Discussion: map

something like this
https://picasaweb.google.com/lh/photo/Txmjjnfzt8NZ...

Mina luen kartta.

:)

There is no vegetaion, I left it out because there was lots of green even on bare rock. I thought there was something wrong in my vegetaion implementation, but looks like the reason is in point classification. It's not correct in that las file, there is lots of ground points classified as something else. So big parts of the hills are missing in contours - those missing parts were green on my original map. Map might have been better wtih green, it would tell where the map is all wrong.

Makes me wonder why classification is so wrong, some sort of automatic algorithm I guess and it did not handle that steep pilars as it should.

If you were there with that map you must have noticed there is something wrong, big time.

Now you tell me!

All the classifiers are automatic. As you have seen, some are better than others. Sometimes there is a manual pass afterwards to clean up. Sometimes the classifiers are set too conservatively in order to "make sure" no non-ground (veg, building) points are left on the ground surface. The goal is to meet the error spec at the average specified post spacing, and most agencies are just interested in their 2 foot contour products, not knolls, cliffs and small reentrants.

I often re-classify datasets myself in order to gain back more of those ground points that have been incorrectly rejected. There's a compiled version of the classifier I use here. There are others around. I think LAStools has one? Read the Evans paper there for more details. This one is designed specifically for forested areas. I usually set the scale to the avg post spacing and the curvature threshold to 0.35 or 0.4. I've played extensively with both terms and with the surface model,trying different ones other than the TPS. I use a simple Delaunay Triangulation, which was just as good and much faster. Ed Despard has modified the TPS in the MCC C code here to run much, much faster. I translated the MCC into IDL and use that. I also have a python version that James Scarborough translated.

When re-classifying with a less conservative cut you will sometimes have some veg accidentally left on the ground surface, so you have to be wary of "errors of comission."

Give it a try on this set and see if it helps.

Finnish data has gone trough manual pass and quality check. I have spotted only two small oddities so far, bot those were tiny ones compared to these half-of-the-hill-is-missing ones. No wonder if some cliffs are missing if the hill is missing too.

Yeah, some of the contours were a bit funny :)

It's not an easy area for the automatic classification --- there are cracks and crevasses, knobbly boulders, etc, so it wouldn't be clear where the ground is. Still...

Yeah, one of the hills with 10m cliffs was a mere dot knoll on the map.

I'll post map with vegetation. I guess pretty much yellow= elevation is about ok, green = < 6 m wrong, white = > 6 wrong. Half of the map was green, lots of white and some yellow stripes here and there.