United States Department of Agriculture
Forest Service
Burned Area Emergency Response
IMAGERY SUPPORT
Pre-Fire
Post-Fire
PROCESS
50
Pre-Fire
Imagery collected over a forest in a pre-fire
condition will have very high near infrared
band values and very low shortwave infrared
band values.
BURNED
AREAS
(%)
40
REFLECTANCE
A Burned Area Reflectance Classification (BARC) is
a satellite derived estimate of post-fire condition.
The BARC has four classes: high, moderate, low,
and unburned. BARC data are created by comparing
satellite near infrared reflectance values to shortwave
infrared reflectance values.
IMAGERY
EXPLOITING SPECTRAL RESPONSE CURVES
Near infrared light is largely reflected by healthy
green vegetation.
30
20
HEALTHY
VEGETATION
10
Differential
ELECTROMAGNETIC SPECTRUM (Wavelength µm)
0
0.45
0.69
VISIBLE
0.75
0.90
NEAR INFRARED (NIR)
2.09
Post-Fire
Imagery collected over a forest after a fire will
have very low near infrared band values and
very high shortwave infrared band values.
2.35
SHORTWAVE INFRARED (SWIR)
Differential
Subtracting the post-fire image from the
pre-fire image produces an image with
values that reflect the magnitude of change
resulting from the fire.
Shortwave infrared light is largely reflected by rock and bare soil.
Satellite imagery collected over a forest in a pre-fire condition will have very high near infrared values and very low shortwave
infrared values. After a fire, the relationship is reversed.
It is the difference between reflectance in the near infrared and shortwave infrared bands that BARC data attempts to exploit.
The best way to do this is to measure the relationship between these bands prior to and after the fire, and then calculate the
difference. Those areas where that difference is the largest are most likely to be severely burned, whereas those areas where
that difference is small are likely to be unburned or very lightly burned.
BARC (4 Class)
An analyst thresholds the differential product
into four classes that estimate the degree of
burn severity.
BARC (4 Class)
FIELD
CALIBRATION
Burned Area Emergency Response (BAER) teams are provided an adjustable BARC which they adjust to match field observations
and generate a soil burn severity map. This field-calibrated soil burn severity map will be used to estimate the likely future
downstream impacts due to flooding, landslides, and soil erosion.
BAER teams compare the BARC to ground
observations and adjust the break points
between the four classes, if needed.
BURN SEVERITY CLASSES
Field Calibration
APPLICATION
Unburned. Reveals a wide variety
of potential fuels, from the low
shrubs on the forest floor to the
heavily wooded areas.
Low. Although some of the grass
burned, the root mounds are still
standing and only slightly scorched.
The trees are still standing and only
slightly scorched.
Moderate. Foliage on the trees
is scorched, but not completely
consumed.
Field Calibrated Soil Burn Severity
The calibrated burn severity data is overlaid
on additional geospatial data to produce a
field calibrated soil burn severity map that
can be used for remediation efforts.
High. Trees are blackened and all
foliage and understory vegetation
has been consumed.
Field Calibrated Soil Burn Severity
(4 Class)
IMAGERY SOURCES RSAC uses the best available imagery to create BARC (Burned Area Reflectance Classification) data. Image sources include Landsat ETM + & TM, EO-1 ALI (Earth Observing-1 Advanced Land Imager), SPOT (Système pour l’Observation de la Terre), and other commercial satellite vendors.
ADDITIONAL RESOURCES Parson, Annette; Robichaud, Peter R.; Lewis, Sarah A.; Napper, Carolyn; Clark, JT. 2010. Field Guide For Mapping Post-Fire Soil Burn Severity. Gen. Tech. Rep. RMRS-GTR-243. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 49 p.
Clark, JT; Bobbe, T. 2006. Using Remote Sensing to Map and Monitor Fire Damage in Forest Ecosystems. In: Ch. 5; Understanding Forest Disturbance and Spatial Patterns: Remote Sensing and GIS Approaches (M.A. Wulder and S.E. Franklin, eds.), Taylor & Francis, London, 246 p.
CONTACT Carl Albury, Remote Sensing Specialist, calbury@fs.fed.us | www.fs.fed.us/eng/rsac/baer
AUTHORS Brad Quayle1, Carl Albury 2, Jennifer Lecker2 1 USDA Forest Service Remote Sensing Applications Center (RSAC); 2 RedCastle Resources Inc. On site Support USDA Forest Service Remote Sensing Applications Center RSAC reference # 10045-Post2
Graphic Design: Linda R. Smith2; Photography: Aerial, Keri Greer; Field Calibration, Stefan Doerr Learn, Share, Recycle USDA is an equal opportunity provider and employer.