Workshops

XIII. High-resolution satellite imagery and machine learning for forest monitoring: March 28th, 2024

Time zone: CET

14:30–14:40	Welcome by EEBiomass Project office Nuno Carvalhais (Max-Planck Institute for Biogeochemistry)
14:30–14:40	Tree-level carbon stocks at continental scale Martin Brandt (University of Copenhagen)
15:05–15:30	Tracking Amazon forest dynamics Eric Bastos Gorgens (Universidade Federal dos Vales do Jequitinhonha e Mucuri) Robson Borges de Lima (Universidade do Estado do Amapá)
15:30 – 15:55	*Mapping tropical forest degradation in high resolution with deep learning (ADJOURNED)* Ricardo Dalagnol (University of California, Los Angeles, UCLA)
15:55 – 16:15	Joint Discussion
16:15 – 16:35	Open In-Depth Discussion

During the constructive discussions a few clarifications on the tree-based methods:
the comparisons with biomass products is available a supplementary part here; LIDAR is a main source for training models (Liu et al 2023; and Li et al 2023); canopy height data availability at 30m and at 3 m upon request; evaluation with ground observations ( Li et al 2023; Li et al preprint).

XII. Disturbances and ecosystem recovery : January 24th, 2024

XI. Biomass and Climate Change : November 9th, 2023

Plants on Earth play a crucial role in mitigating climate change by sequestering carbon. However, their ability to do so is evolving in response to climate change and faces threats from human activities and natural disturbances. Thus, monitoring and understanding the link between carbon sequestration (biomass) by vegetation and climate change, particularly the resilience of terrestrial ecosystems, is essential to support climate policy development and the advancement of natural climate solutions.