Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data
Structural changes in savanna trees vary spatially and temporally because of both biotic and abiotic drivers, as well as the complex interactions between them. Given this complexity, it is essential to monitor and quantify woody structural changes in savannas efficiently. We implemented a non-destru...
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MDPI AG
2025-02-01
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| author | Tasiyiwa Priscilla Muumbe Jussi Baade Pasi Raumonen Corli Coetsee Jenia Singh Christiane Schmullius |
| author_facet | Tasiyiwa Priscilla Muumbe Jussi Baade Pasi Raumonen Corli Coetsee Jenia Singh Christiane Schmullius |
| author_sort | Tasiyiwa Priscilla Muumbe |
| collection | DOAJ |
| description | Structural changes in savanna trees vary spatially and temporally because of both biotic and abiotic drivers, as well as the complex interactions between them. Given this complexity, it is essential to monitor and quantify woody structural changes in savannas efficiently. We implemented a non-destructive approach based on Terrestrial Laser Scanning (TLS) and Quantitative Structure Models (QSMs) that offers the unique advantage of investigating changes in complex tree parameters, such as volume and branch length parameters that have not been previously reported for savanna trees. Leaf-off multi-scan TLS point clouds were acquired during the dry season, using a Riegl VZ1000 TLS, in September 2015 and October 2019 at the Skukuza flux tower in Kruger National Park, South Africa. These three-dimensional (3D) data covered an area of 15.2 ha with an average point density of 4270 points/m<sup>2</sup> (0.015°) and 1600 points/m<sup>2</sup> (0.025°) for the 2015 and 2019 clouds, respectively. Individual tree segmentation was applied on the two clouds using the comparative shortest-path algorithm in LiDAR 360(v5.4) software. We reconstructed optimized QSMs and assessed tree structural parameters such as Diameter at Breast Height (DBH), tree height, crown area, volume, and branch length at individual tree level. The DBH, tree height, crown area, and trunk volume showed significant positive correlations (R<sup>2</sup> > 0.80) between scanning periods regardless of the difference in the number of points of the matched trees. The opposite was observed for total and branch volume, total number of branches, and 1st-order branch length. As the difference in the point densities increased, the difference in the computed parameters also increased (R<sup>2</sup> < 0.63) for a high relative difference. A total of 45% of the trees present in 2015 were identified in 2019 as damaged/felled (75 trees), and the volume lost was estimated to be 83.4 m<sup>3</sup>. The results of our study showed that volume reconstruction algorithms such as TreeQSMs and high-resolution TLS datasets can be used successfully to quantify changes in the structure of savanna trees. The results of this study are key in understanding savanna ecology given its complex and dynamic nature and accurately quantifying the gains and losses that could arise from fire, drought, herbivory, and other abiotic and biotic disturbances. |
| format | Article |
| id | doaj-art-a8879d953612433ca1ddccec81f55a5c |
| institution | DOAJ |
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| language | English |
| publishDate | 2025-02-01 |
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| spelling | doaj-art-a8879d953612433ca1ddccec81f55a5c2025-08-20T02:52:35ZengMDPI AGRemote Sensing2072-42922025-02-0117575710.3390/rs17050757Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS DataTasiyiwa Priscilla Muumbe0Jussi Baade1Pasi Raumonen2Corli Coetsee3Jenia Singh4Christiane Schmullius5Department for Earth Observation, Friedrich Schiller University Jena, Löbdergraben 32, 07743 Jena, GermanyDepartment of Physical Geography, Friedrich Schiller University Jena, Löbdergraben 32, 07743 Jena, GermanyUnit of Computing Sciences, Tampere University, Korkeakoulunkatu 1, 33720 Tampere, FinlandScientific Services, Savanna and Grassland Research Unit, South African National Parks (SANParks), Skukuza 1350, South AfricaDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USADepartment for Earth Observation, Friedrich Schiller University Jena, Löbdergraben 32, 07743 Jena, GermanyStructural changes in savanna trees vary spatially and temporally because of both biotic and abiotic drivers, as well as the complex interactions between them. Given this complexity, it is essential to monitor and quantify woody structural changes in savannas efficiently. We implemented a non-destructive approach based on Terrestrial Laser Scanning (TLS) and Quantitative Structure Models (QSMs) that offers the unique advantage of investigating changes in complex tree parameters, such as volume and branch length parameters that have not been previously reported for savanna trees. Leaf-off multi-scan TLS point clouds were acquired during the dry season, using a Riegl VZ1000 TLS, in September 2015 and October 2019 at the Skukuza flux tower in Kruger National Park, South Africa. These three-dimensional (3D) data covered an area of 15.2 ha with an average point density of 4270 points/m<sup>2</sup> (0.015°) and 1600 points/m<sup>2</sup> (0.025°) for the 2015 and 2019 clouds, respectively. Individual tree segmentation was applied on the two clouds using the comparative shortest-path algorithm in LiDAR 360(v5.4) software. We reconstructed optimized QSMs and assessed tree structural parameters such as Diameter at Breast Height (DBH), tree height, crown area, volume, and branch length at individual tree level. The DBH, tree height, crown area, and trunk volume showed significant positive correlations (R<sup>2</sup> > 0.80) between scanning periods regardless of the difference in the number of points of the matched trees. The opposite was observed for total and branch volume, total number of branches, and 1st-order branch length. As the difference in the point densities increased, the difference in the computed parameters also increased (R<sup>2</sup> < 0.63) for a high relative difference. A total of 45% of the trees present in 2015 were identified in 2019 as damaged/felled (75 trees), and the volume lost was estimated to be 83.4 m<sup>3</sup>. The results of our study showed that volume reconstruction algorithms such as TreeQSMs and high-resolution TLS datasets can be used successfully to quantify changes in the structure of savanna trees. The results of this study are key in understanding savanna ecology given its complex and dynamic nature and accurately quantifying the gains and losses that could arise from fire, drought, herbivory, and other abiotic and biotic disturbances.https://www.mdpi.com/2072-4292/17/5/757savannaterrestrial laser scanningmulti-temporalchangestructurequantitative structure models |
| spellingShingle | Tasiyiwa Priscilla Muumbe Jussi Baade Pasi Raumonen Corli Coetsee Jenia Singh Christiane Schmullius Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data Remote Sensing savanna terrestrial laser scanning multi-temporal change structure quantitative structure models |
| title | Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data |
| title_full | Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data |
| title_fullStr | Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data |
| title_full_unstemmed | Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data |
| title_short | Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data |
| title_sort | quantifying tree structural change in an african savanna by utilizing multi temporal tls data |
| topic | savanna terrestrial laser scanning multi-temporal change structure quantitative structure models |
| url | https://www.mdpi.com/2072-4292/17/5/757 |
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