Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests
The determination of diameter at breast height (DBH) is critical in forestry, serving as a key metric for deriving various parameters, including tree volume. Light Detection and Ranging (LiDAR) technology has been increasingly employed in forest inventories, and the development of cost-effective, us...
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MDPI AG
2025-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/1/141 |
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| author | Tobias Ofner-Graff Valentin Sarkleti Philip Svazek Andreas Tockner Sarah Witzmann Lukas Moik Ralf Kraßnitzer Christoph Gollob Tim Ritter Martin Kühmaier Karl Stampfer Arne Nothdurft |
| author_facet | Tobias Ofner-Graff Valentin Sarkleti Philip Svazek Andreas Tockner Sarah Witzmann Lukas Moik Ralf Kraßnitzer Christoph Gollob Tim Ritter Martin Kühmaier Karl Stampfer Arne Nothdurft |
| author_sort | Tobias Ofner-Graff |
| collection | DOAJ |
| description | The determination of diameter at breast height (DBH) is critical in forestry, serving as a key metric for deriving various parameters, including tree volume. Light Detection and Ranging (LiDAR) technology has been increasingly employed in forest inventories, and the development of cost-effective, user-friendly smartphone and tablet applications (apps) has expanded its broader use. Among these are augmented reality (AR) apps, which have already been tested on mobile devices for their accuracy in measuring forest attributes. In February 2024, Apple introduced the Mixed-Reality Interface (MRITF) via the Apple Vision Pro (AVP), offering sensor capabilities for field data collection. In this study, two apps using the AVP were tested for DBH measurement on 182 trees across 22 sample plots in a near-natural forest, against caliper-based reference measurements. Compared with the reference measurements, both apps exhibited a slight underestimation bias of −1.00 cm and −1.07 cm, and the root-mean-square error (RMSE) was 3.14 cm and 2.34 cm, respectively. The coefficient of determination (R<sup>2</sup>) between the reference data and the measurements obtained by the two apps was 0.959 and 0.978. The AVP demonstrated its potential as a reliable field tool for DBH measurement, performing consistently across varying terrain. |
| format | Article |
| id | doaj-art-1392ebc407d84ca8ab4497953f18623d |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-1392ebc407d84ca8ab4497953f18623d2025-01-10T13:20:22ZengMDPI AGRemote Sensing2072-42922025-01-0117114110.3390/rs17010141Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in ForestsTobias Ofner-Graff0Valentin Sarkleti1Philip Svazek2Andreas Tockner3Sarah Witzmann4Lukas Moik5Ralf Kraßnitzer6Christoph Gollob7Tim Ritter8Martin Kühmaier9Karl Stampfer10Arne Nothdurft11Department of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Engineering, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Engineering, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaDepartment of Forest- and Soil Sciences, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU University), 1180 Vienna, AustriaThe determination of diameter at breast height (DBH) is critical in forestry, serving as a key metric for deriving various parameters, including tree volume. Light Detection and Ranging (LiDAR) technology has been increasingly employed in forest inventories, and the development of cost-effective, user-friendly smartphone and tablet applications (apps) has expanded its broader use. Among these are augmented reality (AR) apps, which have already been tested on mobile devices for their accuracy in measuring forest attributes. In February 2024, Apple introduced the Mixed-Reality Interface (MRITF) via the Apple Vision Pro (AVP), offering sensor capabilities for field data collection. In this study, two apps using the AVP were tested for DBH measurement on 182 trees across 22 sample plots in a near-natural forest, against caliper-based reference measurements. Compared with the reference measurements, both apps exhibited a slight underestimation bias of −1.00 cm and −1.07 cm, and the root-mean-square error (RMSE) was 3.14 cm and 2.34 cm, respectively. The coefficient of determination (R<sup>2</sup>) between the reference data and the measurements obtained by the two apps was 0.959 and 0.978. The AVP demonstrated its potential as a reliable field tool for DBH measurement, performing consistently across varying terrain.https://www.mdpi.com/2072-4292/17/1/141LiDARtree diameter estimationApple Vision Promeasurement accuracy |
| spellingShingle | Tobias Ofner-Graff Valentin Sarkleti Philip Svazek Andreas Tockner Sarah Witzmann Lukas Moik Ralf Kraßnitzer Christoph Gollob Tim Ritter Martin Kühmaier Karl Stampfer Arne Nothdurft Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests Remote Sensing LiDAR tree diameter estimation Apple Vision Pro measurement accuracy |
| title | Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests |
| title_full | Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests |
| title_fullStr | Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests |
| title_full_unstemmed | Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests |
| title_short | Potential of Apple Vision Pro for Accurate Tree Diameter Measurements in Forests |
| title_sort | potential of apple vision pro for accurate tree diameter measurements in forests |
| topic | LiDAR tree diameter estimation Apple Vision Pro measurement accuracy |
| url | https://www.mdpi.com/2072-4292/17/1/141 |
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