Much the problem of the modern era– too much data, uneven data, and yet, should we keep it all? Here’s the problem space: attach GPS collar to a coyote, send that data home, and you have a recipe for gleaning a lot of information about the movement of that animal across the landscape. In order to maximize the data collected while also maximizing the battery … Continue reading Cleaning animal tracking data — throwing away extra points
There’s all sorts of reasons why what I’ve been doing so far is wrong (see the previous 5 posts). More on that later. But in case you needed 3D visualization of the chipping I’ve been working through, look no further: Continue reading LiDAR and pointcloud extension pt 6
Now for the crazy stuff: The objective is to allow us to do vertical and horizontal summaries of our data. To do this, we’ll take chipped LiDAR input and further chip it vertically by classifying it. First a classifier for height that we’ll use to do vertical splits on our point cloud chips: And now, let’s pull apart our point cloud, calculate heights from approximate … Continue reading LiDAR and pointcloud extension pt 5
Now, we navigate into unknown (and perhaps silly) territory. Now we do point level calculations of heights, and drop the new calculated points back into the point cloud as though it were a Z value. I don’t recommend this code as a practice– this is as much as me thinking aloud as anything Caveat emptor: Continue reading LiDAR and pointcloud extension pt 4
Digging a little deeper. Ran the chipper on a smaller number of points and then am doing a little hacking to get height per chip (if you start to get lost, go to Paul Ramsey’s tutorial). Here’s my pipeline file. Note the small chipper size– 20 points per chip. Easy enough to load (though slow for the sake of the chip size): Now we can … Continue reading LiDAR and pointcloud extension pt 3
As much for my edification as anyones: Want to get at just a few points within the pointcloud extension? A with query will get you there: Continue reading LiDAR and pointcloud extension pt 2
Paul Ramsey has a great tutorial on using the pointcloud extension with PostgreSQL / PostGIS: http://workshops.boundlessgeo.com/tutorial-lidar/ You can get point cloud and all that goodness running a variety of ways. Probably the easiest is to download OpenGeo Suite from Boundless: http://boundlessgeo.com/solutions/opengeo-suite/download/ If you are an Ubuntu user, try a docker instance to run PostGIS with PDAL, pointcloud, etc in a container: https://github.com/vpicavet/docker-pggis Also, I’m working … Continue reading LiDAR and pointcloud extension
Docker. See: https://github.com/vpicavet/docker-pggis for a quick and easy Docker running PostGIS. Understand, this isn’t production ready (the connection permissions make my teeth hurt a little) but, so nice to have a one stop shop for postgis, pgrouting, and pointcloud. Now I may have to write blog posts on pointcloud. Point cloud didn’t get in the PostGIS Cookbook because it was too hard to build. I … Continue reading The easiest way to get PostGIS and friends running:
Now I feel like a salesman. I feel obliged to mention the Packt buy one get one free sale (ends tomorrow): http://www.packtpub.com/?utm_source=referral&utm_medium=marketingPR&utm_campaign=2000thTitle If you want a postgresql title to go with the PostGIS Cookbook (just sayin’): http://www.packtpub.com/search?keys=postgresql&sort=0&types=0&forthcoming=1&available=1&count=20&op=Go Ok. Enough. Back to fun reading: Continue reading Packt Sale — 2 books for the price of one
This is starting to feel real… PostGIS Cookbook(s). 2904 pages. Page count for a single book can be calculated as in the following code: The preceding query will result in the following: A special thanks to my family, my co-authors, all the contributors to PostGIS, and to Regina Obe for helping me through the hardest bit of code in my part of the book. Check … Continue reading PostGIS Cookbook(s)
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