#Greater Manchester

4 posts

Choropleth map of population density in the 331 local authority districts of England and Wales from Census 2021, in seven classes from pale yellow (under 100 residents per km²) to deep red (over 5,000). London, Birmingham, Manchester, Liverpool, Leeds, Newcastle and the south coast cities stand out in red; Wales, Cumbria, Northumberland and Lincolnshire are pale. The map has a classified legend, a 100 km scale bar, a north arrow, latitude and longitude labels and an inset locator map of Europe.

Tutorial Python

Make a map in Python with matplotlib and cartopy: projections, classified choropleths, scale bars, north arrows and inset maps

A cartopy tutorial for publication-quality maps in Python: choose a projection, draw a classified choropleth of Census 2021 population density with a proper legend, add a scale bar, a true-north arrow, an inset locator map and gridlines, style it for light and dark backgrounds, export at 300 dpi to PNG, PDF and SVG, and shade the Copernicus DEM for Greater Manchester.

Beginner 14 min read 23 October 2026

Three panels of the same 1 km by 0.7 km area at Salford Quays. Left: square WorldCover pixels, mostly red built-up land with blue dock basins and small green and yellow patches. Middle: the same area as 142 polygons with black outlines that follow the pixel staircase. Right: the polygons after coverage simplification at 10 m, with smoother outlines and no gaps between them.

Tutorial Python Part 3 of 3

Raster to vector in Python: polygonize with rasterio, rasterize boundaries and convert a GeoTIFF to a Cloud Optimized GeoTIFF

Convert raster to vector in Python with rasterio.features.shapes on 10 m ESA WorldCover for Greater Manchester: polygonize water and built-up land, fix invalid polygons, simplify without gaps, rasterize ONS district boundaries for land-cover shares, then write and validate a Cloud Optimized GeoTIFF with rio-cogeo and measure HTTP range reads.

Intermediate 14 min read 23 October 2026

Tutorial Python Part 2 of 3

Spatial joins in GeoPandas: sjoin, predicates, sjoin_nearest and point in polygon

A practical guide to spatial joins in GeoPandas with real Greater Manchester data: 13,187 NaPTAN bus stops, 1,386 OpenStreetMap schools, 215 ONS wards and 1,702 LSOAs. Covers point in polygon with sjoin, predicates, counts per polygon, how='left'/'inner'/'right', sjoin_nearest with max_distance, clip and overlay, and a timing comparison of a naive loop against the spatial index.

Beginner 12 min read 23 October 2026

Tutorial Python Part 1 of 3

Coordinate reference systems in Python: EPSG codes, pyproj transforms and reprojecting vectors and rasters

A practical guide to coordinate reference systems in Python with pyproj, GeoPandas and rasterio, tested on real Greater Manchester data. Covers EPSG codes, WGS 84 vs British National Grid (EPSG:27700), the always_xy axis-order trap, OSTN15 vs Helmert datum shifts checked against 13,187 NaPTAN bus stops, measured area and distance errors in the wrong CRS, and reprojecting a GeoDataFrame and a Copernicus DEM raster.

Beginner 13 min read 23 October 2026