Identifying optimal spectral bands from in situ measurements of Great Lakes coastal wetlands using second-derivative analysis

Abstract

Extensive, in situ, reflectance spectra (i.e., 252 bands) were acquired for the dominant botanical and substrate classes within Prentiss Bay and Horseshoe Bay, Lake Huron. These spectral radiance measurements were transformed into relative percent reflectance and then resampled to emulate the band configurations of the airborne, hyperspectral imagery that was also acquired of the sites. Second-derivative analysis was applied to these transformed spectra in order to identify which spectral bands were the most botanically explanative (i.e., optimal) for the differentiation of coastal wetland vegetation in the Great Lakes. This research identified 8 optimal bands in the visible–NIR wavelength region (in order of decreasing importance: 685.5, 731.5, 939.9, 514.9, 812.3, 835.5, 823.9 and 560.1 nm) that appear to contain the majority of the coastal wetland information content of the full spectral resolution, 48-band, hyperspectral signatures. A reduction of band number without significant information loss is important because it makes it practical to utilize small pixels without fear of sacrificing the ability to differentiate the botanical communities.