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SAFARI 2000 1-Degree Estimates of Burned Biomass, Area, and Emissions, 2000

A new method is used to generate spatial estimates of monthly averaged biomass burned area and spatial and temporal estimates of trace gas and aerosol emissions from open fires in southern Africa.Global burned area data for the year 2000 (GBA2000) supplemented with the Along Track Scanning Radiometer (ATSR) fire count data are employed to quantify the area burned at 1-km resolution by using a fractional vegetation cover map derived from satellite observations. To account for the spatial heterogeneity in main types of vegetation within each 1-km grid cell, fuel load maps were developed from biomass density data sets for herbaceous and tree covered land together with fractional tree and vegetation cover maps. To represent the fire characteristics, land cover is classified into forests, woodlands, and grasslands, based on satellite-derived data sets for fractional tree cover. Combustion factors for each land cover type takes into account fuel composition, tree cover density, and the dryness of herbaceous vegetation. In addition, the emission factors (EF) are calculated; EF for grassland fires represent spatial and seasonal variations in fuel conditions using a modified combustion efficiency calculation. This data set contains spatial and temporal estimates of trace gas and aerosol emissions from open fires in southern Africa for the following variables:acetic acid (CH3COOH); methanol (CH3OH); methane (CH4); carbon dioxide (CO2); carbon monoxide (CO); formaldehyde (HCHO); non-methane hydrocarbons (NMHC); and particulate matter less than 2.5 um in diameter (PM2.5). Annual amounts of total area burned and CO2 emissions for southern Africa are compared to those from other authors.

MASTER: California Fire-Burn Area Emergency Response, California, August 2008

This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during four flights aboard a DOE B200 aircraft over California, U.S., from 2008-08-20 to 2008-08-27. Objectives included mapping for California Fire-Burn Area Emergency Response (BAER). This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

TROPESS Chemical Reanalysis Surface Biomass Burning NOx emissions Monthly 2-dimensional Product V1 (TRPSCRENOXBM2D) at GES DISC

The TROPESS Chemical Reanalysis Surface Biomass Burning NOx emissions Monthly 2-dimensional Product contains nitrogen oxides (NO and NO2) emissions from biomass burning sources. The data are part of the Tropospheric Chemical Reanalysis v2 (TCR-2) for the period 2005-2021. TCR-2 uses JPL's Multi-mOdel Multi-cOnstituent Chemical (MOMO-Chem) data assimilation framework that simultaneously optimizes both concentrations and emissions of multiple species from multiple satellite sensors.The data files are written in the netCDF version 4 file format, and each file contains a year of data at monthly resolution, and a spatial resolution of 1.125 x 1.125 degrees. The principal investigator for the TCR-2 data is Miyazaki, Kazuyuki.

SAFARI 2000 Emissions Estimates, MODIS Burned Area Product, Dry Season 2000

The recently generated MODIS burned area product over southern Africa for the month of September 2000 was used to calculate regional biomass burning emissions from grassland and woodland fires for a number of trace gases and particulates at 1 km spatial resolution. A dynamic regional fuel load model developed for southern Africa in support of SAFARI 2000 fire emissions modeling is used to compute spatially explicit southern Africa fuel load data. Regional grassland and woodland emissions are estimated using ecosystem-specific emission factor algorithms for carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), non-methane hydrocarbons (NMHC), and particulate matter with diameter less than 2.5 um (PM2.5) for southern African savanna fires (Korontzi et al., 2004). In addition, the emissions database for this region is expanded by incorporating emission factors for a variety of compounds, including oxygenated volatile organic compounds (OVOC), halocarbons, nitrogen oxides (NOx), ammonia (NH3), sulfur dioxide (SO2), hydrogen cyanide (HCN), and particulate ionic components measured during the SAFARI 2000 dry season field campaign.The data set archived by ORNL DAAC provides a MODIS-based estimate of CO (carbon monoxide) pyrogenic emissions (in kg) for southern Africa in September 2000 at 1 km. The data image file is stored in GeoTIFF binary format. Pyrogenic emissions of the other trace gases and particulates estimated by this study will be archived by ORNL DAAC when the data sets are finalized.

