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The Use of AVHRR Satellite Imagery
to Monitor Boreal Ecosystem Forest
Fires
Donald R o Cahoon, Jr.' and Brian
Jo
Stocks2
Abstract - Forest fires are an integral part of the natural forces that shape
the composition and evolution of the boreal forest. These fires, often very
intense, commonly grow to sizes large enough for satellite monitoring
using the National Oceanic and Atmospheric Administration (NOAA)
Advanced Very High Resolution Radiometer (AVHRR) instrument. The
AVHRR instrument acquires l-km and 4-km resolution (at nadir) satellite
imagery in five spectral bands. Multispectral methods have been
developed, using the AVHRR imagery, to estimate the size and growth rate
of bumed forest. The AVHRR bumed area estimates have been evaluated
and the error determined for both the l-km and 4-km imagery. Applying
these methods, the spatial distribution and extent of forest fires has been
mapped for the 1987 and 1992 Russian boreal forest fire season. Due to a
strong contrast in the total area bumed in each of the 2 years, the large
interannual variability of bumed forest is demonstrated.
INTRODUCTION
The boreal ecosystem is a forested belt, mostly comprised of conifer trees, that
stretches across the Northern Hemisphere's circumpolar countries. The boreal
forest covers over 12 million km2 of the Earth's surface which is about 10% of the
total land surface area. In terms of areal extent, the boreal forest ranks about fifth
compared to all terrestrial biomes, but ranks second only to tropical forests in total
plant mass (Whittaker and Likens 1975). Given the ecosystem's size and total
available plant mass it is not surprising that the World's boreal forests contain
almost 40% of all terrestrial carbon (Kasischke et al. 1995a). This means that the
boreal forest must play an extremely important role in the global carbon budget
and it is important to characterize any disturbance and process that perturbs the
carbon cycle within this ecosystem. Fire is one such disturbance.
Because of the enormous geographical scale for which the boreal forest
extends, a trade-off between satellite resolution, accuracy of estimating the acreage
burned, and frequency of satellite coverage has been made. In reality, there are
three satellite systems that could potentially be used to monitor forest fires.
Landsat and SPOT quickly come to mind because of their high spatial resolution,
but do not offer the repeat coverage needed to compensate for cloud cover
Scientist,NASAILangley Research Center, Harnpton, VA.
Senior Research Scientist, Canadian Forest Service, Sault. Ste. Marie, ONT, Canada.
1 Research
obscuration of the land surface. Also, the amount of data and cost of enough
imagery to cover the entire boreal region would be unrealistic. Rather, we have
chosen to use AVHRR imagery because it offers a reasonable resolution at a low
cost, and it provides multiple overpasses each day. After an evaluation of the
AVHRR imagery, we have found that estimates of the surface area can be within a
few percent. This error is considered reasonable for the large geographical scale
we are evaluating as long as consistent results can be obtained.
To develop consistent surface area estimation results, we have developed a
methodology for processing the AVHRR imagery. The following sections will
describe the AVHRR instrument and archived imagery, the burned area estimation
methodology and error analysis, and describe some of our ongoing research on
boreal forest fires.
AVHRR INSTRUMENT
The AVHRR instrument has flown on several National Oceanic and
Atmospheric Administration
(NOAA) sun-synchronous polar-orbiting
meteorological satellites since 1978 and provides a nearly continuous archived
data set. These satellites have flown in a morning and afternoon configuration
which provides four overpasses each day in the low to mid-latitudes, and upwards
toward 8 overpasses in the higher latitudes of the boreal forest. The AVHRR
instrument is a scanning imager which scans in the across track direction and
acquires data in five spectral bands (table 1). The swath width is just over 2800
km given a nominal orbital altitude of 830 km and a total scan angle of 110.8".
Each cross track scan provides 2048 observations (pixels) with an instantaneous
field-of-view (IFOV) of approximately 1.4 mrad. The precise IFOV for each
channel varies slightly and is included in table 1.
Table 1.
- AVHRR channel characteristics.
