7th Workshop on Forest Fire Management - EARSeL, European ...

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III - FIRE DETECTION AND FIRE MONITORING
a gradient of fire types); (ii) Airborne Hyperspectral Sensor (AHS) data
(opportunistic imaging of several vegetation fires at ~1.5m resolution);
(iii) China-Brazil Earth Resources Satellite (CBERS) (burned area mapping
at 20m resolution with 26 day repeat cycle); (iv) Advanced Spaceborne
Thermal Emission and Reflection Radiometer and Landsat Thematic Mapper
(TM and ETM+) (active fire detection and burned area mapping at 30m resolution
with 16 day repeat cycle); (v) Moderate Resolution Imaging
Spectroradiometer (MODIS) onboard Terra and Aqua satellites (1km active
fire detection and characterization from the Thermal Anomalies (TA) product
– 12hour interval (can be reduced depending on use); and (vi)
Geostationary Operational Environmental Satellite (GOES) imager (4km
active fire detection and characterization from the WildFire Automated
Biomass Burning Algorithm (WF-ABBA) – 30min interval).
2.1 - Fire Product Assessment
Our assessment of the TA and WF-ABBA fire products built on the study of
Morisette et al. (2005). We used coincident and near coincident higher spatial
resolution data to map sub-pixel fires within the MODIS and GOES imager
footprints (see Giglio et al., 2008; Csiszar et al., 2006; Schroeder et al.,
2008c). The effects of short-term variations in fire behavior were analyzed
using Landsat ETM+ and ASTER data acquired 30min apart (see Csiszar and
Schroeder, 2008). We used the Vegetation Continuous Fields (VCF) product
to stratify our results in terms of the percentage tree cover found in and
around the fire pixel area.
2.2 - Consideration of Cloud Obscuration Omission Errors
Opaque clouds can greatly reduce the ability to detect fires using spaceborne
instruments due to severe attenuation of the spectral signal emitted
by either flaming or smoldering phases of biomass combustion. In order
account for the resulting omission errors, we applied a probabilistic
approach to the WF-ABBA product over Brazilian Amazonia using precipitation
estimates, a cloud mask, and land use data, all derived from the GOES
imager data (for details see Schroeder et al., 2008b).
2.3 - Fire Characterization
Fire characterization is required in order to understand the processes leading
to and resulting from biomass burning. Currently, fire size and temperature
estimates are calculated by the WF-ABBA product, whereas both WF-
ABBA and TA provide estimates of Fire Radiative Power. In order to assess
those parameters we used coincident data from ASTER and Landsat ETM+.