A Global Inventory of Burned Areas at 1 Km Resolution for the Year 2000 Derived from Spot Vegetation Data

Biomass burning constitutes a major contribution to global emissions of carbon dioxide, carbon monoxide, methane, greenhouse gases and aerosols. Furthermore, biomass burning has an impact on health, transport, the environment and land use. Vegetation fires are certainly not recent phenomena and the impacts are not always negative. However, evidence suggests that fires are becoming more frequent and there is a large increase in the number of fires being set by humans for a variety of reasons. Knowledge of the interactions and feedbacks between biomass burning, climate and carbon cycling is needed to help the prediction of climate change scenarios. To obtain this knowledge, the scientific community requires, in the first instance, information on the spatial and temporal distribution of biomass burning at the global scale. This paper presents an inventory of burned areas at monthly time periods for the year 2000 at a resolution of 1 kilometer (km) and is available to the scientific community at no cost. The burned area products have been derived from a single source of satellite-derived images, the SPOT VEGETATION S1 1 km product, using algorithms developed and calibrated at regional scales by a network of partners. In this paper, estimates of burned area, number of burn scars and average size of the burn scar are described for each month of the year 2000. The information is reported at the country level. This paper makes a significant contribution to understanding the effect of biomass burning on atmospheric chemistry and the storage and cycling of carbon by constraining one of the main parameters used in the calculation of gas emissions.

[1]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[2]  J. Randerson,et al.  Continental-Scale Partitioning of Fire Emissions During the 1997 to 2001 El Niño/La Niña Period , 2003, Science.

[3]  Joel S. Levine,et al.  Satellite analysis of the severe 1987 forest fires in northern China and southeastern Siberia , 1994 .

[4]  S. Flasse,et al.  Characterizing the spectral-temporal response of burned savannah using in situ spectroradiometry and infrared thermometry , 2000 .

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

[6]  J. Grégoire,et al.  The GBA2000 initiative: Developing a global burnt area database from SPOT-VEGETATION imagery , 2003 .

[7]  Anthony C. Janetos,et al.  Using Remote Sensing to Assess Russian Forest Fire Carbon Emissions , 2002 .

[8]  M. Andreae,et al.  Emission of trace gases and aerosols from biomass burning , 2001 .

[9]  D. Cahoon,et al.  Determining Effects of Area Burned and Fire Severity on Carbon Cycling and Emissions in Siberia , 2002 .

[10]  James M. Vose,et al.  Biomass Burning and Global Change Volume 2 Biomass Burning in South America , Southeast Asia , and Temperate and Boreal Ecosystems , and the Oil Fires of Kuwait , 2003 .

[11]  J. Cihlar,et al.  Hotspot and NDVI Differencing Synergy (HANDS): A New Technique for Burned Area Mapping over Boreal Forest , 2000 .

[12]  J. Pereira,et al.  Radiometric analysis of SPOT-VEGETATION images for burnt area detection in Northern Australia , 2002 .

[13]  A MULTITEMPORAL CHANGE-DETECTION ALGORITHM FOR THE MONITORING OF BURNT AREAS WITH SPOT-VEGETATION DATA , 2002 .

[14]  Christopher M. Bishop,et al.  Classification and regression , 1997 .

[15]  B. K. Wyatt,et al.  The potential of SPOT-Vegetation data for fire scar detection in boreal forests , 1998 .

[16]  Shinichi Morishita,et al.  On Classification and Regression , 1998, Discovery Science.

[17]  D. Roy,et al.  Burned area mapping using multi-temporal moderate spatial resolution data—a bi-directional reflectance model-based expectation approach , 2002 .

[18]  F. Siegert,et al.  Increased damage from fires in logged forests during droughts caused by El Niño , 2001, Nature.

[19]  Kelly K. Caylor,et al.  A simulation analysis of the detectability of understory burns in miombo woodlands , 2004 .

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

[21]  Belward Alan steven,et al.  The Advance of Burnt Areas in Central Africa as Detected by ERS-1 ATSR-1. , 1998 .

[22]  Daniela Stroppiana,et al.  Satellite monitoring of fire in the EXPRESSO study area during the 1996 dry season experiment: Active fires, burnt area, and atmospheric emissions , 1999 .

[23]  Ignazio Gallo,et al.  EXPLOITING SPATIAL AND TEMPORAL INFORMATION FOR EXTRACTING BURNED AREAS FROM TIME SERIES OF SPOT-VGT DATA , 2001 .

[24]  J. Lelieveld,et al.  A 1°×1° resolution data set of historical anthropogenic trace gas emissions for the period 1890–1990 , 2001 .

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

[26]  P. Dunbar,et al.  DEVELOPMENT & ASSESSMENT OF THE GLOBAL LAND ONE-KM BASE ELEVATION DIGITAL ELEVATION MODEL (GLOBE) , 1998 .

[27]  E. Dwyer,et al.  Characterization of the spatio‐temporal patterns of global fire activity using satellite imagery for the period April 1992 to March 1993 , 2000 .

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

[29]  José M. C. Pereira,et al.  A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping , 1999, IEEE Trans. Geosci. Remote. Sens..

[30]  A. Fernández,et al.  Automatic mapping of surfaces affected by forest fires in Spain using AVHRR NDVI composite image data , 1997 .

[31]  J. Roujean,et al.  A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data , 1992 .

[32]  J. Pereira,et al.  A contribution for a global burned area map. , 2002 .

[33]  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 .

[34]  P. Barbosa,et al.  An Algorithm for Extracting Burned Areas from Time Series of AVHRR GAC Data Applied at a Continental Scale , 1999 .

[35]  Gerhard Wotawa,et al.  Inter‐annual variability of summertime CO concentrations in the Northern Hemisphere explained by boreal forest fires in North America and Russia , 2001 .

[36]  J. Colby,et al.  Topographic Normalization in Rugged Terrain , 1991 .

[37]  E. Kasischke,et al.  Fire, Global Warming, and the Carbon Balance of Boreal Forests , 1995 .

[38]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[39]  Robert H. Fraser,et al.  Multi‐temporal Mapping of Burned Forest over Canada Using Satellite‐based Change Metrics , 2003 .

[40]  M. Schultz.  On the use of ATSR fire count data to estimate the seasonal and interannual variability of vegetation fire emissions , 2002 .

[41]  J. Levine.  Biomass Burning from the Perspective of the Global Carbon Cycle , 1991 .

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