The
identification of the spatial patterns of fuel load accumulation are
critical to effective fire management regime, which reduce continuous
fuel loads on the landscape capable of producing drastic and uncontrollable
fires. Tree health and susceptibility to disease are related to variables
that can have a spatial component (i.e. moisture, elevation). Therefore,
methods that utilize the spatial relationship (spatial autocorrelation)
of datasets are suitable for estimation of parameters such as health
and fuel load. Geostatistics were used to interpolate surface maps
of tree health and fuel load, using the fundamental assumption of
geostatistics that observations close to one another are more similar
then observations further apart. |
|
|
Program
window showing the parameters for geostatistical analysis
|
The main focus
of the geostatistical interpolation was to highlight areas where
trees with high fuel load or poor health were clustered in the
sampled regions. A combined interpolation using fuel load and
species health was also produced to help identify the most endangered
historic trees. The interpolated surfaces should be interpreted
as indicators of variable clustering, not a predictor of health
or fuel load.
|