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Measuring height growth using airborne laser scanning and digital aerial photogrammetry in a disturbed Canadian boreal forest Rakofsky, Joseph
Abstract
Enhancing forest inventories using airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) is a spatially extensive means of providing accurate and consistent measures of forest stand structure. While the cost of multi-temporal ALS is still sometimes prohibitive to its integration for growth assessment, DAP point cloud data have been proposed as a cost-effective alternative to those from ALS for inventory re-measurement. As such, the primary objective of this thesis was to examine the capacity of ALS and DAP technologies to assess height growth (HL) in a disturbed boreal forest near Slave Lake, Alberta. First, this thesis determined the variables to be used in modeling height growth, and investigated how the predictive model errors responded to stand condition. To evaluate appropriate variables for predictive modeling, a model using only height metrics (growth_single) was compared with one using height, canopy cover and height variability metrics (growth_multi). The growth_multi model estimated height growth with an RMSE of 1.42 m (%RMSE = 164.18%) and the growth_single model estimated height growth with an RMSE of 1.76 m (%RMSE = 203.03%). To evaluate error response to stand condition, an iterative process was used to measure the accuracy of optimized height models while incrementing the mortality in the dataset. %RMSE increased with increasing plot-level mortality as a parabolic asymptotic curve. When the maximum allowable mortality was approximately 25% the %RMSE was just below 100%. Second, this thesis determined growth patterns near Slave Lake with respect to eight ecological variables, ecosite type and ecosite phase. Analysis of variance (ANOVA) tests were conducted to test the significances of differences between the means of height growth (ΔH). Patterns demonstrated by the ecological variables were most apparent using nutrient regime, moisture regime, species dominance and the soils classification. Growth patterns among ecosites and ecosite phases followed the patterns of the ecological variables that describe them. This research finds that, prior to utilizing multi-temporal remote sensing methods to assess stand-level height growth, forest managers must first understand local forest growth rates and mortality rates to ensure that the growth magnitudes and forest condition permit accurate height growth estimation using predictive models.
Item Metadata
Title |
Measuring height growth using airborne laser scanning and digital aerial photogrammetry in a disturbed Canadian boreal forest
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2019
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Description |
Enhancing forest inventories using airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) is a spatially extensive means of providing accurate and consistent measures of forest stand structure. While the cost of multi-temporal ALS is still sometimes prohibitive to its integration for growth assessment, DAP point cloud data have been proposed as a cost-effective alternative to those from ALS for inventory re-measurement. As such, the primary objective of this thesis was to examine the capacity of ALS and DAP technologies to assess height growth (HL) in a disturbed boreal forest near Slave Lake, Alberta.
First, this thesis determined the variables to be used in modeling height growth, and investigated how the predictive model errors responded to stand condition. To evaluate appropriate variables for predictive modeling, a model using only height metrics (growth_single) was compared with one using height, canopy cover and height variability metrics (growth_multi). The growth_multi model estimated height growth with an RMSE of 1.42 m (%RMSE = 164.18%) and the growth_single model estimated height growth with an RMSE of 1.76 m (%RMSE = 203.03%). To evaluate error response to stand condition, an iterative process was used to measure the accuracy of optimized height models while incrementing the mortality in the dataset. %RMSE increased with increasing plot-level mortality as a parabolic asymptotic curve. When the maximum allowable mortality was approximately 25% the %RMSE was just below 100%.
Second, this thesis determined growth patterns near Slave Lake with respect to eight ecological variables, ecosite type and ecosite phase. Analysis of variance (ANOVA) tests were conducted to test the significances of differences between the means of height growth (ΔH). Patterns demonstrated by the ecological variables were most apparent using nutrient regime, moisture regime, species dominance and the soils classification. Growth patterns among ecosites and ecosite phases followed the patterns of the ecological variables that describe them.
This research finds that, prior to utilizing multi-temporal remote sensing methods to assess stand-level height growth, forest managers must first understand local forest growth rates and mortality rates to ensure that the growth magnitudes and forest condition permit accurate height growth estimation using predictive models.
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Genre | |
Type | |
Language |
eng
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Date Available |
2019-04-17
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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 |
10.14288/1.0378284
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2019-05
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International