This large-scale open dataset consists of outlines of buildings derived
from high-resolution 50 cm satellite imagery. It contains 816M building
detections in Africa, South Asia and Southeast Asia. The inference spanned
an area of 39.1M km².
For each building in this dataset we include the polygon describing its
footprint on the ground, a confidence score indicating how sure we are that
this is a building, and a Plus Code corresponding to
the center of the building. There is no information about the type of
building, its street address, or any details other than its geometry.
Building footprints are useful for a range of important applications: from
population estimation, urban planning and humanitarian response to
environmental and climate science. The project being based in Ghana, the
current focus is on the continent of Africa.
Inference was carried out during Aug 2022.
For more details see the official
website of the Open
Buildings dataset.
Note that updated versions of this data are available. The newest version,
Version 3.0 (with inference carried out on May 2023), is available as
GOOGLE/Research/open-buildings/v3/polygons.
Table Schema
Table Schema
Name
Type
Description
area_in_meters
DOUBLE
Area in square meters of the polygon.
confidence
DOUBLE
Confidence score [0.5;1.0] assigned by the model.
full_plus_code
STRING
The full Plus Code at the building polygon centroid.
W. Sirko, S. Kashubin, M. Ritter, A. Annkah, Y.S.E. Bouchareb, Y. Dauphin,
D. Keysers, M. Neumann, M. Cisse, J.A. Quinn. Continental-scale building
detection from high resolution satellite imagery.
arXiv:2107.12283, 2021.
This large-scale open dataset consists of outlines of buildings derived from high-resolution 50 cm satellite imagery. It contains 816M building detections in Africa, South Asia and Southeast Asia. The inference spanned an area of 39.1M km². For each building in this dataset we include the polygon describing its footprint on …
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis dataset, now superseded by a newer version, provides outlines of 816 million buildings in Africa, South Asia, and Southeast Asia derived from 50 cm satellite imagery.\u003c/p\u003e\n"],["\u003cp\u003eEach building is represented by a polygon footprint, a confidence score, and a Plus Code for its centroid, but lacks information on building type or address.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is intended for applications like population estimation, urban planning, and environmental science, with a primary focus on Africa.\u003c/p\u003e\n"],["\u003cp\u003eA newer version of this dataset, Version 3.0 with inference from May 2023, is available as GOOGLE/Research/open-buildings/v3/polygons.\u003c/p\u003e\n"],["\u003cp\u003eBuilding footprints are accompanied by a confidence score and Plus Code, allowing users to assess data reliability and location.\u003c/p\u003e\n"]]],[],null,["# Open Buildings V2 Polygons [deprecated]\n\n**Caution:** This dataset has been superseded by [GOOGLE/Research/open-buildings/v3/polygons](/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v3_polygons). \n\nDataset Availability\n: 2022-08-30T00:00:00Z--2022-08-30T00:00:00Z\n\nDataset Provider\n:\n\n\n [Google Research - Open Buildings](https://sites.research.google/open-buildings/)\n\nTags\n:\n africa \n asia \n building \n built-up \n open-buildings \n population \n south-asia \n southeast-asia \n structure \ntable \n\n#### Description\n\nThis large-scale open dataset consists of outlines of buildings derived\nfrom high-resolution 50 cm satellite imagery. It contains 816M building\ndetections in Africa, South Asia and Southeast Asia. The inference spanned\nan area of 39.1M km².\n\nFor each building in this dataset we include the polygon describing its\nfootprint on the ground, a confidence score indicating how sure we are that\nthis is a building, and a [Plus Code](https://plus.codes/) corresponding to\nthe center of the building. There is no information about the type of\nbuilding, its street address, or any details other than its geometry.