What do we offer? 

MONITORING URBAN GROWTH
around SAO PAULO CITY
in BRAZIL

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This dataset contains a collection of geospatial images and data over Sao Paulo, the major city of Brazil.

OneAtlas Tiles API WMTS access

We provide the access to OneAtlas Tiles API over Sao Paulo. This is a streaming service that allows you to access to the imagery through an API. For ease of use in prototyping, we allow BasicAuth authentification to this dataset. The large satellite images are cut into tiles of 256 px by 256 px according to the XYZ format (a simpler version of the WMTS format). Each tile is provided in JPEG or PNG format and only comprised the RGB channels (i.e. the Infrared channel has been removed). A specific processing has been applied to the images to make them nice to display. Please note that this prevents scientific usage of the images but still enable machine learning usage. The native projection is GEOGRAPHIC (EPSG:4326) but for ease of display on mobile device and browsers, the images are also available in WebMercator and tiled according to the format used by GoogleMaps and many other web mapping services. For SPOT images, resolution levels are provided from L1 to L16 in GEOG and L17 in WebMercator.

Access to the OneAtlas for Innovation API documentation here.

Download SPOT images 

If you want to work with the images as they are collected by our SPOT6 and SPOT7 satellites, we also provide an optionnal download option. It is a collection of SPOT6 and SPOT7 images acquired monthly between August 2015 and June 2016. There are altogether more than 25 images piling up over the area. Images are available for download in PRIMARY format and in ORTHO format, so that you can select the format that suits you best. The data is delivered as a BUNDLE where the panchromatic band is separated from the multi-spectral bands (red, green, blue, infra-red). This means that you will work with the standard resolution of the sensor (1.5 m. for panchromatic and 6 m. for multi-spectral). The pixel depth is 12 bits and the image format is JPEG2000.

More Content

For your convinience, we have gathered below some links to more open-source geospatial content:

• Sentinel-2 images on Google Cloud Platform
• SRTM Digital Elevation Model
• Open Street Map content in GeoJSON

To complement your project, we also encourage you to check the OpenData Website of Sao Paulo

And finally, if you want to experiment with Machine Learning, you should also download our Vehicle Dataset.

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Monitoring Toulouse City
with Pléiades imagery
and OneAtlas Tiles API (R&D)

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This dataset contains a collection of geospatial images and data over Toulouse, a city in the south of France.

OneAtlas Tiles API WMTS access

We provide access to OneAtlas Tiles API over Toulouse. This is a streaming service that allows you to access to the imagery through an API. For ease of use in prototyping, we allow BasicAuth authentification to this dataset. The large satellite images are cut into tiles of 256 px by 256 px according to the XYZ format (a simpler version of the WMTS format). Each tile is provided in JPEG or PNG format and only comprised the RGB channels (i.e. the Infrared channel has been removed). A specific processing has been applied to the images to make them nice to display. Please note that this prevents scientific usage of the images but still enable machine learning usage. The native projection is GEOGRAPHIC (EPSG:4326) but for ease of display on mobile device and browsers, the images are also available in WebMercator and tiled according to the format used by GoogleMaps and many other web mapping services. For Pleiades images, resolution levels are provided from L1 to L17 in GEOG and L18 in WebMercator. 

Access to the OneAtlas for Innovation API documentation here.

Change Detection / Machine learning

You can also use WMTS tiles to monitor changes by applying change detection or machine learning techniques at the tile level. Here is a example two tiles from the same location in 2013 and in 2016. Why not try to develop a tool that detects changes based between two tiles based on machine learning?

Download Pleiades Images

On request, we can also provide access in download to 43 Pléiades images acquired over the city of Toulouse from July 2013 to April 2016. These Images are available for download in ORTHO format. The data is delivered as a PANSHARPENED mode where the panchromatic band is merged from the multi-spectral bands (red, green, blue, infra-red). The pixel depth is 8 bits and the image format is JPEG2000.

WorldDEM 12m Digital Surface Model (DSM)

The WorldDEM data is available globally from pole to pole with consistent quality and resolution. The data was acquired in the timeframe of the years 2010-2014. 

