A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning
Crown projection area (CPA) is a critical parameter in assessing inter-tree competition and estimating biomass volume. A multi-layer seeded region growing-based approach to the fully automated assessment of CPA based on 3D-point-clouds derived from terrestrial laser scanning (TLS) is presented. Independently repeated manual CPA-measurements in a subset of the stand serve as the reference and enable quantification of the inter-observer bias. Allometric models are used to predict CPA for the whole stand and are compared to the TLS-based estimates on the single tree- and stand-level. It is shown that for single trees, the deviation between CPA measurements derived from TLS data and manual measurements is on par with the deviations between manual measurements by different observers. The inter-observer bias propagates into the allometric models, resulting in a high uncertainty of the derived estimates at tree-level. Comparing the allometric models to the TLS measurements at stand-level reveals the high influence of crown morphology, which only can be taken into account by the TLS measurements and not by the allometric models.
Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning
Crown projection area (CPA) is a critical parameter in assessing inter-tree competition and estimating biomass volume. A multi-layer seeded region growing-based approach to the fully automated assessment of CPA based on 3D-point-clouds derived from terrestrial laser scanning (TLS) is presented. Independently repeated manual CPA-measurements in a subset of the stand serve as the reference and enable quantification of the inter-observer bias. Allometric models are used to predict CPA for the whole stand and are compared to the TLS-based estimates on the single tree- and stand-level. It is shown that for single trees, the deviation between CPA measurements derived from TLS data and manual measurements is on par with the deviations between manual measurements by different observers. The inter-observer bias propagates into the allometric models, resulting in a high uncertainty of the derived estimates at tree-level. Comparing the allometric models to the TLS measurements at stand-level reveals the high influence of crown morphology, which only can be taken into account by the TLS measurements and not by the allometric models.
Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning
Tim Ritter (author) / Arne Nothdurft (author)
2018
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Structural assessment using terrestrial laser scanning point clouds
| Emerald Group Publishing | 2021
Automated registration of dense terrestrial laser-scanning point clouds using curves
| Online Contents | 2014