Comparison of Methods for Estimation of Stem Volume, Stem Number and Basal Area from Airborne Laser Scanning Data in a Hemi-Boreal Forest

This study compares methods to estimate stem volume, stem number and basalarea from Airborne Laser Scanning (ALS) data for 68 field plots in a hemi-boreal, sprucedominated forest (Lat. 58°N, Long. 13°E). The stem volume was estimated with fivedifferent regression models: one model based on height and density metrics from the ALSdata derived from the whole field plot, two models based on similar combinations derivedfrom 0.5 m raster cells, and two models based on canopy volumes from the ALS data. Thebest result was achieved with a model based on height and density metrics derived from0.5 m raster cells (Root Mean Square Error or RMSE 37.3%) and the worst with a modelbased on height and density metrics derived from the whole field plot (RMSE 41.9%). Thestem number and the basal area were estimated with: (i) area-based regression modelsusing height and density metrics from the ALS data; and (ii) single tree-based informationderived from local maxima in a normalized digital surface model (nDSM) mean filteredwith different conditions. The estimates from the regression model were more accurate(RMSE 52.7% for stem number and 21.5% for basal area) than those derived from thenDSM (RMSE 63.4%-91.9% and 57.0%-175.5%, respectively). The accuracy of theestimates from the nDSM varied depending on the filter size and the conditions of theapplied filter. This suggests that conditional filtering is useful but sensitive tothe conditions.