Computer Vision and AI for Environmental Monitoring, Biodiversity Analysis, and Ecosystem Restoration Call for Papers

Workshop
AI4Nature@AVSS2026
https://www.ai4nature.tech
Computer Vision and AI for Environmental Monitoring, Biodiversity Analysis, and Ecosystem Restoration


The global climate and biodiversity crises demand a paradigm shift in
how we monitor, analyze, and protect our natural world. This workshop,
AI4Nature, explores the transformative role of advanced visual and
signal-based systems in addressing these challenges. In alignment with
AVSS 2026's theme of "Expanding Horizons," we move beyond traditional
security and surveillance to focus on ecological and environmental
applications. The workshop will showcase cutting-edge research in
computer vision, deep learning, and multi-modal sensor fusion for the
automated monitoring of biodiversity (e.g., species identification,
population counting, behavioral analysis), the detection of
environmental threats (e.g., pollution, poaching, wildfire, invasive
species), and the assessment of ecosystem health. By bringing together
computer vision researchers, ecologists, and environmental scientists,
AI4Nature aims to foster interdisciplinary collaboration and chart a
roadmap for a new generation of intelligent, autonomous systems
dedicated to the sustainability and restoration of our planet's
ecosystems.

Topics

The workshop will focus on, but is not limited to, the following topics:
1. Computer Vision for Biodiversity Analysis:
- AI-driven species identification, counting, and tracking from camera
traps, baited remote underwater video systems (Bruvs), drones, and
underwater vehicles.

- Individual animal re-identification using biometrics (e.g., fur
patterns, scars, fin shapes) for population studies.
- Automated analysis of animal behavior and social interactions in the wild.

2. Multi-Modal Environmental Monitoring:
- Sensor fusion for ecological surveillance, combining video, audio
(bioacoustics), thermal, LiDAR, and eDNA data.

- Anomaly detection (and early-warning systems) for environmental
threats such as poaching, illegal logging, pollution events (e.g., oil
spills, microplastics), invasive species, and wildfire ignition.

- Multimodal foundation models for understanding complex ecosystem
dynamics, linking visual data with climatic and chemical parameters.

3. Autonomous Systems for Ecology: 
-UAV/drone-based monitoring of remote or inaccessible habitats
(forests, coastlines, marine protected areas).

- Autonomous surface and underwater vehicles for marine biodiversity
assessment and seafloor habitat mapping.

- Edge AI for real-time, in-situ analysis on robotic platforms,
enabling adaptive mission planning.

4. AI for Ecosystem Health and Restoration:
- Habitat change detection using high-resolution satellite and aerial imagery.

- Assessment of restoration interventions through automated vegetation
and geomorphological analysis.

- Digital twins of ecosystems for predictive modeling and scenario
analysis to support evidence-based conservation interventions and
policy.

This workshop is highly timely as the European Union's Green Deal,
Biodiversity Strategy 2030, and Nature Restoration Law create an
urgent demand for the scalable, accurate, and cost-effective
monitoring technologies that our community can provide

Submission https://cmt3.research.microsoft.com/AIforNATURE2026

Important dates
Paper submission deadline May 20, 2026
Notification of acceptance June 10, 2026
Camera ready deadline July 1, 2026
Workshop date August 31, 2026

Organizing Committee
Concetto Spampinato, University of Catania, Italy
Marco Milazzo, University of Palermo, Italy
Cosimo Distante, CNR, Italy
Paolo Spagnolo, CNR, Italy
Ilyes Benaissa, CNR, Italy