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Worldwide building footprints derived from satellite imagery

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Introduction

Bing Maps is releasing open building footprints around the world. We have detected 856M buildings from Bing Maps imagery between 2014 and 2021 including Maxar and Airbus imagery. The data is freely available for download and use under ODbL. This dataset complements our other releases.

sample footprints

Regions included

building regions

You can download the layer above as GeoJSON here.

License

This data is licensed by Microsoft under the Open Data Commons Open Database License (ODbL).

Updates

  • 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

FAQ

What does the data include?

855,652,826 building footprint polygon geometries located around the world in line delimited GeoJSON format.

Location Count Link Size (Compressed)
Abyei 171 Abyei.zip 12.3KB
Afghanistan 6,588,191 Afghanistan.zip 511.6MB
Africa 4,631 Africa.zip 383.3KB
Albania 1,180,677 Albania.zip 87.1MB
Algeria 6,854,110 Algeria.zip 576.3MB
Andorra 8,605 Andorra.zip 837.0KB
Angola 4,845,154 Angola.zip 331.7MB
Anguilla 9,273 Anguilla.zip 733.5KB
Antigua and Barbuda 45,997 Antigua and Barbuda.zip 3.3MB
Argentina 6,751,335 Argentina.zip 543.9MB
Armenia 938,929 Armenia.zip 73.4MB
Aruba 65,361 Aruba.zip 4.8MB
Asia 38,521 Asia.zip 2.8MB
Austria 3,804,289 Austria.zip 334.8MB
Azerbaijan 2,096,023 Azerbaijan.zip 152.9MB
Bahrain 197,877 Bahrain.zip 18.5MB
Bangladesh 15,186,144 Bangladesh.zip 1.0GB
Barbados 147,195 Barbados.zip 10.8MB
Belarus 6,680,004 Belarus.zip 500.5MB
Belgium 4,445,133 Belgium.zip 392.9MB
Belize 143,087 Belize.zip 9.8MB
Benin 1,785,978 Benin.zip 123.7MB
Bhutan 122,682 Bhutan.zip 8.4MB
Bolivia 3,017,298 Bolivia.zip 215.8MB
Bonaire 14,315 Bonaire.zip 1.0MB
Bosnia and Herzegovina 2,391,531 Bosnia and Herzegovina.zip 169.5MB
Botswana 1,180,475 Botswana.zip 80.5MB
Brazil 59,513,459 Brazil.zip 4.4GB
British Indian Ocean Territory 928 British Indian Ocean Territory.zip 72.3KB
British Virgin Islands 10,298 British Virgin Islands.zip 774.9KB
Bulgaria 4,033,011 Bulgaria.zip 303.4MB
Burkina Faso 2,076,120 Burkina Faso.zip 142.7MB
Burundi 1,932,454 Burundi.zip 132.3MB
Cambodia 3,874,208 Cambodia.zip 264.6MB
Cameroon 2,221,618 Cameroon.zip 155.3MB
Cayman Islands 22,655 Cayman Islands.zip 1.8MB
Central African Republic 379,478 Central African Republic.zip 25.1MB
Chad 1,136,146 Chad.zip 78.4MB
Chile 6,210,325 Chile.zip 474.7MB
Colombia 7,169,856 Colombia.zip 551.8MB
Comoros 119,701 Comoros.zip 8.1MB
Congo (DRC) 7,713,400 Congo (DRC).zip 516.7MB
Costa Rica 1,461,644 Costa Rica.zip 111.6MB
Croatia 2,834,874 Croatia.zip 216.5MB
Cuba 2,860,000 Cuba.zip 199.2MB
Curacao 103,745 Curacao.zip 7.7MB
Cyprus 743,709 Cyprus.zip 59.0MB
Czech Republic 2,367,402 Czech Republic.zip 199.8MB
Czechia 2,585,333 Czechia.zip 208.8MB
Denmark 3,264,995 Denmark.zip 299.4MB
Djibouti 22,718 Djibouti.zip 1.6MB
Dominica 31,942 Dominica.zip 2.2MB
Dominican Republic 2,228,536 Dominican Republic.zip 155.8MB
