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Drones paper

Estimating crown diameters in urban forests with Unmanned Aerial System-based photogrammetric point clouds

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Pages 468-505 | Received 06 May 2018, Accepted 02 Oct 2018, Published online: 09 Jan 2019
 

ABSTRACT

Field measurements are the main source of information when determining stand parameters, which are essential to produce an effective forest management plan. However, conducting terrestrial measurements is neither time- nor cost-efficient in most cases. In recent years, the advent of sophisticated remote sensing technologies has enabled the extraction of accurate and robust information about the physical characteristics of trees. Crown diameter is one of the most important stand parameters that should be measured or estimated. This study proposes a Polynomial Fitting Based (PFB) methodology to estimate crown diameters of urban trees with Unmanned Aerial System (UAS)-based data. Crown diameters estimated with the PFB methodology were compared not only to a reference data but also to those estimated based on five widely used image segmentation algorithms, which were the Mean Shift Segmentation (MSS), Morphological Profiles Based Segmentation (MPBS), Multiresolution Segmentation (MRS), Seeded Region Growing Segmentation (SRGS) and Watershed Segmentation (WS). Quantitative investigations revealed that the PFB approach outperformed the other segmentation-based approaches. The PFB approach estimated the crown diameters with root-mean-square errors (RMSE) ranging from 0.69 m to 0.92 m. The PFB methodology was found to be a practical and robust approach for the estimation of crown diameters, which plays a very significant role in effective forest management.

Acknowledgments

This study was supported by the Firat University Scientific Research Projects Unit (FUBAP) under project no MF-15.40. We would like to thank the anonymous reviewers for their constructive comments and suggestions. This study was based on the corresponding author Volkan Yilmaz’s PhD thesis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Firat University Scientific Research Projects Unit (FUBAP) [MF-15.40].

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