Volume XXXIX-B1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B1, 429-433, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B1-429-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B1, 429-433, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B1-429-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

  27 Jul 2012

27 Jul 2012

USING A MICRO-UAV FOR ULTRA-HIGH RESOLUTION MULTI-SENSOR OBSERVATIONS OF ANTARCTIC MOSS BEDS

A. Lucieer, S. Robinson, D. Turner, S. Harwin, and J. Kelcey A. Lucieer et al.
  • School of Geography and Environmental Studies, Surveying and Spatial Sciences Group University of Tasmania Private Bag 76, Hobart, Tasmania 7001, Australia

Keywords: Unmanned Aerial Vehicle (UAV), Antarctica, moss beds, Structure from Motion (SfM) point cloud, terrain mapping, multispectral imagery

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.