Using an unmanned aerial vehicle (UAV) to capture micro-topography of antarctic moss beds

International Journal of Applied Earth Observation and Geoinformation

Volumn 27, Issue PARTA, 2014, Pages 53-62

  Lucieer, Arko ^a   Turner, Darren ^a   King, Diana H ^b   Robinson, Sharon A ^b  

^a UNIVERSITY OF TASMANIA   (Australia)

^b UNIVERSITY OF WOLLONGONG   (Australia)

Author keywords

Digital surface model (DSM); Moss health; Multi view stereopsis; Snowmelt; Structure from motion (SfM); Water availability

Indexed keywords

ACCURACY ASSESSMENT; ALGORITHM; CLIMATE EFFECT; COMPUTER SIMULATION; IMAGE RESOLUTION; MICROTOPOGRAPHY; MONTE CARLO ANALYSIS; MOSS; ORTHOPHOTO; SNOW COVER; SNOWMELT; SPATIAL RESOLUTION; THREE-DIMENSIONAL MODELING; UNMANNED VEHICLE; WATER AVAILABILITY;

ANTARCTICA;

BRYOPHYTA;

EID: 84894272759     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2013.05.011     Document Type: Article

References (53)

1. Abudu, S., Cui, C., Saydi, M., King, J.P., 2012. Application of snowmelt runoff model(SRM) in mountainous watersheds: a review. Water Science and Engineering 5, 123-136.
2. Adams, B., Arthern, R., Bromwich, D., Marshall, G., Worby, T., Bockheim, J., di Prisco,G., Verde, C., Convey, P., Roscoe, H., Jones, A., Vaughan, D., Woodworth, P.,Scambos, T., Cook, A., Lenton, A., Comiso, J., Gugliemin, M., Summerhayes, C.,Meredith, M., Naveira-Garabato, A., Chown, S., Stevens, M., Worland, R., Hen-nion, F., Huiskes, A., Bergstrom, D., Hodgson, D., Bindschadler, R., Bargagli, R.,Metzl, N., van der Veen, K., Monaghan, A., Speer, K., Rintoul, S., Hellmer, H.,Jacobs, S., Heywood, K., Holland, D., Yamanouchi, T., Barbante, C., Bertler, N.,Boutron, C., Hong, S., Mayewski, P., Fastook, J., Newsham, K., Robinson, S.A., Forcarda, J., Trathan, P., Turner, J., Smetac, V., Gutt, J., Pörtner, H., Peck, L.,Gili, J., Wiencke, C., Fahrbach, E., Atkinson, A., Webb, D., Isla, E., Orejas, C., Rossi, S., Shanklin, J., 2009. The instrumental period. In: Turner, J., Bindschadler,R., Convey, P., Di Prisco, G., Fahrbach, E., Gutt, J., Hodgson, D., Mayewski, P., Summerhayes, C. (Eds.), Antarctic Climate Change and the Environment. Sci-entific Committee for Antarctic Research (SCAR), Cambridge, pp. 183-298, URL http://www.scar.org/publications/occasionals/acce.html
3. Anisimov, O., Fitzharris, B., Hagen, J., Jefferies, B., Marchant, H., Nelson, F., Prowse, T., Vaughan, D., 2001. Polar regions (Arctic and Antarctic). In: McCarthy, J.,Canziani, O., Leary, N., Dokken, D., White, K. (Eds.), Climate Change 2001:Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to theThird Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge University Press, Cambridge, pp. 801-841.
4. Brabyn, L., Beard, C., Seppelt, R., Rudolph, E., Türk, R., Green, T., 2006. Quantified veg-etation change over 42 years at Cape Hallett, East Antarctica. Antarctic Science18, 561-572.
5. Chen, J.L., Wilson, C.R., Blankenship, D., Tapley, B.D., 2009. Accelerated Antarctic iceloss from satellite gravity measurements. Nature Geoscience 2, 859-862.
6. Clarke, L.J., Robinson, S.A., Hua, Q., Ayre, D.J., Fink, D., 2012. Radiocarbon bomb spikereveals biological effects of Antarctic climate change. Global Change Biology 18,301-310.