Channel
Wavelength
(microns)
Cross track
IFOV (mrad)
Along track
IFOV (mrad)
Channel selection of the AVHRR instrument was driven by operational
meteorological and oceanographic requirements. However, over time the fire
community has found ways to apply the channel selection to its own research. In
summary, channel 1 and channel 2 can be used to differentiate smoke from clouds
(Chung and Le 1984). Channel 2, because of its sensitivity to the reflectance fi-om
vegetated surfaces, provides tremendous contrast between bum and unburned
areas (Cahoon et al. 1992; Cahoon et al. 1994; Kasischke et al. 1995a). Channel 3
has long been demonstrated to be sensitive to hot temperature sources (Matson and
Dozier 1981; Scorer 1987) and is useful for mapping active forest fires (Cahoon et
al. 1994; Stocks et al. 1996). Channels 4 and 5 are both similar in that they are low
in contrast when calibrated, but provide a basis for distinguishing between burned
areas and water in mid-afternoon imagery (Cahoon et al. 1994).
The imagery is archived in either of two formats, local area coverage (LAC) or
global area coverage (GAC). The LAC format is the full 1-krn (at nadir)
resolution product and is recorded onboard the spacecraft and downlinked to
specific sites. The AVHRR 1-km data are also continuously broadcast to any
ground-station within the satellite's horizon; which is referred to as high resolution
picture transmission format (HRPT) data. In the archives HRPT and LAC data are
the same. Due to a limited amount of onboard memory for recording LAC data, a
4/15 subsampled product is continuously recorded for broadcast to selected ground
stations. This format is the global area coverage (GAC) and is frequently referred
the 4 km imagery. The GAC subsampling scheme is shown in figure 1.
I
Averaged and Saved
Discarded
Figure 1. - GAC subsampling scheme. Each row is a portion of a scan line.
Each box is one image pixel. The dark box represents a GAC "4 km" pixel.
BURNED AREA ESTIMATION METHODOLOGY
The surface area of bum scars is estimated using either LAC or GAC archived
imagery. In a previous study, Cahoon et al. (1992) demonstrated that, given the
large fire sizes in the boreal system that GAC imagery is sufficient for estimating
the area. In the following section we will examine the surface area estimation
error using both the LAC and GAC imagery. This section will lay out the
methodology through which we process the AVHRR imagery.
Because of the intermittent availability of clear-sky imagery, which negates the
possibility of observing the entire study region at one time, a clear-sky mosaic is
created. From this mosaic, all bum scars can be observed in a single image,
making the area-burned estimate simpler and alleviating the concerns of double
counting or missing any burned area. The development of the clear-sky mosaic is
a several-step process which will be described with the use of matrix notation. An
individual multispectral(3-banded) AVHRR scene is represented by matrix Dn and
the mosaic of all the individual AVHRR scenes is matrix M, where
n is the total number of AVHRR scenes; i and j define the number of elements, d
and m, in the matrices. Each pixel in the AVHRR image is corrected for brightness
changes due to the solar zenith angle. Using the NOAA-supplied navigation data,
each element dii is the result of resampling the original NOAA scene into a
cylindrical-equidistant map projection. Since each AVHRR scene is resampled,
for every Dn the elements dii represent the same geographical region and are a
function of latitude (q) and longitude (A). The mosaic image (M) is the same size
and spatially represents the same geographical area as the AVHRR scenes Dn.
Then each element of both M and Dn can be compared, with the results of the
comparison composited into a final scene (M'). The comparison,
M'ij = MIN (Dnii. M i j )
(2)
tests for the minimum between the mosaicked image (M) and the AVHRR scene
(Dn) in the AVHRR channel 2 band, and saves the elements for all channels of the
minimum-valued image in the new mosaic M'. The testing is iterative, where M'
is substituted for M, and continues n times through all of the scenes. Since clouds
are highly reflective and the burned area is of low reflectance in the AVHRR
channel 2, the burned areas are retained while the clouds are removed.
