Articles containing the keyword 'sub-optimality loss'

The aim of this study was to estimate economic losses, which are caused by forest inventory errors of tree species proportions and site types. Our study data consisted of ground truth data and four sets of erroneous tree species proportions. They reflect the accuracy of tree species proportions in four remote sensing data sets, namely 1) airborne laser scanning (ALS) with 2D aerial image, 2) 2D aerial image, 3) 3D and 2D aerial image data together and 4) satellite data. Furthermore, our study data consisted of one simulated site type data set. We used the erroneous tree species proportions to optimise the timing of forest harvests and compared that to the true optimum obtained with ground truth data. According to the results, the mean losses of Net Present Value (NPV) because of erroneous tree species proportions at an interest rate of 3% varied from 124.4 € ha^–1 to 167.7 € ha^–1. The smallest losses were observed using tree species proportions predicted using ALS data and largest using satellite data. In those stands, respectively, in which tree species proportion errors actually caused economic losses, they were 468 € ha^–1 on average with tree species proportions based on ALS data. In turn, site type errors caused only small losses. Based on this study, accurate tree species identification seems to be very important with respect to operational forest inventory.

• Haara, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: arto.haara@luke.fi
• Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
• Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 2, FI-00791 Helsinki, Finland https://orcid.org/0000-0001-5429-3433 E-mail: sakari.tuominen@luke.fi