5 posts
Process large satellite rasters in Python with dask and rioxarray. Open eight full Sentinel-2 scenes lazily, choose a chunk size, inspect the task graph, watch CPU and memory with dask diagnostics, compare peak memory with eager NumPy, time chunk sizes and thread counts, and write a median NDVI GeoTIFF to disk chunk by chunk.
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.
Read ERA5 climate reanalysis in Python with xarray from free, login-free cloud Zarr stores, clip it to the UK, compute area-weighted means and anomalies against 1991–2020, export a Cloud Optimised GeoTIFF and check it against Met Office stations.
Stream a Copernicus 30 m DEM of the Edale valley, reproject it to British National Grid, scale it to a 150 mm print and write a watertight binary STL using only NumPy, with checks that prove the mesh is printable.
Read only the pixels you need from a cloud-hosted Copernicus DEM, reproject to British National Grid, derive hillshade, slope and aspect with NumPy, compute zonal statistics and draw an elevation profile — all in one script.