BOREAS Follow-On FLX-04 Tower Flux and Meteorological Data from NSA Burn Site

Tower flux and meteorological data were collected above 4 black spruce forest sites in the NSA that experienced stand-replacing wildfires in 1989,1981,1964 and 1930. At each site, 4-6 weeks of data were collected during the peak growing season (June-September) in either 1999 or 2000. Fluxes were measured using paired portable solar powered eddy flux systems. The data are part of an ongoing age sequence study that will result in year round eddy flux and meteorological measurements in seven sites that burned between 2 and 150 years ago.

ABoVE: Wildfire Carbon Emissions and Burned Plot Characteristics, NWT, CA, 2014-2016

This dataset provides estimates of wildfire carbon emissions and uncertainties at 30-m resolution, and measurements collected at burned and unburned field plots from the 2014 wildfire sites near Yellowknife, Northwest Territories (NWT), Canada. Field data were collected at 211 burned plots in 2015 and include site characteristics, tree cover and species, basal area, delta normalized burn ratio (dNBR), plot characteristics, soil carbon, and carbon combusted. Data were collected at 36 unburned plots with characteristics similar to the burned plots in 2016. The emission estimates were derived from a statistical modeling approach based on measurements of carbon consumption at the 211 burned field plots located in seven independent burn scars. Estimates include uncertainty of field observations of aboveground and belowground combustion, as well as prediction uncertainty from a multiplicative regression model. To apply the model across all 2014 NWT fire perimeters, the final model covariates were re-gridded to a common 30-m grid defined by the Arctic Boreal and Vulnerability Experiment (ABoVE) Project. The regression model was then applied to burned pixels defined by a threshold of Landsat-derived differenced Normalized Burn Ratio (dNBR) within fire perimeters. Derived carbon emissions and uncertainty in g/m2 are provided for each 30-m grid cell. The modeled NWT domain encompasses 29 tiles within the ABoVE 30-m reference grid system.

ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015

This dataset provides maps at 30-m resolution of landscape surface burn severity (surface litter and soil organic layers) from the 2014-2015 fires in the Northwest Territories and Northern Alberta, Canada. The maps were derived from Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) imagery and two separate multiple linear regression models trained with field data; one for the Plains and a second for the Shield ecoregion. Field observations were used to estimate area burned in each of five severity classes (unburned, singed, light, moderate, severely burned) in six stratified randomly selected plots of 10 x 10-m in size across a 1-ha site. Using this five class scale a burn severity index (BSI) for each 1-ha site was calculated using multiple weighted and averaged field parameters. Pre- and post-fire phenologically paired Landsat 8 images were used to model the five discrete severity classes using midpoints as breaks.

ABoVE: Characterization of Carbon Dynamics in Burned Forest Plots, NWT, Canada, 2014

This dataset provides field data from boreal forests in the Northwest Territories (NWT), Canada, that were burned by wildfires in 2014. During fieldwork in 2015, 211 burned plots were established. From these plots, thirty-two forest plots were selected that were dominated by black spruce and were representative of the full moisture gradient across the landscape, ranging from xeric to sub-hygric. Plot observations included slope, aspect, and moisture. At each plot, one intact organic soil profile associated with a specific burn depth was selected and analyzed for carbon content and radiocarbon (14C) values at specific profile depth increments to assess legacy carbon presence and combustion. Vegetation observations included tree density. Stand age at the time of the fire was determined from tree-ring counts. Estimates of pre-fire below and aboveground carbon pools were derived. The percent of total NWT wildfire burned area comprising of "young" stands (less than 60 years old at time of fire) was estimated.

