capcarb

The goal of capcarb is to provide a home for reproducible analysis and open data for the analysis of embodied carbon, known as capital carbon or CapCarb, associated with transport systems.

Installation

Install from GitHub with:

# install.packages("devtools")
devtools::install_github("creds2/capcarb")

library(capcarb)
library(tidyverse)
library(tmap)
tmap_mode("view")

Generating input data

There was no readily available boundary data for the TfN region, so it was constructed as follows, using open data from the Propensity to Cycle Tool (PCT):

regions = pct::pct_regions
# mapview::mapview(regions)
tfn_zone_text = "manc|yorks|lanc|chesh|liv|north-e|north-y|cumbria|humb"
regions_tfn = regions[grepl(pattern = tfn_zone_text, ignore.case = TRUE, x = regions$region_name), ]
# mapview::mapview(regions_tfn)
tfn_region = sf::st_union(regions_tfn)
plot(tfn_region, lwd = 4)
plot(regions, add = TRUE, border = "grey", col = "NA")

tfn_region_27700 = sf::st_transform(tfn_region, 27700)

Motorway data was accessed as follows (after pre-cleaning Ordnance Survey data):

roads_uk = readRDS("~/hd/data/os/Download_mastermap-roads-2019_1483661.Rds")
names(roads_uk)

 [1] "gml_id"                                            "identifier"                                       
 [3] "beginLifespanVersion"                              "localId"                                          
 [5] "namespace"                                         "fictitious"                                       
 [7] "validFrom"                                         "reasonForChange"                                  
 [9] "roadClassification"                                "routeHierarchy"                                   
[11] "formOfWay"                                         "trunkRoad"                                        
[13] "primaryRoute"                                      "roadClassificationNumber"                         
[15] "operationalState"                                  "provenance"                                       
[17] "length"                                            "length_uom"                                       
[19] "matchStatus"                                       "startGradeSeparation"                             
[21] "endGradeSeparation"                                "averageWidth"                                     
[23] "averageWidth_uom"                                  "minimumWidth"                                     
[25] "minimumWidth_uom"                                  "confidenceLevel"                                  
[27] "inDirection"                                       "inDirection_uom"                                  
[29] "inOppositeDirection"                               "inOppositeDirection_uom"                          
[31] "cycleFacility"                                     "wholeLink"                                        
[33] "roadStructure"                                     "alternateIdentifier|ThematicIdentifier|identifier"
[35] "identifierScheme"                                  "roadName"                                         
[37] "alternateName"                                     "geometry"   

table(roads_uk$roadClassification)

               A Road                B Road Classified Unnumbered              Motorway 
               440770                215962                361711                 16710 
       Not Classified          Unclassified               Unknown 
               363169               2150266               1563113 

motorways_uk = roads_uk[roads_uk$roadClassification == "Motorway", ]
motorways_tfn = motorways_uk[tfn_region_27700, ]
saveRDS(motorways_tfn, "motorways_tfn.Rds")

Roads in Leeds

roads_leeds = readRDS("roads_leeds.RDS")
aggregate(roads_leeds$length, by = list(roads_leeds$roadClassification), sum)
#>                 Group.1          x
#> 1                A Road  413116.75
#> 2                B Road   85369.64
#> 3 Classified Unnumbered  178685.63
#> 4              Motorway  202262.91
#> 5        Not Classified  283781.92
#> 6          Unclassified 2339655.83
#> 7               Unknown  613394.89
roads_leeds %>% 
  sf::st_drop_geometry() %>% 
  group_by(roadClassification) %>% 
  summarise(length_km = sum(length) / 1000) %>% 
  ggplot() +
  geom_bar(aes(roadClassification, length_km), stat = "identity")
#> `summarise()` ungrouping output (override with `.groups` argument)

Motorways in the TfN region

motorways_tfn = readRDS("motorways_tfn.Rds")

tm_shape(tfn_region_27700) + tm_borders() +
  tm_shape(motorways_tfn) + tm_lines()
#> Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 7.0.0

The data is quite detailed, as shown below:

a58m = motorways_tfn %>% 
  dplyr::filter(roadClassificationNumber == "A58(M)")
tm_shape(a58m) + tm_lines("averageWidth", palette = "viridis", lwd = 2)