The goal of this CycleInfraLnd R package is to download data from the Transport for London Cycling Infrastructure Database and import it into R as spatial data (Simple features).
The Cycling Infrastructure Database contains the following assets that are either lines(l) or points(p):
-
Advanced Stop Line (l)
-
Crossing (l)
-
Cycle lane/track (l)
-
Restricted Route (l)
-
Cycle Parking (p)
-
Restricted Point (p)
-
Signage (p)
-
Signal (p)
-
Traffic Calming (p)
More information on the CID can be found here and in this TFL blog.
The Database Schema, Asset Information Guide and README provide important and useful information about the content of the database and how it was collected.
You can install the developed version of CycleInfraLnd from Github with:
# install.packages("devtools")
devtools::install_github("PublicHealthDataGeek/CycleInfraLnd")These examples show the two functions in this package that allow you to obtain either lines or points from the Cycling Infrastructure Database. The example list in the help file contains all variations of this code for each of the different asset types i.e. the different lines and points that are available in the Cycling Infrastructure Database.
library(CycleInfraLnd)
get_cid_lines(type = "advanced_stop_line")
#> Simple feature collection with 3775 features and 11 fields
#> geometry type: LINESTRING
#> dimension: XY
#> bbox: xmin: -0.4837958 ymin: 51.30687 xmax: 0.2300917 ymax: 51.6707
#> epsg (SRID): 4326
#> proj4string: +proj=longlat +datum=WGS84 +no_defs
#> # A tibble: 3,775 x 12
#> FEATURE_ID SVDATE ASL_FDR ASL_FDRLFT ASL_FDCENT ASL_FDRIGH ASL_SHARED
#> <chr> <date> <chr> <chr> <chr> <chr> <chr>
#> 1 RWG276569 2018-03-07 FALSE FALSE FALSE FALSE FALSE
#> 2 RWG276570 2018-03-09 FALSE FALSE FALSE FALSE FALSE
#> 3 RWG276571 2018-03-09 FALSE FALSE FALSE FALSE FALSE
#> 4 RWG150409 2017-09-19 FALSE FALSE FALSE FALSE FALSE
#> 5 RWG150410 2017-09-20 FALSE FALSE FALSE FALSE FALSE
#> 6 RWG150415 2017-09-21 FALSE FALSE FALSE FALSE FALSE
#> 7 RWG150416 2017-09-21 FALSE FALSE FALSE FALSE FALSE
#> 8 RWG150424 2017-09-22 FALSE FALSE FALSE FALSE FALSE
#> 9 RWG150449 2017-09-27 FALSE FALSE FALSE FALSE FALSE
#> 10 RWG150329 2017-09-18 TRUE TRUE FALSE FALSE FALSE
#> # … with 3,765 more rows, and 5 more variables: ASL_COLOUR <chr>,
#> # BOROUGH <chr>, PHOTO1_URL <chr>, PHOTO2_URL <chr>, geometry <LINESTRING
#> # [°]>
get_cid_points(type = "signal")
#> Simple feature collection with 443 features and 10 fields
#> geometry type: POINT
#> dimension: XY
#> bbox: xmin: -0.417572 ymin: 51.37778 xmax: 0.1080144 ymax: 51.62969
#> epsg (SRID): 4326
#> proj4string: +proj=longlat +datum=WGS84 +no_defs
#> # A tibble: 443 x 11
#> FEATURE_ID SVDATE SIG_HEAD SIG_SEPARA SIG_EARLY SIG_TWOSTG SIG_GATE
#> <chr> <date> <chr> <chr> <chr> <chr> <chr>
#> 1 RWG039736 2017-08-24 TRUE FALSE FALSE FALSE FALSE
#> 2 RWG039729 2017-07-06 TRUE FALSE FALSE FALSE FALSE
#> 3 RWG108125 2017-06-21 TRUE FALSE TRUE FALSE FALSE
#> 4 RWG001914 2017-05-31 TRUE TRUE FALSE FALSE FALSE
#> 5 RWG001915 2017-05-31 TRUE TRUE FALSE FALSE FALSE
#> 6 RWG039732 2017-08-23 TRUE FALSE TRUE FALSE FALSE
#> 7 RWG001919 2017-05-06 TRUE TRUE FALSE FALSE FALSE
#> 8 RWG039728 2017-05-31 TRUE TRUE FALSE FALSE FALSE
#> 9 RWG039730 2017-07-06 TRUE FALSE FALSE FALSE FALSE
#> 10 RWG039731 2017-07-18 TRUE TRUE FALSE FALSE FALSE
#> # … with 433 more rows, and 4 more variables: BOROUGH <chr>, PHOTO1_URL <chr>,
#> # PHOTO2_URL <chr>, geometry <POINT [°]>