tphconv: Convert Transport Poverty Hub Data to Rasters and Vectors with GISCO IDs

Overview

tphconv is an R package for converting public transport accessibility data from the Transport Poverty Hub into raster and vector spatial formats with GISCO IDs. It’s designed to:

• Read gzipped CSV files containing point-based accessibility measures (e.g., number of people reachable within 10–20 minutes by public transport).
• Reproject WGS84 (EPSG:4326) coordinates into a target grid (default EPSG:3035) and perform necessary offset for the data to line up with GISCO INSPIRE grids (https://ec.europa.eu/eurostat/web/gisco/geodata/grids, https://ec.europa.eu/eurostat/web/gisco/geodata/population-distribution/population-grids).
• Rasterize the point data onto a regular grid (e.g., 1 km resolution) or generate vector polygon grids.
• Convert to vector polygons for further analysis.
• Generate GISCO IDs for each grid cell, which can be useful for linking with other datasets.

This makes it easy to integrate transport accessibility information into GIS workflows for analysis and visualization.

Installation

You can install the development version of tphconv from GitHub:

# install.packages("remotes")
remotes::install_github("e-kotov/tphconv")

Data Source

Accessibility data is provided by the Transport Poverty Hub Dashboard, which requires a free EU account to log in. The dashboard allows you to download precomputed CSV files on a 1 km grid for various countries, including Luxembourg.

Once you have downloaded a file (e.g., ver1_0_LU_1km_pt_ppl_within_10-20_min.csv.gz), you can point tphconv to it directly.

Functions

• tph_to_raster() – Reads a CSV, reprojects, and rasterizes accessibility data into a SpatRaster or writes it to disk if out_raster_file is specified (with extensions that are supported by terra).

• tph_to_vector() – Reads a CSV, reprojects, and converts accessibility data into a SpatVector or sf object, or writes it to disk if out_vector_file is specified (with extensions that are supported by sf, such as GPKG, GeoJSON, Shapefile, etc.).

• tph_to_table() – Reads a CSV and returns a simple tibble with GISCO IDs, optionally including centroid coordinates and GISCO lower left corner coordinates.

Usage Examples

Most defaults should work as long as the data provider does not change the format of the CSV files. The package is designed to handle the standard format used by the Transport Poverty Hub, but arguments can be adjusted if necessary.

Convert a CSV to a Raster

library(tphconv)

# Locate the example data shipped with the package
tph_file <- system.file(
  "extdata",
  "ver1_0_LU_1km_pt_ppl_within_10-20_min.csv.gz",
  package = "tphconv"
)

# Convert to a SpatRaster
raster_layer <- tph_to_raster(input_file = tph_file)

library(terra)
plot(raster_layer[[1]], main = "Transport Poverty Hub Accessibility Data")

Note that the raster layer also has the GISCO IDs by default (can be disabled with add_id = FALSE). In QGIS these will be visible in the Raster Attribute Table, otherwise they are just another numeric layer with labels.

raster_layer

class       : SpatRaster 
size        : 81, 56, 2  (nrow, ncol, nlyr)
resolution  : 1000, 1000  (x, y)
extent      : 4015000, 4071000, 2934000, 3015000  (xmin, xmax, ymin, ymax)
coord. ref. : ETRS89-extended / LAEA Europe (EPSG:3035) 
source(s)   : memory
names       : opportunities_people,                        gisco_id 
min values  :                    0, CRS3035RES1000mN3014000E4036000 
max values  :                61065, CRS3035RES1000mN2934000E4057000 

Write Raster to Disk

tmp_file <- tempfile(fileext = ".tiff")
output_path <- tph_to_raster(
  input_file = tph_file,
  out_raster_file = tmp_file
)

# Check the output
g <- terra::rast(output_path)
g
unlink(tmp_file) # Clean up temporary file

class       : SpatRaster 
size        : 81, 56, 2  (nrow, ncol, nlyr)
resolution  : 1000, 1000  (x, y)
extent      : 4015000, 4071000, 2934000, 3015000  (xmin, xmax, ymin, ymax)
coord. ref. : ETRS89-extended / LAEA Europe (EPSG:3035) 
source      : file3d183d8ea354.tiff 
names       : opportunities_people,                        gisco_id 
min values  :                    0, CRS3035RES1000mN3014000E4036000 
max values  :                61065, CRS3035RES1000mN2934000E4057000 

Convert to Vector Polygons

library(tphconv)

# Locate the example data shipped with the package
tph_file <- system.file(
  "extdata",
  "ver1_0_LU_1km_pt_ppl_within_10-20_min.csv.gz",
  package = "tphconv"
)

