Comparing Johnson’s SB and Weibull Functions to Model the Diameter Distribution of Forest Plantations through ALS Data

Abstract

The analysis of the diameter distribution is important for forest management since the knowledge of tree density and growing stock by diameter classes is essential to define management plans and to support operational decisions. The modeling of diameter distributions from airborne laser scanning (ALS) data has been performed through the two-parameter Weibull probability density function (PDF), but the more flexible PDF Johnson’s SB has never been tested for this purpose until now. This study evaluated the performance of the Johnson’s SB to predict the diameter distributions based on ALS data from two of the most common forest plantations in the northwest of the Iberian Peninsula (Eucalyptus globulus Labill. and Pinus radiata D. Don). The Weibull PDF was taken as a benchmark for the diameter distributions prediction and both PDFs were fitted with ALS data. The results show that the SB presented a comparable performance to the Weibull for both forest types. The SB presented a slightly better performance for the E. globulus, while the Weibull PDF had a small advantage when applied to the P. radiata data. The Johnson’s SB PDF is more flexible but also more sensitive to possible errors arising from the higher number of stand variables needed for the estimation of the PDF parameters.