Abstract
Timely detection of insect infestation (or other disturbance) in a forest is vital for an adequate response plan to be developed. To determine the status of an active infestation of southern pine beetle (Dendroctonus frontalis) in the Bienville National Forest, WorldView-2 imagery was utilized. Principal components analysis (PCA) was performed and correlated with spectral reflectance bands to assess differences between the classification of spectral reflectance bands and principal components. Unsupervised classification of combinations of principal components (e.g., combining principal components 1 and 2, principal component 1 alone, and principal component 2 alone) was performed and compared with combinations of principal component correlations with spectral reflectance bands (e.g., all bands, bands 1–5, bands 6–8, and bands 2, 4, and 5). Combining principal components 1 and 2 was more accurate than other methods, closely followed by spectral bands 1–5. Employing PCA will aid resource managers in quickly detecting areas of active insect infestation and allow them to deploy adequate response measures to prevent or mitigate continued outbreaks.
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