Fig 1.
Map of the sidewalks and pedestrian areas of the ‘walkable Barcelona’.
In yellow, Barcelona’s Rondes ring road. Source: the authors. Base Cartography from CartoBCN, under CC BY 4.0.
Fig 2.
Diagram of the workflow, with the three main processing blocks in separate rows.
Steps are numbered in the order they were performed, and the processing name appears in bold with the selected processing tool in parentheses below. The main motivation of the tool choice among alternatives appears in italics underneath. Source: the authors.
Fig 3.
Workflow steps to produce a directed graph from the source data.
The complexity of the data is expressed as node and vertex count at each step, in a logarithmic scale. The processing time required is shown as elapsed minutes from the initial condition. Source: the authors.
Fig 4.
Effect of the densification in the accuracy of the centerlines: Default sidewalk geometry (left) and densified sidewalk geometry (right).
Source: the authors. Base Cartography from CartoBCN, under CC BY 4.0.
Fig 5.
Densified sidewalk polygons (light blue) with their originating seed points (dark blue), and resulting ridges (black lines) with their ridge end vertices (red).
Source: the authors. Base Cartography from CartoBCN, under CC BY 4.0.
Fig 6.
Calculated widths of the extracted straight skeleton, represented as a circle with the computed width as its radius, with its center in the middle of the ridge segment.
Source: the authors. Base Cartography from CartoBCN, under CC BY 4.0.
Fig 7.
Decomposition of the single sidewalk polygon into fragments enabling index-assisted spatial queries.
Fragments are randomly colored according to the modulo-10 of their feature identifier for differentiation purposes. Source: the authors.
Fig 8.
Extracted straight skeleton corresponding to the ridge segments within the sidewalk polygon.
Source: the authors.
Fig 9.
Simplified skeleton in black, with removed segments identified as dangles in red.
Source: the authors.
Fig 10.
Crosswalks of the ‘walkable Barcelona’.
Source: the authors.
Fig 11.
Comparison of Tobler’s original hiking formula compared to the adapted formula.
Maximum walking speed (5% downhill slope) denoted with a gray vertical dashed line. Walkable slope ranges (lower than 20%) are shaded in gray. Source: the authors.
Fig 12.
Graphical representation of the homogenization process where each node receives a weight corresponding to the sum of the half-distances of all its incident edges.
Nodes and half-edges are randomly colored according to modulo-10 of the feature identifier of the terminal node for differentiation purposes. Source: the authors.
Fig 13.
Betweenness centrality at a 15-minute walking distance (0,9m/s mean speed, 810m equivalent distance), considering slope, crosswalks, and the topology of the walkable network.
Source: the authors.
Fig 14.
Map of the sidewalks of Barcelona according to the width.
Source: the authors.
Fig 15.
Density distribution of the width of the extracted sidewalk segments, weighted by their length.
The vertical dotted line corresponds to the weighted median. Source: the authors.
Fig 16.
Map of the sidewalks of Barcelona according to the slope.
Source: the authors.
Fig 17.
Density distribution of the longitudinal slope of the extracted sidewalk segments, weighted by their length.
The vertical dotted line corresponds to the weighted median. Source: the authors.
Fig 18.
Correlation map between betweenness centrality (15 minutes walking, 0.9m/s) and width of the sidewalks.
In red are those sidewalks with the highest coefficient, representing high levels of potential conflict between through-movement and sidewalks capacity. In blue, the walkable network with a low coefficient represents the less densified sidewalks by proximity movements. Source: the authors.