Open Earth Monitor — Global Workshop 2024

Global Trait-Based Vegetation Monitoring: Leveraging Multispectral Imagery for Restoration Project Assessment

Restoration projects are crucial for ecosystem recovery and biodiversity conservation, but their large-scale monitoring poses significant challenges. Conventional approaches often rely on intensive manual work, incur high costs and need help with standardisation, making monitoring on a global scale impossible. Public satellite missions such as Sentinel-2 have great potential to transform ecosystem monitoring due to their high spatial and temporal resolution when linked directly to ecosystem characteristics. Here, we present several global, high-resolution (20m) maps of vegetation traits derived from Sentinel-2 multispectral imagery, reflecting the mean trait value during the vegetation period at annual intervals from 2019 onwards. Using a hybrid inversion approach of the physically-based radiative transfer model PROSAIL, we estimate leaf functional traits (e.g. chlorophyll content, equivalent water thickness, or leaf mass per area) and canopy structural traits (e.g. leaf area index). Validation using in-situ data suggests that the trait maps can effectively track local temporal changes. Further, we show how the generated trait maps can map functional trait diversity at a coarser resolution. Altogether, these products provide deeper insights into ecosystem health, biodiversity status and restoration efforts.