In estimating the total regional burned area, it was first necessary to classify
which image pixels contained bumed area. An unsupervised minimum distance
classification on AVHRR channels 1, 2, and 4 was than used iteratively to isolate
the scar pixels and statistically determine the edge pixels that are counted as
having a burn scar. The iterative process continues until bum scars, that have been
correlated with known fire activity determined from the AVHRR imagery, are
isolated and falsely classified pixels have been minimized.
The resulting scar map is subjected to another processing step to determine the
area of each pixel. Since a cylindrical-equidistant projection is used and each side
of a pixel is parallel to both meridians and parallels, the distance along each pixel
in terms of degrees of latitude and longitude is easy to determine as well as the
surface area. The area of every pixel classified as a scar is then integrated to derive
the total area burned.
BURNED AREA ERROR ANALYSIS
An extensive analysis has been conducted to evaluate the error of estimating
the burned surface area using both the LAC and GAC imagery. The details are
outlined in Cahoon et al. (1992). In brief, surface targets of known area are
delineated in both the LAC and GAC imagery. These targets are a series of lakes
in Canada that often contain several islands, sometimes of considerable size, and
thus are not homogeneous. The heterogeneous nature of the lake targets is similar
to that of bum scars which contain unburned areas within a its perimeter. The
results from this analysis are in figure 2.
The mean surface area estimation error associated with using LAC imagery is
lower than that of GAC imagery across the entire size range, even though for
larger targets the difference is practically negligible. This comes as no surprise
since we expect the analysis of higher resolution imagery to yield better results
when working with small areas. However, it is interesting to note that for larger
targets, the error variance for the GAC-derived estimates is less than that of the
LAC analysis. This likely has a lot to do with the overlap of the AVHRR pixels
(Cahoon et al. 1992). The overlap is considerable for the 1-km data and the edge
of a target is defined by a gradual gradient, leaving room for interpretation as to
where to define the target's edge. Much of the surface area estimate errors are due
to blurred edges of targets. At least for the GAC imagery, some of this overlap has
been eliminated by subsampling, leaving a better defined edge and fewer perimeter
pixels to skew the analysis one way or another.
Overall, the results show that for LAC imagery a mean error of about 2% can
be expected, and that 90% of all targets will fall within 4% error for targets down
to 100 km2. For the GAC imagery, the mean error is about 2% worse than that of
the LAC imagery for targets that are 100 km2, and drops off to being negligible
when evaluating targets that are 10,000krn2 or more in size. Burned area estimate
errors, from both the 1988 Yellowstone Fires (Cahoon et al. 1992) and the 1987
Great Dragon Fire in China (Cahoon et al. 1994), are consistent with these results.
RESEARCH APPLICATION: RUSSIAN BOREAL FOREST FIRES
Forest fires have been a major disturbance regime affecting the world's boreal
forests for millennia. Increased development within the world's boreal zone has
necessitated fire management programs designed to protect human interest and
forest investment. While these programs have been largely effective in reducing
unwanted fires in selected regions, forest fires continue to exert enormous
influence in the world's boreal forests. With the rising concern that potential
global warming will lead to an increase of fire activity within the boreal forests
(Flannigan and Van Wagner 1991, Wotton and Flannigan 1993, Stocks 1993,
Fosberg et al. 1996),much attention as recently been focused on the important role
the boreal forest plays in the Earth's carbon budget (Kasischke et al. 1995b), and
how an increase in fire activity will impact that budget and potentially provide
.
I
-
a m . .
I
10j
. . . ...
Area (km2)
..I
104
. .
a
.
m
.
Figure 2. AVHRR-derived surface area estimation error for various target
sizes. LAC errors shown by dashed line; GAC errors shown by solid line. The
lower line, for both LAC and GAC, represents mean error and the upper line
shows the upper error bound for 90% of all targets.
positive feedback to global warming (Kurz et al. 1994). Given these concerns and
the need for a quantitative assessment and a historical perspective of boreal fire
activity, we have begun to use the satellite techniques described in this paper to
assess the total area burned in the boreal forest during the last 15 years for which
AVHRR data are archived.
