Economic losses caused by tree species proportions and site type errors in forest management planning
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 f...
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2019-06-01
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doaj-7f0fc548e6ac4ef68c10f27d39aaea6f2020-11-24T21:05:16ZengFinnish Society of Forest ScienceSilva Fennica2242-40752242-40752019-06-0153210.14214/sf.10089Economic losses caused by tree species proportions and site type errors in forest management planningArto Haara0Annika Kangas1Sakari Tuominen2Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, FinlandNatural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, FinlandNatural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 2, FI-00791 Helsinki, FinlandThe 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.forest inventoryuncertaintysub-optimality lossvalue of information |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arto Haara Annika Kangas Sakari Tuominen |
spellingShingle |
Arto Haara Annika Kangas Sakari Tuominen Economic losses caused by tree species proportions and site type errors in forest management planning Silva Fennica forest inventory uncertainty sub-optimality loss value of information |
author_facet |
Arto Haara Annika Kangas Sakari Tuominen |
author_sort |
Arto Haara |
title |
Economic losses caused by tree species proportions and site type errors in forest management planning |
title_short |
Economic losses caused by tree species proportions and site type errors in forest management planning |
title_full |
Economic losses caused by tree species proportions and site type errors in forest management planning |
title_fullStr |
Economic losses caused by tree species proportions and site type errors in forest management planning |
title_full_unstemmed |
Economic losses caused by tree species proportions and site type errors in forest management planning |
title_sort |
economic losses caused by tree species proportions and site type errors in forest management planning |
publisher |
Finnish Society of Forest Science |
series |
Silva Fennica |
issn |
2242-4075 2242-4075 |
publishDate |
2019-06-01 |
description |
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. |
topic |
forest inventory uncertainty sub-optimality loss value of information |
work_keys_str_mv |
AT artohaara economiclossescausedbytreespeciesproportionsandsitetypeerrorsinforestmanagementplanning AT annikakangas economiclossescausedbytreespeciesproportionsandsitetypeerrorsinforestmanagementplanning AT sakarituominen economiclossescausedbytreespeciesproportionsandsitetypeerrorsinforestmanagementplanning |
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1716769394924716032 |