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Environment

Watershed vs. Region Growing for Individual Tree Segmentation from Airborne LiDAR: An Urban Case Study in Bologna

Aldo Canfora, Tommaso Rondini, Matteo Falcioni, Mirko Degli Esposti

Featured August 4, 2026

Original Paper

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Simply

This study compares two computer methods to find individual trees from laser scans, then uses their size to estimate how much carbon they store and pollen they make, helping cities plan their green spaces better.

In depth
The paper presents a modular pipeline for individual tree segmentation from airborne LiDAR data, comparing watershed and region growing algorithms. It then leverages the extracted tree height and crown radius to compute preliminary carbon storage and pollen production indicators, providing a scalable framework for data-driven urban greenery planning.

Key Takeaways

  • 1
    Compares two distinct LiDAR-based algorithms, watershed and region growing, for individual tree segmentation in urban environments.
  • 2
    Reveals significant inconsistencies and outdated records in municipal Open Data, highlighting the need for LiDAR-derived ground truth.
  • 3
    Develops a modular pipeline to extract structural features and compute ecological indicators like carbon storage and pollen production for urban trees.

Conceptual Flow

HIGH LEVEL
1
Methodology: From Laser Scans to Tree Insights

The study takes laser scan data, finds individual trees using two computer methods, and then calculates important tree facts like size and pollen output.

Laser Scan Data
Process & Analyze
Tree Maps
Tree Facts
2
Results: Better Tree Data for City Planning

The new laser scan methods found many more trees and better tall trees than old city records, helping create more accurate maps for urban planning.

Old City Records
New Laser Tree Maps
Compare & Improve
Better Tree Inventory
Planning Tools