Development of a System of Compatible Individual Tree Diameter and Aboveground Biomass Prediction Models Using Error-In-Variable Regression and Airborne LiDAR Data

• Published in: Remote sensing (Basel, Switzerland) Vol. 10; no. 2; p. 325
• Main Authors: Fu, Liyong, Liu, Qingwang, Sun, Hua, Wang, Qiuyan, Li, Zengyuan, Chen, Erxue, Pang, Yong, Song, Xinyu, Wang, Guangxing
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2018
• Subjects: Airborne sensing; Biomass; Compatibility; Data processing; Estimation; Lidar; Mathematical models; Modelling; Parameter estimation; Prediction models; Regression analysis; Statistical methods; Trees; Uncertainty analysis

Estimating individual tree diameters at breast height (DBH) from delineated crowns and tree heights on the basis of airborne light detection and ranging (LiDAR) data provides a good opportunity for large-scale forest inventory. Generally, ground-based measurements are more accurate, but LiDAR data a...