Abstract
Abstract. The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM) data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E). Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius) from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean), stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean) and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean), with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet) showed RMSEs (in percent of the surveyed stand mean) of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.
Highlights
1.1 MotivationIn Nordic boreal forestry, aerial imagery has the potential to gain increasing importance as a source of data for detailed spatial estimates of forest variables
This study aims to investigate the possibilities to estimate species-specific mean stem volume (V), mean basal area (BA) and basal-area-weighted mean tree height (H) at stand level using spectral and 3D data from the Digital Mapping Camera (DMC) sensor in combination with Airborne Laser Scanning (ALS) Digital Elevation Model (DEM) data
The results (Table 1, Figure 2) show higher accuracy for the total volume estimates compared to species-specific stem volume estimates, as measured by Root Mean Square Error (RMSE) in percentage of the surveyed mean
Summary
1.1 MotivationIn Nordic boreal forestry, aerial imagery has the potential to gain increasing importance as a source of data for detailed spatial estimates of forest variables. Forest companies commonly utilize ALS-assessed forest information, estimated primarily using area-based methods (Magnussen och Boudewyn, 1998; Næsset, 2002b; Næsset et al, 2004) In boreal forest, these methods deliver stand level estimation accuracies in terms of Root Mean Square Error (RMSE) for tree height typically in the range of 2.5-13.6% (in percent of the surveyed mean), stem diameter in the range of 5.9-15.8% and stem volume 8.4-16.6% (Næsset et al, 2004; McRoberts et al, 2010). Ground elevation was assessed using manual photo-interpretation of the images viewed in stereo in a limited number of locations with visible ground and interpolated to full spatial cover At their test site in Norway, tree height was estimated for forest stands using regression with standard error ranging from 0.9 m to 2.1 m, which is similar to accuracy achieved using photointerpretation. Stem volume, basal area the result shows RMSEs of 8.8%, 13.1% and 14.9%, respectively, at stand level
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