Assessing terrain modelling and forest inventory capabilities of digital aerial photogrammetry from autonomous aerial systems
department or school: Forestry, Faculty of
data provider: DSpace
degree campus: UBCV
creator: Graham, Alexander Naoki Vernon
issued: 2019-08-27T17:58:47Z
issued: 2019
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Autonomous aerial systems-based digital aerial photogrammetry (AAS-DAP) is an emerging technology that has the capacity to generate dense three-dimensional (3D) point clouds similar to airborne laser scanning (ALS). Over forested stands, these point-clouds can be used to model forest attributes using an area-based approach however, model accuracy is dependent on digital elevation model quality used to gather vegetation heights above ground. It is known that canopy occlusion contributes to larger gaps in terrain registration from AAS-DAP compared to ALS point clouds. Due to the recent emergence of AAS-DAP as a cost-effective remote sensing platform, few studies have investigated the terrain modelling and forest inventory capacity of AAS-DAP over complex conifer forests. In Chapter 3, through the use of a sensitivity analysis, I established a set of optimal ground points from AAS-DAP by using commercially provided ALS ground points as reference. This optimal set of ground points was then used to test common terrain surface interpolation routines in Chapter 4. Interpolation routines include inverse-distance weighted, natural neighbour, triangulated irregular network, and spline with tension. Using field-measured tree height and stem diameter, allometric relationships were established for dependent variables: mean tree height (Hmean), Lorey’s height (HLorey) and stem volume per hectare (Vstem). Models were then fit among dependent variables and metrics calculated from the vertical distribution of the AAS-DAP point cloud normalized by the different AAS-DAP terrain surfaces in addition to a reference surface generated from commercially provided ALS ground points. A Kruskal-Wallis with Dunn’s posthoc test found no significant difference between predictions derived from different terrain surfaces for all three dependent variables; however, the inverse-distance-weighted method produced a distribution of predictions most similar to those from the ALS-DEM. The best performing …
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/71482
note: ASSESSING TERRAIN MODELLING AND FOREST INVENTORY CAPABILITIES OF DIGITAL AERIAL PHOTOGRAMMETRY FROM AUTONOMOUS AERIAL SYSTEMS by Alexander Naoki Vernon Graham B.A., The University of British Columbia, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2019 © Alexander Graham, 2019 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis/dissertation entitled: Assessing terrain modelling and forest inventory capabilities of digital aerial photogrammetry from autonomous aerial systems submitted by Alexander Graham in partial fulfillment of the requirements for the degree of Master of Science in Forestry Examining Committee: Nicholas C. Coops, Forest Resource Management, Forestry Supervisor Allan L. Carroll, Forest and Conservation Sciences, Forestry Supervisory Committee Member Mike Wilcox, FYBR Solutions Inc. Supervisory Committee Member Naomi B. Schwartz, Geography, Arts Additional Examiner Additional Supervisory Committee Members: Supervisory Committee Member Supervisory Committee Member iii Abstract Autonomous aerial systems-based digital aerial photogrammetry (AAS-DAP) is an emerging technology that has the capacity to generate dense three-dimensional (3D) point clouds similar to airborne laser scanning (ALS). Over forested stands, these point-clouds can be used to model forest attributes using an area-based approach however, model accuracy is dependent on digital elevation model quality used to gather vegetation heights above ground. It is known that canopy occlusion contributes to larger gaps in terrain registration from AAS-DAP compared to ALS point clouds. Due to the recent emergence of AAS-DAP as a cost-effective remote sensing platform, few studies have investigated the terrain modelling and forest in…
has type: Thesis/Dissertation
date issued: 2019-11
is shown at: 10.14288/1.0380670
language: eng
degree discipline: Forestry
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/71482