Global LCVM: EO Data integration for global land cover and vegetation mapping

GlobalLCVM is advancing the future of global land use monitoring by combining the power of Artificial Intelligence (AI) with remote sensing expertise and multi-mission Earth Observation (EO) data. ​

Our mission: to deliver accurate, scalable insights into land cover and vegetation, especially in forests, wetlands, and croplands around the globe.​

Why It Matters: Effective land cover mapping is crucial for:​

  • Natural resource management​
  • Biodiversity conservation​
  • Climate change adaptation​

Yet mapping Earth’s surface remains a challenge. The complexity and variability of EO data demand innovative methods that can bridge technical and scientific domains.​

Our Integrated Approach: In partnership with Inria, GlobalLCVM takes a holistic, AI-driven approach rooted in:​

  • Advanced machine learning and AI techniques​
  • Deep knowledge of remote sensing science​
  • Cross-mission data fusion from EO satellites​

This synergy enables us to build robust, adaptive mapping frameworks designed to meet the demands of upcoming ESA Synthetic Aperture Radar (SAR) missions and beyond.​

GlobalLCVM Objectives

Design synergistic multi-mission AI-
data driven frameworks for land
cover and vegetation mapping.

Address challenges in applications of
SAR and INSAR to better understand
the behavior of a diverse set of land
cover classes.

Advance user readiness for ROSE-L
and next-generation Sentinel-1 SAR
missions.

GlobalLCVM Proposed Study Areas

GlobalLCVM Project Partners

GlobalLCVM Project Progress

Engagement & Collaboration Opportunities

Collaborate With Us​

Whether you’re in research, environmentalpolicy, or EO technology, GlobalLCVM isopen to collaboration. Join us in pushing theboundaries of AI + EO for a moresustainable and informed planet.​

Upcoming Events:​

  • EGU General Assembly 2026, May 2026​
  • ISPRS and CSRS 2026, July 2026​

Past events:​

  • ESA Living Planet Symposium 2025, June 2025
  • IEEE-GRSS International School on Advanced SAR Remote Sensing, QC, Canada, September 2025​​


​

Dr. Masoud Mahdianpari
Project PI,​
masoud.mahdianpari@c-core.ca​