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iForest - Biogeosciences and Forestry

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Estimating the accuracy of smartphone app-based removal estimates against actual wood-harvesting data from clear cuttings

Ville Vähä-Konka   , Lauri Korhonen, Kalle Kärhä, Matti Maltamo

iForest - Biogeosciences and Forestry, Volume 17, Issue 3, Pages 140-147 (2024)
doi: https://doi.org/10.3832/ifor4377-017
Published: May 14, 2024 - Copyright © 2024 SISEF

Research Articles


Trestima® is a computer vision-based smartphone application that utilises relascope theory to obtain estimates of forest attributes from smartphone photographs. The aim of this study was to investigate the accuracy of Trestima estimation and evaluate whether it is sufficiently accurate for operational use in forestry. Our data consisted of 37 forest stands, encompassing 73.5 ha in southeastern Finland, where Trestima estimates were obtained by forestry professionals during their work. The results were compared with harvester data obtained from clear-cut stands. The number of photographs taken per stand ranged between 1-29 (average: 7.3; standard deviation: 5.0). The total amount of industrial roundwood harvested from the stands was 21.531 m3 and the average harvest removal per hectare was 282 m3. The accuracy of Trestima estimation was relatively good when ≥ 10 photographs per stand were taken. In this case, the root mean square error percent (RMSE%) value associated with roundwood volume was 17.7%. When the number of photographs per stand was < 10, the accuracy of Trestima was much weaker (RMSE% 22.7-55.3%). On average, Trestima underestimated harvested volumes in Scots pine (Pinus sylvestris L.) stands (Bias% 11.4-89.2), although the bias was smaller (Bias% -12.7-12.4) with Norway spruce (Picea abies [L.] Karst.) stands. The Trestima smartphone application is a possible option for traditional field measurements in operational forestry, provided that its usage instructions are strictly followed, which is not always the case in practice.

  Keywords


Forest Inventory, Forest Mensuration, Smartphone, Machine Vision, Computer Vision, Relascope, Harvester Data

Authors’ address

(1)
Ville Vähä-Konka 0000-0003-4225-7712
Lauri Korhonen 0000-0002-9352-0114
Kalle Kärhä 0000-0002-8455-2974
Matti Maltamo 0000-0002-9904-3371
University of Eastern Finland, School of Forest Sciences, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu (Finland)

Corresponding author

 
Ville Vähä-Konka
ville.vaha-konka@uef.fi

Citation

Vähä-Konka V, Korhonen L, Kärhä K, Maltamo M (2024). Estimating the accuracy of smartphone app-based removal estimates against actual wood-harvesting data from clear cuttings. iForest 17: 140-147. - doi: 10.3832/ifor4377-017

Academic Editor

Enrico Marchi

Paper history

Received: May 11, 2023
Accepted: Apr 22, 2024

First online: May 14, 2024
Publication Date: Jun 30, 2024
Publication Time: 0.73 months

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