Tracing golden monkeys through time

My collegue TUYISINGIZE Deogratias (“Deo) and others at Dian Fossey Gorilla Fund International have been studying golden monkeys (Cercopithecus kandti) in Rwanda. Golden monkeys are an endangered monkey along the Albertine Rift (including the Virungas, host to the endangered mountain gorilla). They are also cute as can be, but more on that another time. Deo has been leading efforts to track the golden monkeys in … Continue reading Tracing golden monkeys through time

A little Gorilla Time

I miss my mountain gorilla friends in Rwanda. Let’s write a little more code to support them. I’ll be visiting Karisoke again next week, so it seems timely to post a little more code (HT Jean Pierre Samedi Mucyo for working with me on this one). The problem today is simple — given a time series of gorilla locations and dates, can we calculate rate … Continue reading A little Gorilla Time

Taking Slices from LiDAR data: Part IX

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, […]

Continue reading Taking Slices from LiDAR data: Part IX

Taking Slices from LiDAR data: Part VIII

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, […]

Continue reading Taking Slices from LiDAR data: Part VIII

Taking Slices from LiDAR data: Part VII

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, […]

Continue reading Taking Slices from LiDAR data: Part VII

Using foreign data wrapper to use PostGIS with SQLServer

Here was the problem that needed solved last week (we have a few similar problems in upcoming projects, so this was an exciting thing to try): we needed to use PostGIS to access data in a SQLServer database. The SQLServer database backs the web site in question, the underlying content management system, etc., so no– removing SQLServer isn’t really an option at this stage. Obviously … Continue reading Using foreign data wrapper to use PostGIS with SQLServer

Taking Slices from LiDAR data: Part VI

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

PostgreSQL table drop — a little fun with ouroboros

My latests posts on PDAL have been fun. For the moment, a quick bit of code for dropping all the tables in your PostgreSQL database. BTW, the following is a bad idea. Many bad ideas are really useful. This is a really useful but bad idea: How does this work? Let’s do a quick step through. First we echo “\dt”. This just prints literally (the literally … Continue reading PostgreSQL table drop — a little fun with ouroboros

Taking Slices from LiDAR data: Part V

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

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