Let’s start putting some of the pieces together. Earlier, I presented a method for deriving a digital surface model from LiDAR data of a forest canopy, using a tree-shaped interpolator that scales the individual tree canopy shapes according to the height of the LiDAR return from the ground. Now I present the whole project, forest and all. I wanted to render my DSM at a … Continue reading Digital Surface Model– a whole forest and then some
One of my goals in modeling canopy height is to estimate sub-canopy biophysical variables that give indications of habitat suitability. For example, suppose we have a rare plant that is canopy gap dependent. How do we model it’s distribution? With a statewide LiDAR dataset from which we can derive canopy location and height, we can identify canopy gaps. While I haven’t gotten to the modeling … Continue reading Modeling (relative) Sub-Canopy Biophysical Variables with PovRay
One limitation I’ve run into in rendering large scenes of trees in PovRay, whether for fun for work is memory usage. I’ve found that about a half million trees is about as many as I can place on a 32-bit system before running out of memory. Sometime this year I’ll switch to 64-bits, but in the mean time, I hacked together a solution for reducing … Continue reading Optimizing Pov-Ray include files– smaller trees with the same effect
Below is my metacode for iterating through a grid of images to render the vegetation surface model from povray. The real code will be implemented in BASH and AWK, although this would be a perfect use of Python, if I knew how to use it… . PostGIS Tables: cuy_veg_points: Load veg points into database and make 2D geometry cuy_terrain_points: Load terrain points into … Continue reading Rendering a vegetation surface model using PovRay (cont.)
Early on, I was working on the problem of rendering a virtual forest based on real LiDAR data in order to do things like a detailed, vegetation included, viewshed. There are other things we can do with this data, including discovering the boundary of the canopy (and thus find canopy gaps) and rendering a vegetation surface model. Let’s start with a single tree. If we … Continue reading Rendering a vegetation surface model using PovRay
Not much to say here. I had a bit of inspiration, remembering a Christoph Hormann tutorial http://www.imagico.de/pov/icons.html on making transparent icons in povray and realized that what he was describing was the final piece in the povray for viewsheds milleau: no_image option for an object forces it to interact with the scene in every way, but to be seen by the camera. I’ll post the … Continue reading No Image– a very simple solution for calculating viewshed
This is a “wouldn’t it be nice” post– i.e. a I-don’t-have-time-to-write-it-and-everything-else-on-my-list post. Wouldn’t it be nice if in addition to returning GeoRSS, WFS, OGC, KML, etc. GeoServer returned a POV-Ray file? It could be returned as part of a simple GET post like this: http://localhost:8080/geoserver/wms?bbox=2100506,575982,2290532,739026&styles=&Format=application/povray&request=GetMap&version=1.1.1&layers=base:contours&width=800&height=644&srs=EPSG:102722&camera=2195519,657504,1000&look_at=2195029,657004,500 Vector symbolization could be a POV-Ray approximation of the WFS render styles using coordinates and POV primitives. Also, a PHP … Continue reading POV-ray for GIS Visualization
Ok, your average terrain-only based viewshed (view is from a road to the southeast, viewshed is in cyan): Note that based on these estimates, we should be able to see most of the valley walls from this little slice of road. I don’t buy that. That section of road is pretty closed in with trees. Let’s add them: As you may see, just a little … Continue reading Povray Viewshed with Trees (finally) (cont.)
Povray Viewshed with Trees: if we cannot yet have veracity, at least may we have verisimilitude. Continue reading Povray Viewshed with Trees (finally)
Just a short teaser post until I remember to bring the code home with me, but I’ve placed trees within the bounds of a canopy layer determined from some county LiDAR dataset. The tree locations, heights, and rotation are set using pseudo-random numbers, which looks a lot better than a monoculture of the same tree. Eventually, estimating stem locations and canopy heights to do this … Continue reading Povray Landscape with Trees
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