Do you mean SPACE-filling, a curve whose range contains the entire 2-dimensional unit square? You can also use fractal geometry (see: Applied Mathematics and Computation, Volume 27, Issue 1, July 1988, Pages 67–79, Measuring the fractal geometry of landscapes). I used an ordinary grid design to create landscapes in my paper 'Exploring the interaction of avian frugivory and plant spatial heterogeneity and its effect on seed dispersal kernels using a simulation model' in Ecography. But we modified the arena by using a toroidal wrap, meaning that rather than disappearing beyond the limits of the simulation arena, individual birds re-appeared on the other side of the landscape (we also used toroidal distances rather than true Euclidean distances to account for this in the construction of seed dispersal kernels). So yes, a grid is good, but it might need some tweaking for your specific purposes lol :)

Thanks for your reply.  Recently I was lucky to have worked in an area where the inventory I helped with was created using the SPACE-filling curve.  Distances were considerable for that area.  The random points are interesting for method, but not a good design for areas being considered for forest management.

The cruise grids I have had more experience with have had certain spacing for different reasons,  and for the most part my preferences are with the big BAF methods.  Having studied with one of those responsible for its common use in NH, I realize I still l have a lot to learn about the best use of Big BAF.  That being said, thankfully, forestry is very much an art and so choice of grids is often a personal one.

The proximity of big BAF points makes for more data over an area.  Especially in private lands the familiarity with the landscape is better with closer inventory points.  Those who have asked for the inventory often appreciate that.

There is also a lot to be said for the fact that closer points means the person collecting the data knows they were just 300 feet away from the last point (for example) and so a sense of safety might be higher as well--sometimes that is an advantage in forestry. 

Clearly if any trees are being cut, a random sample is not as useful as a grid inventory.  It seems there are other reasons as well, and so still my question stands:  What are the best reasons one would choose a regular grid over another sample model?

I thought I answered the question. But you can use whatever you like – there are no rules lol :)

You did a great job of describing an altermative to the grid.  My written illuistrattion of SPACE-filling  vs. grid maintaines the question. 

Rules or not, it seems to me that resiliency data and forest inventory can be collected in the same sample design.  Random design does seem to be chosen often for resiliency.  Wouldn't a sample grid be used just as well for the purpose, yeilding useful data for more than one type of analysis?

Yes. I'm not a fan of random designs because it is possible they may not sample your items of interest, but a grid is more likely to encounter the objects. If you don't encounter any trees (or birds) then you won't have any to analyse lol :)

Methinks you have no idea what I encountered all week!  LOL!

Yes, I have no idea what happens at the Thompson School of Applied Science during the week haha :)

Seriously Mr Pegman, what amount of timber cruise data (including shrub and herbaceous layer data) do you think would be useful  to someone assessing resiliency and resource heterogeniety?