Forest Inventories at Burned and Unburned Tropical Forest Sites, Acre, Brazil, 2014

This dataset provides measurements for diameter at breast height (DBH) and species identification of trees for inventories taken at five tropical forest sites in Acre state, Brazil, in the southwestern Amazon region. The sites included one in a forest reserve (Reserva Bonal) and four within forest fragments situated on private property. The inventory sites included forests burned in 2005 and 2010 and also unburned forests. Surveys were conducted in July and August 2014.

NACP Peatland Landcover Type and Wildfire Burn Severity Maps, Alberta, Canada

This data set provides landcover maps of (1) peatland type (bog, fen, marsh, swamp) with levels of biomass (open, forested) and (2) Burn Severity Index (BSI) (Dyrness and Norum, 1983) for four wildfire areas in northern Alberta, Canada. The four wildfire sites include the Utikuma fire site of 2011, Kidney Lake fire site of 2011, Fort McMurray west fire site of 2009, and Fort McMurray east fire site of 2009. The peatland classification at 12.5-m resolution (fen vs. bog including treed vs. open vs. shrubby) at each wildfire site was based on a pre-burn 2007 multi-date, multi-sensor fusion (Optical-IR, C-band and L-band SAR) approach. Over 350 field locations were sampled in central Alberta to train and validate the peatland type maps. The additional site, Wabasca, was an unburned site. Burn severity was measured in the field using the Burn Severity Index (BSI) (Dyrness and Norum 1987), a qualitative assessment of burnt moss that uses a 1-5 scale, with 1 being unburnt and 5 being severely burnt. The field data of ground consumption were correlated with Landsat pre- and post-burn imagery, specific to peatlands, to develop multivariate models for calculating burn severity and %-not-sphagnum-moss. These models were used to generate the Burn Severity Maps at 30-m resolution (percent unburned moss, and the burn severity index (BSI)). All sites were visited in 2013 for field measurements and the Utikuma site was also visited in 2012 for field measurements. Additional biophysical data for the various peatlands (aboveground biomass – tree and shrub, plant heights, density, etc. were collected and will be provided in another data set.

SAFARI 2000 MODIS 500-m Burned Area Products, Southern Africa, Dry Season 2000

The SAFARI 2000 project was selected as the first regional test for a prototype regional 500 m MODIS burned area product. The MODIS burned area product maps the 500 m location and approximate day of burning using a change detection algorithm based on a bi-directional reflectance model-based expectation method applied to the MODIS near-infrared and shortwave infrared bands (Roy et al., 2002). The algorithm was applied to recently reprocessed 500 m daily MODIS land surface reflectance data to produce burned area data sets for all of southern Africa for 2000 forward. This archived data set contains MODIS 500 m burned area products for two dry season months (July and September 2000).Burned area products are spatially explicit data sets that describe the approximate day of burning at 500 m resolution for all of southern Africa south of the Equator, including Madagascar. The burned area maps are compressed GeoTiff files. Several text files are included in the compressed files to aid ENVI (Research Systems, Inc.) users, including ENVI header files and ENVI density slice files. The data set also includes a projection parameters file.The MODIS burned area data set was validated using a methodology based upon the interpretation of multitemporal Landsat Enhanced Thematic Mapper plus (ETM+) data as described in Roy et al. (in press).

ABoVE: Burn Severity, Fire Progression, and Field Data, NWT, Canada, 2015-2016

This data set provides a fire progression map for year 2015 and measures of burn severity and vegetation community biophysical data collected from areas that were burned by wildfires in 2014 and 2015 in the Northwest Territories, Canada. Field data collected in 2016 include an estimate of burn severity, woody seedling/sprouting data, soil moisture, peat depth, thaw depth, and vegetation cover for selected sites.

