Postdoctoral position OT-21943

Postdoctoral: Produce and interpret high-resolution maps of cover types after deforestation in Africa

33140 VILLENAVE-D'ORNON

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INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

- You will be welcomed in the unit ISPA Unit at INRAE Bordeaux site (Villenave d'Ornon) within the Remote Sensing Lab. The Soil-Plant-Atmosphere Interactions Joint Research Unit (ISPA), with around 100 permanent and non-permanent staff, is concerned with understanding and modeling material and energy flows and cycles in anthropized, agricultural and forest ecosystems. Our work aims to assess the sustainability of agroecosystems and forest ecosystems in a changing environment under climatic and anthropogenic constraints, in order to guarantee sustainable plant production in terms of quantity and quality, and preserve the environment. UMR ISPA is a joint INRAE and Bordeaux Sciences Agro research unit. The unit is based at the INRA Bordeaux-Aquitaine research center. It is under the supervision of the Agroecosystems department (AGROECOSYSTEM) and the Ecology and Biodiversity department (ECODIV).

- You will be in charge of:

Context:

The One Forest Vision Initiative is a new research programme between African countries and France launched in 2023 with a duration of five years, aiming to monitor changes of central african rainforests for height, biomass and diversity, in order to better understand the impacts of climate change and anthropogenic pressure on these diverse and important ecosystems, and provide science-based knowledge to protect and restore forests in the region. 

The development of satellite imagery and LiDAR, combined with recent progress in AI, are disrupting the way forests are being monitored. While forests are in particular essential for carbon sequestration and biodiversity, they are profoundly affected by climate change, degradation and deforestation. Accurate and granular forest maps are essential for forest managers and public institutions in order to adapt management practices and policies.

The Research Pillar 3 of the One Forest Vision Programme has assembled an international team of established researchers in machine learning, remote sensing, forest ecology (Paris Laboratoire des Sciences du Climat et de l’Environnement, INRAE, IRD, CNRS and CIRAD) in order to produce accurate and periodically updated maps of forest structure (height), biomass carbon stocks, and activity data related to forest loss and gains (disturbances, including degradation, fires, clearcut) using cutting edge artificial intelligence models driven by satellite and new field observations collected by the GEOTREES project in collaboration with Dr. J. Chave from CNRS. 

The INRAE-Bordeaux team is looking for an experienced and motivated Research Scientist who will actively contribute to the production, validation, interpretation and publication of forest maps, with a focus on producing the best possible maps of the cover types after deforestation events.

Missions:

  • Implement tools to incorporate input data sources from multiple spaceborne and airborne platforms as input or validation to AI models (ENVISAT ASAR, Sentinel-1, Palsar-1&2, Nisar, Icesat 2, orthophotos, airborne LiDAR) to map cover types after deforestation events. After deforestation, the areas can be left as they are, allowing the forest to regrow and lead to secondary forests, or they can be used for agricultural or pastoral activities. The mission will analyze what happens after deforestation and map the vegetation types, including trying to differentiate between crop types if agriculture is established after deforestation.
  • Implement a variety of methods to analyze phenology based on the seasonal variations of the optical/microwave vegetation indices, to differentiate between the different cover types and crop types, secondary forests, prairies, permanent crops (sugarcane, soybean, corn, etc.).
  • The missions will cover  data processing , model design, training, inference, interpretation of  results and publication in peer-reviewed journals:
  • Apply and improve existing deep-learning models of forest attributes.
  • Access and process satellite imagery and LiDAR using  community  tools developed by the lab (e.g., Sentinel 1 and 2, Gedi, LiDAR HD, Spot).
  • Interact with data-scientists from Kayrros, a SME based in Paris who will help for running the models at large scale over the full central African biome.
  • Promote and diffuse the results of research results at scientific conferences, workshops organized with African countries as part of the One Forest Vision Initiative, and write research publications in collaboration with national and international experts. Several publications in high-profile journals are expected from the project.

Main supervisor: Frédéric Frappart. Research director at INRAE

Co-supervisors: P. Ciais (LSCE) J-P Wigneron (INRAE), Marc Peaucelle (INRAE)

References:

Schwartz, Martin, et al. "FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and Global Ecosystem Dynamics Investigation (GEDI) data with a deep learning approach." Earth System Science Data 15.11 (2023): 4927-4945.

Height maps with vision transformers in Ghana:

Fayad, Ibrahim, et al. "Vision Transformers, a new approach for high-resolution and large-scale mapping of canopy heights." arXiv preprint arXiv:2304.11487 (2023).

GEDI: https://gedi.umd.edu

S1/S2 satellite imagery: https://sentinels.copernicus.eu/web/sentinel/home

LiDAR HD: https://geoservices.ign.fr/lidarhd

Degradation and deforestation tool:

Ygorra, B., Frappart, F., Wigneron, J. P., Moisy, C., Catry, T., Baup, F., ... & Riazanoff, S. (2021). Monitoring loss of tropical forest cover from Sentinel-1 time-series: A CuSum-based approach. International journal of applied earth observation and geoinformation, 103, 102532.

 

Ygorra, B., Frappart, F., Wigneron, J. P., Moisy, C., Catry, T.,, ... & Riazanoff, S.  (2023). ReCuSum: A polyvalent method to monitor tropical forest disturbances. ISPRS Journal of Photogrammetry and Remote Sensing, 203, 358-372.

Training and skills

PhD

- Recommended training:

  • You have a PhD in Remote Sensing / Forest monitoring / Machine Learning / Computer Science.

- Knowledge required:

  • You have experience in building and using ML models in the context of EO-based monitoring of forests and / or land surface properties.
  • You have experience in remote sensing.
  • You have a publication track record and ability to present scientific results to the scientific community, as well as to a diverse range of stakeholders and public audience.

- Appreciated experience:

  • You have a PhD

- Skills sought:

  • You like problem solving, you are autonomous, but want to work in a collaborative environment.
  • You are able to lead and structure research  projects.
  • You are curious, enjoy learning and a research environment.
  • You want to work on problems that can benefit the environment.

 

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
parenting support: CESU childcare, leisure services;
- skills development systems: trainingcareer advise;
social support: advice and listening, social assistance and loans;
holiday and leisure services: holiday vouchers, accommodation at preferential rates;
sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter

Offer reference

  • Contract: Postdoctoral position
  • Duration: 24 months
  • Beginning: 01/06/2024
  • Remuneration: Gross salary from 2 668,15 to 3 367,18 €
  • Reference: OT-21943
  • Deadline: 29/05/2024

Contact

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