What can you accomplish by combining Pleiades optical data and elevation data? Does it provide aid for change detection, visualization or the interaction with a user?

For your convinience, we also provide in the dataset some open-source geospatial content:

• Sentinel-2 images over Toulouse on Google Cloud Platform
• SRTM Digital Elevation Model
• Open Street Map content in GeoJSON

To complement your project, you shouls also check the OpenData Website of the city of Toulouse

Finally, if you want to experiment with Machine Learning, you should also download our Vehicle Dataset

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San Francisco City Monitoring
with Pléiades imagery
and OneAtlas Tiles API

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OneAtlas Tiles API WMTS access

We provide access to OneAtlas Tiles API over San Francisco. This is a streaming service that allows you to access to the imagery through an API. For ease of use in prototyping, we allow BasicAuth authentification to this dataset. The large satellite images are cut into tiles of 256 px by 256 px according to the XYZ format (a simpler version of the WMTS format). Each tile is provided in JPEG or PNG format and only comprised the RGB channels (i.e. the Infrared channel has been removed). A specific processing has been applied to the images to make them nice to display. Please note that this prevents scientific usage of the images but still enable machine learning usage. The native projection is GEOGRAPHIC (EPSG:4326) but for ease of display on mobile device and browsers, the images are also available in WebMercator and tiled according to the format used by GoogleMaps and many other web mapping services. For Pleiades images, resolution levels are provided from L1 to L17 in GEOG and L18 in WebMercator.

Access to the OneAtlas for Innovation API documentation here.

Download Pleiades Imagery

if you want to experiment with the source imagery, we also provide access on request to download of Pleiades imagery. This dataset is composed of 4 Pléiades images providing full coverage of the whole San Francisco Bay area in 2014, 2016 and 2017. Pléiades images are 0.50m. images in 4 bands (blue, green, red and infra-red). The imagery will be delivered to you in DIMAP format with the imagery stored in JPEG2000. You can learn more on this page. 

More Content

For your convinience, you will find below some links to open-source geospatial content:

• Sentinel-2 images on Google Cloud Platform
• SRTM Digital Elevation Model
• Open Street Map content in GeoJSON

To complement your project, you shouls also check the OpenData Website of the City of San Francisco

Finally, if you want to experiment with Machine Learning, you should also download our Vehicle Dataset

    

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Rotterdam Harbor Monitoring
with OneAtlas Tiles API

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OneAtlas Tiles API WMTS access

We mostly provide access to OneAtlas Tiles API over Rotterdam Harbor. This is a streaming service that allows you to access to the imagery through an API. For ease of use in prototyping, we allow BasicAuth authentification to this dataset. The large satellite images are cut into tiles of 256 px by 256 px according to the XYZ format (a simpler version of the WMTS format). Each tile is provided in JPEG or PNG format and only comprised the RGB channels (i.e. the Infrared channel has been removed). A specific processing has been applied to the images to make them nice to display. Please note that this prevents scientific usage of the images but still enable machine learning usage. The native projection is GEOGRAPHIC (EPSG:4326) but for ease of display on mobile device and browsers, the images are also available in WebMercator and tiled according to the format used by GoogleMaps and many other web mapping services. For Pleiades images, resolution levels are provided from L1 to L17 in GEOG and L18 in WebMercator.

Access to the OneAtlas for Innovation API documentation here.

Download Pléiades and KazEOSat-2 Imagery

if you want to experiment with the source imagery, we also provide access on request to download Pleiades and KazEOSat-2 imagery. This dataset is composed of images covering the Rotterdam Harbor area. Pléiades images are 0.50m. images in 4 bands (blue, green, red and infra-red). The imagery will be delivered to you in DIMAP format with the imagery stored in JPEG2000. You can learn more on this page. 

More Content

For your convenience, we have gathered below links to more open-source geospatial content:

• Sentinel-2 images on Google Cloud Platform
• SRTM Digital Elevation Model
• Open Street Map content in GeoJSON

To complement your project, you shouls also check the OpenData Website of Rotterdam harbor

Finally, if you want to experiment with Machine Learning, you should also download our Vehicles and Ships Machine Learning Training Dataset.

