Urban landscape of Central Europe

Data product

To run:

1. Clone this repository.

2. Run pixi install, then pixi run build and optionally pixi run tests . These commands setup the enviroment and all the required packages.

   • Alternatively you can manually install the conda-forge dependencies, but you have to still run the pixi build and tests commands: pixi add momepy umap-learn fast_hdbscan jupyterlab pyarrow matplotlib lonboard folium mapclassify datashader dask pip sidecar glasbey scikit-image colorcet pandas holoviews bokeh=3.1 esda pytest hdbscan

3. To run jupyter use either pixi run jupyter lab or pass extra arguments like pixi run jupyter lab --port 8888.

4. To run the analysis on the whole dataset - first, make sure you have the correct folder structure in place. Then, run:

   • code/download_buildings.ipynb to download all the cadastre data for central europe

   • code/explore_cadastre_data.ipynb to standardise all the cadstre data from different countries into a single format

   • code/generate_regions.ipynb to split the buildings into regions for independent processing

   • code/download_streets.ipynb to download the raw overture streets for every region

   • code/processing_apartment_blocks.ipynb to update socialist housing in Czechia ( needs to be run after building simplification)

   • bash full_run.sh to run the entire processing pipeline from building, street preprocessing, element generation, characters calculations and morphotope creation.

   • code/divisive_kmeans.ipynb to generate the heirarchy of morphotopes.

   • code/noise.ipynb to assign the noise points to the nearest clusters.

   • code/cluster_naming.ipynb to see the cluster naming notebook.

   • code/comparisons.ipynb to generate comparisons with other data products.

   • code/cluster_exploration.ipynb to map specific regions.

   • code/interactive_chars_exploration.ipynb to interactively plot characters in specific regions.

5. (optional) to run the analysis on individual regions use - code/process_region.ipynb and code/region_clustering.ipynb notebooks.