Comparing parametric and non-parametric methods of predicting Site Index for radiata pine using combinations of data derived from environmental surfaces, satellite imagery and airborne laser scanning

摘要

Site Index (SI) is one of the main measures of forest productivity used throughout the world. For even-age plantations Site Index is defined as the height of dominant trees at a given reference age. Site Index is normally determined from field measurements and expressed from these measurements at the resolution of the stand. Development of fine resolution spatial surfaces describing variation in productivity across broad landscapes would be of considerable use in improving stand management. Using data obtained from a large Pinus radiata D. Don forest located in the central North Island, New Zealand, the objective of this study was to compare the precision of parametric and non-parametric models of Site Index that included explanatory variables extracted from aerially acquired Light Detection and Ranging (LiDAR), satellite imagery or environmental surfaces and combinations of these three data sources. Models were constructed both with and without age as an explanatory variable as managers may not always have access to stand age. A total of 32 models (16 data sources x two model methods) were constructed using data from 484 plots. Validation methods used to examine precision and bias of these models included leave one out cross validation and k-fold analysis.