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This repository is an R package that provides helpers for working with the National Library of Scotland (NLS) OS town-plan XYZ tile pyramids, used for the Leeds tram mapping case study.

Install

Core package functions

Tile maths:

NLS tile access:

Tile selection:

Example: small mosaic near Hyde Park

Downloading/stitching a larger Leeds mosaic

For a reproducible end-to-end download/stitch workflow (including chunked merging), see the standalone script:

  • scripts/download_leeds_nls_tiles.R

That script caches downloaded tiles under .cache/ and writes tiles_merged_leeds.tif (these outputs are gitignored).

You can download a 100MB file with all of the tiles in a 1km radius of central Leeds from the releases of this repo and open up in QGIS or similar as shown below:

Documentation

Notes

Keep remote tile downloads limited when rendering documentation, and prefer running larger downloads via the script above.

Plan

  • Download the town map dataset from Scottish Library: https://maps.nls.uk/os/townplans-england/leeds2.html
  • Digitise the tramway centerlines from there
  • Digitise the tram network from Alex’s image data
  • Combine both datasets into a single tramway network
  • Bonus: track lines
  • Comparing with OSM

Rail Map online data

See png-to-geojson.py

Town plan data

Individual tiles can be accessed from URLs such as https://mapseries-tilesets.s3.amazonaws.com/os/town-england/North/19/259898/168840.png.

This is a raster tile pyramid: zoom level 19, tile coordinates 259898, 168840.

The general pattern is: https://mapseries-tilesets.s3.amazonaws.com/os/town-england/North/{z}/{x}/{y}.png

You can copy-paste that URL into QGIS ‘XYZ Tiles’ to access the tiles directly as shown below:

You can also use the ceramic package to download tiles:

Extracting tram network from image

The following Python code processes the image images/paste-2.png to extract the Leeds tram network lines (purple), skeletonizes them, and converts the result to LineStrings.

Research

  • Compare with historic economic and usage data