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A comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations
Citation
Iqbal, IA and Osborn, J and Stone, C and Lucieer, A, A comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations, Remote Sensing, 13, (17) Article 3536. ISSN 2072-4292 (2021) [Refereed Article]
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Copyright Statement
Copyright 2021 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Abstract
Digital aerial photogrammetry (DAP) has emerged as a potentially cost-effective alternative to airborne laser scanning (ALS) for forest inventory methods that employ point cloud data. Forest inventory derived from DAP using area-based methods has been shown to achieve accuracy similar to that of ALS data. At the tree level, individual tree detection (ITD) algorithms have been developed to detect and/or delineate individual trees either from ALS point cloud data or from ALS- or DAP-based canopy height models. An examination of the application of ITDs to DAP-based point clouds has not yet been reported. In this research, we evaluate the suitability of DAP-based point clouds for individual tree detection in the Pinus radiata plantation. Two ITD algorithms designed to work with point cloud data are applied to dense point clouds generated from small- and medium-format photography and to an ALS point cloud. Performance of the two ITD algorithms, the influence of stand structure on tree detection rates, and the relationship between tree detection rates and canopy structural metrics are investigated. Overall, we show that there is a good agreement between ALS- and DAP-based ITD results (proportion of false negatives for ALS, SFP, and MFP was always lower than 29.6%, 25.3%, and 28.6%, respectively, whereas, the proportion of false positives for ALS, SFP, and MFP was always lower than 39.4%, 30.7%, and 33.7%, respectively). Differences between small- and medium-format DAP results were minor (for SFP and MFP, differences between recall, precision, and F-score were always less than 0.08, 0.03, and 0.05, respectively), suggesting that DAP point cloud data is robust for ITD. Our results show that among all the canopy structural metrics, the number of trees per hectare has the greatest influence on the tree detection rates
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | forest inventory, Pinus radiata plantation, individual tree detection, airborne laser scanning, photogrammetry, digital aerial photography, small-format photography, medium-format photography, image 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: | Softwood plantations |
| UTAS Author: | Iqbal, IA (Mr Irfan Iqbal) |
| UTAS Author: | Osborn, J (Dr Jon Osborn) |
| UTAS Author: | Lucieer, A (Professor Arko Lucieer) |
| ID Code: | 148012 |
| Year Published: | 2021 |
| Web of Science® Times Cited: | 1 |
| Deposited By: | Geography and Spatial Science |
| Deposited On: | 2021-11-30 |
| Last Modified: | 2021-12-21 |
| Downloads: | 6 View Download Statistics |
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