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Mapping water content in drying Antarctic moss communities using UAS-borne SWIR imaging spectroscopy

Version 2 2024-01-30, 04:19
Version 1 2023-11-03, 05:11
journal contribution
posted on 2024-01-30, 04:19 authored by Darren TurnerDarren Turner, Emiliano CimoliEmiliano Cimoli, Arko LucieerArko Lucieer, Ryan HaynesRyan Haynes, Krystal Randall, Melinda J Waterman, Vanessa LucieerVanessa Lucieer, Sharon A Robinson
Antarctic moss beds are sensitive to climatic conditions, and both their survival and community composition are particularly influenced by the availability of liquid water over summer. As Antarctic regions increasingly face climate pressures (e.g., changing hydrology and heat waves), advancing capabilities to efficiently and non-destructively monitor water content in moss communities becomes a key research priority. Because of the complexity induced by multiple micro-climatic drivers and its fragility, tracking the evolution and responses of moss bed moisture requires monitoring methods that are non-intrusive, efficient, and spatially significant, such as the use of unoccupied aerial systems (UAS). In this study, we combine a multi-species drying laboratory experiment with short-wave infrared (SWIR) spectroscopy analyses to first develop a Random Forest regression Model (RFM) capable of predicting Antarctic moss turf water content (~5% error). The RFM was then applied to UAS-borne SWIR imaging data (900–1700 nm, <16 nm spectral resolution) of the moss beds at high spatial resolution (2 cm) across three sites in the vicinity of Casey Station, Antarctica. The sites differed in terrain, snow cover, and moisture availability to evaluate method capabilities under different conditions. Optimum RFM parameters and input variables (spectral indices and reflectance spectra) were determined. Maps of moss moisture were validated via acquiring moss spectra and water content (using sponges inserted into the moss turf) collected in situ, for which an exponential correlation (R2 = 0.72) was reported. RFM further allowed investigation of the influential spectral variables to model water content in moss and associated spectral water absorption features. We demonstrated that UAS-borne SWIR imaging is a promising new tool to map and quantify water content in Antarctic moss beds. Hyperspectral mapping facilitates the exploration of the spatial variability of moss health and enables the creation of a baseline against which changes in these moss communities can be measured.



  • Article

Publication title

Remote Sensing in Ecology and Conservation








Architecture and Design, Ecology and Biodiversity, Geography, Planning, and Spatial Sciences, TIA - Research Institute



Publication status

  • Published online

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Copyright 2023 The Authors. Remote Sensing in Ecology and Conservationpublished by John Wiley & Sons Ltd on behalf of Zoological Society of London. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivsLicense, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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