If you ever wanted to polygonize something like a street network with shapely, you may have noticed missing geometries in the result, like in the case of Vienna below. I had the same issue, and this is a note to myself… Continue reading Fixing missing geometries in a polygonized network
Blog
Introduction to GeoPandas and its Python ecosystem
A talk from the OpenGeoHub Summer School 2022. Workshop materials The ecosystem of packages for spatial data handling and analysis in Python is extensive and covers both vector and raster analytics from small to large distributed data. This talk covers only a small part, focusing on vector data processing with GeoPandas at its core. First,… Continue reading Introduction to GeoPandas and its Python ecosystem
How to create a vector-based web map hosted on GitHub
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… Continue reading How to create a vector-based web map hosted on GitHub
Understanding the structure of cities through the lens of data
The workshop organised together with James D. Gaboardi during the Spatial Data Science Symposium 2022 is now available online. See the recording below and access the workshop material on Github from which you can even run the code online, in your browser. Annotation Martin & James will walk you through the fundamentals of analysis of… Continue reading Understanding the structure of cities through the lens of data
Introducing Dask-GeoPandas for scalable spatial analysis in Python
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… Continue reading Introducing Dask-GeoPandas for scalable spatial analysis in Python
Dask-GeoPandas vs PostGIS vs GPU: Performance and Spatial Joins
Paul Ramsey saw a spatial join done using a GPU and tried to do the same with PostGIS, checking how fast that is compared to the GPU-based RAPIDS.AI solution. Since Paul used parallelisation in PostGIS, I got curious how fast Dask-GeoPandas is on the same task. So, I gave it a go. Let’s download the… Continue reading Dask-GeoPandas vs PostGIS vs GPU: Performance and Spatial Joins
Methodological Foundation of a Numerical Taxonomy of Urban Form
The final paper based on my PhD thesis is (finally!) out in the Environment and Planning B: Urban Analytics and City Science. We looked into ways of identifying patterns of urban form and came up with the Methodological foundation of a numerical taxonomy of urban form. You can read it on the journal website (open… Continue reading Methodological Foundation of a Numerical Taxonomy of Urban Form
Capturing the Structure of Cities with Data Science
During the Spatial Data Science Conference 2021, I had a chance to deliver a workshop illustrating the application of PySAL and momepy in understanding the structure of cities. The recording is now available for everyone. The materials are available on my GitHub and you can even run the whole notebook in your browser using the… Continue reading Capturing the Structure of Cities with Data Science
xyzservices: a unified source of XYZ tile providers in Python
A Python ecosystem offers numerous tools for the visualisation of data on a map. A lot of them depend on XYZ tiles, providing a base map layer, either from OpenStreetMap, satellite or other sources. The issue is that each package that offers XYZ support manages its own list of supported providers. We have built xyzservices… Continue reading xyzservices: a unified source of XYZ tile providers in Python
Evolution of Urban Patterns: Urban Morphology as an Open Reproducible Data Science
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… Continue reading Evolution of Urban Patterns: Urban Morphology as an Open Reproducible Data Science