    

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Paris Area Monitoring
with RADAR imagery

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This dataset was first provided in the frame of Airbus Global Earth Challenge 2017 to support usage of Earth Observation imagery in urban applications. It consists of 25 TerraSAR-X images acquired over the city of Paris. All images have been already processed and ortho-rectified.

You can find OpenData from Paris on this page: opendata.paris.fr

SAR instruments operate at any time of day and in all weather conditions, i.e. an almost certainty of collecting useable imagery. SAR satellites like TerraSAR are multi-mode and offer different permutations of spatial resolution and coverage per acquisition, and are positionally very accurate. Also, as SAR systems are ‘active’ sensors the imagery possesses a grainy, speckled appearance compared to optical data. TerraSAR data operates at the X-band frequency, and can be considered as complementary to optical imagery collected by SPOT or Pleiades. TerraSAR data can be rendered in a range of resolutions (typically in the 1-3m range) which trade off the image speckle versus feature detail.

Furthermore, SAR imagery is collected under various polarisation modes of the transmitted signal versus the backscattered returned signal, where either can be horizontally or vertically polarised. The SAR data offered here is in ‘HH’ mode - representing the horizontally polarised backscatter from an original horizontally polarised transmitted signal. The spatial resolution is 3m though the data has been resampled to 1.5m.

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Machine Learning Dataset
for Aircraft Detection

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This dataset is focused on recognition of aircrafts by machine learning. This dataset contains a database of over 600 small images of commercial planes, military aircraft and helicopters. It also contains 40 large scale SPOT images at 1.5 m. resolution to test aircraft detection algorithms on real satellite images.

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Machine Learning Dataset
for Vehicles Detection

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This dataset is focused on recognition of vehicles by machine learning. It is a preliminary dataset that contains roughly 500 tiles of Pleiades imagery in various locations on the Earth. Each tile is provided with a segmentation mask for cars, trucks and groups of cars or trucks.

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#API-01
Catalog API

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The Airbus Defense and Space Cloud Catalog API is a REST endpoint that enables to search the entire Pléiades and SPOT imagery archive. It is designed to follow the OpenSearch specification as much as possible although the results are returned as a GeoJSON file rather than an Atom or RSS feed.

All requests to the API must include an API key. This API key is provided upon request on the registration page below and full acceptance of the Terms & Conditions.

Access to the Catalog API documentation here.

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AGRICULTURE AND FORESTRY
IN THE STATE OF CALIFORNIA

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This dataset offers various Earth Observation products over the full state of California in the United States of America :

Spot, Sentinel 2, NAIP, Fieldmaps, contains over 80 SPOT images covering the entire state of California at 1.5 m. resolution (and 6 m. resolution in multi-spectral). The full dataset has been acquired almost completely between August and September 2014. This provides a very good consistency of the imagery over the whole territory. This dataset is available in two flavors: atmospheric correction (which is perfect for visualization in RGB) or raw radiometry. The lastest is ideally suited to create agricultural analytics with 4 bands (blue, green, red, infra-red) and acquisition on 12 bits providing valuable information even in the shadows of the trees for example. The images are provided in GEOG projection.

• SPOT images from Summer 2014 @1.5m. resolution
• Sentinel-2 images at 10m. resolution from 2014, 2015 and 2016
• DMC constellation images at 22m. resolutionfrom 2014, 2015 and 2016
• Access to Airbus multi-satellite catalog API to identify new acquisition
• NAIP coverage over California (to come)
• KazEOSat-2 images over some locations in California (to come)

This dataset contains over 80 SPOT images covering the entire state of California at 1.5 m. resolution (and 6 m. resolution in multi-spectral). The full dataset has been acquired almost completely between August and September 2014. This provides a very good consistency of the imagery over the whole territory. This dataset is available in two flavors: atmospheric correction (which is perfect for visualization in RGB) or raw radiometry. The lastest is ideally suited to create agricultural analytics with 4 bands (blue, green, red, infra-red) and acquisition on 12 bits providing valuable information even in the shadows of the trees for example. The images are provided in GEOG projection.
For more information about the SPOT6 and SPOT7 constellation, visit this link: https://www.intelligence-airbusds.com/

Optical imagery from the UK2 satellite, part of the Disaster Monitoring Constellation (or DMC), provides a high temporal revisit, wide swath, medium spatial resolution specification which is designed to acquire very wide area coverages (national, continental) or time series, in three spectral bands. The spatial resolution of 22m is suited for mapping scales of 1:50,000 or smaller. Imagery is acquired from vertically above (i.e. from ‘nadir’).

