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The potential of low-cost 3D imaging technologies for forestry applications: Setting a research agenda for low-cost remote sensing inventory tasks
Citation
McGlade, J and Wallace, L and Reinke, K and Jones, S, The potential of low-cost 3D imaging technologies for forestry applications: Setting a research agenda for low-cost remote sensing inventory tasks, Forests, 13, (2) Article 204. ISSN 1999-4907 (2022) [Refereed Article]
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Copyright Statement
Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).
Abstract
Limitations with benchmark light detection and ranging (LiDAR) technologies in forestry have prompted the exploration of handheld or wearable low-cost 3D sensors (<2000 USD). These sensors are now being integrated into consumer devices, such as the Apple iPad Pro 2020. This study was aimed at determining future research recommendations to promote the adoption of terrestrial low-cost technologies within forest measurement tasks. We reviewed the current literature surrounding the application of low-cost 3D remote sensing (RS) technologies. We also surveyed forestry professionals to determine what inventory metrics were considered important and/or difficult to capture using conventional methods. The current research focus regarding inventory metrics captured by low-cost sensors aligns with the metrics identified as important by survey respondents. Based on the literature review and survey, a suite of research directions are proposed to democratise the access to and development of low-cost 3D for forestry: (1) the development of methods for integrating standalone colour and depth (RGB-D) sensors into handheld or wearable devices; (2) the development of a sensor-agnostic method for determining the optimal capture procedures with low-cost RS technologies in forestry settings; (3) the development of simultaneous localisation and mapping (SLAM) algorithms designed for forestry environments; and (4) the exploration of plot-scale forestry captures that utilise low-cost devices at both terrestrial and airborne scales.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | RGB-D, SfM, remote sensing, forest inventory, point cloud |
| Research Division: | Engineering |
| Research Group: | Geomatic engineering |
| Research Field: | Photogrammetry and remote sensing |
| Objective Division: | Plant Production and Plant Primary Products |
| Objective Group: | Forestry |
| Objective Field: | Forestry not elsewhere classified |
| UTAS Author: | Wallace, L (Dr Luke Wallace) |
| ID Code: | 148676 |
| Year Published: | 2022 |
| Web of Science® Times Cited: | 9 |
| Deposited By: | Geography and Spatial Science |
| Deposited On: | 2022-02-02 |
| Last Modified: | 2022-03-04 |
| Downloads: | 4 View Download Statistics |
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