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UBC Theses and Dissertations
Characterizing post-fire tree attributes using quantitative structure models based on drone and mobile laser scanning point clouds Qi, Yangqian
Abstract
Wildfires burn with a mixture of severities across the landscape and create complex forest structures. Quantifying the structural changes in post-fire forests is critical to evaluating the ecological impacts of wildfires. Advances in drone laser scanning (DLS) and mobile laser scanning (MLS) have enabled the acquisition of high-density point clouds to better resolve detailed tree structures. Yet, few studies have examined their combined capability to describe forest structures. To characterize post-fire tree attributes in interior dry forests in British Columbia, nine study sites in the area burned by the 2017 Elephant Hill wildfire were scanned in 2019 using DLS and MLS. First, I examined the utility of DLS and MLS both individually and combined to estimate tree attributes using quantitative structure models (QSMs) across varying canopy cover levels. Second, I investigated the QSM-derived tree attributes to interpret the effects of burn severities at individual tree and plot scales. The results showed that the fused laser scanning datasets outperformed single laser scanning datasets in estimating tree attributes across canopy cover levels. Specifically, with increasing canopy cover, diameter at breast height, crown diameter, and crown base height were best predicted using the fused data. Height was accurate regardless of canopy cover, which was independent of data collection platforms. Tree volumes could be best modelled by the fused data with increasing canopy cover. In terms of burn severities, the results suggested that smaller pre-fire trees tend to experience higher levels of crown scorch than larger pre-fire trees. Among trees with similar pre-fire sizes, those within mature stands experienced relatively lower levels of crown scorch than those within young stands. At the plot level, low-severity fires had minor effects, moderate-severity fires mostly decreased tree height, and high-severity fires significantly reduced diameter at breast height, height, and biomass. The results also revealed that stands dominated by trees with large crowns and relatively wide spacing could burn less severely than stands characterized by regenerating trees with high densities. The findings of this thesis facilitate forestry practitioners to select appropriate laser scanning tools in forest inventory assessment and develop site-specific management plans for fire-prone forests.
Item Metadata
Title |
Characterizing post-fire tree attributes using quantitative structure models based on drone and mobile laser scanning point clouds
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2022
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Description |
Wildfires burn with a mixture of severities across the landscape and create complex forest structures. Quantifying the structural changes in post-fire forests is critical to evaluating the ecological impacts of wildfires. Advances in drone laser scanning (DLS) and mobile laser scanning (MLS) have enabled the acquisition of high-density point clouds to better resolve detailed tree structures. Yet, few studies have examined their combined capability to describe forest structures. To characterize post-fire tree attributes in interior dry forests in British Columbia, nine study sites in the area burned by the 2017 Elephant Hill wildfire were scanned in 2019 using DLS and MLS. First, I examined the utility of DLS and MLS both individually and combined to estimate tree attributes using quantitative structure models (QSMs) across varying canopy cover levels. Second, I investigated the QSM-derived tree attributes to interpret the effects of burn severities at individual tree and plot scales.
The results showed that the fused laser scanning datasets outperformed single laser scanning datasets in estimating tree attributes across canopy cover levels. Specifically, with increasing canopy cover, diameter at breast height, crown diameter, and crown base height were best predicted using the fused data. Height was accurate regardless of canopy cover, which was independent of data collection platforms. Tree volumes could be best modelled by the fused data with increasing canopy cover. In terms of burn severities, the results suggested that smaller pre-fire trees tend to experience higher levels of crown scorch than larger pre-fire trees. Among trees with similar pre-fire sizes, those within mature stands experienced relatively lower levels of crown scorch than those within young stands. At the plot level, low-severity fires had minor effects, moderate-severity fires mostly decreased tree height, and high-severity fires significantly reduced diameter at breast height, height, and biomass. The results also revealed that stands dominated by trees with large crowns and relatively wide spacing could burn less severely than stands characterized by regenerating trees with high densities. The findings of this thesis facilitate forestry practitioners to select appropriate laser scanning tools in forest inventory assessment and develop site-specific management plans for fire-prone forests.
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Genre | |
Type | |
Language |
eng
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Date Available |
2022-08-12
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0417307
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2022-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
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DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International