Cloud-Native Geospatial: GeoParquet, COGs, and STAC
The modern formats and cataloguing standards that are reshaping how spatial data is stored, accessed, and shared
The geospatial industry is in the middle of a format revolution. GeoJSON files copied to S3 buckets, shapefiles emailed between teams, and WMS services that time out under load are giving way to a new stack built around cloud-native principles: data that can be accessed in parts, indexed without downloading, and queried directly from object storage.
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Spatial ETL Pipelines with GeoPandas and Shapely
Building robust, reproducible geospatial data transformation workflows entirely in Python
Most geospatial data arrives dirty: mismatched projections, broken geometries, inconsistent attribute schemas. GeoPandas and Shapely give you a powerful, Pythonic toolkit for cleaning, transforming, and enriching spatial data before it reaches your database or analysis pipeline.
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