BFIT - Multisource Feature Extraction for Biomass and Forest Inventory Toolbox

Supporting the needs of the primary government of Canada organization on the project, namely the Canadian Forest Service.

Detecting and graphically displaying underlying trends and discussion topics that are of interest to the analyst

Beneficial to anyone who is interested in searching or researching documents for specific discussion topics

Multisource Feature Extraction for Biomass and Forest Inventory Toolbox

The objective of the project was to develop tools for processing and analysis of above-ground biomass and related forest variables from multiple EO sources. The new tools were developed in the open source RADARSAT-2 Toolbox to be used by Government of Canada (GoC) researchers to study biomass and forestry applications.

The project looked at the relationships between the water cloud model, random volume over ground model, polarimetric classifications and biomass estimations from SAR data, as well as vegetation indices and biomass estimation from optical data. Biomass was estimated based on allometric equations and regression models. The project implemented methods of co-registering and fusing information derived from various SAR and optical missions including RADARSAT-2, SENTINEL-1, ENVISAT, TerraSAR-X, ALOS and Landsat.

The planned work will make use of the existing processing and visualization framework and the existing tools for calibration, coregistration, orthorectification, interferometry and polarimetry within the RADARSAT-2 Toolbox.