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Assessing variability and long-term trends in burned area by merging multiple satellite fire products
L. Giglio, J. T. Randerson, G. R. van der Werf, P. S. Kasibhatla, G. J. Collatz, D. C. Morton,R. S. DeFries
Biogeosciences (BG) & Discussions (BGD) , 2010,
Abstract: Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.
Assessing variability and long-term trends in burned area by merging multiple satellite fire products
L. Giglio,J. T. Randerson,G. R. van der Werf,P. S. Kasibhatla
Biogeosciences Discussions , 2009,
Abstract: Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees to develop relationships between burned area and Terra MODIS active fire data. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) allowed the data set to be extended prior to the MODIS era. With our data set we estimated the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 12 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3) estimates of trace gas and aerosol emissions.
Increasing Spatial Detail of Burned Scar Maps Using IRS?AWiFS Data for Mediterranean Europe  [PDF]
Fernando Sedano,Pieter Kempeneers,Peter Strobl,Daniel McInerney,Jesús San Miguel
Remote Sensing , 2012, DOI: 10.3390/rs4030726
Abstract: A two stage burned scar detection approach is applied to produce a burned scar map for Mediterranean Europe using IRS-AWiFS imagery acquired at the end of the 2009 fire season. The first stage identified burned scar seeds based on a learning algorithm (Artificial Neural Network) coupled with a bootstrap aggregation process. The second stage implemented a region growing process to extend the area of the burned scars. Several ancillary datasets were used for the accuracy assessment and a final visual check was performed to refine the burned scar product. Training data for the learning algorithm were obtained from MODIS-based polygons, which were generated by the Rapid Damage Assessment module of the European Forest Fire Information System. The map produced from this research is the first attempt to increase the spatial detail of current burned scar maps for the Mediterranean region. The map has been analyzed and compared to existing burned area polygons from the European Forest Fire Information System. The comparison showed that the IRS-AWiFS-based burned scar map improved the delineation of burn scars; in addition the process identified a number of small burned scars that were not detected on lower resolution sensor data. Nonetheless, the results do not clearly support the improved capability for the detection of smaller burned scars. A number of reasons can be provided for the under-detection of burned scars, these include: the lack of a full coverage and cloud free imagery, the time lag between forest fires and image acquisition date and the occurrence of fires after the image acquisition dates. On the other hand, the limited spectral information combined with the presence of undetected cloud shadows and shaded slopes are reasons for the over-estimation of small burned scars.
Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)
G. R. van der Werf, J. T. Randerson, L. Giglio, G. J. Collatz, M. Mu, P. S. Kasibhatla, D. C. Morton, R. S. DeFries, Y. Jin,T. T. van Leeuwen
Atmospheric Chemistry and Physics (ACP) & Discussions (ACPD) , 2010,
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 contribut
Interannual Changes of Fire Activity in the Protected Areas of the SUN Network and Other Parks and Reserves of the West and Central Africa Region Derived from MODIS Observations  [PDF]
Jean-Marie Grégoire,Dario Simonetti
Remote Sensing , 2010, DOI: 10.3390/rs2020446
Abstract: Time series of fire occurrence, derived from MODIS data, have been used to characterise the spatio-temporal distribution of fire events during the 2004–2009 period in 17 protected areas (PAs) of West and Central Africa, with particular attention to those of the SUN network in Senegal, Burkina Faso, Benin and Niger. The temporal distribution of the fire activity and the number of fire occurences are quite different inside the PAs and in their surrounding area. A progressive increase of the length of the burning season is observed in the West Africa PAs. Quantitatively, the general trend over the last five years is an increase of the fire density (+22%) inside the PAs and a decrease (?27%) outside. The results indicate that the capacity of the PAs to maintain the biological diversity of the region is probably decreasing due to the combined effects of the anthropic pressure inside the PAs and of an on-going isolation process.
