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Base

Overview​

The Overture Maps base theme provides the land, water, infrastructure, and bathymetry features that are necessary to render a complete basemap. The majority of these features come from OpenStreetMap. We classify OSM features into type, subtype, and class based on their tags. The land and ocean polygons are derived from the Daylight Coastlines. The theme includes six feature types:

  • bathymetry: derived vectorized bathymetric data products from ETOPO1 and GLOBathy data.
  • infrastructure: Infrastructure features such as communication towers and lines, piers, and bridges from OpenStreetMap.
  • land: physical representations of land surfaces derived from the inverse of OSM Coastlines; translates natural tags from OpenStreetMap.
  • land_cover: derived from ESA WorldCover, high-resolution optical Earth observation data.
  • land_use: classifications of the human use of a section of land; translates landuse tag from OpenStreetMap.
  • water: physical representations of inland and ocean marine surfaces; translates natural and waterway tags from OpenStreetMap.

Data access and retrieval​

Overture's base theme data is freely available on both Amazon S3 and Microsoft Azure Blob Storage at these locations:

ProviderLocation
Amazon S3
s3://overturemaps-us-west-2/release/2025-02-19.0/theme=base/type=bathymetry/*
Azure Blob Storage
https://overturemapswestus2.blob.core.windows.net/release/2025-02-19.0/theme=base/type=bathymetry/*

Overture distributes its datasets as GeoParquet, a column-oriented spatial data format that is a backwards-compatible extension of Apache Parquet. Parquet (and GeoParquet) is optimized for "cloud-native" queries, which means you can use many developer-friendly tools to efficiently fetch column "chunks" of cloud-hosted data. We encourage users who are new to GeoParquet to consult this guide.

The Getting Data section of this documentation offers instructions for using several tools to access Overture data, including DuckDB and Overture's Python command-line tool. See examples below for addresses.

We recommend querying and downloading only the Overture data you need. If you have a particular geographic area of interest, there are several options for using a simple bounding box to extract address data.

Schema design choices​

  • basic classification of features into type, subtype and class where appropriate.
  • parsing and normalization of common OSM tags, such as height and ele.
  • extraction of consistent OSM tags, such as wikidata to top-level properties.
  • direct pass-through of remaining relevant OSM tags.

Schema reference​

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