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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Main Authors: Arto Haara, Annika Kangas, Sakari Tuominen
Format: Article
Language:English
Published: Finnish Society of Forest Science 2019-06-01
Series:Silva Fennica
Subjects:
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spelling 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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