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Research article - Peer-reviewed, 2012

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

Lindberg, Eva; Hollaus, Markus

Abstract

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.

Published in

Remote Sensing
2012, volume: 4, number: 4, pages: 1004-1023

Authors' information

Swedish University of Agricultural Sciences, Department of Forest Resource Management
Hollaus, Markus
Vienna University of Technology (TU Wien)

Associated SLU-program

Remningstorp

UKÄ Subject classification

Remote Sensing
Forest Science

Publication Identifiers

DOI: https://doi.org/10.3390/rs4041004

URI (permanent link to this page)

https://res.slu.se/id/publ/40995