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Skip to Search Results- 19Remote Sensing
- 3Deep Learning
- 3Machine Learning
- 2Archaeology
- 2Computer Vision
- 2Convolutional Neural Network
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Spring 2012
Carbon and water fluxes are essential components of biospheric processes which directly or indirectly influence climate, surface energy balance, hydrologic processes and hence influence the vegetation productivity, distribution and characteristics. In this research, promising techniques for...
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Fall 2018
Terrestrial vegetation contributes strongly to dynamic biosphere-atmosphere exchanges of mass and energy, through activities such as photosynthesis, that help shape the Earth’s climate. The boreal forest is located in high latitudes and subject to large seasonal temperature fluctuations and a...
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Fall 2019
Photoacoustic imaging systems have proven to be power tools for visualizing optical absorption contrast within highly turbid media such as biological tissues. They provide high chromophore specificity in vivo due to the dramatic optical absorption contrast which exists between biological targets....
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Predictive Mapping of Yellow Rail (Coturnicops noveboracensis) Density and Abundance in the Western Boreal Forest via Ground and Satellite Remote Sensors
DownloadFall 2019
The Yellow Rail (Coturnicops noveboracensis) is a small, secretive, wetland bird, which is apparently rare throughout most of its range. Almost nothing is known about its abundance and density in the wetlands of the western boreal forest. Emerging technologies have enabled us to effectively...
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Fall 2022
The objective of signal decomposition is to extract and separate distinct signal components from a composite signal. Signal decomposition has been studied in many applications, such as image, video, audio, and speech signals. This thesis focuses on the category of signal decomposition on...
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Fall 2021
While research has been done in North America on the uses of various near surface geophysical techniques on european settler sites, the pre-contact sites of the First Nations people are often seen as too difficult to interpret separately from the environment they are in. This research set out to...
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Scalable Solutions to Image Abnormality Detection and Restoration using Limited Contextual Information
DownloadFall 2020
Detecting and interpreting image abnormalities and restoring images are essential to many processing pipelines in diverse fields. Challenges involved include randomness and unstructured nature of image artefacts (from signal processing perspective) and performance constraints imposed by...
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Fall 2023
Studying structural changes in tropical forests is essential for understanding changes in ecosystem complexity. In this thesis, I studied changes in ecosystem structure using two different airborne Light Detection and Range (LiDAR) systems collected 16-years apart (the 2005 dry season and the...
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Wildfire Fuel Mapping with Convolutional Neural Networks for Remote Automated Exposure Assessment
DownloadFall 2023
While beneficial to the natural environment in many cases, wildfires become hazardous when they intersect with the built environment. As such, there is an ongoing effort to understand the fire environment, the fuels it contains, and the way that wildfire interacts with the built environment. In...