Tree Competition Index And Parameters Estimation Based On LiDAR Data

Airborne LiDAR has a unique advantage in obtaining individual tree height,crown width,position and other spatial information.Competition in the forest is one of the important factors that affect the growth of tree stem-shape.Researching distance-dependent competition indices will provide important theoretical support for the comprehensive utilization of the tree parameters and location information which extracted from airborne LiDAR data.Taking Qinghai spruce(Picea crassifolia)natural forest for example,based on the analysis of the growth condition of stand,we used Pearson correlation and variation partitioning analysis to explore the effect of competition on the growth of tree height-diameter ratio,to have filtered out the optimal method to select competitors and the model parameters of distance-weighted size ratio index model,which are suitable for airborne LiDAR data characteristics.Then,used the individual tree height and position information extracted from airborne LiDAR data to calculate the competition index.The correlation analysis and the method of establishment of tree height curve model with competition index to invert DBH were carried out to verify the validity of the competitive index.Results are list that:1)The natural forest of Qinghai spruce(Picea crassifolia)in the study area has a relatively stable composition and spatial structure,which is the top community in healthy development,and has a certain regional representation.2)The distance-weighted size ratio competition index is significantly correlated with the height-diameter ratio,can effectively reflect the competitive pressure of the forest,and its model is suitable for the characteristics of the airborne LiDAR data.When the vertical search cone method was used to determine competitors and the sum tree heights of subject tree and competitors used as the distance parameter,the result will be better.Selecting tree height as the size ratio parameter will have more ecological significance.3)Based on small footprint Airborne LiDAR data it is possible to extract the high precision individual tree height and position information.The competition index obtained on the basis of these information has a strong correlation with the competition index of the measured data,and can reflect the influence of competitive pressure on the variation of stem taper growth.It can improve the accuracy of inversion DBH effectively by introducing the competition index into the tree height curve model.According to the analysis above,we can speculate that for the stand in the study area,based on airborne LiDAR data,we can obtain the effective distance-weighted size ratio index,which can be used to assist in improving the accuracy of DBH,volume or biomass inverted from airborne LiDAR data.These studies will provide an important basis for further study of forest growth model based on airborne LiDAR,and have important implications for the effective application of airborne LiDAR in forest investigation and monitoring,as well as the scientific management and protection of Picea crassifolia natural forest in Qilian Mountains.