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Dryad

Data from: Hyperspectral imaging has a limited ability to remotely sense the onset of beech bark disease

Abstract

This dataset includes hyperspectral and beech bark disease assessment data from our study area, Mont-Saint-Bruno National Park in Saint-Bruno-de-Montarville, Quebec, Canada. Here, we tested whether airborne hyperspectral imagery - involving data from 344 wavelengths in the visible, near infrared (NIR), and shortwave infrared (SWIR) - can be used to assess the severity and progression of beech bark disease in southern Quebec, in the hope of developing new methods for effective remote sensing of this fungal infection that is widespread in eastern North America. Field data on disease severity were linked to airborne hyperspectral data using georeferenced red-green-blue (RGB) drone imagery to delineate beech crowns of interest. We also looked for a relationship between this same disease severity variable and hyperspectral data at leaf level (with canopy leaf samples). This dataset therefore comprises four sections: 1. Canopy-level hyperspectral data (n=126); 2. Crown geometries for the 126 beech trees with aerial hyperspectral imaging; 3. Leaf-level hyperspectral data on selected beech trees (n=37) and 4. Beech bark disease assessment data (n=160).