Browsing by Author "Mckeeman, Taylor"

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    Thermal remote sensing of mountain pine beetle green attack
    (2022-03) Mckeeman, Taylor; McDermid, Greg; Castilla, Guillermo; Reid, Mary
    Mountain pine beetle (Dendroctonus ponderosae Hopkins, MPB) has caused extensive damage in the forests of western North America. There has been little success in identifying affected trees at the green-attack stage via remote sensing: a goal that would greatly support targeted management efforts to reduce the spread during times of epidemic populations. High-resolution thermal remote sensing has yet to be tested for this application. In this thesis I describe the theoretical foundations that explain why the measurement of thermal radiance is a justified approach to green-attack detection. I then develop experiments in a greenhouse and in forest stands of lodgepole pine to simulate MPB attack and to test my two proposed hypotheses: the warm-tree effect and the cool-tree effect. In the greenhouse, completely green and healthy-looking geraniums showed statistically significant warming trends after 10 hours of droughting compared to watered subjects, revealing an estimated difference of 1.5 degrees Celsius in minimum canopy temperature and support for the warm-tree effect. The cool-tree effect (not observed in the greenhouse) was detected in one of my field sites, but a review of the data revealed suspicious patterns which led to an indeterminate conclusion regarding its validity. Patterns of the warm tree effect were visible in my second field site early on, but then seemed to vanish as the experiment progressed. I speculated that the 10- to 20-year drought that began during my study period explains my observations most appropriately, though explorative modelling of its impacts showed low relative predictive power. I subsequently concluded that the validity of the warm-tree effect, though promising, was also indeterminant and that it requires further investigation. This work should be applied in further research to validate the warm-tree effect in actual MPB green-attack trees. These efforts should consider using the minimum or 5th percentile canopy measurements (found to be the strongest metric) and controlling for the potential impacts from incoming solar radiation and the distance from tree to sensor.
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    A Workflow to Minimize Shadows in UAV-based Orthomosaics
    (Journal of Unmanned Vehicle Systems, NRC Research Press, 2019-01-08) Rahman, Mir Mustafizur; McDermid, Gregory J.; Mckeeman, Taylor; Lovitt, Julie
    Shadows from buildings, terrain, and other elevated features represent lost and/or impaired data values that hinder the quality of optical images acquired under all but the most diffuse illumination conditions. This is particularly problematic in high-spatial-resolution imagery acquired from unmanned aerial vehicles (UAVs), which generally operate very close to the ground. However, the flexibility and low cost of re-deployment of the platform also presents opportunities, which we capitalize on in a new workflow designed to eliminate shadows from UAV-based orthomosaics. Our straightforward, three-step procedure relies on images acquired from two different UAV flights, where illumination conditions produce diverging shadow orientations: one before solar noon and another after. From this multi-temporal image stack, we first identify and then eliminate shadows from individual orthophoto components, then construct the final orthomosaic using a feature-matching strategy with the commercial software package Photoscan. The utility of our strategy is demonstrated over a treed-wetland study site in northwestern Alberta, Canada: a complex scene containing wide variety of shadows, which our workflow effectively eliminated. While shadow-reduced orthomosaics are generally less useful for feature-identification tasks that rely on the shadow element of image interpretation, they create a superior foundation for most other image-processing routines, including classification and change-detection.