Using an Unmanned Aerial Vehicle (UAV) for ultra-high resolution mapping of Antarctic moss beds

Polar regions are experiencing rapid and severe climatic shifts with major changes in temperature, wind speed and UV-B radiation already observed in Antarctica. Since vegetation is isolated to the coastal fringe and climatic records only extend back 50 years, with limited spatial resolution, we urgently need new proxies to determine if coastal climate has changed over the past century. In a manner similar to trees, old growth mosses also preserve a climate record along their shoots. Our ability to accurately date these mosses and map their extent in sufficient spatial detail means that, for the first time, mosses can be used as sentinels to provide crucial information on how the Antarctic coastal climate has changed over past centuries and how biota has responded to these changes. The spatial scale of the moss beds (tens of m2) makes satellite imagery (even very high resolution imagery of 0.5 m) unsuitable for mapping their extent in sufficient detail. Due to logistical constraints aerial photography is impractical. Recent developments in the use of unmanned aerial vehicles (UAVs) for remote sensing applications provide exciting new opportunities for ultra-high resolution mapping and monitoring of the environment. In this study, we developed a UAV consisting of a remote controlled helicopter carrying three different cameras: visible colour, near-infrared, and thermal infrared for cost-effective, efficient, and ultra-high resolution mapping of terrestrial vegetation in the Windmill Islands, Antarctica. These three sensors allow us to map different physical characteristics of the moss beds at resolutions of several centimetres. This paper and presentation will address the issues encountered in developing a UAV system, discuss the different UAV sensors and components, and demonstrate how this system can be applied in these fragile remote polar ecosystems.

[1]  T. Schmugge,et al.  Research Article: Using Unmanned Aerial Vehicles for Rangelands: Current Applications and Future Potentials , 2006 .

[2]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[3]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[4]  R. Dunford,et al.  Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest , 2009 .

[5]  John Turner,et al.  Antarctic climate change and the environment , 2009, Antarctic Science.

[6]  Craig S. T. Daughtry,et al.  Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring , 2010, Remote. Sens..

[7]  Ryosuke Shibasaki,et al.  UAV-Borne 3-D Mapping System by Multisensor Integration , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Arko Lucieer,et al.  Constraints on transport and weathering of petroleum contamination at Casey Station, Antarctica , 2007 .

[9]  An Unmanned Aerial Vehicle for Rangeland Photography , 2005 .

[10]  Sharon A. Robinson,et al.  Living on the edge – plants and global change in continental and maritime Antarctica , 2003 .

[11]  J. Turner,et al.  Antarctic climate change during the last 50 years , 2005 .

[12]  Albert Rango,et al.  Texture and Scale in Object-Based Analysis of Subdecimeter Resolution Unmanned Aerial Vehicle (UAV) Imagery , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Frédéric Baret,et al.  Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots , 2008, Sensors.

[14]  Sharon A. Robinson,et al.  Surface reflectance properties of Antarctic moss and their relationship to plant species, pigment composition and photosynthetic function , 2002 .

[15]  Peter A. Burrough,et al.  High-resolution landform classification using fuzzy k-means , 2000, Fuzzy Sets Syst..

[16]  Jose A. Jiménez-Berni,et al.  A new era in remote sensing of crops with unmanned robots , 2008 .

[17]  Sharon A. Robinson,et al.  Some like it wet - biological characteristics underpinning tolerance of extreme water stress events in Antarctic bryophytes. , 2006, Functional plant biology : FPB.

[18]  Guoqing Zhou,et al.  Foreword to the Special Issue on Unmanned Airborne Vehicle (UAV) Sensing Systems for Earth Observations , 2009, IEEE Trans. Geosci. Remote. Sens..

[19]  M. Hutchinson A new procedure for gridding elevation and stream line data with automatic removal of spurious pits , 1989 .