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Hi
Yucel,
I
don't know of a wizard that does it, but here are 2 approaches that work. .
.
===================================================================
QUESTION:
How do I summarise classification files areas, based on region polygons? ANSWER:
ER Mapper provides an "Area Summary Report", under VIEW -> STATISTICS. Before using reports under this menu, first use PROCESS -> CALCULATE STATISTICS. The
statistics calculation recognizes divisions within datasets of *regions*
and *classified regions*. However it doesn't work with both at the same time - well not in the way you want. So you'll need to employ a more long-winded technique that involves blanking out the cells outside of each shire, then saving to dataset before calculating the statistics. This has to be done for each shire/region. Blanking out cells can be done easily after a region is defined (along the shire boundary) in annotation. The 'blanking-out' formula is
IF (INREGION(r1)) THEN Input1 ELSE NULL
(With
region 'r1' set to the shire boundary region.)
NOTE:
If you have very many of these to process then the technique above
could probably be shortened if some time is spent re-working it. For example, you could try saving the shire region into classified image header. ---------------Alternative method
------------------------
If you've got more regions that classes then it's more efficient to do things differently, as follow... 1)
Define regions for all shire boundaries, and save them into your to
the
classified image header. Note ER Mapper has vector -> polygon conversion functionality (if you already have boundaries in an .erv vector file). 2)
Define a null value for the image. A good value to choose may be
255.
REPEAT
THE FOLLOWING STEPS FOR ALL SIX CLASSES
3) Load the image into a new algorithm then use a formula "If (i1 = 0) then i1 else null" (to show only class 0). 4) Save to Dataset 5) Calculate stats then View statistics area report. It will tell you the area of class 0 within all shires. =================================================================== If
you're working with many datasets then work out the best way to streamline the
above process according to the exact situation you've got.
Cheers,
Andrew.
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