I finally got PDAL properly compiled with Point Cloud Library (PCL) baked in. Word to the wise — CLANG is what the makers are using to compile. The PDAL crew were kind enough to revert the commit which broke GCC support, but why swim upstream? If you are compiling PDAL yourself, use CLANG. (Side note, […]
I finally got PDAL properly compiled with Point Cloud Library (PCL) baked in. Word to the wise — CLANG is what the makers are using to compile. The PDAL crew were kind enough to revert the commit which broke GCC support, but why swim upstream? If you are compiling PDAL yourself, use CLANG. (Side note, […]
I finally got PDAL properly compiled with Point Cloud Library (PCL) baked in. Word to the wise — CLANG is what the makers are using to compile. The PDAL crew were kind enough to revert the commit which broke GCC support, but why swim upstream? If you are compiling PDAL yourself, use CLANG. (Side note, […]
I finally got PDAL properly compiled with Point Cloud Library (PCL) baked in. Word to the wise — CLANG is what the makers are using to compile. The PDAL crew were kind enough to revert the commit which broke GCC support, but why swim upstream? If you are compiling PDAL yourself, use CLANG. (Side note, the revert to support GCC was really helpful for ensuring … Continue reading Taking Slices from LiDAR data: Part VI
For this post, let’s combine the work in the last 4 posts in order to get a single pipeline for doing the following: Calculate relative height of LiDAR data Slice that data into bands of heights Load the data into a PostgreSQL/PostGIS/pgPointCloud database. Now, we can use parallel to make this run a little faster: Sadly, we can run into issues in running this in … Continue reading Taking Slices from LiDAR data: Part V
In PDAL, a pipeline file can be used to do a variety of operations. Within the following context, I think of a pipeline file like an ad hoc preferences file, where I can use an external command to iterate through the things I want to change, while holding constant everything else in the pipeline file. In my use case for this vignette, I’ll use the … Continue reading Taking Slices from LiDAR data: Part IV
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
“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
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
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