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Individual tree detection in coastal western hemlock forests using remotely piloted aircraft system acquired digital aerial photogrammetric point clouds

University of British Columbia

Determining the number of trees in a stand, known as stand density, is one of the key fundamental inventory metrics that inform managers of the current conditions of the forest. Stand density can be a challenging variable to measure using field-based surveys, and as a result, foresters have turned to remote sensing to help identify and count individual trees in a given area. Currently, the field of remote sensing is undergoing rapid changes through the utilization of remotely piloted aircraft systems (RPAS) technology. The increased utilization of this new technology has seen renewed interest in the application of individual tree detection (ITD) to digital aerial photogrammetric point clouds (DAP). To date, much of the previously developed ITD methodologies have been developed for airborne laser scanning (ALS) and traditional aerial imagery. DAP is unique as it provides point cloud-based data as well as retaining the spectral information from the original images. This thesis analyzes the application and subsequent modification of an established tree detection routine to RPAS acquired DAP. In particular, modifications are proposed and evaluated which aim to improve its applicability to DAP, with particular emphasis on the incorporation of spectral information. The new routine, which utilizes point-level spectral information in sub-crown level clustering, improved overall true positive detection by ~6.3%, with the most significant improvements in true positive detection found in lower canopy class stems. The ITD routine was also tested without the inclusion of spectral information, and was shown to produce poorer results by ~4.1%; indicating that the inclusion of these data is beneficial for ITD approaches. This new ITD routine and the use of point level spectral information, represent an advancement of understanding the role of DAP for ITD in the era of RPAS remote sensing in forested environments.

Text

2019-10-28

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/72093

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/