Skip to content

Updated theme guides #205

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
Dana Bauer (danabauer) merged 2 commits into from
Jun 25, 2025
Merged

Updated theme guides #205

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
5e9d9dd
update theme guides with june data and information
stepps00 Jun 25, 2025
c8c6d43
adjust buildings conflation priority
stepps00 Jun 25, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions docs/guides/addresses.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@ import UtahAddresses from '!!raw-loader!@site/src/queries/duckdb/addresses_utah.

_Note: This theme is currently in Alpha. We invite the Overture community to test the addresses schema and data and offer feedback via the [data](https://github.com/OvertureMaps/data/issues) and [schema](https://github.com/OvertureMaps/schema/issues) repos._

Overture maintains over 446 million address point entities. Data in the address theme is derived from over 170 sources, many distributed by [OpenAddresses](https://openaddresses.io/) and [AddressForAll](https://www.addressforall.org/en/), but also includes open data from the [City of New York](https://data.cityofnewyork.us/City-Government/NYC-Address-Points/g6pj-hd8k), the [U.S. Department of Transportation](https://www.transportation.gov/gis/national-address-database), and various public agencies.
Overture maintains over 446 million address point entities. Data in the address theme is derived from over 175 sources, many distributed by [OpenAddresses](https://openaddresses.io/) and [AddressForAll](https://www.addressforall.org/en/), but also includes open data from the [City of New York](https://data.cityofnewyork.us/City-Government/NYC-Address-Points/g6pj-hd8k), the [U.S. Department of Transportation](https://www.transportation.gov/gis/national-address-database), and various public agencies.

For licensing information, please see the [Attribution and Licensing page](https://docs.overturemaps.org/attribution/).

Expand All @@ -29,9 +29,9 @@ Address data can be used for a variety of purposes, which can include:
- **Normalization**: Adhering to standard and consistent forms of address components.
- **Validation and Verification**: Confirming an address exists within a known list of addresses.

| ![Overture address coverage](/img/addresses/address-coverage-h3-may.png) |
| ![Overture address coverage](/img/addresses/address-coverage-h3-june.png) |
|:--:|
| *Coverage of Overture address data, visualized using H3 cells.* |
| *June coverage of Overture address data, visualized using H3 cells.* |

## Dataset description

Expand Down
13 changes: 7 additions & 6 deletions docs/guides/buildings.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -74,12 +74,13 @@ Currently, the Overture buildings dataset is a combination of the following open
| Source | Type | Conflation <br /> Priority | Count |
| -------------------------- | --------------------- | -------------------------- | ----------- |
| [OpenStreetMap](//osm.org) | Community-contributed | 1 | ~635 Million |
| [Esri Community Maps](https://communitymaps.arcgis.com/home) | Community-contributed | 2| ~15 Million |
| [Instituto Geográfico Nacional (España)](https://www.ign.es/) | National dataset | 3 | ~13 Million |
| [Google Open Buildings](https://sites.research.google/open-buildings/)| ML-derived roofprints<br /> (&gt;90% precision) | 4 | ~350 Million |
| [Microsoft](https://github.com/microsoft/GlobalMLBuildingFootprints) |ML-derived roofprints | 5 | ~738 Million |
| [Google Open Buildings](https://sites.research.google/open-buildings/)| ML-derived roofprints<br /> (&lt;90% precision) | 6 |~650 Million |
| [Buildings in East Asian Countries](https://zenodo.org/records/8174931)| ML-derived roofprints<br /> | 7 |~228 Million |
| [Esri Community Maps](https://communitymaps.arcgis.com/home) | Community-contributed | 2| ~11 Million |
| [Instituto Geográfico Nacional (España)](https://www.ign.es/) | National dataset | 3 | ~11.7 Million |
| [City of Vancouver, Canada](https://opendata.vancouver.ca/) | Municipal dataset | 4 | ~14 Thousand |
| [Google Open Buildings](https://sites.research.google/open-buildings/)| ML-derived roofprints<br /> (&gt;90% precision) | 5 | ~350 Million |
| [Microsoft](https://github.com/microsoft/GlobalMLBuildingFootprints) |ML-derived roofprints | 6 | ~723 Million |
| [Google Open Buildings](https://sites.research.google/open-buildings/)| ML-derived roofprints<br /> (&lt;90% precision) | 7 |~650 Million |
| [Buildings in East Asian Countries](https://zenodo.org/records/8174931)| ML-derived roofprints<br /> | 8 |~213 Million |

