Landscape Position using GDAL — PT 3

More landscape position pictures — just showing riparianess. See also https://smathermather.wordpress.com/2014/11/22/landscape-position-using-gdal/ and https://smathermather.wordpress.com/2014/11/24/landscape-position-using-gdal-pt-2/ Map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL Continue reading Landscape Position using GDAL — PT 3

Landscape Position using GDAL

Hat tip again to Seth Fitzsimmons. I’ve been looking for a good, easy to use smoothing algorithm for rasters. Preferably something so easy, I don’t even need to write a little python, and so efficient I can run it on 30GB+ datasets and have it complete before I get distracted again by the next shiny project (a few hours). Seth’s solution? Downsample to a low … Continue reading Landscape Position using GDAL

Kicking the tires of PostGIS 2.0 — Testing ST_MakeValid

The feature in PostGIS 2.0 that excited me most was not topology support, raster support, or 3D functions.  Ok, raster was near the top of my list.  But what I was really excited by was the ST_MakeValid function.  Sad, isn’t it?  Lack of vision probably– excited to try to solve recurring technical snafus in a computationally inexpensive way, rather than being more excited by the … Continue reading Kicking the tires of PostGIS 2.0 — Testing ST_MakeValid

Landscape Position: Conclusion? (part 2)

From earlier post: “I’ve managed to pilot most of a fast high resolution landscape position workflow with PovRay as my magic tool. The final steps I hope to pipe through PostGIS Raster. In the meantime a screenshot and description: blues are riparian, raw ocre, etc upland categories, grey is mostly flat lake plain and mid slopes, all derived from just a high res DEM input … Continue reading Landscape Position: Conclusion? (part 2)

Landscape Position: Conclusion?

I’ve managed to pilot most of a fast high resolution landscape position workflow with PovRay as my magic tool. The final steps I hope to pipe through PostGIS Raster. In the meantime a screenshot and description: blues are riparian, raw ocre, etc upland categories, grey is mostly flat lake plain and mid slopes, all derived from just a high res DEM input (no hydro lines … Continue reading Landscape Position: Conclusion?

Landscape Position Continued– Median and ImageMagick

Highlighting ridges with 250ft buffer (on 2.5ft DEM) with just ImageMagick: convert lscape_posit.png -median 100 median100.png composite -compose difference lscape_posit.png median100.png difference_median100.png Input: Output: BTW, median calculations of this size are slow, even in ImageMagick. Continue reading Landscape Position Continued– Median and ImageMagick

Landscape Position Continued– absolutely relative position calculation

I apologize in advance– this first post will be heavy on code, short on explanation. Landscape position, e.g. previous posts, can be trivial to calculate, but to make the calculations scalable to a large area, some batching is necessary. In this case, instead of a McNab index, we’re calculating the traditional GIS landscape position. Enter my favorite non-geographic tool, PovRay… . To the difference between, … Continue reading Landscape Position Continued– absolutely relative position calculation

Landscape Position and McNab Indices (cont.2)

In one and two previous posts, I talked about McNab indices and what they mean and how to compute them.  This is a short post just showing another screenshot of a McNab mesoscale.  The previous image was from a stream valley running through the glaciated Allegheny Plateau.  This image is a stream cut through the soft shale of the Lake Plain of the Eastern Basin … Continue reading Landscape Position and McNab Indices (cont.2)