VIIRS/NPP Burned Area Monthly L4 Global 500m SIN Grid V002

The daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Burned Area (VNP64A1) Version 2 data product is a monthly, global gridded 500-meter (m) product containing per-pixel burned area and quality information. The VNP64 burned area mapping approach employs 750 m VIIRS imagery coupled with 750 m VIIRS active fire observations. The hybrid algorithm applies dynamic thresholds to composite imagery generated from a burn-sensitive Vegetation Index (VI) derived from VIIRS shortwave infrared channels M8 and M11, and a measure of temporal texture. VIIRS bands that are both sensitive and insensitive to biomass burning are used to detect changes caused by fire and to differentiate them from other types of change. The mapping algorithm ultimately identifies the date of burn, to the nearest day, for 500 m grid cells within the individual sinusoidal tile being processed. The date is encoded in a single data layer of the output product as the ordinal day of the calendar year on which the burn occurred (range 1–366), with a value of 0 for unburned land pixels and additional values reserved for missing data and water grid cells. The VNP64A1 data product is designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined burned area product to promote the continuity of the Earth Observation System (EOS) mission. The data layers provided in the VNP64A1 product include Burn Date, Burn Date Uncertainty, and Quality Assurance (QA), along with First Day and Last Day of reliable change detection of the year. A low resolution browse is also provided showing the burned date layer with a color map applied in JPEG format.Known Issues* Additional information on known issues is provided in Section 8 of the User Guide and on the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS).Improvements/Changes from Previous Versions* Improved calibration algorithm and coefficients for entire Suomi NPP mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data. * Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.* More details can be found in this [VIIRS Land V2 Changes document](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf).

ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014

This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites.

ABoVE: Characterization of Burned and Unburned Spruce Forest Sites, Tanana, AK, 2017

This dataset provides the results of field observations of soil characteristics and depth to permafrost, survey results for Composite Burn Index (CBI) determination, and Landsat-derived estimates of Relative Difference Normalized Burn Ratio (RdNBR) for 38 burned and unburned forest sites near Tanana, Alaska in 2017. Forests in the study area, at the confluence of the Yukon and Tanana Rivers about 200 km west of Fairbanks, are predominately black spruce on wetter soils and white spruce on drier soils. The burned areas were from wildfires that occurred in the summer of 2015.

SAFARI 2000 Biomass Burning Emissions, Selected Sites, Dry Season 2000

Biomass burning is a major source for gaseous and particulate atmospheric pollution over southern Africa and globally. The purpose of this study was to quantify biomass burning emissions in an attempt to better understand and predict associated environmental impacts. Sixty biomass burning experiments were carried out November 2000-January 2001 in three regions of southern Africa that are representative of major regional ecosystem types: Etosha National Park (Namibia), Kruger National Park (South Africa), and woodland sites in Zambia and Malawi. Organic halogen-containing gases were measured in the exhaust of these fires as well as the smoke mixing ratios of CO, CO2, NOx, CH4 and N2O. Fuel and ash samples were analyzed for elemental composition. These data allow investigators to assess the elemental mass balance for each experimental burn as well as the corresponding emission factors for individual compounds as functions of the biofuel composition.This data set contains four types of data:Baseline data for individual fires (time-series engineering data and mixing ratios and mass fluxes of CO, CO2 and NOx);Elemental analyses of fuel and ash (C, N, S, P, Cl, Br, I, K, Ca, Na, and Mg content of biofuel samples and ash);Flux data (integrated mass fluxes of CO, CO2, NOx and total mass of burned elements relative to the fuel element and the above fuel analyses);Emissions data (emissions of NH3, SO2, CH3COOH, HCOOH, HCl, HONO, and HNO3 and inorganic Cl and Br; ionic and elemental compositions of particles; and emissions of CO2, CO and NOx for different types of biofuel).

openGEO-OpenOct 2021View details →

Early Transcriptomic Response to Burn injury: Severe Burns are Associated with Immune Pathway Shutdown

GEO Series GSE182616. Homo sapiens. 785 samples. Type: Expression profiling by array.

openGEO-OpenMay 2025View details →

Single-cell RNA transcriptome shows IFITM1 regulates stem cell activation in limbal epithelium in response to alkali burn.

GEO Series GSE277598. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2018View details →

Leptin and fractalkine: Novel subcutaneous cytokines in burn injury.

GEO Series GSE102811. Rattus norvegicus. 8 samples. Type: Expression profiling by high throughput sequencing.