Ecuador 4,329,641 Ecuador.zip 321.7MB
Egypt 11,864,145 Egypt.zip 1.0GB
El Salvador 1,111,558 El Salvador.zip 83.0MB
Equatorial Guinea 178,597 Equatorial Guinea.zip 12.9MB
Eritrea 262,569 Eritrea.zip 18.3MB
Estonia 737,110 Estonia.zip 58.1MB
Ethiopia 4,126,913 Ethiopia.zip 285.2MB
Europe 12,216 Europe.zip 1004.8KB
FYRO Makedonija 774,962 FYRO Makedonija.zip 57.2MB
Faroe Islands 30,004 Faroe Islands.zip 2.6MB
Finland 4,598,752 Finland.zip 387.6MB
France 23,396,212 France.zip 2.1GB
French Guiana 69,716 French Guiana.zip 5.2MB
French-Guadeloupe 216,903 French-Guadeloupe.zip 15.8MB
French-Martinique 176,510 French-Martinique.zip 12.9MB
Gabon 359,032 Gabon.zip 26.5MB
Gaza Strip 268,186 Gaza Strip.zip 20.7MB
Georgia 1,090,394 Georgia.zip 78.1MB
Germany 28,177,869 Germany.zip 2.6GB
Ghana 4,728,049 Ghana.zip 351.2MB
Golan Heights 20,919 Golan Heights.zip 1.7MB
Greece 5,766,786 Greece.zip 448.4MB
Grenada 50,583 Grenada.zip 3.5MB
Guatemala 2,585,837 Guatemala.zip 185.9MB
Guinea-Bissau 293,103 Guinea-Bissau.zip 20.4MB
Guinea 1,588,864 Guinea.zip 108.4MB
Guyana 253,146 Guyana.zip 17.5MB
Haiti 1,564,132 Haiti.zip 104.1MB
Honduras 702,846 Honduras.zip 49.2MB
Hungary 5,689,493 Hungary.zip 437.6MB
Iceland 199,077 Iceland.zip 18.3MB
India 83,950,819 India.zip 6.3GB
Iran 7,290,330 Iran.zip 605.0MB
Iraq 8,188,203 Iraq.zip 663.1MB
Ireland 2,335,404 Ireland.zip 193.8MB
Isle of Man 40,823 Isle of Man.zip 3.7MB
Israel 1,360,355 Israel.zip 116.4MB
Italy 12,007,582 Italy.zip 1.0GB
Ivory Coast 3,128,370 Ivory Coast.zip 218.1MB
Jamaica 900,778 Jamaica.zip 62.9MB
Jordan 1,158,539 Jordan.zip 98.5MB
Kazakhstan 7,202,364 Kazakhstan.zip 551.2MB
Kingdom of Saudi Arabia 5,919,197 Kingdom of Saudi Arabia.zip 486.5MB
Kosovo 737,451 Kosovo.zip 54.5MB
Kuwait 48,917 Kuwait.zip 3.7MB
Kyrgyzstan 2,219,078 Kyrgyzstan.zip 166.8MB
Laos 1,698,185 Laos.zip 117.2MB
Lapthal 22 Lapthal.zip 1.8KB
Latvia 1,232,238 Latvia.zip 97.1MB
Lebanon 1,013,451 Lebanon.zip 85.4MB
Lesotho 808,152 Lesotho.zip 54.4MB
Liberia 459,196 Liberia.zip 32.5MB
Libya 2,117,880 Libya.zip 171.2MB
Lithuania 2,161,065 Lithuania.zip 170.8MB
Luxembourg 156,171 Luxembourg.zip 14.8MB
Madagascar 3,858,230 Madagascar.zip 250.8MB
Malawi 4,550,131 Malawi.zip 294.8MB
Maldives 46,503 Maldives.zip 3.5MB
Mali 1,833,915 Mali.zip 121.7MB
Malta 74,823 Malta.zip 8.1MB
Mauritania 820,230 Mauritania.zip 56.1MB
Mauritius 310,055 Mauritius.zip 25.2MB
Mayotte 58,174 Mayotte.zip 4.1MB
Mexico 23,765,721 Mexico.zip 1.8GB
Moldova 2,232,210 Moldova.zip 169.1MB
Mongolia 441,496 Mongolia.zip 31.4MB
Montenegro 369,178 Montenegro.zip 26.3MB
Montserrat 3,989 Montserrat.zip 303.7KB
Morocco 3,176,667 Morocco.zip 268.4MB
Mozambique 7,663,943 Mozambique.zip 498.4MB
Myanmar 9,509,715 Myanmar.zip 633.5MB
Namibia 842,206 Namibia.zip 59.1MB
Nepal 6,349,307 Nepal.zip 433.6MB
Netherlands 3,539,902 Netherlands.zip 328.3MB
Nicaragua 783,377 Nicaragua.zip 56.7MB
Niger 1,768,697 Niger.zip 118.2MB
North America 3,250 North America.zip 252.0KB
North Korea 39,129 North Korea.zip 3.0MB
Norway 3,771,466 Norway.zip 326.9MB
