Quantifying Structural Vegetation Change on Arctic Tundra: A Multi-Decadal Study Integrating Remotely Sensed Imagery and Traditional Field Measurements
Arctic regions have experienced an amplified rate of climate warming in recent decades, contributing to well-documented increases in tundra vegetation productivity. Satellite remote sensing has historically played a crucial role in detecting and quantifying trends at regional and biome scales; howev...
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| Format: | Thesis |
| Language: | unknown |
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University of Montana
2024
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| Online Access: | https://scholarworks.umt.edu/etd/12347 https://scholarworks.umt.edu/context/etd/article/13482/viewcontent/Moser_Thesis_Final.pdf |
| Summary: | Arctic regions have experienced an amplified rate of climate warming in recent decades, contributing to well-documented increases in tundra vegetation productivity. Satellite remote sensing has historically played a crucial role in detecting and quantifying trends at regional and biome scales; however, coarse resolution imagery has proven insufficient for capturing fine-scale variability in vegetation response. Considering the spatial heterogeneity of tundra vegetation, high resolution, plot-scale remote sensing observations are necessary. This study couples traditional field measurements with high-resolution unmanned aerial vehicle (UAV) imagery and plane-based aerial photos to quantify changes in vegetation on the North Slope of Alaska over a 28-year period. In-situ field measurements of vegetation characteristics were recorded in 1995 at a series of plots across the North Slope. Measurements were repeated in 2021 and 2023, revealing substantial increases in the overall mean canopy height and overall mean maximum shrub height, both of which doubled over the study period. Graminoid and deciduous shrub cover generally increased across the plots, with decreases in bryophytes and litter. Canopy height models (CHMs) for each site were previously derived by Ellenson 2022 from stereo color-infrared aerial photographs captured in 1995. High resolution UAV imagery of the sites was collected in 2023 and used to replicate the established photogrammetric processing workflow to generate CHMs at varying resolutions. The 2023 CHMs generally were more accurate in capturing both the mean measured canopy height and the variability in distribution of heights. Maximum shrub height was underestimated by CHMs at all resolutions for 2023. Both estimated canopy and maximum shrub heights consistently increased as pixel resolution increased for all plots, revealing a trend that necessitates further research to establish best practices for determining optimal spatial resolution of CHMs. Differences in microtopography and surface ... |
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