作者: Johan Viklund
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摘要: In Sweden the cap portion of harvested stem volume derives from Non-Industrial Private Forest (NIPF) owners. current study a Decision Support Tool (DST) for wood procurement planning based on stereo-matching aerial images is presented. Two stages are described, namely (1) automatic segmentation using Mean Shift algorithm; (2) wall-to-wall mapping stands Semi-Global Matching (SGM) in combination with high-resolution Digital Elevation Model (DEM). The was conducted coniferous boreal forest area northern Sweden. 365 sample plots (8 m radius) were measured field where HGV (dm) ranged between 49.0 - 246.0 dm (mean 139.3 dm), DGV 67.0 400.0 mm 196.8 mm), VOL 7.0 665.0 m3/ha 151.1 m3/ha) and BA 20.0 635.0 dm2/ha 204.9 dm2/ha). Point clouds extracted 60% forward overlap. A canopy cover metric used to improve estimations. Plot level accuracies calculated leave-one-stand-out-cross-validation resulting Root Square Error (in percent surveyed mean) for: 11.2%, 15.2%, (m3/ha) 33.5% 30.3%. Each stand given an average estimated variables enabling ranking their values. results indicated that proposed DST can be as support planning. Aerial appropriate data source DST, mainly because readily availability low cost.