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Co-accessibility

  • Nov 12
  • 2 min read
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Coaccessibility measures how different age groups can reach urban amenities on foot, providing indicators of accessibility equity and age-diverse access.


Purpose of Tool:

The coaccessibility tool is an open-source Python library that computes demographic breakdowns of individuals who can walk to urban amenities (points of interest) within given walking time thresholds (5, 10, 15 minutes) across a street-network. It quantifies how many children, adults and elderly persons can reach each destination, and computes an age-diversity (co-accessibility) index for each place. GitHub+1In the Equal-Life context, this tool helps operationalise built-environment exposure assessment for children’s development by providing metrics of accessibility equity and age-diverse access to urban amenities — key for the physical exposome and social exposure dimensions.


Classification of tool:

Model / analytical tool (Python library for spatial accessibility & demographic access modelling)


Required skills:

  • Python (to run the library, data processing, spatial queries)

  • GIS / geospatial analysis (street-network, walkshed computation, demographic grids)

  • Familiarity with database spatial systems (e.g., PostGIS) and open street-network data. GitHub+1


Required input data:

  • Pedestrian walkable street-network data (e.g., extracted from OSM)

  • Population grid data broken down by age groups for origins (residential blocks)

  • Points of Interest (amenities) data for destinations

  • Walking time thresholds/settings (5, 10, 15 minutes) and walking speed parameters GitHub


Output:

  • For each destination: number of children, adults, elderly persons who have walking access within specified thresholds; percentage breakdowns by age group. GitHub+1

  • An age-diversity (entropy/equitability) index for populations with access to each destination, highlighting places with high or low demographic access diversity. zenodo.org

  • Spatial data layers (geodataframes/shapefiles) that can be mapped or further analysed to identify accessibility inequities across neighbourhoods.


Relation to other tools:

  • This tool can be seen as a detailed, demographic-sensitive layer of the built-environment modelling chain: first mapping street networks and POIs (e.g., via tools like CTnetwork), then computing walksheds and accessibility (e.g., via interactive tools like CTwalk Map) and finally analysing co-accessibility/age-diversity of access using coaccessibility.

  • It supports the Equal-Life Toolbox’s goal of providing open-source tools for measuring external exposome exposures (physical and built environment) by adding a social dimension: who can access what, how equitably.

  • Its outputs could feed into exposure-outcome modelling (children’s developmental & mental-health outcomes) by providing metrics of access equity and diversity which may correlate with wellbeing, social-cohesion and child-friendly environments.


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