Thermal remote sensing of mountain pine beetle green attack

Date
2022-03
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Abstract
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.
Description
Keywords
Mountain Pine Beetle, Thermal imaging, Green attack, Drone
Citation
Mckeeman, T. (2022). Thermal remote sensing of mountain pine beetle green attack (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.