\n\nBuilding footprints are useful for a range of important applications: from\npopulation estimation, urban planning and humanitarian response to\nenvironmental and climate science. The project being based in Ghana, the\ncurrent focus is on the continent of Africa.\n\nInference was carried out during Aug 2022.\n\nFor more details see the official\n[website](https://sites.research.google/open-buildings/) of the Open\nBuildings dataset.\n\nNote that updated versions of this data are available. The newest version,\nVersion 3.0 (with inference carried out on May 2023), is available as\n[GOOGLE/Research/open-buildings/v3/polygons](/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v3_polygons).\n\n### Table Schema\n\n**Table Schema**\n\n| Name | Type | Description |\n|--------------------|----------|-----------------------------------------------------------------------------|\n| area_in_meters | DOUBLE | Area in square meters of the polygon. |\n| confidence | DOUBLE | Confidence score \\[0.5;1.0\\] assigned by the model. |\n| full_plus_code | STRING | The full [Plus Code](https://plus.codes/) at the building polygon centroid. |\n| longitude_latitude | GEOMETRY | Centroid of the polygon. |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\n### Citations\n\nCitations:\n\n- W. Sirko, S. Kashubin, M. Ritter, A. Annkah, Y.S.E. Bouchareb, Y. Dauphin,\n D. Keysers, M. Neumann, M. Cisse, J.A. Quinn. Continental-scale building\n detection from high resolution satellite imagery.\n [arXiv:2107.12283](https://arxiv.org/abs/2107.12283), 2021.\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\n// Visualization of GOOGLE/Research/open-buildings/v2/polygons.\n\nvar t = ee.FeatureCollection('GOOGLE/Research/open-buildings/v2/polygons');\n\nvar t_060_065 = t.filter('confidence \u003e= 0.60 && confidence \u003c 0.65');\nvar t_065_070 = t.filter('confidence \u003e= 0.65 && confidence \u003c 0.70');\nvar t_gte_070 = t.filter('confidence \u003e= 0.70');\n\nMap.addLayer(t_060_065, {color: 'FF0000'}, 'Buildings confidence [0.60; 0.65)');\nMap.addLayer(t_065_070, {color: 'FFFF00'}, 'Buildings confidence [0.65; 0.70)');\nMap.addLayer(t_gte_070, {color: '00FF00'}, 'Buildings confidence \u003e= 0.70');\nMap.setCenter(3.389, 6.492, 17); // Lagos, Nigeria\nMap.setOptions('SATELLITE');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/GOOGLE/GOOGLE_Research_open-buildings_v2_polygons)\n\n### Visualize as a FeatureView\n\n\nA `FeatureView` is a view-only, accelerated representation of a\n`FeatureCollection`. For more details, visit the\n[`FeatureView` documentation.](/earth-engine/guides/featureview_overview)\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar fvLayer = ui.Map.FeatureViewLayer(\n 'GOOGLE/Research/open-buildings/v2/polygons_FeatureView');\n\nvar visParams = {\n rules: [\n {\n filter: ee.Filter.expression('confidence \u003e= 0.60 && confidence \u003c 0.65'),\n color: 'FF0000'\n },\n {\n filter: ee.Filter.expression('confidence \u003e= 0.65 && confidence \u003c 0.70'),\n color: 'FFFF00'\n },\n {\n filter: ee.Filter.expression('confidence \u003e= 0.70'),\n color: '00FF00'\n },\n ]\n};\n\nfvLayer.setVisParams(visParams);\nfvLayer.setName('Buildings');\n\nMap.setCenter(3.389, 6.492, 17); // Lagos, Nigeria\nMap.add(fvLayer);\nMap.setOptions('SATELLITE');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/GOOGLE/GOOGLE_Research_open-buildings_v2_polygons_FeatureView) \n[Open Buildings V2 Polygons \\[deprecated\\]](/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v2_polygons) \nThis large-scale open dataset consists of outlines of buildings derived from high-resolution 50 cm satellite imagery. It contains 816M building detections in Africa, South Asia and Southeast Asia. The inference spanned an area of 39.1M km². For each building in this dataset we include the polygon describing its footprint on ... \nGOOGLE/Research/open-buildings/v2/polygons, africa,asia,building,built-up,open-buildings,population,south-asia,southeast-asia,table \n2022-08-30T00:00:00Z/2022-08-30T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://sites.research.google/open-buildings/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v2_polygons)"]]
