This data set is an active fire detection product resulting from the application of The Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to Geostationary Environmental Operational Satellite (GOES) imager data for all of South America from 2000 through 2005. GOES imager data are available at 30 minute intervals with a nominal 4 x 4-km resolution.
The data provided are the latitude/longitude, brightness temperature, estimates of sub-pixel fire size and temperature, Global Land Cover Characterization (GLCC) ecosystem type, and a pixel-fire flag (0-5, information regarding the probability of a fire or processing characteristics) for each active fire detected by WF_ABBA for a 30 minute imager interval.
Spatial area coverage data files are provided as a complement to individual fire detection data files because the area of the latter varied according to the GOES imager scan mode in use.
Versions 5.9 and 6.0 WF_ABBA data are provided. Differences between the two versions are assumed to be small though (typically less than 10%). An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues in version 6.0. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset.
There are nine compressed (*.zip) files with this data set. The zip files expand to the filtered ASCII text data files (.filt), and seven coverage files text (.txt).
Cite this data set as follows:
UW-Madison CIMSS GOES Biomass Burning Monitoring Program (UW-CIMSS). 2013. LBA-ECO LC-35 GOES Imager Active Fire Detection Data, South America: 2000-2005. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee USA http://dx.doi.org/10.3334/ORNLDAAC/1180
The LBA Data and Publication Policy [http://daac.ornl.gov/LBA/lba_data_policy.html] is in effect for a period of five (5) years from the date of archiving and should be followed by data users who have obtained LBA data sets from the ORNL DAAC. Users who download LBA data in the five years after data have been archived must contact the investigators who collected the data, per provisions 6 and 7 in the Policy.
This data set was archived in August 2013. Users who download the data between August 2013 and July 2018 must comply with the LBA Data and Publication Policy.
Data users should use the investigator contact information in this document to communicate with the data provider.
Data users should use the data set citation and other applicable references provided in this document to acknowledge use of the data.
Project: LBA (Large-Scale Biosphere-Atmosphere Experiment in the Amazon)
Activity: LBA-ECO
LBA Science Component: Land Use and Land Cover
Team ID: LC-35 (Csiszar / Longo / Setzer)
The investigators were Csiszar, Dr. Ivan Andras; Longo, Dr. Karla Maria; Brunner, Jason; Freitas, Dr. Saulo Ribeiro de; Morisette, Dr. Jeffrey Thomas; Prins, Elaine; Schmidt, Christopher C.; Schroeder, Wilfrid and Setzer, Dr. Alberto. You may contact Brunner, Jason (jasonb@ssec.wisc.edu).
LBA Data Set Inventory ID: LC35_GOES_WF_ABBA
This data set is an active fire detection product resulting from the application of The Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to Geostationary Environmental Operational Satellite (GOES) imager data for all of South America from 2000 through 2005. GOES imager data are available at 30 minute intervals with a nominal 4 x 4-km resolution.
The data provided are the latitude/longitude, brightness temperature, estimates of sub-pixel fire size and temperature, Global Land Cover Characterization (GLCC) ecosystem type, and a pixel-fire flag (0-5, information regarding the probability of a fire or processing characteristics) for each active fire detected by WF_ABBA for a 30 minute imager interval.
Spatial area coverage data files are provided as a complement to individual fire detection data files because the area of the latter varied according to the GOES imager scan mode in use.
Versions 5.9 and 6.0 WF_ABBA data are provided. Differences between the two versions are assumed to be small though (typically less than 10%). An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues in version 6.0. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset.
There are nine compressed (*.zip) files that contain temporally-filtered fire product text files (.filt) and seven .txt coverage files (the coverage files contain coordinate information of the area covered for each individual file--one .txt file for each year and satellite).
File naming convention:
The nine compressed *.zip files are named as g__?YYYY_VXX_filt.zip
where
g__ represents the satellite (g8=GOES-8, g12=GOES-12)
? = samerica = South America
YYYY = year 2000 to 2006
_VXX = V59 or V60 to represent the version number (v59 = version 5.9, v60 = version 6.0)
_filt =filtered .zip
File names:
g08samerica2000_v59_filt.zip
g08samerica2000_v60_filt.zip
g08samerica2001_v59_filt.zip
g08samerica2002_v59_filt.zip
g08samerica2002_v60_filt.zip
;g08samerica2003_v60_filt.zip
g12samerica2003_v60_filt.zip
g12samerica2004_v60_filt.zip
g12samerica2005_v60_filt.zip
When expanded, the nine .zip files contain
temporally-filtered fire product text files named
as follows: fyyyydddhhmm.samer.v??.g?.filt
where:
yyyy represents the four digit year
ddd represents the julian day of the year (1-365)
hhmm represents the hour and minute in UTC
samer represents the continent (samer = South America)
v?? represents the version number (v59 = version 5.9, v60 = version 6.0)
g? represents the satellite (g8=GOES-8, g12=GOES-12).
