Abstract

Cryptogamic covers are a wide range of photoautotrophic plants which synthesize their own food while using sunlight as an energy source. Globally, cryptogrammic covers (such as cyanobacteria, algae, fungi, lichens, and bryophytes) annually uptake about 7% of the net primary production of terrestrial vegetation and account for about half of annual biological terrestrial nitrogen fixation. On the basis of these contributions to global carbon and nitrogen cycling, it is crucial to be able to accurately monitor seasonal and regional patterns of cryptogamic cover distribution and abundance. However, lichen-encrusted rock seldom comprises 100% of the ground cover within a pixel of remote-sensed imagery, and thereby arise challenges in lichen mapping and monitoring. Here we explore spectroscopic methods and spectral mixture analysis (SMA) to overcome the challenges of reflectance spectroscopy-based optical remote sensing detection and characterization of crustose lichen species. One suite of discrete wavelengths (λ1 = {400, 470, 520, 570, 680, 800, 1080, 1120, 1200, 1300, 1470, 1670, 1750, 2132, 2198, 2232 nm}) and two wavelength regions (λ2 = {λ: 800 nm ≤ λ ≤ 1300 nm} and λ3 = {λ: 2000 nm ≤ λ ≤ 2400 nm}) were investigated for their ability to discriminate between substrate and different lichen species. We found that the spectral region 800–1300 nm performed best at lichen-substrate differentiation and interspecial lichen differentiation. Furthermore, measures of central tendency from multiple wavelength regions are superior to most individual wavelength regions, particularly for lichen-rock unmixing.

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