IA 5.3. Advanced vegetation characterization based on Earth Observation data fusion and Artificial Intelligence over forestland ecosystems

OVERVIEW

Status

100%

What kind of result is this?	New methodologies based on remote sensing datasets to check evolution of key forestland metrics and phenological parameters.
What’s the area addressed?	Advanced Technology Solutions Landscape management
What’s the covered phase?	Restoration & Adaptation Recovery and rehabilitation
What’s the addressed challenge?	How to measure in a feasible and viable way as well as high latency the changes and evolution of key post-fire metrics?
What value is proposed?	A pilot of forestland fuel mapping, its changes (e.g. soil moisture, vegetation water) and tendencies, monitor post-fire vegetation recovery (e.g. geospatial wildfire contours, fire severity) will be implemented through data fusion of EO multi and hyperspectral datasets, LiDAR data and machine learning approaches
Who can use it?	Policymakers and researchers involved in forestland policies, recovery and management
What type of tool is it?	Geoinformation Layers to an API to consul as geoservice
How does it look like?	Shapes, raster files and CSV datasets
This tool is…	⊠ a new tool	☐ an improved tool
What are the vision & mission statement?	To generate and “automatic” flux and anomalies detection based on A.I. architectures to suit the API and associated geoservice
Technology Readiness Level (TRL)	8
Documentation	D5.4 Modelling of fire combustion and convective processes
This IA is implemented in the Living Lab(s)…	Catalonia