The DMC constellation has acquired the full state of California in 2014, 2015 and 2016. This enables to create agriculture analytics products as well as change detection services at the level of the state. Note that the 3 spectral bands (R, G, NIR) have a radiometric calibration similar to Landsat 7 enabling to use the same tools.

For more information about DMC Constellation, check this link: http://www.intelligence-airbusds.com/en/84-dmc-constellation

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URBAN MONITORING:
Change Detection Bundle

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This datasets offers 8 pairs of images over several location of the Earth and focusing on monitoring of changes in urban areas. Each location is covered by two pairs of images : one pair of Pléiades images (@0.5m.) and one pair of SPOT images (@1.5m.) at roughly one year time difference. The images are for download and they are in DIMAP format. 

 

Las Vegas (USA)

• Pléiades images from 2017-07-27 and 2016-07-22
• SPOT images from 2016-05-12 and 2015-10-24

Hong Kong (China)

• Pléiades images from 2016-01-01 and 2014-12-09
• SPOT images from 2016-11-15 and 2015-10-09

Shanghai (China)

• Pléiades images from 2017-05-27 and 2016-04-19
• SPOT images from 2017-04-23 and 2016-03-16

Toulouse (France)

• Pléiades images from 2017-04-10 and 2016-03-22
• SPOT images from 2017-04-24 and 2016-03-30

 

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OIL, GAS & MINING:
Change Detection Bundle

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This datasets offers 6 pairs of images over several location of the Earth and focusing on monitoring of changes in urban areas. Each location is covered by two pairs of images : one pair of Pléiades images (@0.5m.) and one pair of SPOT images (@1.5m.) at roughly one year time difference.

 

Rumaila near Basra (Iraq)

• Pléiades images from 2016-08-19 and 2015-05-28
• SPOT images from 2017-06-21 and 2016-04-19

Amenas (Algeria)

• Pléiades images from 2016-05-20 and 2015-08-28
• SPOT images from 2016-03-10 and 2015-08-27

Odessa (USA)

• Pléiades images from 2017-01-01 and 2015-12-08
• SPOT images from 2015-07-26 and 2013-10-20

 

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DEFENCE & SECURITY:
Change Detection Bundle

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This datasets offers 4 pairs of images over several location of the Earth and focusing on monitoring of crisis areas. Each location is covered by two pairs of images : one pair of Pléiades images (@0.5m.) and one pair of SPOT images (@1.5m.) at roughly one year time difference.

Mosul (Iraq)

• Pléiades images from 2017-02-01 and 2016-04-03
• SPOT images from 2017-05-29 and 2016-05-23

Nampo (North Korea)

• Pléiades images from 2017-09-01 and 2016-03-09
• SPOT images from 2017-04-11 and 2016-03-16

 

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PRECISION MAPPING:
Images and Videos from OPAZ

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OPAZ is a dedicated Earth Observation system for Zephyr, our High Altitude Pseudo Satellite (HAPS).

OPAZ is currently a prototype being developed. It will provide persistent surveillance over regional areas at 20cm resolution optical imagery and video. During our past flight test campaigns in Spain, over Barcelona, Catalonia (2016) and Burrueco, Andalusia (2017), OPAZ prototype took some images and video footage. 

This dataset contains prototype image and video sequences from OPAZ:

• Videos above Barcelona, Catalonia in April 2016 @18cm resolution
• OPAZ images above Burrueco, Andalusia in November 2017 @17cm resolution

This is NOT the final product which will be commercialized. The datasets are currently not geolocalised.

*OPAZ: Optical Advanced EO System for Zephyr

How would you use real time video over a city?

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