![GOOGLE/Research/open-buildings/v3/polygons](https://developers.google.com/earth-engine/datasets/images/GOOGLE/GOOGLE_Research_open-buildings_v3_polygons_sample.png)

Dataset Availability
:   2023-05-30T00:00:00Z--2023-05-30T00:00:00Z

Dataset Producer
:


    [Google Research - Open Buildings](https://sites.research.google/open-buildings/)

Tags
:
    [africa](https://developers.google.com/earth-engine/datasets/tags/africa) [asia](https://developers.google.com/earth-engine/datasets/tags/asia) [building](https://developers.google.com/earth-engine/datasets/tags/building) [built-up](https://developers.google.com/earth-engine/datasets/tags/built-up) [open-buildings](https://developers.google.com/earth-engine/datasets/tags/open-buildings) [population](https://developers.google.com/earth-engine/datasets/tags/population) [south-asia](https://developers.google.com/earth-engine/datasets/tags/south-asia) [southeast-asia](https://developers.google.com/earth-engine/datasets/tags/southeast-asia) [table](https://developers.google.com/earth-engine/datasets/tags/table) structure

#### Description

This large-scale open dataset consists of outlines of buildings derived
from high-resolution 50 cm satellite imagery. It contains 1.8B building
detections in Africa, Latin America, Caribbean, South Asia and Southeast
Asia. The inference spanned an area of 58M 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](https://plus.codes/) 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 is based in Ghana, with an
initial focus on the continent of Africa and new updates on South Asia,
South-East Asia, Latin America and the Caribbean.

Inference was carried out during May 2023.

For more details see the official
[website](https://sites.research.google/open-buildings/) of the Open
Buildings dataset.

### Table Schema

**Table Schema**

| Name | Type | Description |
|---|---|---|
| area_in_meters | DOUBLE | Area in square meters of the polygon. |
| confidence | DOUBLE | Confidence score \[0.65;1.0\] assigned by the model. |
| full_plus_code | STRING | The full [Plus Code](https://plus.codes/) at the building polygon centroid. |
| longitude_latitude | GEOMETRY | Centroid of the polygon. |

### Terms of Use

**Terms of Use**

[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)

### Citations

Citations:

- 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](https://arxiv.org/abs/2107.12283), 2021.

### Explore with Earth Engine

> [!NOTE]
> **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)

### Code Editor (JavaScript)

```javascript
// Visualization of GOOGLE/Research/open-buildings/v3/polygons.

var t = ee.FeatureCollection('GOOGLE/Research/open-buildings/v3/polygons');

var t_065_070 = t.filter('confidence >= 0.65 && confidence < 0.7');
var t_070_075 = t.filter('confidence >= 0.7 && confidence < 0.75');
var t_gte_075 = t.filter('confidence >= 0.75');

Map.addLayer(t_065_070, {color: 'FF0000'}, 'Buildings confidence [0.65; 0.7)');
Map.addLayer(t_070_075, {color: 'FFFF00'}, 'Buildings confidence [0.7; 0.75)');
Map.addLayer(t_gte_075, {color: '00FF00'}, 'Buildings confidence >= 0.75');
Map.setCenter(3.389, 6.492, 17);  // Lagos, Nigeria
Map.setOptions('SATELLITE');
```
Python setup

See the [Python Environment](https://developers.google.com/earth-engine/guides/python_install) page for information on the Python API and using
`geemap` for interactive development.

```python
import ee
import geemap.core as geemap
```

### Colab (Python)

```python
# Visualization of GOOGLE/Research/open-buildings/v3/polygons.
t = ee.FeatureCollection('GOOGLE/Research/open-buildings/v3/polygons')

t_065_070 = t.filter('confidence >= 0.65 && confidence < 0.7')
t_070_075 = t.filter('confidence >= 0.7 && confidence < 0.75')
t_gte_075 = t.filter('confidence >= 0.75');

m = geemap.Map()
m.set_center(3.389, 6.492, 17)
m.add_layer(t_065_070, {'color': 'FF0000'}, 'Buildings confidence [0.65; 0.7)')
m.add_layer(t_070_075, {'color': 'FFFF00'}, 'Buildings confidence [0.7; 0.75)')
m.add_layer(t_gte_075, {'color': '00FF00'}, 'Buildings confidence >= 0.75')
m
```
[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/GOOGLE/GOOGLE_Research_open-buildings_v3_polygons)

### Visualize as a FeatureView


A `FeatureView` is a view-only, accelerated representation of a
`FeatureCollection`. For more details, visit the
[`FeatureView` documentation.](https://developers.google.com/earth-engine/guides/featureview_overview)

> [!NOTE]
> **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)

### Code Editor (JavaScript)

```javascript
var fvLayer = ui.Map.FeatureViewLayer(
  'GOOGLE/Research/open-buildings/v3/polygons_FeatureView');

var visParams = {
  rules: [
    {
      filter: ee.Filter.expression('confidence >= 0.65 && confidence < 0.7'),
      color: 'FF0000'
    },
    {
      filter: ee.Filter.expression('confidence >= 0.7 && confidence < 0.75'),
      color: 'FFFF00'
    },
    {
      filter: ee.Filter.expression('confidence >= 0.75'),
      color: '00FF00'
    },
  ]
};

fvLayer.setVisParams(visParams);
fvLayer.setName('Buildings');

Map.setCenter(3.389, 6.492, 17);  // Lagos, Nigeria
Map.add(fvLayer);
Map.setOptions('SATELLITE');
```
Python setup

See the [Python Environment](https://developers.google.com/earth-engine/guides/python_install) page for information on the Python API and using
`geemap` for interactive development.

```python
import ee
import geemap.core as geemap
```

### Colab (Python)

```python
# Visualization of GOOGLE/Research/open-buildings/v3/polygons.
t = ee.FeatureCollection('GOOGLE/Research/open-buildings/v3/polygons')

t_065_070 = t.filter('confidence >= 0.65 && confidence < 0.7')
t_070_075 = t.filter('confidence >= 0.7 && confidence < 0.75')
t_gte_075 = t.filter('confidence >= 0.75');

m = geemap.Map()
m.set_center(3.389, 6.492, 17)
m.add_layer(t_065_070, {'color': 'FF0000'}, 'Buildings confidence [0.65; 0.7)')
m.add_layer(t_070_075, {'color': 'FFFF00'}, 'Buildings confidence [0.7; 0.75)')
m.add_layer(t_gte_075, {'color': '00FF00'}, 'Buildings confidence >= 0.75')
m
```
[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/GOOGLE/GOOGLE_Research_open-buildings_v3_polygons_FeatureView) [Open Buildings V3 Polygons](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v3_polygons) This large-scale open dataset consists of outlines of buildings derived from high-resolution 50 cm satellite imagery. It contains 1.8B building detections in Africa, Latin America, Caribbean, South Asia and Southeast Asia. The inference spanned an area of 58M km². For each building in this dataset we include the polygon describing ... GOOGLE/Research/open-buildings/v3/polygons, africa,asia,building,built-up,open-buildings,population,south-asia,southeast-asia,table 2023-05-30T00:00:00Z/2023-05-30T00:00:00Z -90 -180 90 180 Google Earth Engine https://developers.google.com/earth-engine/datasets

- [](https://doi.org/https://sites.research.google/open-buildings/)
- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v3_polygons)