I need some clarifications before I can get to work on this,

because I am getting a bit confused.

If we have 3D input points for the TIN construction, then

the resulting triangles should be 3D face primitives not

areas (of which I assumed they were 2D primitives in the

GRASS vector model), shouldn't they?

We would then also be talking about kernels, not centroids,

which should be placed in the 3D geometric center of each

traingular face?

Or am I getting this totally wrong?

Also, it seems to me that for a 3D delaunay triangulation

the algorithm has to search for the nearest point in 3D

space, because if it uses a 2D search, than it will be fooled

by undercutting points and triangulate the wrong

point triplets (I admit that undercuts don't usually appear in terrain

surface modelling, but I have some data where they do).

I guess the problem of building topology for massive data sets should

be solved in the GRASS vector libraries, not in individual modules?

Benjamin

Helena Mitasova wrote:

In relation to handling of large data sets - changing the algorithm

may not solve the issue. I haven't tried it with larger data set but

based on my previous experiences it may get stuck on topology building.

So that would need to be solved first (and you cannot skip topology

this time, as we did with points, because the result are areas and

nothing would work with the resulting map without topology).

As for 3D - Benjamin, if you could just add the original z value to the

output vertices (the value for centroid can be computed by calling the

tin.c ) that will be sufficient to get the basic functionality and display

the resulting TIN in 3D. For more sophisticated triangulations using

the existing libraries would be a more comprehensive solution,

as suggested by Markus (as long as we can make them part of GRASS

distribution)

Helena

On Jan 28, 2008, at 4:40 AM, Benjamin Ducke wrote:

I noticed this one too a few days back when I was looking for a

3D hull algorithm. Looks like a promising collection of algorithm

for GRASS.

However, for a quick fix of v.delaunay, as suggested by Helena:

Might it not be enough to replace the 2D distance measure in

v.delaunay with a 3D distance, so it will do the tesselation in

3D space correctly?

I could try and find some time to look into that if you think

it feasible.

Benjamin

Markus Neteler wrote:

On Jan 28, 2008 9:29 AM, Maris Nartiss <maris.gis@gmail.com> wrote:

Fixing large dataset and 3D support problems would be a nice

improvement of GRASS vector support

Possibly we need to substitute the algorithm? I found for example

http://www.qhull.org/

"Qhull computes the convex hull, Delaunay triangulation, Voronoi

diagram, halfspace intersection about a point, furthest-site Delaunay

triangulation, and furthest-site Voronoi diagram. The software runs in

2-d, 3-d, 4-d, and higher dimensions. Qhull implements the Quickhull

algorithm for computing the convex hull. It handles roundoff errors

from floating point arithmetic. Qhull also computes volumes, surface

areas, and approximations to the convex hull."

(seems to be GPL compliant)

Markus

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Benjamin Ducke, M.A.

Archäoinformatik

(Archaeoinformation Science)

Institut für Ur- und Frühgeschichte

(Inst. of Prehistoric and Historic Archaeology)

Christian-Albrechts-Universität zu Kiel

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_______________________________________________

grass-dev mailing list

grass-dev@lists.osgeo.org

http://lists.osgeo.org/mailman/listinfo/grass-dev

--

Benjamin Ducke, M.A.

Archäoinformatik

(Archaeoinformation Science)

Institut für Ur- und Frühgeschichte

(Inst. of Prehistoric and Historic Archaeology)

Christian-Albrechts-Universität zu Kiel

Johanna-Mestorf-Straße 2-6

D 24098 Kiel

Germany

Tel.: ++49 (0)431 880-3378 / -3379

Fax : ++49 (0)431 880-7300

www.uni-kiel.de/ufg