Abstract
Balsam woolly adelgid is an invasive pest of firs in the United States. Aerial surveys are conducted for detection of adelgid infestations but other remotely sensed data may also be useful. Our objective was to determine if high spectral resolution, branch-level data can be used to distinguish infested from noninfested trees. Stepwise discriminant analysis yielded a three-variable model (the red-green index and two narrow-bands (one at 670 nm and the other at 1912 nm)) that classified infested versus non-infested trees with 94% accuracy compared with the 83% accuracy obtained with a single-variable model. The response of trees in narrow spectral bands was integrated across wavebands to simulate measurements from the multispectral SPOT5-HRVIR sensor. Stepwise discriminant analysis again yielded a three-variable model (simple ratio, the SPOT5-HRVIR band in the SWIR region and NDVI) with similar accuracy (93%) at discriminating infested from non-infested trees compared with the 83% accuracy obtained with a single-variable model.
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