si_zones and si_centroids represent administrative zones between which
flows are to be estimated.
Examples
si_zones
#> Simple feature collection with 107 features and 13 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: -1.800362 ymin: 53.699 xmax: -1.292229 ymax: 53.94589
#> Geodetic CRS: WGS 84
#> # A tibble: 107 × 14
#> geo_code geo_name lad11cd lad_name all bicycle foot car_driver
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 E02002330 Leeds 001 E08000035 Leeds 2809 52 300 2170
#> 2 E02002331 Leeds 002 E08000035 Leeds 2387 53 469 1573
#> 3 E02002332 Leeds 003 E08000035 Leeds 2471 39 341 1666
#> 4 E02002333 Leeds 004 E08000035 Leeds 3743 80 529 2340
#> 5 E02002334 Leeds 005 E08000035 Leeds 2995 53 170 2421
#> 6 E02002335 Leeds 006 E08000035 Leeds 3056 33 106 2549
#> 7 E02002336 Leeds 007 E08000035 Leeds 2690 35 94 2178
#> 8 E02002337 Leeds 008 E08000035 Leeds 3187 31 238 2222
#> 9 E02002338 Leeds 009 E08000035 Leeds 3155 52 343 2024
#> 10 E02002339 Leeds 010 E08000035 Leeds 2501 41 360 1552
#> # ℹ 97 more rows
#> # ℹ 6 more variables: car_passenger <dbl>, motorbike <dbl>, train_tube <dbl>,
#> # bus <dbl>, taxi_other <dbl>, geometry <POLYGON [°]>
sf:::plot.sfg(si_zones$geometry)
sf:::plot.sfg(si_centroids$geometry, add = TRUE)
