ABiLAS
Recipient: Ústav výzkumu globální změny AV ČR, v. v. i.
Keywords: xxx
Annotation of project:
Airborne laser scanning (ALS) provides detailed information on the structure of forest ecosystems, enabling effective monitoring of above-ground biomass (AGB). Modern ALS data processing methods combine analytical approaches from remote sensing (RS) and machine learning (ML), allowing for more accurate AGB estimations. The automation of this approach and its implementation into a web-based environment will lead to the expansion of the EnviLAB platform with a new module ABiLAS for processing ALS data using ML methods. This module will include a database of synthetic data for training ML algorithms and a user interface for uploading and analyzing custom ALS data. The outputs will be available to both experts and the general public, contributing to the effective monitoring of forest ecosystems and adaptation to climate change.




