TechnicalGIS

#ESA WorldCover

8 posts

Tutorial Python

Least-cost path analysis in Python: cost surfaces and walking routes up Yr Wyddfa

Build a walking cost surface from real slope (Copernicus GLO-30) and land cover (ESA WorldCover), compute the accumulated cost surface and the least-cost path with scikit-image's MCP_Geometric, add a direction-aware Dijkstra version with SciPy, and compare the routes with the straight line and the OpenStreetMap footpaths from Pen-y-Pass to the summit of Yr Wyddfa (Snowdon).

Intermediate 14 min read

Bar chart comparing the area of each land cover class in Ireland from WorldCover pixel counting with the error-adjusted estimate and its 95% confidence interval.

Tutorial Remote Sensing

Land cover accuracy assessment in Python: confusion matrix, Olofsson area estimates and sample size

Assess a real land cover map in Python: ESA WorldCover 2021 against 8,597 Eurostat LUCAS 2022 field survey points in Ireland. Build the confusion matrix, compute overall, user's and producer's accuracy, see why kappa is discouraged, and use the Olofsson et al. (2014) stratified estimators to get error-adjusted areas with 95% confidence intervals and to plan a new stratified random sample.

Advanced 20 min read

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

Tutorial Python

Zonal statistics in Python: exactextract vs rasterstats, with partial pixels, land-cover fractions and a benchmark

Calculate zonal statistics in Python with exactextract and rasterstats on real data: ONS 2021 LSOA boundaries for Cumbria with GHSL population, the Copernicus DEM and ESA WorldCover. Covers partial-pixel weighting vs pixel centroids, CRS alignment, categorical land-cover fractions, a speed benchmark, GeoPackage export and choropleth maps.

Intermediate 14 min read

Six 128 by 128 pixel Sentinel-2 image chips of Nottingham, each shown above the same chip with its label mask overlaid: a city centre with red buildings and grey streets, a suburb, a forest, farmland, flooded gravel pits in blue and an industrial estate.

Tutorial Python Part 1 of 3

Training data for deep learning on satellite imagery: Sentinel-2 image chips in Python

Build a labelled deep learning dataset from free data: stream a Sentinel-2 L2A composite from the Planetary Computer, rasterise Overture building footprints over ESA WorldCover, cut georeferenced image chips, split them by spatial block so the test set does not leak, check the class balance and load it all as a TorchGeo dataset.

Intermediate 13 min read

Tutorial Python

Land surface temperature from Landsat in Python: mapping London's urban heat island

Calculate land surface temperature from Landsat 8 and 9 Collection 2 Level-2 data in Python: ST_B10 scale and offset, QA_PIXEL cloud masking, LST by land cover and NDVI, an urban-rural transect, hotspots with OpenStreetMap and an honest comparison with air temperature, for London in the July 2022 heatwave.

Intermediate 17 min read