Pa-li-chia-ssu 234 Pa-li-chia-ssu.zip 16.6KB
Pakistan 19,399,807 Pakistan.zip 1.5GB
Panama 1,127,611 Panama.zip 80.9MB
Paracel Islands 347 Paracel Islands.zip 29.7KB
Paraguay 2,382,243 Paraguay.zip 169.6MB
Peru 7,470,993 Peru.zip 550.4MB
Poland 17,931,193 Poland.zip 1.4GB
Portugal 5,875,178 Portugal.zip 475.3MB
Puerto Rico 1,456,268 Puerto Rico.zip 105.6MB
Republic of Yemen 3,048,460 Republic of Yemen.zip 222.2MB
Republic of the Congo 212,365 Republic of the Congo.zip 14.6MB
Reunion 349,450 Reunion.zip 26.9MB
Romania 12,345,591 Romania.zip 929.6MB
Russia 65,592,760 Russia.zip 4.9GB
Rwanda 2,937,226 Rwanda.zip 202.2MB
Saint Barthelemy 6,742 Saint Barthelemy.zip 522.0KB
Saint Helena, Ascension and Tristan da Cunha 4,196 Saint Helena, Ascension and Tristan da Cunha.zip 311.3KB
Saint Lucia 75,099 Saint Lucia.zip 5.2MB
San Marino 7,728 San Marino.zip 691.9KB
Sang 129 Sang.zip 9.1KB
Senegal 1,848,802 Senegal.zip 132.5MB
Serbia 4,751,385 Serbia.zip 358.2MB
Seychelles 38,345 Seychelles.zip 2.8MB
Sierra Leone 514,685 Sierra Leone.zip 35.7MB
Slovakia 2,515,328 Slovakia.zip 200.2MB
Slovenia 1,126,167 Slovenia.zip 90.6MB
Somalia 50,419 Somalia.zip 3.6MB
South Africa 22,954,325 South Africa.zip 1.6GB
South America 46 South America.zip 3.5KB
South Sudan 120,553 South Sudan.zip 8.0MB
Spain 2,857,746 Spain.zip 257.0MB
Sri Lanka 3,162,836 Sri Lanka.zip 220.9MB
St Kitts and Nevis 27,786 St Kitts and Nevis.zip 2.0MB
St Martin 9,747 St Martin.zip 783.9KB
St Vincent and the Grenadines 47,587 St Vincent and the Grenadines.zip 3.3MB
State of Qatar 507,224 State of Qatar.zip 41.1MB
Sudan 2,851,260 Sudan.zip 199.2MB
Sultanate of Oman 393,799 Sultanate of Oman.zip 32.2MB
Suriname 244,018 Suriname.zip 17.6MB
Swaziland 636,538 Swaziland.zip 43.6MB
Sweden 6,449,888 Sweden.zip 541.0MB
Switzerland 292,095 Switzerland.zip 27.1MB
Syria 4,432,148 Syria.zip 354.2MB
São Tomé and Príncipe 35,084 São Tomé and Príncipe.zip 2.5MB
Tajikistan 2,006,822 Tajikistan.zip 151.5MB
Tanzania 685,763 Tanzania.zip 45.3MB
Thailand 24,503,490 Thailand.zip 1.7GB
The Bahamas 129,246 The Bahamas.zip 9.9MB
The Gambia 349,894 The Gambia.zip 24.3MB
Togo 1,440,071 Togo.zip 102.5MB
Trinidad and Tobago 495,217 Trinidad and Tobago.zip 36.0MB
Tunisia 3,411,631 Tunisia.zip 299.5MB
Turkey 18,058,257 Turkey.zip 1.4GB
Turkmenistan 1,472,716 Turkmenistan.zip 112.0MB
Turks and Caicos Islands 15,713 Turks and Caicos Islands.zip 1.2MB
US Virgin Islands 50,266 US Virgin Islands.zip 3.8MB
Uganda 773,722 Uganda.zip 53.0MB
Ukraine 26,771,785 Ukraine.zip 1.9GB
United Arab Emirates 940,322 United Arab Emirates.zip 82.1MB
United Kingdom 18,240,684 United Kingdom.zip 1.6GB
Uruguay 1,150,564 Uruguay.zip 87.1MB
Uzbekistan 6,511,858 Uzbekistan.zip 524.1MB
Vatican City 91 Vatican City.zip 11.6KB
Venezuela 8,095,813 Venezuela.zip 587.8MB
Vietnam 23,866,366 Vietnam.zip 1.7GB
West Bank 664,890 West Bank.zip 54.9MB
Western Halaib Triangle 156 Western Halaib Triangle.zip 11.2KB
Zambia 4,072,766 Zambia.zip 274.4MB
Zimbabwe 5,205,824 Zimbabwe.zip 347.3MB
Île Saint-Martin 14,919 Île Saint-Martin.zip 1.1MB

