Using advanced object detection and instance segmentation algorithms, our AI service can accurately identify and count individual trees in aerial or ground imagery. The system supports multiple counting methods—such as ROI-based, zone-based, and line- crossing counting—to adapt to varying environments like orchards, forests, or reforested zones. By integrating shape and size filters, the algorithm distinguishes between trees and other vegetation.

• • Forest inventory
• • Plantation monitoring
• • Yield forecasting in orchards

Using panoptic segmentation and AI-driven depth cues, we estimate tree trunk diameter at breast height (DBH) from images, even when only partial tree views are available. This is particularly useful in managed forests and orchards where trunk diameter correlates with tree age, health, and commercial value. Automated DBH estimation streamlines forest inventories and reduces human error.

• • Forest management
• • Ecosystem modeling
• • Logging industry logistics planning