We have legs for walking. This is a true fact. Walking for long distances can be painful. This is also a true fact. This package rwalkable eases the pain by exploring the walkability of neighbourhoods.
We make use of osmdata and dodgr packages to estimate walkability metrics such as points of interest per hectare.
nearby()Walkable neighbourhoods have lots of points of interest (amenities) that are within some walkable distance.
Let’s look at points of interest nearby Paris, France and compare them to Paris, Texas, USA
devtools::load_all("../")
#> Loading rwalkable
paris <- nearby("3rd Arrondissement, Paris, France")
paris
#> Within 800 m of 3rd Arrondissement, Paris, France
#> 7.1 points of interest per hectare
#> 2.2 road branches per hectare
the_other_paris <- nearby("Paris, Texas, USA")
the_other_paris
#> Within 800 m of Paris, Texas, USA
#> 0 points of interest per hectare
#> 0.4 road branches per hectareThe location can also defined by a vector of longitidue and latitude representing the centre of a neighbourhood.
By default, we consider an distance walkable if it’s within 800m radius of the location.
We can modify this with the radius argument, which takes a walking distance in metres,
nearby("Paris, France", radius = 2000)or we can estimate all points of interest for a given walking time in minutes
nearby("Paris, France", radius = walk_time(15))By default all amenities are to be points of interest, this can modified with the amenities argument. Valid amenities can be found on OpenStreetMap
nearby("Paris, France", amenities = "cafe")We can also make an interactive map of the neighbourhood with the amenities using leaflet. There’s a dropdown menu on the top right hand side of the map to filter amenties that are not interesting out.
Here’s a walkable neighbourhood
plot(paris, overlay_isochrone = TRUE)
#> dist is assumed to be in decimal degrees (arc_degrees).And a not so walkable neighbourhood
plot(the_other_paris, overlay_isochrone = TRUE)
#> dist is assumed to be in decimal degrees (arc_degrees).