Study On The Crown Asymmetry Index For Eucalyptus Pilularis Plantation

Over the past 50 years,crown asymmetry of forest trees has been evaluated through several indices constructed from the perspective of projected crown shape or displacement often on an ad hoc basis to address specific objectives.Although sharing some similarities,these indices are largely incoherent and noncomparable as they differ not only in the scale but also in the direction of their values in indicating the degree of crown asymmetry.The data for this work came from a long-term E.pilularis correlated curve trend(CCT)experiment located in Bulls Ground State Forest,near Kew,on the mid north coast of New South Wales,Australia.Five existing crown asymmetry indices(CAls),eight new CAIs were adapted from measures of circularity for digital images in computer graphics,indices of income inequality in economics,and a bilateral symmetry indicator in plant leaf morphology.As the first attempt at devising normative measures of crown asymmetry,this study adopted a relative scale between 0 for perfect symmetry and 1 for extreme asymmetry.After necessary modifications,all CAIs are included in the scale range of[0,1].The performances of the 13 CAIs were compared over different numbers of measured crown radii for 30 projected crowns of mature Eucalyptus pilularis trees through benchmarking statistics and rank order correlation analysis.The results show that the index(CAI13)adapted from the simple bilateral measure proved to be the least biased and most precise.Its performance was closely followed by that of three other CAIs(CAI4?CAI8.CAI10).It came as no surprise that CAI4 was the best performer in the group of existing CAIs.CAI4 has an added advantage over CAI13 in indicating not only the degree but also the direction of crown asymmetry.Its added advantage would be particularly useful if CAI4 were used for evaluating the risk of treefalls,examining neighbourhood competition among individual trees,and-.depicting spatial canopy and stand dynamics.CAI8 was the best performer in the group of measures of circularity for digital images in computer graphics.CAI10 was the best performer in the group of indices of income inequality in economics.No matter which CAI is chosen in a research or management application,the minimum number of crown radii that is needed to provide at least an indicative measure of crown asymmetry is four.For more accurate and consistent measures,at least 6 or 8 crown radii are needed in the CAI calculations.At the same time,the range of variability in crown morphology of the trees also needs to be taken into consideration.Although the CAIs are based on projected crown radii,they can be readily extended to individual tree crown metrics commonly extracted from LiDAR and remote sensing data.The addition of a normative measure of crown asymmetry to individual crown metrics will facilitate the process of big data analytics and artificial intelligence in forestry where crown morphology is among the factors to be considered for decision making in forest management.