Model Benchmarking

[Keven Bennett]

    I am working with ONRC in developing an iterative spread model of
Spartina in Willapa bay.  The intent of the model is to give one the
ability to 'see' how Spartina is distributed on the ground in a given
time in a given year at 10 meter resolution.
    We have the model running with perameters we believe are reasonable
representations of the primary factors that affect the spread (with the
exception of magnitude and direction of streamflows).
    We want to benchmark our output with 1994 and 1997 data from DNR
which is fairly accurate high resolution vector data derived from CIR
aerial photography, but we have issues to address first:
    We can't directly compare the two years with the two years
corresponding output because the vector data captures polygons with
areas much smaller than 100 sq. meters (10 meter cells).  The resonable
assumption is that the model output should have less total area than the
'94 and '97 data we want to accept as true.  The question is how much?
Any suggestions on arriving at a figure for this?
    If it is safe to make the assumption that any polygon less than 50
sq. meters using ArcView's rasterization algorithms (convert to grid in
correct analysis window), then can we justify that a match of our model
output to the area arrived at by rasterizing the DNR data as 'reasonably
accurate'?
    These are kind of vague questions, but this is the kind of issues we
are confronted with.
    Keven Bennett