The IT4forest team uses digital tools and develops innovative algorithms for analysing the forest environment, extracting features of forest stand structure and even measuring the shape of individual trees. We apply remote sensing multispectral time series analysis and LIDAR point cloud analysis in combination with neural networks and machine learning algorithms to detect and monitor environmental changes and forest health.
Forest It Methods
Methods - most used
- Multispectral change detection methods to analyse land cover change
- Phenology and time series analysis of vegetated surfaces and for forest health
- Neuronal networks and AI methods for automatic image processing and classification
- 3D image segmentation algorithm for object extraction
- LiDAR data analytics and modelling for measuring forest characteristics including stand height, biomass distribution, volume.