This large-scale open dataset consists of outlines of buildings derived
from high-resolution 50 cm satellite imagery. It contains 516M building
detections across an area of 19.4M km2 (64% of the African continent).
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 April 2021.
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 516M building detections across an area of 19.4M km2 (64% of the African continent). For each building in this dataset we include the polygon describing its footprint on the ground, a confidence …
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis dataset, superseded by a newer version, provides outlines of 516M buildings across 64% of the African continent derived from 50 cm satellite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 indicating its location.\u003c/p\u003e\n"],["\u003cp\u003eBuilding type, street address, and details beyond geometry are not included in this dataset.\u003c/p\u003e\n"],["\u003cp\u003eThe inference for this dataset was carried out in April 2021, and an updated Version 3.0 is available with inference from May 2023.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is licensed under CC-BY-4.0 and is intended for applications like population estimation, urban planning, and environmental science.\u003c/p\u003e\n"]]],["This dataset, now superseded by version 3, provides building outlines derived from 50cm satellite imagery, encompassing 516 million detections over 19.4 million km² (64% of Africa). Each building includes a polygon footprint, a confidence score, and a Plus Code for its center. The data, generated in April 2021, is accessible via Earth Engine and includes the area, confidence level, plus code and a polygon's centroid in the table schema.\n"],null,["**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: 2021-04-30T00:00:00Z--2021-04-30T00:00:00Z\n\nDataset Provider\n:\n\n\n [Google Research - Open Buildings](https://sites.research.google/open-buildings/)\n\nTags\n:\n africa \n building \n built-up \n open-buildings \n population \n structure \ntable \n\nDescription \nThis large-scale open dataset consists of outlines of buildings derived\nfrom high-resolution 50 cm satellite imagery. It contains 516M building\ndetections across an area of 19.4M km2 (64% of the African continent).\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 April 2021.\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\nTable 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\nTerms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\nCitations \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\nExplore with Earth Engine **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\nCode Editor (JavaScript) \n\n```javascript\n// Visualization of GOOGLE/Research/open-buildings/v1/polygons.\n\nvar t = ee.FeatureCollection('GOOGLE/Research/open-buildings/v1/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_v1_polygons)\n\nVisualize 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\nCode Editor (JavaScript) \n\n```javascript\nvar fvLayer = ui.Map.FeatureViewLayer(\n 'GOOGLE/Research/open-buildings/v1/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_v1_polygons_FeatureView) \n[Open Buildings V1 Polygons \\[deprecated\\]](/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v1_polygons) \nThis large-scale open dataset consists of outlines of buildings derived from high-resolution 50 cm satellite imagery. It contains 516M building detections across an area of 19.4M km2 (64% of the African continent). For each building in this dataset we include the polygon describing its footprint on the ground, a confidence ... \nGOOGLE/Research/open-buildings/v1/polygons, africa,building,built-up,open-buildings,population,table \n2021-04-30T00:00:00Z/2021-04-30T00:00:00Z \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_v1_polygons)"]]