Road_Network_OSM_Lab_1
Tsegaye D. Lemma
2023-05-24
Produce a Isle Of Wight slope map
# Extract the OSM network from geofabrik
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(sf)## Linking to GEOS 3.11.1, GDAL 3.6.2, PROJ 9.1.1; sf_use_s2() is TRUElibrary(osmextract)## Data (c) OpenStreetMap contributors, ODbL 1.0. https://www.openstreetmap.org/copyright.
## Check the package website, https://docs.ropensci.org/osmextract/, for more details.library(stplanr)
library(raster)## Loading required package: sp##
## Attaching package: 'raster'## The following object is masked from 'package:dplyr':
##
## selectiow_osm = oe_get("Isle of Wight", provider = "geofabrik", stringsAsFactors = FALSE, quiet = FALSE, force_download = TRUE, force_vectortranslate = TRUE)## The input place was matched with: Isle of Wight##
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|======================================================================| 100%## File downloaded!## Start with the vectortranslate operations on the input file!## 0...10...20...30...40...50...60...70...80...90...100 - done.## Finished the vectortranslate operations on the input file!## Reading layer `lines' from data source
## `C:\Users\Tsegaye\AppData\Local\Temp\Rtmp2FtYKa\geofabrik_isle-of-wight-latest.gpkg'
## using driver `GPKG'
## Simple feature collection with 51008 features and 9 fields
## Geometry type: LINESTRING
## Dimension: XY
## Bounding box: xmin: -5.715479 ymin: 43.35489 xmax: 0.2409745 ymax: 50.89601
## Geodetic CRS: WGS 84#`C:\Users\Tsegaye\AppData\Local\Temp\RtmpGeTUe6\geofabrik_isle-of-wight-latest.gpkg' data stored heremyRoadNetworkPath <- "U:/AfriGeoinformation_RoadNetwork/Road_Network_OSM_Lab_1"
setwd(myRoadNetworkPath)
dir()## [1] "Road_Network_OSM_Lab_1.Rmd" "SlopesIoW.html"iow_network = iow_osm %>%
dplyr::filter(highway %in% c('primary', "primary_link", 'secondary',"secondary_link", 'tertiary', "tertiary_link",
"trunk", "trunk_link", "residential", "cycleway", "living_street", "unclassified",
"motorway", "motorway_link", "pedestrian", "steps", "track")) #remove: "service",
table(iow_network$highway)##
## cycleway living_street pedestrian primary primary_link
## 253 5 38 664 22
## residential secondary secondary_link steps tertiary
## 2972 438 1 459 615
## tertiary_link track unclassified
## 3 4211 876# Clean the road network
#library(stplanr)
iow_network$group = stplanr::rnet_group(iow_network)
plot(iow_network["group"])
iow_network_clean = iow_network %>% filter(group == 1) #the network with more connected segments
100*nrow(iow_network_clean)/nrow(iow_network) #percentage of the remaining highways## [1] 87.61959iow_network_segments = stplanr::rnet_breakup_vertices(iow_network_clean)
nrow(iow_network_segments)/nrow(iow_network_clean) #multiply factor## [1] 1.540108# Import DEM (extracted with QGIS SRTM Downloader plugin and clipped)
library(raster)
DEM = raster("https://github.com/U-Shift/Declives-RedeViaria/releases/download/0.2/IsleOfWightNASA_clip.tif")
class(DEM)## [1] "RasterLayer"
## attr(,"package")
## [1] "raster"summary(values(DEM))## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -18.0 0.0 0.0 21.3 31.0 243.0res(DEM) #27m of resolution## [1] 0.0002777778 0.0002777778network = iow_network_segments
raster::plot(DEM)
plot(sf::st_geometry(network), add = TRUE) #check if they overlay
# install.packages("remotes")
#remotes::install_github("ropensci/slopes") # we used remotes to install the packages "slopes"# Get the slope value for each segment (abs), using slopes package
library(slopes)
library(geodist)
network$slope = slope_raster(network, dem = DEM) #about 15sec
network$slope = network$slope*100 #percentage
summary(network$slope) #!## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 1.728 3.095 3.892 5.092 152.888# Classify slopes
network$slope_class = network$slope %>%
cut(
breaks = c(0, 3, 5, 8, 10, 20, Inf),
labels = c("0-3: flat", "3-5: mild", "5-8: medium", "8-10: hard", "10-20: extreme", ">20: impossible"),
right = F
)
round(prop.table(table(network$slope_class))*100,1)##
## 0-3: flat 3-5: mild 5-8: medium 8-10: hard 10-20: extreme
## 48.4 25.7 16.9 4.2 4.4
## >20: impossible
## 0.4# make an interactive map
library(tmap)
palredgreen = c("#267300", "#70A800", "#FFAA00", "#E60000", "#A80000", "#730000") #color palette
tmap_mode("view")## tmap mode set to interactive viewingtmap_options(basemaps = leaflet::providers$CartoDB.Positron) #mapa base
slopemap =
tm_shape(network) +
tm_lines(
col = "slope_class",
palette = palredgreen,
lwd = 2, #line width
title.col = "Slope [%]",
popup.vars = c("Highway" = "highway",
"Slope: " = "slope",
"Class: " = "slope_class"),
popup.format = list(digits = 1),
# id = "slope"
id = "name" #if it gets too memory consuming, delete this line
)
slopemap