Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest

The rule of thumb “the right tree in the right place” is a common idea in different countries to avoid damages caused by trees on sidewalks. Although many new planting techniques can be used, the estimation of the trunk flare diameter (TFD) could help the planning process to give tree roots more spa...

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Main Authors: Rogério Bobrowski, Monika Winczek, Lucas Polo Silva, Tarik Cuchi, Marta Szostak, Piotr Wężyk
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/14/18/4661
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author Rogério Bobrowski
Monika Winczek
Lucas Polo Silva
Tarik Cuchi
Marta Szostak
Piotr Wężyk
author_facet Rogério Bobrowski
Monika Winczek
Lucas Polo Silva
Tarik Cuchi
Marta Szostak
Piotr Wężyk
author_sort Rogério Bobrowski
collection DOAJ
description The rule of thumb “the right tree in the right place” is a common idea in different countries to avoid damages caused by trees on sidewalks. Although many new planting techniques can be used, the estimation of the trunk flare diameter (TFD) could help the planning process to give tree roots more space to grow over the years. As such, we compared the applicability of point clouds based on iPad Pro 2020 image processing and a precise terrestrial laser scanner (TLS FARO) for the modeling of the TFD using different modeling procedures. For both scanning methods, 100 open-grown and mature trees of 10 different species were scanned in an urban park in Cracow, Poland. To generate models, we used the PBH (perimeter at breast height) and TFD variables and simple linear regression procedures. We also tested machine learning algorithms. In general, the TFD value corresponded to two times the size of a given DBH (diameter at breast height) for both methods of point cloud acquisition. Linearized models showed similar statistics to machine learning techniques. The random forest algorithm showed the best fit for the TFD estimation, R<sup>2</sup> = 0.8780 (iPad Pro), 0.8961 (TLS FARO), RMSE (m) = 0.0872 (iPad Pro), 0.0702 (TLS FARO). Point clouds generated from iPad Pro imageries (matching approach) promoted similar results as TLS FARO for the TFD estimations.
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spelling doaj.art-516306b17d7d4a8cb9b7d59049991e3a2023-11-23T18:46:25ZengMDPI AGRemote Sensing2072-42922022-09-011418466110.3390/rs14184661Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban ForestRogério Bobrowski0Monika Winczek1Lucas Polo Silva2Tarik Cuchi3Marta Szostak4Piotr Wężyk5Department of Forest Engineering, Agrarian and Environmental Sciences Sector, Midwestern State University, Irati 84505-677, BrazilDepartment of Forest Resources Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, PolandDepartment of Forest Engineering, Agrarian and Environmental Sciences Sector, Midwestern State University, Irati 84505-677, BrazilDepartment of Forest Engineering, Agrarian and Environmental Sciences Sector, Midwestern State University, Irati 84505-677, BrazilDepartment of Forest Resources Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, PolandDepartment of Forest Resources Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, PolandThe rule of thumb “the right tree in the right place” is a common idea in different countries to avoid damages caused by trees on sidewalks. Although many new planting techniques can be used, the estimation of the trunk flare diameter (TFD) could help the planning process to give tree roots more space to grow over the years. As such, we compared the applicability of point clouds based on iPad Pro 2020 image processing and a precise terrestrial laser scanner (TLS FARO) for the modeling of the TFD using different modeling procedures. For both scanning methods, 100 open-grown and mature trees of 10 different species were scanned in an urban park in Cracow, Poland. To generate models, we used the PBH (perimeter at breast height) and TFD variables and simple linear regression procedures. We also tested machine learning algorithms. In general, the TFD value corresponded to two times the size of a given DBH (diameter at breast height) for both methods of point cloud acquisition. Linearized models showed similar statistics to machine learning techniques. The random forest algorithm showed the best fit for the TFD estimation, R<sup>2</sup> = 0.8780 (iPad Pro), 0.8961 (TLS FARO), RMSE (m) = 0.0872 (iPad Pro), 0.0702 (TLS FARO). Point clouds generated from iPad Pro imageries (matching approach) promoted similar results as TLS FARO for the TFD estimations.https://www.mdpi.com/2072-4292/14/18/4661hand-held laser scanningtree modelingurban treebiometrical parameters
spellingShingle Rogério Bobrowski
Monika Winczek
Lucas Polo Silva
Tarik Cuchi
Marta Szostak
Piotr Wężyk
Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest
Remote Sensing
hand-held laser scanning
tree modeling
urban tree
biometrical parameters
title Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest
title_full Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest
title_fullStr Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest
title_full_unstemmed Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest
title_short Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest
title_sort promising uses of the ipad pro point clouds the case of the trunk flare diameter estimation in the urban forest
topic hand-held laser scanning
tree modeling
urban tree
biometrical parameters
url https://www.mdpi.com/2072-4292/14/18/4661
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