7. Convey, P., Bindschadler, R., di Prisco, G., Fahrbach, E., Gutt, J., Hodgson, D., Mayewski,P., Summerhayes, C., Turner, J., 2009. Antarctic climate change and the environ-ment. Antarctic Science 21, 541.
8. D'Oleire-Oltmanns, S., Marzolff, I., Peter, K., Ries, J., 2012. Unmanned Aerial Vehicle(UAV) for monitoring soil erosion in Morocco. Remote Sensing 4, 3390-3416.
9. Eisenbeiss, H., Sauerbier, M., 2011. Investigation of UAV systems and flight modesfor photogrammetric applications. Photogrammetric Record 26, 400-421.
10. Emslie, S.D., Woehler, E.J., 2005. A 9000-year record of Adélie penguin occupationand diet in the Windmill Islands, East Antarctica. Antarctic Science 17, 57-66.
11. Giesbrecht, M., Woo, M., 2000. Simulation of snowmelt in a subarctic spruce wood-land: Open woodland model. Water Resources Research 36, 2287-2295.
12. Hardin, P.J., Jensen, R.R., 2011. Small-scale unmanned aerial vehicles in environmen-tal remote sensing: challenges and opportunities. GIScience & Remote Sensing 48, 99-111.
13. Harwin, S., Lucieer, A., 2012. Assessing the accuracy of georeferenced point cloudsproduced via multi-view stereopsis from unmanned aerial vehicle (UAV)imagery. Remote Sensing 4, 1573-1599.
14. Hengl, T., Heuvelink, G.B.M., van Loon, E.E., 2010. On the uncertainty of streamnetworks derived from elevation data: the error propagation approach. Hydrol-ogy and Earth System Sciences 14, 1153-1165.
15. Höhle, J., Höhle, M., 2009. Accuracy assessment of digital elevation models by meansof robust statistical methods. ISPRS Journal of Photogrammetry and RemoteSensing 64, 398-406.
16. Kopecký, M.,Čížková, S., 2010. Using topographic wetness index in vegetation ecol-ogy: does the algorithm matter? Applied Vegetation Science 13, 450-459.
17. Lewis Smith, R.I., 1988. Classification and ordination of cryptogamic communitiesin Wilkes Land, Continental Antarctica. Vegetatio 76, 155-166.
18. Lewis Smith, R.I., 1990. Plant community dynamics in Wilkes Land, Antarctica. In:Proceedings of the NIPR Symposium on Polar Biology, pp. 229-244.
19. Lovelock, C., Robinson, S.A., 2002. Surface reflectance properties of Antarctic mossand their relationship to plant species, pigment composition and photosyntheticfunction. Plant, Cell & Environment 25, 1239-1250.
20. Lowe, D.G., 2004. Distinctive image features from scale-invariant keypoints. Inter-national Journal of Computer Vision 60, 91-110.
21. Marks, D., Domingo, J., Susong, D., 1999. A spatially distributed energy balancesnowmelt model for application in mountain basins. Hydrological Processes 13,1935-1959.
22. Melick, D.R., Hovenden, M.J., Seppelt, R.D., 1994. Phytogeography of bryophyte andlichen vegetation in the Windmill Islands, Wilkes Land, Continental Antarctica.Vegetatio 111, 71-87.
23. Newsham, K.K., Robinson, S.A., 2009. Responses of plants in polar regions to UVBexposure: a meta-analysis. Global Change Biology 15, 2574-2589.
24. Niethammer, U., James, M.R., Rothmund, S., Travelletti, J., Joswig, M., 2012. UAV-based remote sensing of the Super-Sauze landslide: evaluation and results.Engineering Geology 128, 2-11.
25. Oksanen, J., Sarjakoski, T., 2005. Error propagation of DEM-based surface derivatives.Computers & Geosciences 31, 1015-1027.
