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Nuijten, Rik Johannes Gerardus

University of British Columbia

To maintain a (social) license to operate, which depends on support from local communities, society, and regulatory bodies, managers in natural resource extraction are increasingly engaged in ecological restoration and reclamation, as well as continuous assessments of ecosystem recovery. This necessitates information on ecosystem status throughout the planning, implementation, and evaluation phases of restoration. Over the last decade, digital aerial photogrammetry (DAP) using drone-based optical imagery has emerged as a cost-effective technique for assessing various ecosystem attributes, such as plant functional type composition. However, its effectiveness for early successional forest ecosystems remains under-explored. The primary goal of this dissertation is to evaluate the role of drone-based DAP in providing spatially explicit, valuable, and cost-effective insights into ecosystem recovery by characterizing a wide range of ecosystem attributes. I acquired three-dimensional (3D) point clouds and multispectral ortho imagery for pipeline right-of-ways (ROW) and wildfire-disturbed sites in Northwest Alberta, Canada. The strengths and limitations in characterizing vegetation structure were examined by comparing modelled canopy heights with field measurements, and analyzing maps derived from point clouds using unsupervised learning techniques. Further, I assessed the capacity to map dominant plant species and functional types, through logistic regression modelling, utilizing metrics that describe spectral reflectance, vegetation structure, and habitat characteristics. A framework was introduced to incorporate reference sites, facilitate species composition comparisons between sites from drone-derived maps, and support ecological interpretation of spatial patterns. I also examined the uncertainty and complexity of information from drone approaches (including alternative technologies to DAP) based on a systematic literature review and sentiment analysis. Lastly, I determined the spatial coverage at which drone approaches can be more cost-effective than field-based approaches, incorporating data acquisition, processing, and analysis costs. This dissertation aims to encourage broader adoption of drone-based remote sensing in ecosystem recovery assessments and to foster interdisciplinary collaboration, particularly in areas where costs, information uncertainty, and complexities can be effectively managed and reduced.

Text

2024-06-25

Attribution-ShareAlike 4.0 International

http://hdl.handle.net/2429/88515

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-sa/4.0/