[44]  Atul K. Jain,et al.  Can we reconcile differences in estimates of carbon fluxes from land-use change and forestry for the 1990s? , 2008 .

[45]  Shobha Kondragunta,et al.  Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product , 2008 .

[46]  J. Pereira,et al.  Global wildland fire emissions from 1960 to 2000 , 2008 .

[47]  D. Morton,et al.  Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data , 2008 .

[48]  Charles Ichoku,et al.  Relationships between energy release, fuel mass loss, and trace gas and aerosol emissions during laboratory biomass fires , 2008 .

[49]  J. Grégoire,et al.  A new, global, multi‐annual (2000–2007) burnt area product at 1 km resolution , 2008 .

[50]  B. Quayle,et al.  A Project for Monitoring Trends in Burn Severity , 2007 .

[51]  T. Loboda,et al.  Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data , 2007 .

[52]  L. Giglio Characterization of the tropical diurnal fire cycle using VIRS and MODIS observations , 2007 .

[53]  F. Chapin,et al.  Human Impacts on the Fire Regime of Interior Alaska: Interactions among Fuels, Ignition Sources, and Fire Suppression , 2006, Ecosystems.

[54]  Yonghe Wang,et al.  Spatial patterns of forest fires in Canada, 1980-1999 , 2006 .

[55]  Jeffrey T. Morisette,et al.  Validation of active fire detection from moderate-resolution satellite sensors: the MODIS example in northern eurasia , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[56]  C. Justice,et al.  Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors , 2006 .

[57]  Xiaoyang Zhang,et al.  Estimating emissions from fires in North America for air quality modeling , 2006 .

[58]  F. Achard,et al.  Ecology: Human role in Russian wild fires , 2006, Nature.

[59]  Y. Kaufman,et al.  Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release , 2005 .

[60]  P. Laris Spatiotemporal problems with detecting and mapping mosaic fire regimes with coarse-resolution satellite data in savanna environments , 2005 .

[61]  J. Randerson,et al.  Global Estimation of Burned Area Using Modis Active Fire Observations , 2022 .

[62]  D. Roy,et al.  Characterizing the surface heterogeneity of fire effects using multi‐temporal reflective wavelength data , 2005 .

[63]  C. Justice,et al.  Validation of the MODIS active fire product over Southern Africa with ASTER data , 2005 .

[64]  I. Prentice,et al.  Relationships among fire frequency, rainfall and vegetation patterns in the wet–dry tropics of northern Australia: an analysis based on NOAA‐AVHRR data , 2005 .

[65]  Ana C. L. Sá,et al.  Comparison of burned area estimates derived from SPOT-VEGETATION and Landsat ETM+ data in Africa: Influence of spatial pattern and vegetation type , 2005 .

[66]  C. Field,et al.  Fire history and the global carbon budget: a 1°× 1° fire history reconstruction for the 20th century , 2005 .

[67]  D. Roya,et al.  Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data , 2005 .

[68]  J. W. Wagtendonk,et al.  Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity , 2004 .

[69]  D. Roy,et al.  Modeling and sensitivity analysis of fire emissions in southern Africa during SAFARI 2000 , 2004 .

[70]  S. Plummer,et al.  Burnt area detection at global scale using ATSR‐2: The GLOBSCAR products and their qualification , 2004 .

[71]  J. Pereira,et al.  Vegetation burning in the year 2000: Global burned area estimates from SPOT VEGETATION data , 2004 .

[72]  G. Brasseur,et al.  Global Wildland Fire Emission Model (GWEM): Evaluating the use of global area burnt satellite data , 2004 .

[73]  Jennifer A. Logan,et al.  An assessment of biofuel use and burning of agricultural waste in the developing world , 2003 .

[74]  Yoram J. Kaufman,et al.  An Enhanced Contextual Fire Detection Algorithm for MODIS , 2003 .

[75]  Ana C. L. Sá,et al.  An estimate of the area burned in southern Africa during the 2000 dry season using SPOT-VEGETATION satellite data , 2003 .

[76]  M. Wooster,et al.  Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products. , 2003 .

[77]  José M. C. Pereira,et al.  An algorithm for mapping burnt areas in Australia using SPOT-VEGETATION data , 2003, IEEE Trans. Geosci. Remote. Sens..

[78]  Yoram J. Kaufman,et al.  Comparative analysis of daytime fire detection algorithms using AVHRR data for the 1995 fire season in Canada: Perspective for MODIS , 2003 .

[79]  S. Page,et al.  The amount of carbon released from peat and forest fires in Indonesia during 1997 , 2002, Nature.

[80]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[81]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[82]  E. Kasischke,et al.  Analysis of the patterns of large fires in the boreal forest region of Alaska , 2002 .

[83]  F. Chapin,et al.  Principles of Terrestrial Ecosystem Ecology , 2002, Springer New York.

[84]  E. P. McClam,et al.  A Method for Satellite Identification of Surface Temperature Fields of Subpixel Resolution , 2002 .

[85]  Yves Bergeron,et al.  Role of vegetation and weather on fire behavior in the Canadian mixedwood boreal forest using two fire behavior prediction systems. , 2001 .

[86]  K. Hirsch,et al.  Direct carbon emissions from Canadian forest fires, 1959-1999 , 2001 .

[87]  C. J. Tucker,et al.  Remote sensing of fires with the TRMM VIRS , 2000 .

[88]  Jose M. Cardoso Pereira,et al.  An assessment of vegetation fire in Africa (1981–1991): Burned areas, burned biomass, and atmospheric emissions , 1999 .

[89]  C. Potter,et al.  Large-scale impoverishment of Amazonian forests by logging and fire , 1999, Nature.

[90]  D. Roy Multi-temporal active-fire based burn scar detection algorithm , 1999 .

[91]  C. Justice,et al.  Potential global fire monitoring from EOS‐MODIS , 1998 .

[92]  H. Eva,et al.  Remote Sensing of Biomass Burning in Tropical Regions: Sampling Issues and Multisensor Approach , 1998 .

[93]  Peter Z. Fulé,et al.  Restoring Ecosystem Health in Ponderosa Pine Forests of the Southwest , 1997, Journal of Forestry.

[94]  H. Poorter,et al.  The fate of acquired carbon in plants: chemical composition and construction costs , 1997 .

[95]  C. Justice,et al.  The quantity of biomass burned in southern Africa , 1996 .

[96]  C. Justice,et al.  Satellite remote sensing of fires during the SAFARI campaign using NOAA Advanced Very High Resolution Radiometer data , 1996 .

[97]  E. Kasischke,et al.  Locating and estimating the areal extent of wildfires in alaskan boreal forests using multiple-season AVHRR NDVI composite data , 1995 .

[98]  E. Prins,et al.  Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991 , 1994 .

[99]  E. Prins,et al.  Geostationary satellite detection of bio mass burning in South America , 1992 .

[100]  V. Caselles,et al.  Mapping burns and natural reforestation using thematic Mapper data , 1991 .

[101]  J. Dozier,et al.  Identification of Subresolution High Temperature Sources Using a Thermal IR Sensor , 1981 .

[102]  P. Crutzen,et al.  Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning , 1980 .

[103]  C. E. Van Wagner,et al.  Conditions for the start and spread of crown fire , 1977 .