Hi all

This is an interesting little problem that some of you might want to
consider.

I have a MI table of 10m squares, each with attribute Ht. You can think
of the table as representing an elevation grid covering a region.

The region needs to be broken up into a set of sub-regions where 70% of
the points that fall in each sub-region are less than or equal to  the
lowest point of that sub-region + .5 m. 

In simple terms think of digging a pond and leaving a small island in
the middle for ducks; 70% of the region defined by the outer perimeter
of the pond is water, 30% land.

For the 100% solution

Start

Find the highest point. Set as original point
Find all the points that are wthin .5m of the original point
Combine 10m squares into an object and then disaggregate
Discard all the new regions that do not contain the original point
Set the ht points that fall into the new sub region to -999

Loop until all hts are -999


Now do it for 70% case. The table is big.

Any suggestions welcome

Tony




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