Text file contents:
Each file provides the following information for each recorded fire pixel:
NOTE:
The value -9 indicates that this parameter was not available or could not be computed for this particular fire pixel, but the fire pixel is still valid.
The temporally-filtered fire product only contains fire pixels that have appeared more than once within the past 12 hours. It is the most conservative and should be used if the user wants to minimize false alarms. Line 4 of the header in the filtered output ASCII file contains information on the number of hours/files that were available for the temporal filtering. At times, the temporally filtered file will not be available because not enough of the previous files were available to conduct the filtering.
Example file: f20002450015.samer.v59.g8.filt
|
NOAA/NESDIS/ORA University of Wisconsin-Madison/CIMSS
GOES-8 ABBA (vs 5.9) Experimental Filtered Fire Product **NOTE: This product is preliminary and has not been quality controlled Date: 2000245 Time: 15 UTC Filtered file: 12 hours 25 files Longitude Latitude T4(K) T11(K) Size(km2) Temp(K) Ecosystem Fire Flag -56.02 2.00 299.9 292.2 .1014 436. 41 0 |
** This statement is in all of the files, refers to earlier processing, and should be ignored.
Coverage files (.txt): The seven coverage files are used to describe the polygon domain of the non-filtered final ASCII files. They consist of a series of locations (latitudes/longitudes) that depict the spatial domain of the non-filtered file at each time. Coverage files are divided by year and satellite.
The file naming convention is as follows: g??samericayyyy_cov.txt
where
g?? represents the satellite (g08 = GOES-8, g12 = GOES-12)
samerica represents the continent (samerica = South America)
yyyy represents the four digit year.
** Note that in 2003 there are two coverage files for GOES-East South America (one for GOES-8 and one for GOES-12):
File names:
g08samerica2000_cov.txt
g08samerica2001_cov.txt
g08samerica2002_cov.txt
g08samerica2003_cov.txt
g12samerica2003_cov.txt
g12samerica2004_cov.txt
g12samerica2005_cov.txt
There are 14 parameters at each non-filtered file time in the coverage file. The date and time are provided, as well as 12 parameters that define the polygon outline of the domain region of the data.
The parameters are as follows:
Notes:
-999.00 denotes a missing coordinate.
Left 2,3,4 and Right 2,3,4 define the bound coordinates for the lower half part of the coverage area. These coordinates are used to help create a more realistic representation of the image area as the latter does not describe an exact square.
Example data record (g08samerica2000_cov.txt):
|
DATE hhmmss UPPER LEFT COORD UPPER RIGHT COORD TOP MIDDLE COORD LOWER MIDDLE COORD
LEFT 1 LEFT 2 LEFT 3 LEFT 4 RIGHT 1 RIGHT 2 RIGHT 3 RIGHT 4 2000 0014500 12.99 -81.99 12.97 -28.64 12.97 -74.00 -18.77 -60.60 10.66 -81.98 -3.78 -82.00 -11.03 -81.99 -18.69 -81.98 -999.00 -999.00 -3.96 -30.41 -11.61 -29.04 -19.81 -25.76 |
The spatial domain consists of full coverage of South America every three hours (at Full Disk satellite imagery times: 0245, 0545, 0845, 1145, 1445, 1745, 2045, and 2345 UTC).
Coverage extends to a latitude of 20 degrees South every half hour except when the satellite is in Rapid Scan Operations mode. When Rapid Scan Operations occurs coverage extends only to a latitude of approximately 2 degrees South (No coverage for most of South America). For RSO coverage; L2, L3, R2, and R3 coordinates are assigned a value of -999.00 (since there is no data at these locations for RSO).
