Environmental Computational Science and Earth Observation Laboratory (ECEO)

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Devis Tuia Min

Prof. Devis Tuia

Environmental Computational Science and Earth Observation (ECEO)

Remote Sensing, Machine learning


Our mission

At ECEO we develop technology to monitor Earth with digital data. We use data from multiple sources (from the smartphone to the satellite) and develop algorithms enabling spatio temporal monitoring of our changing Earth. We study land processes, underwater ecosystems and ecosystems dynamics, for instance related to animal conservation and forest monitoring.

Research topics

1

Develop AI algorithms to make sense of digital data about Earth

2

Monitor endangered ecosystems like coral reefs or tropical forests

3

Map distirbution of species (animals and vegetal) and how they distribute in space and time, especially under climate change

Our key projects


Untitled Design (18)

WildAI

We study behavior of alpine wildlife by analysing automatically a set of videos acquired by camera traps installed in the Swiss National Park.


Swiss National Park

2

Coral reef monitoring in the Red Sea

We develop machine learning technology to map coral reefs with close sensing, support local monitoring programs and build capacity in the Red Sea Nations with dedicated workshops


  • Transnational Red Sea Center (EPFL)
  • Univeristé de Djibouti
  • Red Sea University
Untitled Design (17)

DVPS

With an international consortium, we explore new avenues to develop large scale multisource AI models capable of solving multiple problems at once, the so-called multimodal foundation models.


  • PI School
  • University of Oxford
  • Cambridge
  • ETH

Our results and highlights

1

Completion of coral monitoring mission in Makassar, Indonesia (2025). Release of Swiss scale treeline map.

2

D. Tuia, Clarivate highly cited researcher 2025

3

DVPS, Horizon Europe

Team & talents

Lab team size

17 people

Skills developed by the scientific team

Machine learning algorithms for understanding environmental processes
Low cost monitoring systems based on camera traps (Mammalps project with Swiss National Park), GoPro cameras (coral reefs monitoring) and fixed wings drones (WildDrone project, tested in Kenya and Namibia in 2025)

Regional and social impacts

1

We provide reproducible algorithms and scientific evidence at large scale of the evolution of several critical ecosystems of Earth

2

We collaborate with seveal services of the Canton (Géoinformation, Forets, Agriculture) to support them in their monitoring efforts, in particular to scale them up and automatize

3

Through collaborations with industry (Swisstopo, AXA), we develop technology critical to make their data analysis routiens more efficient and accurate

4

We train the next generation of environmental engineers in data proficiency, and prepare them to the future challenges of process monitoring, which are strongly influenced by big data problems and complex, multi-modal streams

Perspectives and challenges

Main opportunities

  • Democratization of AI is a great opportunity to spread wider our technology
  • Great interest in Valais for AI technology helps us connecting with several key regional players

Future Partnerships

  • Expanding our coral technology in other reefs of the world, towards a citizen-led monitoring system
  • Extending our blue ice mapping technology to other problematics related to polar dynamics

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