rnet_join: Join route networks

In stplanr: Sustainable Transport Planning

Join route networks

Description

This is a spatial join function that is enables adding columns to a 'target' route network from a 'source' route network that contains the base geometry, e.g. from OSM

Usage

rnet_join(
  rnet_x,
  rnet_y,
  dist = 5,
  length_y = TRUE,
  key_column = 1,
  subset_x = TRUE,
  dist_subset = NULL,
  segment_length = 0,
  endCapStyle = "FLAT",
  contains = TRUE,
  max_angle_diff = NULL,
  ...
)

Arguments

rnet_x	Target route network, the output will have the same geometries as features in this object.
rnet_y	Source route network. Columns from this route network object will be copied across to the new network.
dist	The buffer width around rnet_y in meters. 1 m by default.
length_y	Add a new column called length_y? Useful when joining based on length of segments (e.g. weighted mean). TRUE by default.
key_column	The index of the key (unique identifier) column in rnet_x.
subset_x	Subset the source route network by the target network before creating buffers? This can lead to faster and better results. Default: TRUE.
dist_subset	The buffer distance in m to apply when breaking up the source object rnet_y. Default: 5.
segment_length	Should the source route network be split? 0 by default, meaning no splitting. Values above 0 split the source into linestrings with a max distance. Around 5 (m) may be a sensible default for many use cases, the smaller the value the slower the process.
endCapStyle	Type of buffer. See ?sf::st_buffer for details
contains	Should the join be based on sf::st_contains or sf::st_intersects? TRUE by default. If FALSE the centroid of each segment of rnet_y is used for the join. Note: this can result in incorrectly assigning values on sideroads, as documented in #520.
max_angle_diff	The maximum angle difference between x and y nets for a value to be returned
...	Additional arguments passed to rnet_subset.

Details

The output is an sf object containing polygons representing buffers around the route network in rnet_x. The examples below demonstrate how to join attributes from a route network object created with the function overline() onto OSM geometries.

Note: The main purpose of this function is to join an ID from rnet_x onto rnet_y. Subsequent steps, e.g. with dplyr::inner_join() are needed to join the attributes back onto rnet_x. There are rarely 1-to-1 relationships between spatial network geometries so we take care when using this function.

See #505 for details and a link to an interactive example of inputs and outputs shown below.

Examples

library(sf)
library(dplyr)
# Uncomment for interactive examples:
plot(st_geometry(route_network_small))
plot(osm_net_example$geometry, lwd = 5, col = "grey", add = TRUE)
plot(route_network_small["flow"], add = TRUE)
rnetj = rnet_join(osm_net_example, route_network_small, dist = 9)
rnetj2 = rnet_join(osm_net_example, route_network_small, dist = 9, segment_length = 10)
# library(mapview)
# mapview(rnetj, zcol = "flow") +
#   mapview(rnetj2, zcol = "flow") +
#   mapview(route_network_small, zcol = "flow")
plot(sf::st_geometry(rnetj))
plot(rnetj["flow"], add = TRUE)
plot(rnetj2["flow"], add = TRUE)
plot(route_network_small["flow"], add = TRUE)
summary(rnetj2$length_y)
rnetj_summary = rnetj2 %>%
  filter(!is.na(length_y)) %>%
  sf::st_drop_geometry() %>%
  group_by(osm_id) %>%
    summarise(
      flow = weighted.mean(flow, length_y, na.rm = TRUE),
      )
osm_joined_rnet = dplyr::left_join(osm_net_example, rnetj_summary)
plot(sf::st_geometry(route_network_small))
plot(route_network_small["flow"], lwd = 3, add = TRUE)
plot(sf::st_geometry(osm_joined_rnet), add = TRUE)
# plot(osm_joined_rnet[c("flow")], lwd = 9, add = TRUE)
# Improve fit between geometries and performance by subsetting rnet_x
osm_subset = rnet_subset(osm_net_example, route_network_small, dist = 5)
osm_joined_rnet = dplyr::left_join(osm_subset, rnetj_summary)
plot(route_network_small["flow"])
# plot(osm_joined_rnet[c("flow")])
# mapview(joined_network) +
#   mapview(route_network_small)

stplanr documentation built on Sept. 15, 2023, 9:07 a.m.