NDLI: Effects of Individual Tree Detection Error Sources on Forest Management Planning Calculations

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Effects of Individual Tree Detection Error Sources on Forest Management Planning Calculations

Content Provider	MDPI
Author	Vastaranta, Mikko Holopainen, Markus Yu, Xiaowei Hyyppä, Juha Mäkinen, Antti Rasinmäki, Jussi Melkas, Timo Kaartinen, Harri Hyyppä, Hannu
Abstract	The objective was to investigate the error sources of the airborne laser scanning based individual tree detection (ITD), and its effects on forest management planning calculations. The investigated error sources were detection of trees (etd), error in tree height prediction (eh) and error in tree diameter prediction (ed). The effects of errors were analyzed with Monte Carlo simulations. etd was modeled empirically based on a tree’s relative size. A total of five different tree detection scenarios were tested. Effect of eh was investigated using 5% and 0% and effect of ed using 20%, 15%, 10%, 5%, 0% error levels, respectively. The research material comprised 15 forest stands located in Southern Finland. Measurements of 5,300 trees and their timber assortments were utilized as a starting point for the Monte Carlo simulated ITD inventories. ITD carried out for the same study area provided a starting point (Scenario 1) for etd. In Scenario 1, 60.2% from stem number and 75.9% from total volume (Vtotal) were detected. When the only error source was etd (tree detection varying from 75.9% to 100% of Vtotal), root mean square errors (RMSEs) in stand characteristics ranged between the scenarios from 32.4% to 0.6%, 29.0% to 0.5%, 7.8% to 0.2% and 5.4% to 0.1% in stand basal area (BA), Vtotal, mean height (Hg) and mean diameter (Dg), respectively. Saw wood volume RMSE varied from 25.1% to 0.2%, as pulp wood volume respective varied from 37.8% to 1.0% when errors stemmed only from etd. The effect of ed was most significant for Vtotal and BA and the decrease in RMSE was from 12.0% to 0.6% (BA) and from 10.9% to 0.5% (Vtotal) in the most accurate tree detection scenario when ed varied from 20% to 0%. The effect of increased accuracy in tree height prediction was minor for all the stand characteristics. The results show that the most important error source in ITD is tree detection. At stand level, unbiased predictions for tree height and diameter are enough, given the present tree detection accuracy.
File Size	282624
Ending Page	1626
Page Count	13
Starting Page	1614
File Format	PDF
e-ISSN	20724292
DOI	10.3390/rs3081614
Journal	Remote Sensing
Issue Number	8
Volume Number	3
Language	English
Publisher Date	2011-07-25
Access Restriction	Open
Subject Keyword	airborne laser scanning forest inventory simulation accuracy
Content Type	Text
Resource Type	Article

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