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CTnetwork

  • Nov 12
  • 1 min read
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CTnetwork extracts street and POI data from OpenStreetMap and computes connectivity and accessibility metrics for urban areas.


Purpose of Tool:

CTnetwork is a Python package for downloading street-network and Points of Interest (POI) data from OpenStreetMap (OSM) for a given city or bounding-box, and for computing network metrics on the street network (e.g., street betweenness, sinuosity, intersection closeness) as well as accessibility of POIs from different origin locations. GitHub+1


Classification of tool:

Model (or more precisely: a computational modelling / analysis-tool library)


Required skills:

  • Python programming (to use the library functions)

  • GIS/geospatial data understanding (street networks, POIs, bounding boxes, isochrones)

  • Familiarity with OSM data formats and possibly libraries such as OSMnx/networkx (implicitly)


Required input data:

  • A street-network for a given area (via OSM)

  • POI (Points of Interest) data from OSM for that area

  • Parameters specifying the city name(s) or bounding-box (latitude/longitude extents) and network type (e.g., ‘drive’, ‘walk’) e.g., through functions such as streets.get_streets_per_cities or streets.get_streets_per_bbox. GitHub

  • (Optionally) If computing accessibility: origin locations or nodes from which to compute accessibility of POIs


Output:

  • A geospatial dataset (for example shapefiles, or geodataframes) representing the street network enriched with computed centrality metrics (street betweenness, sinuosity, intersection closeness) GitHub+1

  • Results of accessibility calculations: number (or measure) of accessible POIs from given origins via the street network (though note the README indicates that POI-accessibility metrics are still “PENDING” in development) GitHub

  • Possibly output folders with network files, metrics attributes, visualization-ready formats



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