Circular or square plots in ALS-based forest inventories—does it matter?

Abstract

Abstract In airborne laser scanning (ALS)-based forest inventories, there is commonly a discrepancy between the plot shape used for model fitting (typically circular) and the shape of population elements (typically square) where predictions are needed. Circular plots are easy to establish, locate and have the smallest number of edge trees on average. Therefore, a circle is the most common plot shape in both traditional and remote sensing-based forest inventories. In contrast, the shape of population elements used for remote sensing-based predictions is nearly always a square because it enables division of the target population into a grid of non-overlapping plots. In this study, we investigate shape effects for ALS-based forest inventories using circular and square plot shapes. This has not been examined earlier. Aboveground biomass was used as the response variable. The sampling design was created in a way that the probability of selection for any location inside a stem-mapped 30 m × 30 m plot was the same for the circular (radius 7.95 m) and square (side length 14.09 m) plot. This configuration enabled us to compare circular and square plots with the same areas and identical sampling probabilities for every tree in the population. Our primary finding is that for equal area square and circular plots, there is no evidence of systematic prediction error when a model fitted to one shape is used to predict for the other shape. Our secondary finding is that root mean square error (RMSE) value is slightly underestimated (1.2 per cent) when a model fitted to circular plots is used to predict for square plots. A small underestimation of RMSE due to plot shape effect has hardly practical significance in stand-level forest management inventories, but the plot shape effect may be problematic in large area forest surveys.