Abstract

Lichen communities are known to be most resistant and adapted organisms to the extreme environments; however, their abundance is not well mapped. Extensive lichen surveys were conducted as part of the 39th Indian scientific expedition and in-situ spectra (350 nm–2500 nm) of lichens were collected in the Larsemann Hills, East Antarctica during austral summer of 2020. Lichen abundance mapping was carried out with the help of Sentinel-2 MSI L2 data and surveyed records along with in-situ spectra. We generated feature collections for lichen, snow, water, bare surface and trained a random forest (RF) classification algorithms implemented in GEE and generated multi-class outputs. We finally merged all non-lichen classes and produced binary pixels with a confidence value (between 0 and 100) depicting similarity of its spectral response to that of a lichen pixel. Total 92 lichen points, 20 bare rock points, 26 points of water and 74 snow points were used to generate the probabilistic lichen abundance map. Resubstitution accuracy of 97.31% was obtained with 10 number of RF trees. Validation was done with geotagged ground photographs having 232 lichens, 20 bare rocks, 22 water and 69 snow points and achieved test accuracy of 82.44%.

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