Using an Unmanned Aerial Vehicle (UAV) to capture micro-topography of Antarctic moss beds

Mosses, the dominant flora of East Antarctica, show evidence of drying in recent decades, likely due to the regional effects of climate change. Given the relatively small area that such moss beds occupy, new tools are needed to map and monitor these fragile ecosystems in sufficient detail. In this s...

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Bibliographic Details
Published in:International Journal of Applied Earth Observation and Geoinformation
Main Authors: Lucieer, A, Turner, D, King, DH, Robinson, SA
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier Science Bv 2014
Subjects:
Engineering
Geomatic Engineering
Photogrammetry and Remote Sensing
Antarctic
East Antarctica
Antarc*
Antarctica
Online Access:https://doi.org/10.1016/j.jag.2013.05.011
http://ecite.utas.edu.au/88475
Description
Summary:Mosses, the dominant flora of East Antarctica, show evidence of drying in recent decades, likely due to the regional effects of climate change. Given the relatively small area that such moss beds occupy, new tools are needed to map and monitor these fragile ecosystems in sufficient detail. In this study, we collected low altitude aerial photography with a small multi-rotor Unmanned Aerial Vehicle (UAV). Structure from Motion (SfM) computer vision techniques were applied to derive ultra-high resolution 3D models from multi-view aerial photography. A 2cmdigital surface model (DSM) and 1cmorthophoto mosaic were derived from the 3D model and aerial photographs, respectively. The geometric accuracy of the orthophoto and DSM was 4cm. A weighted contributing upstream area was derived with the D-infinity algorithm, based on the DSM and a snow cover map derived from the orthophoto. The contributing upstream area was used as a proxy for water availability from snowmelt, one of the key environmental drivers of moss health. A Monte Carlo simulation with 300 realisations was implemented to model the impact of error in the DSM on runoff direction. Significant correlations were found between these simulated water availability values and field measurements of moss health and water content. In the future ultra-high spatial resolution DSMs acquired with a UAV could thus be used to determine the impact of changing snow cover on the health and spatial distribution of polar vegetation non-destructively.

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