Taking Slices from LiDAR data: Part III

forest_structure Borrowed from: http://irwantoshut.com Continuing my series on slicing LiDAR data in order to analyze a forest, one of the objectives of the current project is to understand the habitats that particular species of birds prefer. This will be accomplished using field info from breeding bird surveys combined with LiDAR data of forest structure to help predict what habitats are necessary for particular species of … Continue reading Taking Slices from LiDAR data: Part III

parallel processing in PDAL

“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

wget for downloading boatloads of data

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

Point Clouds – the (re)start of a journey

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

Yet another approach to ST_Buffer on geography

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

ST_Buffer on Geography — Iteration

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

Final?: ST_Buffer on Geography, or My love for @NullIsland

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

ST_Buffer diving under the covers part 1

This will be a quick post. I just looked at how ST_Buffer is written in the PostGIS codebase, and I thought this was interesting. When you use ST_Buffer and specify geometry, buffer distance, and an integer value, this gets converted in the overloaded function into a quad_segs version. P.S. I would have written more, but Sherlock just started. Continue reading ST_Buffer diving under the covers part 1