A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations
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...
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MDPI AG
2021-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/17/3536 |
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| author | Irfan A. Iqbal Jon Osborn Christine Stone Arko Lucieer |
| author_facet | Irfan A. Iqbal Jon Osborn Christine Stone Arko Lucieer |
| author_sort | Irfan A. Iqbal |
| collection | DOAJ |
| description | 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 <i>Pinus radiata</i> 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. |
| first_indexed | 2024-03-10T08:05:24Z |
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| id | doaj.art-deccc1aa3cd24b069a1bd745e492b61c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T08:05:24Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-deccc1aa3cd24b069a1bd745e492b61c2023-11-22T11:10:26ZengMDPI AGRemote Sensing2072-42922021-09-011317353610.3390/rs13173536A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine PlantationsIrfan A. Iqbal0Jon Osborn1Christine Stone2Arko Lucieer3School of Geography, Planning and Spatial Sciences, University of Tasmania, Hobart 7001, AustraliaSchool of Geography, Planning and Spatial Sciences, University of Tasmania, Hobart 7001, AustraliaDepartment of Primary Industry-NSW, Level 30, 4 Parramatta Square, Parramatta 2150, AustraliaSchool of Geography, Planning and Spatial Sciences, University of Tasmania, Hobart 7001, AustraliaDigital 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 <i>Pinus radiata</i> 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.https://www.mdpi.com/2072-4292/13/17/3536forest inventory<i>Pinus radiata</i> plantationindividual tree detectionairborne laser scanningphotogrammetrydigital aerial photography |
| spellingShingle | Irfan A. Iqbal Jon Osborn Christine Stone Arko Lucieer A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations Remote Sensing forest inventory <i>Pinus radiata</i> plantation individual tree detection airborne laser scanning photogrammetry digital aerial photography |
| title | A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations |
| title_full | A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations |
| title_fullStr | A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations |
| title_full_unstemmed | A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations |
| title_short | A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations |
| title_sort | comparison of als and dense photogrammetric point clouds for individual tree detection in radiata pine plantations |
| topic | forest inventory <i>Pinus radiata</i> plantation individual tree detection airborne laser scanning photogrammetry digital aerial photography |
| url | https://www.mdpi.com/2072-4292/13/17/3536 |
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