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Using a micro-UAV for ultra-high resolution multi-sensor observations of Antarctic moss beds

Citation

Lucieer, A and Robinson, S and Turner, D and Harwin, S and Kelcey, J, Using a micro-UAV for ultra-high resolution multi-sensor observations of Antarctic moss beds, Proceedings of the 22nd International Society for Photogammetry and Remote Sensing Congress, 25 August - 1 September 2012, Melbourne, Australia, Internat Arch Photogram Remote Sens & Spat Inf Sci, pp. 429-433. ISSN 2194-9034 (2012) [Refereed Conference Paper]


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Copyright the Author(s) This work is distributed under the Creative Commons Attribution 3.0 License.

Official URL: https://www.int-arch-photogramm-remote-sens-spatia...

DOI: doi:10.5194/isprsarchives-XXXIX-B1-429-2012

Abstract

This study is the first to use an Unmanned Aerial Vehicle (UAV) for mapping moss beds in Antarctica. Mosses can be used as indicators for the regional effects of climate change. Mapping and monitoring their extent and health is therefore important. UAV aerial photography provides ultra-high resolution spatial data for this purpose. We developed a technique to extract an extremely dense 3D point cloud from overlapping UAV aerial photography based on structure from motion (SfM) algorithms. The combination of SfM and patch-based multi-view stereo image vision algorithms resulted in a 2 cm resolution digital terrain model (DTM). This detailed topographic information combined with vegetation indices derived from a 6-band multispectral sensor enabled the assessment of moss bed health. This novel UAV system has allowed us to map different environmental characteristics of the moss beds at ultra-high resolution providing us with a better understanding of these fragile Antarctic ecosystems. The paper provides details on the different UAV instruments and the image processing framework resulting in DEMs, vegetation indices, and terrain derivatives.

Item Details

Item Type:Refereed Conference Paper
Keywords:Unmanned Aerial Vehicle (UAV), Antarctica, moss beds, Structure from Motion (SfM) point cloud, terrain mapping, multispectral imagery
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Photogrammetry and Remote Sensing
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Antarctic and Sub-Antarctic Environments
UTAS Author:Lucieer, A (Professor Arko Lucieer)
UTAS Author:Turner, D (Dr Darren Turner)
UTAS Author:Harwin, S (Mr Stephen Harwin)
UTAS Author:Kelcey, J (Mr Joshua Kelcey)
ID Code:131717
Year Published:2012
Deposited By:Geography and Spatial Science
Deposited On:2019-04-01
Last Modified:2019-10-16
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