Open Access Data

We are committed to providing high quality data to innovative users through some of Europe’s leading remote sensing open data prgrammes.

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Open Data For a better world

Copernicus Data Warehouse

ESA
Earthnet Programme

Green Deal Promotion
By European Space Imaging

Since our inception in 2002, WorldView data provided by European Space Imaging has played a key role  in open data access programmes with far-reaching applications in:

  • Emergency Services
  • Environmental Initiatives
  • Climate Change
  • Maritime Surveillance
  • Border Security
  • Land Use

We believe in the power of Very High Resolution (VHR) satellite imagery to create a safer, cleaner and more productive world.

For more information about WorldView satellite imagery and open data access, please contact us at opendata@euspaceimaging.com 

Want To Try out our data?

Download sample imagery to see how it fits into your workflow.

Copernicus Data Warehouse

Copernicus is the European Union’s Earth Observation Programme, looking at our planet and its environment for the ultimate benefit of all European citizens. It offers information services based on satellite Earth Observation and in situ (non-space) data. In addition to its own Sentinel constellation, Copernicus offers access to data from third-party satellite operators, known as Copernicus Contributing Missions (CCMs).

Copernicus collects and stores the massive amounts of data collected from both satellites and ground based sensors for a wide range of products and services.  However, as a European Union public service, this data is also available to eligible members of the public for free. View the Data Portfolio for more information.

 

Sentinel Satellite Imagery

Nearly everyone can access Sentinel satellite data through the Copernicus Open Access Hub.

 

Core Data Sets

These are large, pre-defined data sets, covering the needs of the Copernicus services and other Earth Observation activities. Core data sets include WorldView VHR multispectral imagery. Access is granted to users within the following categories:

  • European Union Institutions– Agencies, bodies and contractors defined in EU Treaties
  • EU Member State Public Authorities– Any person, institution or contractor having public or administrative duties; Public research and academic organisations
  • Union Research Projects– Participants in a research project financed under the Union research programmes
  • International NGOs– Any person or institution (government or non-government) that is registered with the UN and involved in humanitarian or environmental activities

For complete information on eligible user categories, please see the User Categories page.

 

ADDitional Data Sets

This is a flexible offering that includes new collections and satellite tasking. This data is made available on a “per project” basis as well as to eligible Horizon 2020 applicants.

Users wishing to access contributing mission data should register to the Coordinated Data Access System (CDS). Once your registration is approved, you will gain access to a personal portal for ordering and subscribing to data sets.

 

How to Register – Data Access Guide

Overview of Available Data – Data Portfolio

ESA Earthnet Programme

In addition to providing users with data from its own Earth observing satellites, the European Space Agency (ESA) uses its multi-mission ground systems to process, archive and distribute data from other satellites – so called Third Party Missions. Very High Resolution (VHR) imagery from the WorldView Constellation can be accessed by researchers and developers for non-commercial applications.

 

Academics, scientists, researchers and qualifying start-ups are eligible to access data from ESA Third Party Missions for non-commercial use.

 

Hopeful users should apply to the ESA portal and submit a project proposal. A response typically takes less than 2 weeks.

Green Deal Promotion
By European Space Imaging

The European Commission has taken a bold stance in building framework for carbon neutrality by 2050 with ambitious benchmarks by the year 2030. European Space Imaging wants to be a part of the solution by helping start-ups, small businesses and researchers realize their innovative ideas.

 

European Space Imaging has access to billions of square km of VHR imagery dating back to 1999. For this promotion, a subset of data covering Europe and it’s surrounding regions will be made available to eligible applicants.

Successful applicants could receive up to 200 square km of imagery from this data set.

A shapefile containing the available AOIs for this promotion can be downloaded here.

Research oriented institutions and small companies in a European Union member state who are working towards solutions that contribute to carbon neutrality goals are eligible to apply for the data.

If you are in the EU and have a project related to helping the environment, we want to hear from you.

 

Hopeful users should apply here and submit a project proposal. A response typically takes less than 2 weeks.

Are you in research or Education?

Find out how you can get up to 80% discount on VHR imagery for any project.

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Architecture of ResNet34-UNet model

UNet architecture for semantic segmentation with ResNet34 as encoder or feature extraction part. ResNet34 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of VGG16-UNet model

UNet architecture for semantic segmentation with VGG16 as the encoder or feature extractor. VGG16 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of ResNet34-FCN model

In this model, ResNet34 is used for feature extraction and the FCN operation remains as is. The feature of ResNet architecture is exploited where just like VGG, as the number of filters double, the feature map size gets halved. This gives a similarity to VGG and ResNet architecture while supporting deeper architecture and addressing the issue of vanishing gradients while also being faster. The fully connected layer at the output of ResNet34 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

Architecture of VGG16-FCN model

In this model, VGG16 is used for feature extraction which also performs the function of an encoder. The fully connected layer of the VGG16 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

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