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

作　　者：Zhengnan Zhang Tiejun Wang Andrew K.Skidmore Fuliang Cao Guanghui She Lin Cao 

机构地区：[1]Co-Innovation Center for Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing,210037,China [2]Faculty of Geo-Information Science and Earth Observation(ITC),University of Twente,P.O.Box 217,7500 AE,Enschede,the Netherlands

出　　处：《Forest Ecosystems》2023年第1期46-55,共10页森林生态系统（英文版）

基　　金：funded by the National Key Research and Development Program(No.2017YFD0600904);the National Natural Science Foundation of China(No.31922055);the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX21_0913);the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD);funded by the China Scholarship Council(Grant No.202108320285);partially supported by the Horizon 2020 Research and Innovation Programme—European Commission‘BIOSPACE Monitoring Biodiversity from Space’project(Grant Agreement ID 834709,H2020-EU.1.1)。

摘　　要：The diameter at breast height(DBH) of trees and stands is not only a widely used plant functional trait in ecology and biodiversity but also one of the most fundamental measurements in managing forests. However, systematically measuring the DBH of individual trees over large areas using conventional ground-based approaches is labour-intensive and costly. Here, we present an improved area-based approach to estimate plot-level tree DBH from airborne Li DAR data using the relationship between tree height and DBH, which is widely available for most forest types and many individual tree species. We first determined optimal functional forms for modelling heightDBH relationships using field-measured tree height and DBH. Then we estimated plot-level mean DBH by inverting the height-DBH relationships using the tree height predicted by Li DAR. Finally, we compared the predictive performance of our approach with a classical area-based method of DBH. The results showed that our approach significantly improved the prediction accuracy of tree DBH(R^(2)=0.85–0.90, rRMSE=9.57%–11.26%)compared to the classical area-based approach(R^(2)=0.80–0.83, rRMSE=11.98%–14.97%). Our study demonstrates the potential of using height-DBH relationships to improve the estimation of the plot-level DBH from airborne Li DAR data.

关 键 词：Plant functional traits Forest inventory Height-DBH relationship LiDAR structural metrics 

分 类 号：S771.8[农业科学—森林工程]