Value-Adding Products and Algorithms for Land Surfaces


THEIA, the land surface data and services hub of IR Data Terra, facilitates access to environmental data and federates scientific expertise on a national scale around five major themes: cryosphere, continental waters, land cover, agrosystems & biodiversity and imagery & radiometry.

4 objectives:

  1. Developing and promoting the use of in situ, aerial and space data by all communities (scientists, academics and public players) for continental surfaces;
  2. Developing value-added products and innovative processing services, distributing them in accordance with FAIR principles and promoting them;
  3. Leading and federating a network of players (scientists, public players, private players) involved in monitoring and managing environmental issues on a local and global scale;
  4. Participating in the scientific, methodological and technical training of communities.

3 key elements:

>> distributed processing capabilities at mainland France level, structured into four (Observation) Data and Services Centres – Toulouse, Montpellier, Strasbourg and Grenoble -, offering access to a wide range of data, products and services;

>> five Scientific Expertise Centres, networking laboratories in order to develop and propose innovative methods, and produce products and services based on in situ aerial and space data;

>> a Thematic Regional Network, bringing together all data users on a regional basis: scientists and users from the public and private sectors.


Using satellite imagery to establish a link between the environment, the habitats that are favourable to these species, and the human and animal populations at risk

Annelise TRAN, CIRAD researcher and THEIA Risks associated with Infectious Diseases SEC, shares her vision of Theia consortium, its achievements as well as the challenges ahead.

clASpy_T : a 3D point cloud classification tool for estuary monitoring

The THEIA portfolio of Lidar data processing tools has been extended with a new software tool for creating 3D point cloud classification models using machine learning: cLASpy_T cLASpy_T aims to […]

A new GeoDEV website, with resources tailored to your profile

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