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Assessing the utility of Airborne Laser Scanning for Terrestrial Ecosystem Mapping

University of British Columbia

Observing landscape patterns at various temporal and spatial scales is central to mapping ecosystems. Traditionally, ecosystem mapping uses a combination of fieldwork and aerial photography interpretation. These methods, however, are time-consuming, prone to subjectivity, and difficult to update. Airborne Laser Scanning (ALS) is an advanced remote sensing technology that has increased in application in the past decade and has the potential to significantly increase and refine information content of ecosystem mapping, especially in the vertical dimension. ALS technology provides detailed information on topography and vegetation structure and has considerable potential to be used for terrestrial ecosystem classification and mapping. In this thesis, the potential to use ALS data to advance ecosystem mapping is examined. The current state of the science for using ALS data to classify and map key ecosystem attributes within an existing ecosystem mapping scheme is discussed by focusing on British Columbia’s Terrestrial Ecosystem Mapping (TEM) and its associated Predictive Ecosystem Mapping (PEM). Based on a detailed literature review, a site-specific case study was also developed with the goal of mapping TEM polygons for a forested landscape on Vancouver Island, British Columbia. To do so an object-based image analysis approach was used. The analysis examined which were the best suite of ALS-based terrain and vegetation metrics to define and distinguish individual site series. It established a workflow for the classification of site series within the study site and examined the capacity to map site series based on ALS derived values. Best segmentation parameters were first established and then the study area was classified for slope position-wetness and finally into the specific site series. In the classification of site series two approaches were used. One approach used only terrain metrics and the other incorporated vegetation metrics. Overall accuracies were 59% and 56% respectively. While this workflow requires refinement, it shows potential for improved accuracies by applying suggestions discussed. The thesis concludes with a discussion summarizing the findings of this research and highlighting future refinement to the methods applied in the case study, while also providing recommendations for the current application of ALS technology to TEM.

Text

2017-07-31

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/62453

Forestry

University of British Columbia

UBCV

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