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Relationship Between Image Spectroscopy Spatial Resolution And Crown Level Tree Species Classification Accuracy, Andrew Richard Fritter

Dissertations and Theses

Hyperspectral imagery has become a common remote sensing data type used in tree species classifications because of its rich spectral signals that allow the detection of the variations in canopy reflectance. While high spatial resolution hyperspectral imagery provides fine spatial resolution for discerning surface objects, it has the inherent drawbacks of expensive acquisition costs, large data sizes, and can be computationally taxing to use. This study attempts to determine a relationship between crown level tree species classification accuracy and hyperspectral spatial resolution. Future tree species classification projects can make use of this relationship by targeting a spatial resolution that best …