Leading into this multiyear study, as test cases, we have completed the burned
area analysis for the Russian boreal forest for the years 1987 (Cahoon et al. 1994)
and 1992 (Cahoon et al. 1996). The 2 years were totally dissimilar in terms of area
burned, with 1987 being a severe fire year for both Russia and the northern
Chinese provinces. It was during 1987 that one of the largest recorded fires in
China's history occurred (about 1.3 million ha) and large fires throughout eastern
Russia were very prevalent (Cahoon et al. 1994). The 1987 analysis was
conducted using over 200 GAC images. As demonstrated in the previous section,
the burned surface area estimation using GAC imagery is not much greater than
6% for fire sizes down to 100 krn2 in size. Fortunately, in the boreal forest, fire
sizes are very large with 95% of the area burned by 5% of the fires. The estimate
of the total area burned during the 1987 fire season is 14.446 million ha.
In contrast, even though there was widespread fire activity in 1992, the total
area burned was 1.5 million hectares. This is a relatively low annual total of
burned acreage which was concurrently experienced in Alaska and Canada. The
1992 analysis used over 100 LAC images that cover the region from 30' to 180'
east longitude. The boreal region was split into 30' longitude blocks. Each block
was processed one at a time (Cahoon et al. 1996).
There was an obvious similarity between 1987 and 1992, widespread fire
activity is primary east of the Yenisey River (about 90°N latitude). The reason for
the higher amount of burned area to the east is likely due to the increase in
population toward the west and the low marshy areas west of the Yenisey River.
With the population increase to the west comes additional fire management
pressures and better access to fires for fire suppression purposes.
CONCLUSIONS
With limited resources and the constant need to assess spatial changes within
our natural resource regimes, satellite and aircraft remote sensing is being drawn
upon to provide spatially dependant data over various scales. The need to monitor
and assess the post-burned size of forest fires is one such role that satellite-based
observation can play. Even though it is more difficult to used space-based
resources to contribute directly to fue fighting, it is not out of the question to
utilize this resource to monitor fire activity and map post-burned fires over large
geographical scales and remote regions.
The remoteness of the boreal ecosystem, a region where considerable travel
and fire reconnaissance is accomplished by air, almost dictates the need in a costcutting era to assess fire activity using satellite imagery. The remoteness,
combined with the current interests in developing a consistent fire record
throughout the entire boreal forest, has lead us to develop the AMIRR techniques
used in our two trial studies, which will be implemented as we embark on a 15year analysis of the interannual variations of burned forest. Further evaluations
will be made regarding the successfulness of detecting and estimating the size of
smaller fires. Further, a test case has also been developed which demonstrates the
potential use of the AVHRR imagery for monitoring fire growth rates (Stocks et a1
1996).
To conduct this research, customized computer code has been developed over a
number of years to implement our approach. Each segment of our software system
has been carefully tested. We have begun to evaluate the potential of commercial
packages for registering and mapping AVHRR images. In one prominent GIs/
image processing package, we have had very limited success with registration and
would not trust the resulting surface area estimates. This does lead to our concern
that any commercial tools that can map fires and estimate the size of burned areas
using AVHRR satellite imagery should carefully be scrutinized for reliability.
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Cahoon, Jr., D. R., B. J. Stocks, J. S. Levine, W. R. Cofer III, and J. M. Pierson,
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Cahoon, Jr., D. R., B. J. Stocks, J. S. Levine, W. R. Cofer, and J. A. Barber, 1996,
Monitoring the 1992 Forest Fires in the Boreal Ecosystem using NOAA
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BIOGRAPICAL SKETCH
Donald R. Cahoon, Jr. is a research scientist with the National Aeronautics and
Space Administration, Langley Research Center, Hampton, Virginia. He has
worked as an analyst of satellite, aircraft, and meteorological data sets for over 11
years. During the last 7 years he has specialized in satellite remote sensing. His
primary applications have been forest fire monitoring and surface radiation budget
studies.
Brian J. Stocks is a senior forest fire scientist with the Canadian Forest Service
in Sault Ste. Marie, Ontario. Over the past 28 years he has specialized in the
development of forest fire danger rating and fire behavior prediction systems, and
is currently involved in the investigation of cause-and-effect relationships between
global change and forest fires.