Site boundaries: (All latitude and longitude given in decimal degrees)
| Site (Region) | Westernmost Longitude | Easternmost Longitude | Northernmost Latitude | Southernmost Latitude | Geodetic Datum |
|---|---|---|---|---|---|
| South America Regular Coverage (South America Regular Coverage) | -82 | -25.75 | 13 | -20 | 1924 International Standard Geodetic Datum |
Time period:
Platform/Sensor/Parameters measured include:
The geographic coordinates contained in this data set correspond to areas of thermal anomalies identified primarily in the fire sensitive mid-infrared spectral region data of the multispectral imager on board the GOES 8 and 12 satellites. Although the occurrences are mostly associated with vegetation fires, other surface features (e.g., warm bright soils) can also cause abnormal high responses in the mid-infrared channel and therefore produce a detection. The user must also be aware that, despite the 4 x 4 km nominal spatial resolution of the product, vegetation fires will normally occupy only a small fraction of the pixel. Similarly, multiple fire lines may be also described by a single detection. Lastly, navigation drifts must be accounted for when analyzing multi-temporal detections.
A thorough validation of this product was implemented by Schroeder et al. (2008). Commission errors were estimated to represent 3% of all detections. Omission errors vary as a function of fire size (graphs available in the referred publication).
The WF_ABBA is a dynamic multispectral thres-holding contextual algorithm that uses the visible (daytime only), 3.9 micron, and 10.7 micron infrared bands to locate and characterize hot spot pixels. The product has a nominal spatial resolution of 4 x 4 km at the sub-satellite point. The algorithm is based on the sensitivity of the 3.9 micron band to high temperature subpixel anomalies and is derived from a technique originally developed by Matson and Dozier (1981) for NOAA Advanced Very High Resolution Radiometer (AVHRR) data.
The algorithm incorporates statistical techniques to automatically identify hot spot pixels in the GOES imagery. Once the algorithm locates a hot spot pixel, it incorporates ancillary data in the process of screening for false alarms and correcting for water vapor attenuation, surface emissivity, solar reflectivity, and semi-transparent clouds.
The AVHRR-derived Global Land Cover Characteristics (GLCC) data base (version 2.0) is used to assign surface emissivity and to screen for false alarms (http://edcdaac.usgs.gov/glcc/glcc.html).
The National Centers for Environmental Prediction (NCEP) Aviation model total column precipitable water products are utilized to correct for water vapor attenuation.
Numerical techniques are used to determine instantaneous estimates of subpixel fire size and average temperature.
An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset. The temporal filtering technique uses a time series of GOES fire products from previous hours to compare with the current fire product.
A fire pixel must appear at least twice (within 0.1 degrees) within the past 12 hours in order to be retained in the final filtered fire product. The filtered fire product can result in delayed identification of a fire start time and eliminates short-lived agricultural management fires. For more information on the algorithm and the determination of subpixel fire characteristics, refer to Prins and Menzel (1992, 1994) and Prins et al. (1998a; b; 2001a; b).
These data are available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Contact for Data Center Access Information:
E-mail: uso@daac.ornl.gov
Telephone: +1 (865) 241-3952
Matson, M., and J. Dozier, 1981: Identification of subresolution high temperature sources using a thermal IR sensor. Photo. Engr. and Rem. Sens., 47, 1311-1318.
Prins, E.M. and W.P. Menzel, 1992: Geostationary satellite detection of biomass burning in South America. Int. J. of Remote Sensing, 13, 2783-2799.
Prins, E.M. and W.P. Menzel, 1994: Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991. Jour. Geo. Res., 99, D8, 16719-16735.
Prins, E.M. and J.M. Feltz, 1998: Characterizing spatial and temporal distributions of biomass burning using multi-spectral geostationary satellite data. Ninth Conference on Satellite Meteorology and Oceanography, Paris, France, May 25-29, 1998, pp. 94-97.
Prins, E.M., J.M. Feltz, W.P. Menzel, and D.E. Ward, 1998: An overview of GOES-8 diurnal fire and smoke results for SCAR-B and the 1995 fire season in South America. J. Geophys. Res., 103, D24, 31821-31836.
Prins, E.M., J.M. Feltz, and C. Schmidt, 2001: An overview of active fire detection and monitoring using meteorological satellites, Proceedings of the 11th Conference on Satellite Meteorology and Oceanography, Madison, WI, October 15-18, 2001, pp. 1-8.
Prins, E.M., J. Schmetz, L. Flynn, D. Hillger, and J.M. Feltz, 2001: Overview of current and future diurnal active fire monitoring using a suite of international geostationary satellites, In Global and Regional Wildfire Monitoring: Current Status and Future Plans, SPB Academic Publishing, The Hague, Netherlands, pp. 145-170.
Schroeder, W., Prins, E., Giglio, L., Csiszar, I., Schmidt, C., Morisette, J., and Morton, D. (2008). Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data. Remote Sensing of Environment, 112, 2711-2726.