## Understanding the Parquet Files

Expand Down
26 changes: 15 additions & 11 deletions docs/guides/places.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,21 +21,25 @@ This guide is focused on the Overture places **data**—its content, scope, prop

## Overview

The Overture places theme has one feature type, called `place`, and contains more than 61 million point representations of real-world entities: schools, businesses, hospitals, religious organizations, landmarks, mountain peaks, and much more. The theme is derived from a conflation of Meta, Microsoft, and PinMeTo data and is available under a [CDLA Permissive 2.0](https://cdla.dev/permissive-2-0/) license.
The Overture places theme has one feature type, called `place`, and contains more than 64 million point representations of real-world entities: schools, businesses, hospitals, religious organizations, landmarks, mountain peaks, and much more. The theme is derived from a conflation of Meta, Microsoft, and PinMeTo data and is available under a [CDLA Permissive 2.0](https://cdla.dev/permissive-2-0/) license.

| ![Overture places theme coverage](/img/places/places-coverage.png) |
| ![Overture places theme coverage](/img/places/places-coverage-h3-june.png) |
|:--:|
| *Overture places data, May 2025* |
| *Overture places data, June 2025* |

| Source | Feature count, May 2025 release |
| Source | Feature count, June 2025 release |
| -------------------------- | --------------------- |
| Meta | 53,765,036 |
| Microsoft | 5,156,084 |
| Microsoft & Meta | 2,640,326 |
| Microsoft & PinMeTo | 54,382 |
| Microsoft, PinMeTo & Meta | 30,306 |
| PinMeTo | 29,882 |
| PinMeTo & Meta | 5,803 |
| meta | 56,677,393 |
| Microsoft | 4,655,498 |
| Microsoft & meta | 2,891,357 |
| Microsoft & PinMeTo | 48,157 |
| PinMeTo | 44,506 |
| Microsoft, PinMeTo & meta | 31,546 |
| Krick & Microsoft | 6,306 |
| PinMeTo & meta | 5,835 |
| Krick | 3,199 |
| Krick, Microsoft & meta | 2,690 |
| Krick & meta | 723 |

