The Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE) is a public research establishment bringing together a working community of 12,000 people, with more than 200 research units and 42 experimental units located throughout France. INRAE is one of the world’s leading institutions in agricultural and food sciences, plant sciences and animal sciences. Its research aims to develop solutions for multi-performance agriculture, high-quality food and sustainable management of resources and ecosystems. Its research aims to develop solutions oriented to improve life, humans, and the Earth that uncovers our most pressing concerns
Mission
You will be based at the UMR TETIS (Territoires, Environnement, Télédétection et Information
Spatiale) in Montpellier, South of France. The lab is part of the “Maison de la Télédétection”, the
Integrated Unit TETIS has access to heavy computing resources (storage, high-performance computing) and software used for research and building capacity and teaching activities (GIS, image processing, statistics, etc.). TETIS also produces and/or contributes to numerous IT developments of various kinds and sizes: modelling platforms (generic spatial modelling, radiative transfer models, etc.), data mining applications, multi-sensor image processing chains, GIS plugins, data distribution portals, observatories.
Background
Maintaining and improving the integrity and biodiversity of natural ecosystems is vital
for achieving the EU biodiversity strategy for 2030, Sustainable Development Goals (SDGs), and
Kunming-Montreal Global Biodiversity Framework. Monitoring progress towards the achievement of the global biodiversity targets requires further development of the adopted monitoring framework
and the operationalization of indicators from global to regional level. Biodiversity indicators allow for consistent monitoring of the state of biodiversity, evaluation of the condition of the ecosystems, the services they provide and the drivers of change. The Group on EO Biodiversity Observation Network (GEO BON) has developed a framework for an integrated biodiversity monitoring system under the general concept of Essential Biodiversity Variables (EBVs), and remote sensing (RS) has been proposed as a flagship tool to monitor biodiversity through RS-based EBVs. Within this framework, we work with CNES, France (Centre National d’Etudes Spatiales), on a joint Flagship Action of biodiversity and vulnerable ecosystems to advance Earth System Science and its responses to the global challenges on biodiversity monitoring.
Within this context, a demonstrator focusing on the mapping of forest ecosystems and the biodiversity of Costa Rican forests was set up during the first phase of the project, using data from the Sentinel-2 satellites and spectral diversity mapping methods. This demonstrator, developed as part of the CODEX research project and funded by the TOSCA Programme (CNES), is based on a cloud infrastructure that enables large volumes of data to be accessed, managed and analysed.
The second phase of the project involves deploying this type of approach over a wider range of
territories covered by tropical forest ecosystems, notably French Guiana. The context of these areas, in particular the high level of cloud cover, as well as the remarkable levels of diversity, mean that we need to rely on a wider range of sensors, such as radar and hyperspectral imagery, to take better account of this context.
For more information:
- https://ceos.org/news/tropical-forests-costa-rica/
- biodivMapR: an R package for a- and ß-diversity mapping using remotely-sensed images • biodivMapR
Job Summary
Against a backdrop of rapidly evolving digital technologies, particularly in terms of how
geospatial data can be accessed and processed on a large scale, you will be involved in the
development cycle for the methods and software tools designed as part of the CODEX research project.
Opportunity to work on strategic remote sensing projects. A stimulating environment with access to
state-of-the-art data and infrastructure.
You will support researchers and engineers in continuing to develop the demonstrator aimed at
manipulating Earth observation data from various satellite sensors in the context of monitoring
tropical forest ecosystems: multispectral and hyperspectral optics, radar and derived products. You
will work closely with the scientists to develop the thematic part and linked to the specificities of
integrated imagery, and in liaison with the infrastructure architects to deploy the demonstrator. You
will work as part of a team (research, engineering) and contribute to scientific production through the technical aspect, as well as being involved in it (publications, reports, etc.).
Desired Knowledge & Skills:
- Implement multi-source data fusion methods (optical, RADAR….)
- Optimize processing pipelines to improve the accuracy and speed of analyses.
- Collaborate with experts in remote sensing, artificial intelligence, and computer
science to develop innovative solutions. - Strong expertise in signal processing and signal physics in remote sensing.
- Solid understanding of SAR analysis techniques, including interferometry and
polarimetry, is highly valued. - Strong command of programming languages used in data science, particularly Python
and R, along with key libraries (NumPy, Pandas, etc.). Knowledge of other languages
is a plus. - Experience with geospatial libraries (GDAL/OGR, OTB, GeoPandas, PySTAC, xarray,
etc.) and machine learning libraries (Scikit-Learn, Keras/TensorFlow, PyTorch, etc.) is
appreciated.
Specific conditions of activity:
- You will be based at the Integrated Unit TETIS (Territoires, Environnement, Télédétection et
Information Spatiale) INRAE, based at the Maison de la télédétection in Montpellier, France.
Recommended training required:
You have a Master’s degree, a PhD, an engineering degree or equivalent in remote
sensing, image or signal processing or data science, or can demonstrate significant
experience in these fields.
- You are keen to learn about an open-source software ecosystem based on standards
and an international geospatial community. - You are a team player with good interpersonal skills.
- You have initiative and autonomy.
- Proficiency in python Experience with OLAP software, knowledge of MDX syntax,
experience with Xarray tools. - Experience with remote sensing data processing software (e.g. GDAL, RasterIO, etc)
and specifications (e.g. STAC) - Familiarity with biodiversity concepts and ecological research methods will be much
appreciated but not mandatory - Excellent analytical, problem-solving, and communication skills
Details
- Location: UMR TETIS Montpellier, South of France
- Contract type: full time temporary position 12 months, as INRAE (salary according to
experience). (aprox. Brut (incl. benefits) 2 400 € - 3 400 € EUR/month) - Expected start date: July 2025
Application
- Before April 30th 2025
- Send CV and cover letter to Sandra LUQUE (sandra.luque [at] inrae [dot] fr) via mail under the subject “Position CODEX”