Welp, my BASH skills could use some honing, but I’m just working on quick-and-dirty stuff for this series. PDAL as a utility is pretty interesting, so we’ll focus our learnings on PDAL. (Prior posts start here). I may have a build tutorial written for getting through the critical (as contrasted with minimal) parts of a PDAL build. I’m getting tired of running everything through docker. … Continue reading Taking slices from LiDAR data
“Frankfurt Airport tunnel” by Peter Isotalo – Own work. Licensed under CC BY-SA 3.0 via Commons. In my ongoing quest to process all the LiDAR data for Pennsylvania and Ohio into one gigantic usable dataset, I finally had to break down and learn how to do parallel processing in BASH. Yes, I still need to jump on the Python band wagon (the wagon is even … Continue reading parallel processing in PDAL
My current project to create a complete dataset of airborne LiDAR data for Ohio and Pennsylvania has been teaching me some simple, albeit really powerful tricks. We’ll just discuss one today — recursive use of wget. This allows us to download entire trees of web sites to mirror, or in our case download all the data. Additionally, wget works on ftp trees as well, with … Continue reading wget for downloading boatloads of data
PDAL now has the capacity to calculate heights from your point cloud data. With pre-classified LiDAR data, this means you can do this pretty easily: A problem you might have is you may not have all the wonderful PDAL goodness built and installed. So you might get something like this: An easy way around this is to let docker do all the work. Once the … Continue reading PDAL and point cloud height
If you have followed this blog for a while, you will notice a continual returning to and refinement of ideas and topics. That’s how the blog started, and this role it has served, as a touch stone in my exploration of topics is critical to how I use it. I hope it is useful to you too, as a reader. So, let’s talk about point … Continue reading Point Clouds – the (re)start of a journey
Another approach to ST_Buffer would be to subdivide the geometries before buffering, and put them all together at the end. ST_SubDivide can do this for us. We can tell it how may vertices we want in each geometry (minimum of 8). Since _ST_BestSRID will try UTM first, we’ll add enough nodes to ensure we always have 8 nodes within the 1,000,000 meter width of a … Continue reading Yet another approach to ST_Buffer on geography
In my previous post, Imagico said: This is nice but still fails in one important aspect – it will create significant inaccuracies once your buffering distance reaches values where buffering in a single local coordinate system is getting problematic which, depending on your precision requirements, will likely happen at distances of a few degrees. A solution to this would require either an iterative split and … Continue reading ST_Buffer on Geography — Iteration
Thanks to Paul Norman’s reminder in a previous post, we now have all the pieces we need to complete an ST_Buffer function that exposes all the wonderful goodness of buffer style parameters to geography users and also chooses the best local coordinate system automatically. We use _ST_BestSRID to choose our local coordinate system. Remember my previous three disadvantages: It didn’t do this at a low … Continue reading Final?: ST_Buffer on Geography, or My love for @NullIsland
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