What is the GeoJSON format?

GeoJSON is a format for encoding a variety of geographic data structures. For intensive documentation and tutorials, refer to this blog.

Why is the data being released?

Microsoft has a continued interest in supporting a thriving OpenStreetMap ecosystem.

Should we import the data into OpenStreetMap?

Maybe. Never overwrite the hard work of other contributors or blindly import data into OSM without first checking the local quality. While our metrics show that this data meets or exceeds the quality of hand-drawn building footprints, the data does vary in quality from place to place, between rural and urban, mountains and plains, and so on. Inspect quality locally and discuss an import plan with the community. Always follow the OSM import community guidelines.

Will the data be used or made available in the larger OpenStreetMap ecosystem?

Yes. The HOT Tasking Manager has integrated Facebook RapiD where the data has been made available.

How did we create the data?

The building extraction is done in two stages:

  1. Semantic Segmentation – Recognizing building pixels on an aerial image using deep neural networks (DNNs)
  2. Polygonization – Converting building pixel detections into polygons

Stage1: Semantic Segmentation

segmenation diagram

Stage 2: Polygonization

polygonization diagram

Were there any modeling improvements used for this release?

We did not apply any modeling improvements for this release. Instead, we focused on scaling our approach to increase coverage, and trained models regionally.

Evaluation set metrics

The evaluation metrics are computed on a set of building polygon labels for each region. Note, we only have verification results for Mexico buildings since we did not train a model for the country.

Building match metrics on the evaluation set:

Region Precision Recall
Africa 94.4% 70.9%
Caribbean 92.2% 76.8%
Central Asia 97.17% 79.47%
Europe 94.3% 85.9%
Middle East 95.7% 85.4%
South America 95.4% 78.0%
South Asia 94.8% 76.7%

We track the following metrics to measure the quality of matched building polygons in the evaluation set:

  1. Intersection over Union – This is a standard metric measuring the overlap quality against the labels
  2. Dominant angle rotation error – This measures the polygon rotation deviation
Region IoU Rotation error [deg]
Africa 64.5% 5.67
Caribbean 64.0% 6.64
Central Asia 68.2% 6.91
Europe 65.1% 10.28
Middle East 65.1% 9.3
South America 66.7% 6.34
South Asia 63.1% 6.25

False positive ratio in the corpus

False positives are estimated per country from randomly sampled building polygon predictions.

Region Buildings Sampled False Positive Rate
Africa 5,000 1.1%
Caribbean 3,000 1.8%
Central Asia 3,000 2.2%
Europe 5,000 1.4%
Mexico 2,000 0.1%
Middle East 7,000 1.8%
South America 5,000 1.7%
South Asia 7,000 1.4%

What is the vintage of this data?

Vintage of extracted building footprints depends on the vintage of the underlying imagery. The underlying imagery is from Bing Maps including Maxar and Airbus between 2014 and 2021.

How good is the data?

Our metrics show that in the vast majority of cases the quality is at least as good as hand digitized buildings in OpenStreetMap. It is not perfect, particularly in dense urban areas but it provides good recall in rural areas.

What is the coordinate reference system?

EPSG: 4326

Will there be more data coming for other geographies?

Maybe. This is a work in progress. Also, check out our other building releases!

Why are some locations missing?

We excluded imagery from processing if tiles were dated before 2014 or there was a low-probability of detection. Detection probability is loosely defined here as proximity to roads and population centers. This filtering and tile exclusion results in squares of missing data.

How can I read large files?

Some files are very large but they are stored in line-delimited format so one could use parallel processing tools (e.g., Spark, Dask) or create a memory efficient script to segment into smaller pieces. See scripts/read-large-files.py for a Python example.


Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Legal Notices

Microsoft, Windows, Microsoft Azure and/or other Microsoft products and services referenced in the documentation may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries. The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks. Microsoft's general trademark guidelines can be found here.

Privacy information can be found here.

Microsoft and any contributors reserve all others rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel or otherwise.

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