I typed that last one too quickly– too many typos, but my wife says I’m not supposed to revise blogs, but move on… . So, for clarity, let’s talk a little more about McNab indices. Field-derived McNab indices are a measure of average angle from the observer to the horizon (mesoscale landform index), or from the observer to another field person a set distance away, … Continue reading Landscape Position and McNab Indices (cont.)
Start-up scripts in Debian Linux aren’t exactly straight forward for the un-initiated. Actually, if memory serves me, they aren’t any more straight forward on Ubuntu Linux either, but such is heredity. We are transitioning some of our GeoServer instances over to 64-bit Debian Linux. In my test Ubuntu environment, I had a hack in place to force the Tomcat Java Servlet to launch on startup, … Continue reading Debian Configuration– Tomcat on Boot
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
In some of my first posts, I discussed the possibility of using povray for viewshed analyses, since it is a more flexible tool, and can better handle complex analyses, like terrain + vegetation, something which most GIS tools cannot. In the end though, I just produced a simple terrain based viewshed analysis. Now, I’m getting ready to go deeper. Now, I’m ready to put some … Continue reading POV-Ray for viewsheds (with trees?)
Ok, so projecting an image isn’t hard at all in POV-Ray. I’m not sure what I was thinking. In my first post on camera calibration in POV-Ray, I suggested that we could analytically solve for lens and topographic distortion in POV-Ray. I haven’t gotten far as I don’t have a work project to take advantage of this yet, but I projected a false color infrared … Continue reading Follow-up (#1) for Camera Calibration in POV-Ray (Porro-Koppe Principle in Virtual)
A complete analytic solution for geometric distortions in remote sensing (ahem, ignoring atmosphere, of course) Ok, so here is another thought experiment. This time, it will take a few months before I have time to write the code for this, but maybe the thought experiment will inspire someone. A major problem of photogrammetry, remote sensing, and computer vision is correction of lens distortion. Thanks to … Continue reading 19th Century Camera Calibration for Remote Sensing in PovRay (or Porro-Koppe Principle in Virtual)
global_settings { max_trace_level 1 } #include “shapes.inc” #include “colors.inc” #include “textures.inc” height_field { png “c:\temp\povray\n2225625.png” // 16-bit integer digital elevation water_level 0.0 texture { pigment { image_map { png “C:\temp\povray\n2225625_drape.png” map_type 0 interpolate 2 once } // Aerial rotate x*90 } } scale <5000, 65536, 5000> // Scale to real world size translate <2224868,0,625008> // Translate to location in Ohio state plane } /// Orthographic … Continue reading POV-Ray for viewsheds code
Ok, here’s the basic idea– we have an orthographic scene with a height_field object scaled to real world units. The observers in the viewshed become points of light, thus for each observer, we “light” the areas visible from each observer, render, and boom, viewshed created. In addition, if we have three or fewer view points, we can render them in, say cyan, yellow, and magenta, … Continue reading Follow on to POV-Ray for GIS Analyses–metametacode, no code yet, sorry!
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