TechnicalGIS

#Raster to vector

2 posts

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

Two land cover maps of a 30 km square around Leicester side by side: the U-Net prediction on the left and the reference labels on the right. Both show the city in grey and red in the centre, surrounded by farmland in pale green, woods in dark green and reservoirs in blue. The prediction's city is smoother, with fewer separate red buildings.

Tutorial Python Part 3 of 3

Deep learning inference on large rasters: sliding-window prediction, COGs and polygons in Python

Run a trained PyTorch U-Net over a whole Sentinel-2 scene of a city it has never seen: tiled sliding-window inference on a large GeoTIFF with overlapping, blended windows, a georeferenced Cloud Optimised GeoTIFF of classes and confidence, raster-to-vector polygons with rasterio.features.shapes in a GeoPackage, and an honest check against reference labels.

Advanced 13 min read