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Assessing the effect of UAV oblique imaging on tree parameter accuracy – a study in Haagse Bos, The Netherlands

Gnanasekaran, Srilakshmi (2021) Assessing the effect of UAV oblique imaging on tree parameter accuracy – a study in Haagse Bos, The Netherlands.

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Abstract:As forest can sequester carbon, it plays a crucial role in regulating carbon dioxide in the atmosphere, thus mitigating the effects of climate change. The sequestered carbon is found in different pools in forests, and aboveground biomass (AGB) is one of the main pools. In order to monitor and report the forest carbon stock, it is essential to estimate the AGB. AGB can be estimated using allometric equations that use the structural information of trees like the diameter at breast height (DBH) and tree heights as input parameters. This tree structural information can be extracted from remote sensing data. The latest development in remote sensing is the advent of Unmanned Aerial Vehicle (UAV). UAVs are flexible, time and cost-efficient means of data collection. Using photogrammetric techniques like Structure from Motion (SfM), it is possible to generate a 3D point cloud from over-lapping 2D images acquired by UAV, thereby enabling tree parameter retrieval. However, the digital camera onboard the UAV lacks penetration capability, which subsequently affects the accuracy of the retrieved tree parameter. Several studies have incorporated oblique images in the SfM model and reported improvement in the density and accuracy of the generated 3D point cloud. However, how incorporating oblique images to build a dense 3D point cloud and surface models for the forests is affected by different canopy structures has not been well documented in the literature. This study was done in the Haagse Bos in The Netherlands. It was aimed to assess and compare the accuracy of DTM, tree height, and DBH retrieved from UAV nadir and UAV oblique datasets under dense and medium dense canopy. This study also assesses the effect of tree height estimation error on the AGB estimates. UAV images used in this study were acquired at nadir and 75 degrees east-facing oblique view angle using DJI Phantom 4. The UAV nadir dataset comprises the DTM, DSM, and orthophoto generated from the nadir images acquired in the double grid. The UAV oblique dataset comprises the DTM, DSM, and orthophoto generated from the combination of nadir images acquired in the double grid and oblique images acquired in a single grid. The accuracies of UAV DTMs and tree heights extracted from UAV CHMs were assessed by comparing to LiDAR DTM and tree heights extracted from LiDAR CHM. The DBH modeled using UAV-derived tree parameters were compared with field-measured DBH. The study's statistical analysis revealed no significant difference between the means of elevation from UAV nadir and UAV oblique DTM in both dense and medium dense canopy. Similarly, there was no significant difference between the means of tree height extracted from UAV nadir and UAV oblique CHMs in both the dense and medium dense canopy blocks. In addition to that, the DBH models using tree parameters retrieved from the UAV nadir dataset and UAV oblique dataset did not differ significantly in both the dense and medium dense blocks. The sensitivity analysis of tree height uncertainties on the accuracy AGB estimation revealed that in the dense block, the errors in tree height affected the AGB accuracy. Whereas in the medium dense block, the tree height errors did not significantly affect the AGB estimates.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:https://purl.utwente.nl/essays/88783
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