For the data analysis and classification they acquired two
30-cm WorldView-3 satellite images, orthorectified them
with a 5-m lidar DEM and then mosaicked them. The
lidar data was also used to create a canopy height model
(CHM) which they overlaid on the mosaic.
Based on existing aerial imagery, researchers first
identified relevant trees for field data collection. Using
Trimble Pro 6H GPS receivers, teams navigated to the
pre-selected trees in each AOI to capture their position,
height, diameter and species type. In total, they surveyed
515 trees, which they further processed into 338
reference samples for both training Trimble eCognition
and validating the results.
Individual tree crown segmentation based on lidar (canopy height model) and WorldView-3 imagery. The background image
displays WorldView-3 in true colors.
Mathieu Varin, CERFO's remote sensing lab manager, stands next to a
Yellow Birch with his Trimble Pro6H GPS receiver.
