An improved area-based approach for estimating plot-level tree DBH from airborne LiDAR data

The diameter at breast height (DBH) of trees and stands is not only a widely used plant functional trait in ecology biodiversity but also one the most fundamental measurements managing forests. However, systematically measuring DBH individual over large areas using conventional ground-based approaches labour-intensive costly. Here, we present an improved area-based approach to estimate plot-level tree from airborne LiDAR data relationship between DBH, which available for forest types many species. We first determined optimal forms modelling height-DBH relationships field-measured DBH. Then estimated mean by inverting predicted LiDAR. Finally, compared predictive performance our with classical method results showed that significantly prediction accuracy (R2 ​= ​0.85–0.90, rRMSE ​9.57%–11.26%) ​0.80–0.83, ​11.98%–14.97%). Our study demonstrates potential improve estimation data.