geography

I am sitting on a train back to Prague after two days of discussing tooling for spatial data science available in the Python, R and Julia ecosystems, with occasional excursions to the worlds of Rust, JavaScript or ESRI. I am coming back from the Spatial Data Science across Languages (SDSL) workshop and I’d like to share a few thoughts1 while they’re fresh. Different maturity of ecosystems As a Python developer, I must admit that what the R-Spatial community managed to create is impressive and is in some aspects further that where we are....

This is the map we have created for the Urban Grammar AI project. It is created using open source software stack and hosted on GitHub, for free. This post will walk you through the whole process of generation of the map, step by step, so you can create your own. It is a bit longer than usual, so a quick outline for better orientation: By the end of this tutorial, you will be able to take your vector data and turn them into a fully-fledged vector map hosted on GitHub with no cost involved, for everyone to enjoy....

Using Python for data science is usually a great experience, but if you’ve ever worked with pandas or GeoPandas, you may have noticed that they use only a single core of your processor. Especially on larger machines, that is a bit of a sad situation. Developers came up with many solutions to scale pandas, but the one that seems to take the lead is Dask. Dask (specifically dask.dataframe as Dask can do much more) creates a partitioned data frame, where each partition is a single pandas....

We have a new paper published in the Geographical Analysis on the opportunities current developments in geographic data science within the Python ecosystem offer to urban morphology. To sum up - there’s a lot to play with and if you’re interested in the quantification of urban form, there’s no better choice for you at the moment. Urban morphology (study of urban form) is historically a qualitative discipline that only recently expands into more data science-ish waters....

On March 30, 2021, I had a chance to deliver a talk as part of the Spatial Analytics + Data Seminar Series organised by the University of Newcastle (Rachel Franklin), the University of Bristol (Levi Wolf) and the Alan Turing Institute. The recording of the event is now available on YouTube. Spatial Signatures: Dynamic classification of the built environment This talk introduces the notion of “spatial signatures”, a characterisation of space based on form and function....

Sometimes our lines and polygons are way too complicated for the purpose. Let’s say that we have a beautiful shape of Europe, and we want to make an interactive online map using that shape. Soon we’ll figure out that the polygon has too many points, it takes ages to load, it consumes a lot of memory and, in the end, we don’t even see the full detail. To make things easier, we decide to simplify my polygon....