26. Perlwitz, J., Pawson, S., Fogt, R.L., Nielsen, J.E., Neff, W.D., 2008. Impact of strato-spheric ozone hole recovery on Antarctic climate. Geophysical Research Letters35, L08714.
27. Rango, A., Laliberte, A., Steele, C., Herrick, J., Bestelmeyer, B., Schmugge, T., Roan-horse, A., Jenkins, V., 2006. Using unmanned aerial vehicles for rangelands:current applications and future potentials. Environmental Practice 8, 159-168.
28. Revill, A.T., Snape, I., Lucieer, A., Guille, D., 2007. Constraints on transport and weath-ering of petroleum contamination at Casey Station, Antarctica. Cold RegionsScience and Technology 48, 154-167.
29. Robinson, S.A., Wasley, J., King, D., 2012. State of Environment Indicator 72-Windmill Islands terrestrial vegetation dynamics, URL: https://data.aad.gov.au/aadc/soe/displayindicator.cfm?soe id=72
30. Robinson, S.A., Wasley, J., Tobin, A.K., 2003. Living on the edge-plants and globalchange in continental and maritime Antarctica. Global Change Biology 9, 1681-1717.
31. Rosnell, T., Honkavaara, E., 2012. Point cloud generation from aerial image dataacquired by a quadrocopter type micro unmanned aerial vehicle and a digitalstill camera. Sensors 12, 453-480.
32. Royles, J., Ogée, J., Wingate, L., Hodgson, D.A., Convey, P., Griffiths, H., 2012. Carbonisotope evidence for recent climate-related enhancement of CO2assimila-tion and peat accumulation rates in Antarctica. Global Change Biology 18, 3112-3124.
33. Selkirk, P.M., Seppelt, R.D., 1987. Species distribution within a moss bed in GreaterAntarctica. Symposia Biologica Hungarica 25, 279-284.
34. Selkirk, P.M., Skotnicki, M.L., 2007. Measurement of moss growth in continentalAntarctica. Polar Biology 30, 407-413.
35. Snavely, N., Seitz, S.M., Szeliski, R., 2007. Modeling the world from internet photocollections. International Journal of Computer Vision 80, 189-210.
36. Son, S.W., Gerber, E.P., Perlwitz, J., Polvani, L.M., Gillett, N.P., Seo, K.H., Eyring, V.,Shepherd, T.G., Waugh, D., Akiyoshi, H., Austin, J., Baumgaertner, A., Bekki, S.,Braesicke, P., Brühl, C., Butchart, N., Chipperfield, M.P., Cugnet, D., Dameris,M., Dhomse, S., Frith, S., Garny, H., Garcia, R., Hardiman, S.C., Jöckel, P., Lamar-que, J.F., Mancini, E., Marchand, M., Michou, M., Nakamura, T., Morgenstern, O.,Pitari, G., Plummer, D.A., Pyle, J., Rozanov, E., Scinocca, J.F., Shibata, K., Smale, D.,Teyssèdre, H., Tian, W., Yamashita, Y., 2010. Impact of stratospheric ozone onSouthern Hemisphere circulation change: a multimodel assessment. Journal ofGeophysical Research 115.
37. Tarboton, D.G., 1997. A new method for the determination of flow directions andupslope areas in grid digital elevation models. Water Resources Research 33,309-319.
38. Tesfa, T.K., Tarboton, D.G., Watson, D.W., Schreuders, K.A.T., Baker, M.E., Wallace,R.M., 2011. Extraction of hydrological proximity measures from DEMs usingparallel processing. Environmental Modelling & Software 26, 1696-1709.
39. Thompson, D.W.J., Solomon, S., 2002. Interpretation of recent Southern Hemisphereclimate change. Science (New York, NY) 296, 895-899.
40. Turner, D., Lucieer, A., Watson, C., 2012. An automated technique for generatinggeorectified mosaics from ultra-high resolution unmanned aerial vehicle (UAV)imagery, based on structure from motion (SfM) point clouds. Remote Sensing 4,1392-1410.