Mega fire emissions in Siberia: potential supply of soluble iron from forests to the ocean  [PDF]
A. Ito
Biogeosciences Discussions , 2011, DOI: 10.5194/bgd-8-1483-2011
Abstract: Significant amounts of carbon and nutrients are released to the atmosphere due to large fires in forests. Characterization of the spatial distribution and temporal variation of the intense fire emissions is crucial for assessing the atmospheric loadings of aerosols and trace gases. This paper discusses issues of the representation of forest fires in the estimation of emissions and the application to an atmospheric chemistry transport model (CTM). The potential contribution of forest fires to the deposition of soluble iron (Fe) into the ocean is highlighted, with a focus on mega fires in eastern Siberia. Satellite products of burned area, active fire, and land cover are used to estimate biomass burning emissions in conjunction with a biogeochemical model. Satellite-derived plume height from MISR is used for the injection height of boreal forest fire emissions. This methodology is applied to quantify fire emission rates in each three-dimensional grid location in the high latitude Northern Hemisphere (> 30° N latitude) over a 5-year period from 2001 to 2005. There is large interannual variation in forest burned area during 2001–2005 (13–51 × 103 km2 yr 1) which results in a corresponding variation in the annual emissions of carbon monoxide (CO) (12–78 Tg CO yr 1). Satellite observations of CO from MOPITT are used to evaluate the model performance in simulating the spatial distribution and temporal variation of the fire emissions. During the major Siberian fire seasons in the summer of 2002 and in the spring of 2003, the model results for CO enhancements due to intense fires are in good agreement with MOPITT observations. These fire emission rates are applied to the aerosol chemistry transport model to examine the relative importance of biomass burning sources of soluble iron compared to those from dust sources. Compared to the dust sources without the atmospheric processing by acidic species, extreme fire events contribute to a significant deposition of soluble iron (10–60%) to downwind regions over the western North Pacific Ocean. It may imply that the supply of nutrients from large forest fires plays a role as a negative biosphere-climate feedback with regards to the ocean fertilization.
Mega fire emissions in Siberia: potential supply of bioavailable iron from forests to the ocean
A. Ito
Biogeosciences (BG) & Discussions (BGD) , 2011,
Abstract: Significant amounts of carbon and nutrients are released to the atmosphere due to large fires in forests. Characterization of the spatial distribution and temporal variation of the intense fire emissions is crucial for assessing the atmospheric loadings of trace gases and aerosols. This paper discusses issues of the representation of forest fires in the estimation of emissions and the application to an atmospheric chemistry transport model (CTM). The potential contribution of forest fires to the deposition of bioavailable iron (Fe) into the ocean is highlighted, with a focus on mega fires in eastern Siberia. Satellite products of burned area, active fire, and land cover are used to estimate biomass burning emissions in conjunction with a biogeochemical model. Satellite-derived plume height from MISR is used for the injection height of boreal forest fire emissions. This methodology is applied to quantify fire emission rates in each three-dimensional grid location in the high latitude Northern Hemisphere (>30° N latitude) over a 5-yr period from 2001 to 2005. There is large interannual variation in forest burned area during 2001–2005 (13–49 × 103 km2 yr 1) which results in a corresponding variation in the annual emissions of carbon monoxide (CO) (14–81 Tg CO y 1). Satellite observations of CO column from MOPITT are used to evaluate the model performance in simulating the spatial distribution and temporal variation of the fire emissions. The model results for CO enhancements due to eastern Siberian fires are in good agreement with MOPITT observations. These validation results suggest that the model using emission rates estimated in this work is able to describe the interannual changes in CO due to intense forest fires. Bioavailable iron is derived from atmospheric processing of relatively insoluble iron from desert sources by anthropogenic pollutants (mainly sulfuric acid formed from oxidation of SO2) and from direct emissions of soluble iron from combustion sources. Emission scenarios for IPCC AR5 report (Intergovernmental Panel on Climate Change; Fifth Assessment Report) suggest that anthropogenic SO2 emissions are suppressed in the future to improve air quality. In future warmer and drier climate, severe fire years such as 2003 may become more frequent in boreal regions. The fire emission rates estimated in this study are applied to the aerosol chemistry transport model to examine the relative importance of biomass burning sources of soluble iron compared to those from dust sources. The model reveals that extreme fire events contribute to a significant deposition of soluble iron (20–40 %) to downwind regions over the western North Pacific Ocean, compared to the dust sources with no atmospheric processing by acidic species. These results suggest that the supply of nutrients from large forest fires plays a role as a negative biosphere-climate feedback with regards to the ocean fertilization.
Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data  [PDF]
Sarah Harris,Sander Veraverbeke,Simon Hook
Remote Sensing , 2011, DOI: 10.3390/rs3112403
Abstract: Wildland fires are a yearly recurring phenomenon in many terrestrial ecosystems. Accurate fire severity estimates are of paramount importance for modeling fire-induced trace gas emissions and rehabilitating post-fire landscapes. We used high spatial and high spectral resolution MODIS/ASTER (MASTER) airborne simulator data acquired over four 2007 southern California burns to evaluate the effectiveness of 19 different spectral indices, including the widely used Normalized Burn Ratio (NBR), for assessing fire severity in southern California chaparral. Ordinal logistic regression was used to assess the goodness-of-fit between the spectral index values and ordinal field data of severity. The NBR and three indices in which the NBR is enhanced with surface temperature or emissivity data revealed the best performance. Our findings support the operational use of the NBR in chaparral ecosystems by Burned Area Emergency Rehabilitation (BAER) projects, and demonstrate the potential of combining optical and thermal data for assessing fire severity. Additional testing in more burns, other ecoregions and different vegetation types is required to fully understand how (thermally enhanced) spectral indices relate to fire severity.
Fire, drought and El Ni o relationships on Borneo during the pre-MODIS era (1980–2000)  [PDF]
M. J. Wooster,G. L. W. Perry,A. Zoumas
Biogeosciences Discussions , 2011, DOI: 10.5194/bgd-8-975-2011
Abstract: Borneo (Indonesia) is Earth's third largest island, and the location of both extensive areas of rainforest and tropical peatlands. It is the site of both regular (seasonal) biomass burning associated with forest clearance and agricultural production preparations, and occasional, but much more severe, large fire episodes releasing enormous volumes of carbon from burning vegetation and peat. The latter's extreme magnitude is believed to be associated with the severity of El Ni o related droughts. Over the last decade, data from the EOS MODIS satellite instruments have been used to study fire on Borneo, but earlier large fire events remain less well documented. Here we focus on the study of Borneo's large fire episodes in the "pre-MODIS" era, and specifically a 20 year period covering both the two strongest El Ni o-Southern Oscillation (ENSO) events on record (1997–1998 and 1982–1983) and an unprecedented series of more frequent, but weaker, El Ni o's. For the five El Ni o episodes occurring between 1980 and 2000, we develop quantitative measures of Borneo's fire activity based on active fire counts derived from NOAA AVHRR Global Area Coverage (CAC) satellite data. We use these metrics to investigate relationships between the strength and timing of the El Ni o-Southern Oscillation (ENSO) event, the associated drought, and the fire activity magnitude. Significant fires are identified across parts of South, Central, East and West Kalimantan, always occurring within two or three fire sub-seasons separated by monsoons. We find that the length, overall strength, and growth rate of individual El Ni o episodes effects the extent and harshness of the drought, and the magnitude of fire activity. We confirm significant correlations between monthly ENSO index and rainfall deficit measures, and between rainfall deficit and fire. The two strongest El Ni o episodes are accompanied by the most abundant fires, showing two and three times the active fire count seen in the next largest fire year. The most significant statistical association found between ENSO strength and fire activity is that between the 16-month sum of the Ni o-3 anomaly and the simultaneously recorded number of active fire counts (r2=0.98, based on the five El Ni o episodes between 1980 and 2000). We independently test our relationship using data from the 2002–2003 El Ni o event, and find that it continues to be robust. Our results confirm that the ENSO phenomenon, via its effects on precipitation, is the primary large-scale, short-term climatic factor controlling fire activity in Borneo.
Timing Constraints on Remote Sensing of Wildland Fire Burned Area in the Southeastern US  [PDF]
Joshua J. Picotte,Kevin Robertson
Remote Sensing , 2011, DOI: 10.3390/rs3081680
Abstract: Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.
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