FACT Buildings Footprint and Height

ML detected building footprints and height open database. Bing Maps open building footprints. with partial global coverage, only US and Europe included here.

Use

1. Pull the image:

docker pull registry.git.nilu.no/fact/data/fact_bldgs:latest

2. Run this data service:

docker run -t -i --name fact_bldgs -e MARIADB_DATABASE=FACT_bldgs -e MYSQL_ROOT_PASSWORD=devops -p 3315:3306 -d registry.git.nilu.no/fact/data/fact_bldgs:0.1

The container makes available a MariaDB instance with the full database on airports and traffic FACT_bldgs. It is reachable on port 3315 of the localhost and the password is 'devops'.

Specifications

Table           |Size (MB)|Rows (#) |
----------------+---------+---------+
footprints      | 91081.03|341191944|
geometry_columns|     0.02|        0|
spatial_ref_sys |     0.02|        0|

Properties in footprints contain a dictionary with height (-1 if missing) and confidence, example:

{ "height": -1.0, "confidence": -1.0 }

All spatial objects are converted to EPSG:4326.

Notes

The code downloads files for European countries and US, transforms them into geojson with right CRS, and then loads them into a DB.

The input data is available from https://github.com/microsoft/GlobalMLBuildingFootprints

Author

Riccardo Boero - ribo@nilu.no

License

All the code and the resulting docker images in this project are subject to:

• GNU Generla Public License v2.

The data is licensed under:

• the Open Data Commons Open Database License (ODbL) v1.0.

Citation

• Boero, Riccardo. 2024. “FACT Data: Buildings Footprint and Height.” OSF. doi:10.17605/OSF.IO/CHDJR.

Part of the Fine scAle eConomic daTa - FACT project:

• Boero, Riccardo. 2024. “Fine scAle eConomic daTa - FACT.” OSF. doi:10.17605/OSF.IO/PV4ZW.