41. Turner, J., Barrand, N.E., Bracegirdle, T.J., Convey, P., Hodgson, D.A., Jarvis, M., Jenk-ins, A., Marshall, G., Meredith, M.P., Roscoe, H., Shanklin, J., French, J., Goosse,H., Guglielmin, M., Gutt, J., Jacobs, S., Kennicutt, M.C., Masson-Delmotte, V.,Mayewski, P., Navarro, F., Robinson, S.A., Scambos, T., Sparrow, M., Summer-hayes, C., Speer, K., Klepikov, A., 2013. Antarctic climate change and the environ-ment: an update. Polar Record, http://dx.doi.org/10.1017/S0032247413000296,in press.
42. Turner, J., Bindschadler, R., Convey, P., Di Prisco, G., Fahrbach, E., Gutt, J., Hodg-son, D., Mayewski, P., Summerhayes, C., 2009. Antarctic Climate Change and theEnvironment. Scientific Committee for Antarctic Research (SCAR), Cambridge.
43. Vallet, J., Panissod, F., Strecha, C., Tracol, M., 2012. Photogrammetric performanceof an ultra light weight swinglet 'UAV'. In: ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII-1/C22, UAV-g 2011 Conference on Unmanned Aerial Vehicle in Geomatics,Zurich, Switzerland, pp. 253-258.
44. Verhoeven, G., 2011. Taking computer vision aloft-archaeological three-dimensional reconstructions from aerial photographs with Photoscan. Archae-ological Prospection 18, 67-73.
45. Wang, J., Li, W., 2001. Establishing snowmelt runoff simulating model using remotesensing data and GIS in the west of China. International Journal of RemoteSensing 22, 3267-3274.
46. Wasley, J., Robinson, S.A., Lovelock, C.E., Popp, M., 2006a. Climate change manipula-tions show Antarctic flora is more strongly affected by elevated nutrients than water. Global Change Biology 12, 1800-1812.
47. Wasley, J., Robinson, S.A., Lovelock, C.E., Popp, M., 2006b. Some like it wet-bio-logical characteristics underpinning tolerance of extreme water stress events inAntarctic bryophytes. Functional Plant Biology 33, 443.
48. Wasley, J., Robinson, S.A., Turnbull, J.D., King, D.H., Wanek, W., Popp, M., 2012.Bryophyte species composition over moisture gradients in the Windmill Islands, East Antarctica: development of a baseline for monitoring climate changeimpacts. Biodiversity 13, 257-264.
49. Watts, A.C., Ambrosia, V.G., Hinkley, E.A., 2012. Unmanned aircraft systems in remotesensing and scientific research: classification and considerations of use. RemoteSensing 4, 1671-1692.
50. Zandbergen, P.A., 2011. Error propagation modeling for terrain analysisusing dynamic simulation tools in ArcGIS Modelbuilder. In: Wilson, J.P.,Gould, M., Evans, I.S., Hengl, T. (Eds.), Geomorphometry 2011. Redlands,California, USA, pp. 57-60, URL: http://www.geomorphometry.org/system/files/Zandbergen2011geomorphometry.pdf
51. Zarco-Tejada, P.J., 2008. A new era in remote sensing of crops with unmanned robots.SPIE Newsroom.
52. Zhang, X., Srinivasan, R., Debele, B., Hao, F., 2008. Runoff simulation of the headwaterof the Yellow River using the SW, model with three snowmelt algorithms. Journalof the American Water Resources Association 44, 48-61.
53. Zhou, G., Ambrosia, V., Gasiewski, A.J., Bland, G., 2009. Foreword to the special issueon unmanned airborne vehicle (UAV) sensing systems for earth observations.IEEE Transactions on Geoscience and Remote Sensing 47, 687-689.