diff --git a/README.md b/README.md index e79d7e8..659fa5b 100644 --- a/README.md +++ b/README.md @@ -3,12 +3,14 @@ Bing Maps is releasing open building footprints around the world. We have detected **1.4B** buildings from Bing Maps imagery between 2014 and 2024 including Maxar, Airbus, and IGN France imagery. The data is freely available for download and use under CDLA Permissive 2.0. This dataset includes our [other releases](#will-there-be-more-data-coming-for-other-geographies). ## Updates -* 2026-02-03 - Added **1.2M** building footprints and **1.2M** height estimates derived from Vexcel imagery between 2021 and 2025. All contributions are from the United States (1.2M). [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) updated 3 February 2026. -* 2026-01-27 - Added **1.0M** building footprints and **1.0M** height estimates derived from Vexcel imagery between 2021 and 2025. All contributions are from the United States (1.1M). [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) updated 27 January 2026. -* 2026-01-23 - Added **1.0M** building footprints and **1.0M** height estimates derived from Vexcel imagery between 2021 and 2025. All contributions are from the United States (1.1M). [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) updated 23 January 2026. -* 2026-01-18 - Added **1.9M** building footprints and **1.9M** height estimates derived from Maxar and Vexcel imagery between 2020 and 2025. All contributions are from the United States (1.1M). [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) updated 18 January 2026. -* 2026-01-09 - Added **3.5M** building footprints and **3.4M** height estimates derived from Maxar and Vexcel imagery between 2020 and 2025. Largest contributions are to Belgium (1.8M), Netherlands (1.6M), and Germany (1.1M). [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) updated 09 January 2026. -* 2025-02-28 - Added **18M** building footprints and **4.2M** height estimates derived from Maxar and Vexcel imagery between 2017 and 2024. Largest contributions are to Turkey (5.8M), Greece (6M), and France (3.8M). [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) updated 28 February 2025. +* 2026-07-24 - Added **431K** building footprints and **431K** height estimates derived from Vexcel imagery in 2025. Largest contributions are to the United States (343K), Norway (50K), and Italy (33K). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 24 July 2026. +* 2026-07-24 - Dataset hosting is moving! You will notice `dataset-links.csv` has a new url https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv. All links are updated from https://minedbuildings.**z5.web**.core.windows.net/ -> https://**bfppub.blob**.core.windows.net/. Older versions will not be moved but updates will be available at this new location going forward. +* 2026-02-03 - Added **1.2M** building footprints and **1.2M** height estimates derived from Vexcel imagery between 2021 and 2025. All contributions are from the United States (1.2M). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 3 February 2026. +* 2026-01-27 - Added **1.0M** building footprints and **1.0M** height estimates derived from Vexcel imagery between 2021 and 2025. All contributions are from the United States (1.1M). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 27 January 2026. +* 2026-01-23 - Added **1.0M** building footprints and **1.0M** height estimates derived from Vexcel imagery between 2021 and 2025. All contributions are from the United States (1.1M). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 23 January 2026. +* 2026-01-18 - Added **1.9M** building footprints and **1.9M** height estimates derived from Maxar and Vexcel imagery between 2020 and 2025. All contributions are from the United States (1.1M). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 18 January 2026. +* 2026-01-09 - Added **3.5M** building footprints and **3.4M** height estimates derived from Maxar and Vexcel imagery between 2020 and 2025. Largest contributions are to Belgium (1.8M), Netherlands (1.6M), and Germany (1.1M). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 09 January 2026. +* 2025-02-28 - Added **18M** building footprints and **4.2M** height estimates derived from Maxar and Vexcel imagery between 2017 and 2024. Largest contributions are to Turkey (5.8M), Greece (6M), and France (3.8M). [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) updated 28 February 2025. * 2025-02-03 - Added **7.4M** building footprints and **2.4M** height estimates derived from from Maxar and Vexcel imagery between 2020 and 2024. The largest contributions are to France (5.8M) and the United States (1.2M). dataset-links.csv updated 3 February 2025. * 2025-01-06 - Added **9.6M** building footprint edits derived from Maxar imagery between 2021 and 2024. Largest contributions are to Chile (3.4M), Norway (2M), Brazil (2M), and Sweden (1.5M). No new height estimates. dataset-links.csv updated 6 January 2025. * 2024-12-02 - Added **12M** building footprint edits and **554k** height estimates derived from Maxar and Vexcel imagery between 2018 and 2024. The largest contributions are to Sudan (5.5M), Ethiopia (3.3M), and Saudi Arabia (590k). dataset-links.csv updated on 2 December 2024. Changed merge logic to update tiles at LOD 19 instead of LOD 15 reducing update boundary visibility. @@ -40,7 +42,7 @@ countries with the largest contributors in Mexico (17M), Ethiopia (16M) and Keny into a GIS tool (e.g., QGIS, ArcGIS) friendly format. * 2022-10-12 - Added **147M** new buildings for North America based on Vexcel and Maxar imagery between 2017 and 2022. This data is a refresh of [US](https://github.com/microsoft/USBuildingFootprints). Updated data format from country-partitioned zip files to country-[l9 quad key](https://learn.microsoft.com/en-us/bingmaps/articles/bing-maps-tile-system#tile-coordinates-and-quadkeys) gzipped partitioned files. Each file extension is .csv.gz but the contents are geojsonl. False positive rate for this dataset is ~1% based on a 4k structure sample. Link table was moved - to a [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) + to a [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) * 2022-07-08 - Added **78M** buildings in Western EU Countries from Maxar imagery between 2014 and 2021 bringing the total structure count to **856M**. Added link to download buildings coverage. * 2022-07-05 - The complete building footprints dataset is available on [Microsoft's Planetary Computer](https://planetarycomputer.microsoft.com/dataset/ms-buildings) @@ -66,7 +68,7 @@ This data is licensed by Microsoft under the [CDLA Permissive 2.0](https://cdla. ### What does the data include? 999M building footprint polygon geometries located around the world in line delimited GeoJSON format. Due to the way we process the data, file extensions are `.csv.gz` see [make-gis-friendly.py](scripts/make-gis-friendly.py) for an example of how to decompress and change file extension. -As of October 2022, we moved the location table to [dataset-links.csv](https://minedbuildings.z5.web.core.windows.net/global-buildings/dataset-links.csv) since it's over 19k records with country-quadkey partitioning. +As of October 2022, we moved the location table to [dataset-links.csv](https://bfppub.blob.core.windows.net/%24web/2026-07-24/dataset-links.csv) since it's over 19k records with country-quadkey partitioning. ### What is the GeoJSON format? GeoJSON is a format for encoding a variety of geographic data structures.