Thread by @martinfleis

We have a new #openaccess paper at @GeogAnalysis 🎉, fresh from the oven. It is called "Evolution of Urban Patterns: Urban Morphology as an Open Reproducible Data Science" and it is available online for anyone onlinelibrary.wiley.com/doi/full/10.11…. Thread time! 🧵 1/n

@GeogAnalysis We (myself, @alefeliciotti and Will Kerr) have looked at opportunities current developments in geographic data science within the Python ecosystem offer to urban morphology. And how all that links to open science, reproducibility and such. 2/n

@GeogAnalysis @alefeliciotti 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. 3/n

@GeogAnalysis @alefeliciotti We have tried to map all the specialised open-source tools urban morphologists can use these days, which resulted in this nice table. The main conclusion? Most of them are plug-ins for QGIS or ArcGIS, hence depend on pointing and clicking. A tricky thing to reproduce. 4/n

@GeogAnalysis @alefeliciotti We prefer code-based science, so we took the Python ecosystem and put it in the test. We have designed a fully reproducible workflow based on GeoPandas, OSMnx, PySAL and momepy to sample and study 42 places around the world, developed at very different times. 5/n

@GeogAnalysis @alefeliciotti We measured a bunch of morphometric characters (indicators for individual aspects of form) and looked at their change in time. And there is a lot to look at. There are significant differences not only in scale (on the figure below) but in other aspects as well. 6/n

@GeogAnalysis @alefeliciotti Switching to a code-based analysis may be associated with a steep learning curve. However, not everyone needs to reach the developer level as the data science ecosystem aims to provide a middle ground user level. That is a bit like Lego—you learn how to put pieces together. 7/n

@GeogAnalysis @alefeliciotti We think that moving from QGIS to Python (or R), as daunting as it may seem to some, is worth it. It helps us overcome the reproducibility crisis science is going through, the crisis caused, among other things, by relying on pointing and clicking too much. 8/n

@GeogAnalysis @alefeliciotti The open research, based on open platforms and community-led governance, has the potential to democratise science and remove unnecessary friction caused by the lack of cooperation between research groups while bringing additional transparency to research methods and outputs. 9/n

@GeogAnalysis @alefeliciotti End of the 🧵.

The paper is open access (yay!) (link in the first post), the research is fully reproducible (even in your browser thanks to amazing MyBinder!) with all code on GitHub (github.com/martinfleis/ev…). Summary on martinfleischmann.net/evolution-of-u…. 10/10

@GeogAnalysis @alefeliciotti I forgot to add that this would not be possible without the amazing #pydata and #geopython community! Thanks to @pysal_devs, @geopandas, @gboeing, @ProjectJupyter, @michaelwaskom, @jorisvdbossche, @astutespruce and many many other unsung heroes!