从点列表创建路线并在 R 中的路段/道路网络上叠加路线(点列表) [英] Creating a route from a list of points and Overlaying the route (list of points) on the road segment/ road network in R

问题描述

我有一个道路网络 shapefile 和点列表.我必须从点列表中创建一条路线，然后叠加/空间连接(整合覆盖路段的点的属性)

可在此处找到示例道路网络形状文件 了解更多详情.

network <- network %>%转换(to_spatial_subdivision，.clean = TRUE)%>%转换(to_components，.select = 1，.clean = TRUE)%E>%变异(权重 = edge_length())

现在我想估计每对连续点之间的最短路径.sfnetwork 不支持多对多路由，所以需要定义一个for循环.如果需要多次重复这个操作，我认为你应该查看R包 (v0.3.0) 于 2021 年 3 月 7 日创建

I have a road network shapefile and list of points. I have to create a route from the list of points and then overlay/ spatially join (integrate the attributes of points that are overlaying the road segments)

The sample road network shape file can be found here https://drive.google.com/drive/folders/103Orz6NuiWOaFoEkM18SlzFTjGYi1rju?usp=sharing

The following is the code for points with lat (x) and long (y) information. The "order" column means, the order of destinations in the route .

points <-tribble (
  ~x,~y, ~order,
  78.14358, 9.921388,1,         
78.14519,   9.921123,2,         
78.14889,   9.916954,3,         
78.14932,   9.912807,4,         
78.14346,   9.913828,5,         
78.13490,   9.916551,6,         
78.12904,   9.918782,7  
)

What I want as an output is a layer of the route joining all the points in the order as mentioned. And I also want to integrate/ do a spatial join of the route to the road segments.

Thanks in advance

解决方案

The following answer is based on the R package sfnetworks which can be installed as follows:

install.packages("remotes")
remotes::install_github("luukvdmeer/sfnetworks")

First of all, load packages

library(sf)
#> Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1
library(sfnetworks)
library(tidygraph)

and data. The points object is converted to sf format.

roads <- st_read("C:/Users/Utente/Desktop/Temp/roads_test.shp") %>% st_cast("LINESTRING")
#> Reading layer `roads_test' from data source `C:\Users\Utente\Desktop\Temp\roads_test.shp' using driver `ESRI Shapefile'
#> Simple feature collection with 785 features and 0 fields
#> geometry type:  MULTILINESTRING
#> dimension:      XY
#> bbox:           xmin: 78.12703 ymin: 9.911192 xmax: 78.15389 ymax: 9.943905
#> geographic CRS: WGS 84
points <- tibble::tribble (
  ~x,~y, ~order,
  78.14358, 9.921388,1,         
  78.14519,   9.921123,2,         
  78.14889,   9.916954,3,         
  78.14932,   9.912807,4,         
  78.14346,   9.913828,5,         
  78.13490,   9.916551,6,         
  78.12904,   9.918782,7  
)
points <- st_as_sf(points, coords = c("x", "y"), crs = 4326)

Plot network and points (just to understand the problem a little bit better)

par(mar = rep(0, 4))
plot(roads, reset = FALSE)
plot(points, add = TRUE, cex = (1:7)/1.5, col = sf.colors(7), lwd = 4)

Convert roads to sfnetwork object

network <- as_sfnetwork(roads, directed = FALSE)

Subdivide edges and select the main component. Check https://luukvdmeer.github.io/sfnetworks/articles/preprocess_and_clean.html for more details.

network <- network %>% 
  convert(to_spatial_subdivision, .clean = TRUE) %>% 
  convert(to_components, .select = 1, .clean = TRUE) %E>% 
  mutate(weight = edge_length())

Now I want to estimate the shortest paths between each pair of consecutive points. sfnetwork does not support many-to-many routing, so we need to define a for-loop. If you need to repeat this operation for several points, I think you should check the R package dodgr.

routes <- list()
for (i in 1:6) {
  path <- st_network_paths(
    network, 
    from = st_geometry(points)[i], 
    to = st_geometry(points)[i + 1]
  )
  routes[[i]] <- path 
}

Extract the id of the edges that compose all shortest paths

idx <- unlist(pull(do.call("rbind", routes), edge_paths))

Hence, if you want to extract the edges from the original network

network_shortest_path <- network %E>% slice(idx)
roads_shortest_path <- network_shortest_path %E>% st_as_sf() 

Plot network and points

par(mar = rep(0, 4))
plot(roads, reset = FALSE)
plot(st_geometry(roads_shortest_path), add = TRUE, col = "darkgreen", lwd = 4)
plot(points, add = TRUE, cex = (1:7)/1.5, col = sf.colors(7), lwd = 4)

^{Created on 2021-03-07 by the reprex package (v0.3.0)}

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