## Dataset description

Expand Down
70 changes: 39 additions & 31 deletions docs/guides/transportation.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -61,6 +61,7 @@ All Overture data, including transportation data, is distributed as GeoParquet,
| prohibited_transitions | STRUCT[] | Defines where traveling from the segment to another is disallowed for navigation. This covers things situations prohibited turns or a transition from road to bike lane disallowing cars. |
| road_surface | STRUCT[] | Defines the surface material on a road such as paved, asphalt, or unpaved. |
| road_flags | STRUCT[] | Additional properties relevant to roads such as is_bridge or is_under_construction. |
| rail_flags | STRUCT[] | Additional properties relevant to rail such as is_tunnel or is_freight. |
| speed_limits | STRUCT[] | Defines the speed limit of the road segment. |
| width_rules | STRUCT[] | Defines the width of the road segment for rendering. |
| destinations | STRUCT[] | Describes the transitions from one segment to another on the way to a specified location. This data is primarily used for routing. |
Expand All @@ -86,38 +87,45 @@ Transportation segments are divided into three subtypes: **rail**, **water**, an
<div>
<Tabs>
<TabItem value="classes" label="classes" default>
| subtype | class | subclass | Feature count, May 2025 release |
| subtype | class | subclass | Feature count, June 2025 release |
|---|---|---|---|
| rail | | | 1,609,337 |
| road | bridleway | | 98,230 |
| road | cycleway | cycle_crossing | 53,764 |
| road | cycleway | | 1,246,074 |
| road | footway | crosswalk | 2,039,673 |
| road | footway | sidewalk | 3,281,282 |
| road | footway | | 15,378,957 |
| road | living_street | | 3,265,976 |
| road | motorway | link | 638,308 |
| road | motorway | | 432,262 |
| road | path | | 13,187,280 |
| road | pedestrian | | 458,725 |
| road | primary | link | 484,551 |
| road | primary | | 6,635,394 |
| road | residential | | 124,922,897 |
| road | secondary | link | 381,553 |
| road | secondary | | 10,618,673 |
| road | service | alley | 1,638,837 |
| road | service | driveway | 16,100,016 |
| road | service | parking_aisle | 6,197,666 |
| road | service | | 32,478,397 |
| road | steps | | 1,805,735 |
| road | tertiary | link | 292,466 |
| road | tertiary | | 19,573,564 |
| road | track | | 24,780,102 |
| road | trunk | link | 541,491 |
| road | trunk | | 3,390,893 |
| road | unclassified | | 29,319,388 |
| road | unknown | | 649,519 |
| water | | | 27,959 |
| rail | funicular | | 1,297 |
| rail | light_rail | | 15,930 |
| rail | monorail | | 2,979 |
| rail | narrow_gauge | | 30,843 |
| rail | standard_gauge | | 1,423,890 |
| rail | subway | | 52,344 |
| rail | tram | | 59,142 |
| rail | unknown | | 372,866 |
| road | bridleway | | 99,049 |
| road | cycleway | cycle_crossing | 55,477 |
| road | cycleway | | 1,259,399 |
| road | footway | crosswalk | 2,109,280 |
| road | footway | sidewalk | 3,394,404 |
| road | footway | | 15,631,725 |
| road | living_street | | 3,296,747 |
| road | motorway | link | 638,701 |
| road | motorway | | 432,035 |
| road | path | | 13,329,876 |
| road | pedestrian | | 461,593 |
| road | primary | link | 487,257 |
| road | primary | | 6,670,265 |
| road | residential | | 125,385,316 |
| road | secondary | link | 385,637 |
| road | secondary | | 10,666,584 |
| road | service | alley | 1,664,772 |
| road | service | driveway | 16,377,919 |
| road | service | parking_aisle | 6,266,426 |
| road | service | | 32,743,206 |
| road | steps | | 1,836,112 |
| road | tertiary | link | 295,551 |
| road | tertiary | | 19,711,085 |
| road | track | | 25,012,146 |
| road | trunk | link | 547,842 |
| road | trunk | | 3,417,014 |
| road | unclassified | | 29,488,205 |
| road | unknown | | 704,794 |
| water | | | 28,224 |

</TabItem>
</Tabs>
Expand Down
2 changes: 1 addition & 1 deletion docs/introduction.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ slug: /
title: Introduction
---

Welcome! Overture provides free and open map data normalized to [one schema](schema). Our [six data "themes"](guides) &mdash; [addresses](guides/addresses), [buildings](guides/buildings), [base](guides/base), [divisions](guides/divisions), [places](guides/places), and [transportation](guides/transportation) &mdash; contain more than 3.7 billion features and will continue to expand in size and scale. The data we use to build our datasets comes from many sources, including OpenStreetMap, Meta, Microsoft, Esri, OpenAddresses, and [more](attribution).
Welcome! Overture provides free and open map data normalized to [one schema](schema). Our [six data "themes"](guides) &mdash; [addresses](guides/addresses), [buildings](guides/buildings), [base](guides/base), [divisions](guides/divisions), [places](guides/places), and [transportation](guides/transportation) &mdash; contain nearly 4.2 billion features and will continue to expand in size and scale. The data we use to build our datasets comes from many sources, including OpenStreetMap, Meta, Microsoft, Esri, OpenAddresses, and [more](attribution).

In this documentation, you'll find [instructions](getting-data) for accessing and handling Overture's large datasets, [reference material](schema/reference) to help you understand the Overture schema, comprehensive [guides](guides) to working with the many themes and types of Overture data, and [hands-on examples](examples) using data wrangling, analysis, and visualization tools you know and love. Want to see what our community has been building? Check out the [community projects](community) section of our documentation for inspiration.

Expand Down
Binary file added static/img/addresses/address-coverage-h3-june.png
View file
Open in desktop
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file removed static/img/addresses/address-coverage-h3-may.png
View file
Open in desktop
Binary file not shown.
Binary file added static/img/places/places-coverage-h3-june.png
View file
Open in desktop
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file removed static/img/places/places-coverage.png
View file
Open in desktop
Binary file not shown.