>
> Thank you!
> In fact such a tool is always a fake. I try not to confuse it with reality -
> it only has to simulate it. This is because of the control paramenters which
> I cannot adjust in a correct way simply because I don't know them. By
> example, what is the optimum soil humidity for nettles? At least nettles
> seem to grow everywhere, so they can tolerate many conditions from sunny to
> pure shady locations. Perhaps they tolerate conditions other plants simply
> don't like, but aren't good in competing with other species. In this
> respect my model won't be very different from a pure guess.
>
> For water availability I got a tip of Prof. Deussen, one of the Xfrog
> authors.
> The function, which defines the ground can also serve as approximation to
> water content.
>
> Rocks are easy - they cast shadows. A simple image which defines shadowing
> from rocks, big plants, houses and so on is sufficient to define smaller
> and less dense vegetation near rocks. Near trees you have to consider the
> roots too, which lower water availability at those points.
>
> Probability maps are nice. In fact I used simple examples for some of my
> images. But with a little practice you can see the difference to an
> iterative approach.
>
>
> Norbert Kern

Yes, I understand/see the iterative process makes a major difference - what
I am wondering is if the method you are using takes into account both the
terrain and the neigboring plants, or just the latter. Anyway, now I have
time so I'll just hunker down and read the PDF.

As far as the reality of the control paramenters -- It doesn't really amtter
if they are the real numbers, does it? The look of the thing is in the
variation itself. You could use entirely fictional plants, and the process
would still give you a result that is pleasing to the eye, because it
defies the regularity of a less intensive approach. If you wanted it to be
*just* like the real world, well, I have a very nice camera you could
borrow ;) Seriously, though, it looks fantastic.

-s
5TF!

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