# Convert to a sf
vector_layer_sf <- tph_to_vector(input_file = tph_file, return_as = "sf")
plot(vector_layer_sf[, "opportunities_people"])

# Convert to a SpatVector
library(terra)
vector_layer_spat_vector <- tph_to_vector(
  input_file = tph_file,
  return_as = "SpatVector"
)
plot(vector_layer_spat_vector, "opportunities_people")

Plots ommited for brevity

Save Vector Polygons to Disk

tmp_file <- tempfile(fileext = ".gpkg")
output_path <- tph_to_vector(
  input_file = tph_file,
  out_vector_file = tmp_file
)

# Check the output
g <- sf::read_sf(output_path)
g
unlink(tmp_file) # Clean up temporary file

Simple feature collection with 1600 features and 2 fields
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: 4015000 ymin: 2934000 xmax: 4071000 ymax: 3015000
Projected CRS: ETRS89-extended / LAEA Europe
# A tibble: 1,600 × 3
   opportunities_people gisco_id                                                   geom
                  <dbl> <chr>                                             <POLYGON [m]>
 1                 2625 CRS3035RES1000mN2934000E4033000 ((4033000 2934000, 4034000 293…
 2                  375 CRS3035RES1000mN2934000E4057000 ((4057000 2934000, 4058000 293…
 3                 7463 CRS3035RES1000mN2935000E4032000 ((4032000 2935000, 4033000 293…
 4                10955 CRS3035RES1000mN2935000E4033000 ((4033000 2935000, 4034000 293…
 5                 4087 CRS3035RES1000mN2935000E4034000 ((4034000 2935000, 4035000 293…
 6                 4804 CRS3035RES1000mN2935000E4037000 ((4037000 2935000, 4038000 293…
 7                  518 CRS3035RES1000mN2935000E4056000 ((4056000 2935000, 4057000 293…
 8                  112 CRS3035RES1000mN2935000E4057000 ((4057000 2935000, 4058000 293…
 9                 3515 CRS3035RES1000mN2936000E4032000 ((4032000 2936000, 4033000 293…
10                 7236 CRS3035RES1000mN2936000E4033000 ((4033000 2936000, 4034000 293…
# ℹ 1,590 more rows
# ℹ Use `print(n = ...)` to see more rows

Convert to simple table with GISCO IDs

This is the fastest function, as it does not create geometries, it only returns a table with original data and GISCO IDs, and optionally the original coordinates of the centroids and/or the coorindates of GISCO lower left corners of the grid cells.

library(tphconv)

# Locate the example data shipped with the package
tph_file <- system.file(
  "extdata",
  "ver1_0_LU_1km_pt_ppl_within_10-20_min.csv.gz",
  package = "tphconv"
)

# Convert to a tibble with GISCO IDs
gisco_table <- tph_to_table(
  input_file = tph_file,
  add_centroid_coords = TRUE, # Optiona, Add centroid coordinates
  add_gisco_corner_coords = TRUE # Optional, Add GISCO lower left corner coordinates
)

head(gisco_table)

                        gisco_id opportunities_people      lon      lat x_centroid y_centroid    x_ll    y_ll
1 CRS3035RES1000mN2934000E4033000                 2625 6.033336 49.45356    4033500    2934500 4033000 2934000
2 CRS3035RES1000mN2934000E4057000                  375 6.363958 49.46471    4057500    2934500 4057000 2934000
3 CRS3035RES1000mN2935000E4032000                 7463 6.018829 49.46205    4032500    2935500 4032000 2935000
4 CRS3035RES1000mN2935000E4033000                10955 6.032604 49.46254    4033500    2935500 4033000 2935000
5 CRS3035RES1000mN2935000E4034000                 4087 6.046380 49.46302    4034500    2935500 4034000 2935000
6 CRS3035RES1000mN2935000E4037000                 4804 6.087708 49.46447    4037500    2935500 4037000 2935000

License

The package is licensed under MIT. Data from the Transport Poverty Hub Dashboard is available under CC-BY-4.0, with reuse policy outlined by the EU Commission Decision of 12 December 2011.

Citation

To cite package ‘tphconv’ in publications use:

Kotov E (2025). tphconv: Convert Transport Poverty Hub Data to Rasters and Vectors. R package version 0.1.0, https://github.com/e-kotov/tphconv.

BibTeX:

@Manual{,
  title = {tphconv: Convert Transport Poverty Hub Data to Rasters and Vectors},
  author = {Egor Kotov},
  year = {2025},
  note = {R package version 0.1.0},
  url = {https://github.com/e-kotov/tphconv},
}