Deriving canopy metrics of urban trees from airborne laser scanning data

Abstract

This study describes an automatic method for assessing various crown metrics for urban trees. We used high resolution (>20 points/m2) airborne laser scanning (ALS) data to derive four key characteristics for roadside trees at individual tree level. The tree level ALS point clouds were filtered with alpha shapes to exclude non-tree objects and measurements were taken directly from the filtered point clouds. The root mean square error (RMSE) of crown length and width, crown base height, and crown volume were 1.04 m, 0.68 m, 0.57 m, and 74.65 m3 respectively. The introduced method may be utilized in urban biomass estimations as well as monitoring the state and wellbeing of individual urban trees.