Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning
Authors: Holmgren J.1; Nilsson M.2; Olsson H.3
Source: Forest Science, Volume 49, Number 3, June 2003 , pp. 419-428(10)
Abstract:
Airborne laser scanning has the ability to measure the vertical and horizontal structure of forest vegetation. The aim of this study is to investigate how measures derived from laser scanning data can be used in regression models for estimation of basal-area-weighted mean tree height and stem volume on 10 m radius field plots. Influence of laser scan angle on tree height estimation and on crown coverage area estimation is also investigated. The study area was located in southern Sweden (lat. 58°30
N, long. 13°40E). The dominating tree species were Norway spruce (Picea abies L. Karst .), Scots pine (Pinus sylvestris L.) and birch (Betula spp.). Linear regression functions (R2=0.89–0.91) used to predict basal-area-weighted mean tree height had a Root Mean Square Error (RMSE) of 1.45–1.56 m, corresponding to 10–11% of average height. Scanning angle was not significant for estimation of basal-area-weighted mean tree height. Two regression models were used for prediction of stem volume. The first model (R2 = 0.90), with laser derived mean height together with laser derived crown coverage area as predicting variables, gave RMSE of 37 m3 ha-1, corresponding to 22% of average stem volume. The second model (R2=0.82), with laser derived tree height together with laser derived stem number as predicting variables, gave RMSE of 43 m3 ha-1, corresponding to 26% of average stem volume. The results implies that airborne laser scanning, if combined with a field sample, has potential of retrieving information with high spatial resolution (10 m radius plot) about tree height and stem volume for a forest area. FOR. SCI. 49(3):419–428.
Keywords: LIDAR; forest inventory; scanning angle; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resources; natural resource management
Document Type: Miscellaneous
Affiliations: 1: Remote Sensing Laboratory, Department of Forest Resources Management and Geomatics, Swedish University of Agricultural Sciences, Umeå, Sweden, S-90183, Phone: +46(0)-90-7866596; Fax: +46(0)-90-141915 Johan.Holmgren@resgeom.slu.se 2: Research Scientist Remote Sensing Laboratory, Department of Forest Resources Management and Geomatics, Swedish University of Agricultural Sciences, Umeå, Sweden, S-90183, Phone: +46(0)-90-7866555 Mats.Nilsson@resgeom.slu.se 3: Professor Remote Sensing Laboratory, Department of Forest Resources Management and Geomatics, Swedish University of Agricultural Sciences, Umeå, Sweden, S-90183, Phone: +46(0)-90-7866198 Hakan.Olsson@resgeom.slu.se
