Agriculture Reference
In-Depth Information
Table 8.1 (con tinued)
Technique
Description
Advantages
Disadvantages
Fuel
components
Sampling
time
Level of
uncertainty
Cost
Training
needed
Fuel
classification
Use a field-keyed fuel clas-
sification category to obtain
the fuel estimates
Direct link to fuel
map entities and
sampling estimates
Few classifications key
fuelbed characteristics
All
4
6
3
5
Fuel hazard
assessments
Rate hazard for various fuel
layers and components on
an ordinal scale and cor-
relate to loadings
Links hazard assess-
ment to fuel load-
ings; easy to teach
and use
Must be developed for
each ecosystem; specific
to Australian fuel
components
Litter, Fine
Woody Debris
(FWD), shrub,
herb
5
5
3
6
Visual
cover-volume
Use canopy cover and
height to estimate volume,
and then use volume and
bulk density to estimate
loading for some fuel
components
Often the only
efficient technique
for measuring shrub,
herb, duff, and litter
loadings
High variability in cover
estimates coupled with
high variability in height
(depth) measurements
Litter, duff,
shrub, herb
4
5
3
5
Indirect methods—imagery techniques
Image
processing
Analyze imagery to mea-
sure fuel conditions
Visual record of
fuelbed
Imagery not correlated to
some fuel attributes
Depends on
imagery
4
5
8
9
Terrestrial
LiDAR
Use scanning LiDAR to
obtain a profile of the
fuelbed to estimate fuel
attributes
Locations of all
fuel particles are
measured
Can't relate LiDAR
strikes to material that
reflected the strike
Depends on
the analysis
7
4
10
9
Direct method s
Planar
intercepts
Estimate fuel attributes
along a vertically oriented
sampling plane
Readily available and
standardized methods
available
Only useful for woody
fuels
1, 10, 100,
1000 h
7
7
7
6
Fixed-area
microplots
Estimate fuel attributes
within a plot frame
Adjust plot size
to fuel component
distributions
High variability across
microplots; may require
many microplots
All
8
8
8
7
 
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