Challenges and lessons from a wetland LiDAR project: a case study of the Okefenokee Swamp, Georgia, USA

References

• Applanix . 2011 . Applanix: a Trimble company [online] Available from:http://www.applanix.com/ [Accessed 24 April 2012]
   Google Scholar
• Axelsson , P. 2000 . DEM generation from laser scanner data using adaptive TIN models . International Archives of Photogrammetry and Remote Sensing , 33 ( B4 ) : 85 – 118 .
   Google Scholar
• Coastal Regional Commission of Georgia (CRCG) . 2011 . Coastal Georgia elevation project [online] Available from:http://www.crc.ga.gov/gis/cgep/Forms/AllItems.aspx [Accessed 24 April 2012]
   Google Scholar
• Crombaghs , M. J.E. , Brugelmann , R. and de Min , E.J. 2000 . On the adjustment of overlapping strips of last altimeter height data . International Archives of Photogrammetry and Remote Sensing , 33 ( B3/1 ) : 230 – 237 .
   Google Scholar
• Cypert , E. 1972 . The origin of houses in the Okefenokee Prairies . American Midland Naturalist , 87 ( 2 ) : 448 – 458 .
   Web of Science ®Google Scholar
• Evans , J. 2009 . Discrete return lidar in natural resources: recommendations for project planning, data processing, and deliverables . Remote Sensing , 1 : 776 – 794 .
   Web of Science ®Google Scholar
• Georgia Weather Network . 2011 . Georgia automated environmental monitoring network [online]. University of Georgia, Griffin Campus Available from:http://www.georgiaweather.net/ [Accessed 10 December 2011]
   Google Scholar
• Habib , A. F. LiDAR strip adjustment using conjugate linear features in overlapping strips . The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences . XXXVII, Part B1, Beijing 2008
   Google Scholar
• Harrison , J. 2009 . Finding anomalies in high-density LiDAR point clouds . Geomatica , 63 ( 4 ) : 397 – 405 .
   Google Scholar
• Hodgson , M. E. 2005 . An evaluation of lidar-derived elevation and terrain slope in leaf-off conditions . Photogrammetric Engineering and Remote Sensing , 71 ( 7 ) : 817 – 823 .
   Web of Science ®Google Scholar
• Hofle , B. and Rutzinger , M. 2011 . Topographic airborne LiDAR in geomorphology: a technological perspective . Zeitschrift Fur Geomorphologie , 55 ( 2 ) : 1 – 29 .
   Google Scholar
• Hogg , A. and Holland , J. 2008 . An evaluation of DEMs derived from LiDAR and photogrammetry for wetland mapping . The Forestry Chronicle , 84 ( 6 ) : 840 – 849 .
   Web of Science ®Google Scholar
• Hopkinson , C. 2005 . Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment . Canadian Journal of Remote Sensing , 31 ( 2 ) : 191 – 206 .
   Web of Science ®Google Scholar
• Isenburg , M. 2011 . LAStools: converting, filtering, viewing, gridding, and compressing LIDAR data [online] Available from:http://www.cs.unc.edu/~isenburg/lastools/ [Accessed 24 April 2012]
   Google Scholar
• James , L. , Watson , D. and Hansen , W. 2006 . Using LiDAR data to map gullies and headwater streams under forest canopy: South Carolina, USA . Catena , 71 ( 1 ) : 132 – 144 .
   Web of Science ®Google Scholar
• Kinsey-Henderson A.E., 2009. Correcting height differences in digital elevation models derived from overlapping LiDAR survey runs. In: R.S. Anderssen, R.D. Braddock, and L.T.H. Newham, eds. 18th world IMACS Congress and MODSIM09 international Congress on modelling and simulation [online]. Available from: http://www.mssanz.org/modsim09/F13/Kinsey-henderson.pdf [Accessed 2 March 2012]
   Google Scholar
• Laerm , J. and Freeman , B. J. 2008 . Fishes of the Okefenokee Swamp , Athens , GA : University of Georgia Press .
   Google Scholar
• Li , S. 2011 . Lidar DEM error analyses and topographic depression identification in a hummocky landscape in the prairie region of Canada . Geomorphology , 129 ( 3–4 ) : 263 – 275 .
   Web of Science ®Google Scholar
• Lillesand , T. M. and Kiefer , R.W. 1994 . Remote sensing and photo interpretation , 3rd. ed , New York : John Wiley & Sons, 750 p .
   Google Scholar
• Liu , X. Y. 2011 . Accuracy assessment of LiDAR elevation data using survey marks . Survey Review , 43 ( 319 ) : 80 – 93 .
   Web of Science ®Google Scholar
• Loudermilk , E. L. 2009 . Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics . International Journal of Wildland Fire , 18 : 676 – 685 .
   Web of Science ®Google Scholar
• Luethy , L. and Ingensand , H. 2001 . How to evaluate the quality of airborne laser scanning data . International Archives Photogrammetry, Remote Sensing Spatial Information Sciences , XXXVI ( 8/W2 ) : 313 – 317 .
   Google Scholar
• Maas , H. Planimetric and height accuracy of airborne laserscanner data: user requirements and system performance [online] . Photogrammetrische Woche2003 . Stuttgart , , Germany Available from:http://www.ifp.unistuttgart.de/publications/phowo03/maas.pdf [Accessed 2 March 2012]
   Google Scholar
• Meng , X. , Currit , N. and Zhao , K. 2010 . Ground filtering algorithms for airborne LiDAR data: a review of critical issues . Remote Sensing , 2 : 833 – 860 .
   Web of Science ®Google Scholar
• National , Digital Elevation Program (NDEP) . 2004 . Guidelines for digital elevation data – version 1 [online] Available from:http://www.ndep.gov/NDEP_Elevation_Guidelines_Ver1_10May2004.pdf [Accessed 24 April 2012]
   Google Scholar
• Petzold , B. , Reiss , P. and Stossel , W. 1999 . Laser scanning – surveying and mapping agencies are using a new technique for the derivation of digital terrain models . ISPRS Journal of Photogrammetry and Remote Sensing , 54 : 95 – 104 .
   Web of Science ®Google Scholar
• RIEGL . 2010 . Data processing software: RiPROCESS for RIEGL Scan Data [online] Available from:http://www.rieglusa.com/software-guide/pdf/11_Datasheet_RiPROCESS_22-09-2010_01.pdf [Accessed 24 April 2012]
   Google Scholar
• Sharma , M. , Paige , G. B. and Miller , S. N. 2010 . DEM development from ground-based LiDAR data: a method to remove non-surface objects . Remote Sensing , 2 : 2629 – 2642 .
   Web of Science ®Google Scholar
• Smart , G. M. , Bind , J. and Duncan , M. J. River bathymetry from conventional LiDAR using water surface returns . 18th World MODSIM . Cairns , , Australia
   Google Scholar
• Tang , T. 2008 . Terrestrial laser scan survey and 3D TIN model construction of urban buildings in a geospatial database . Geocarto International , 23 ( 4 ) : 259 – 272 .
   Google Scholar
• USGS . 2010 . U.S. Geological Survey National Geospatial Program Lidar Guidelines and Base Specification (draft), version 13 [online] Available from:http://lidar.cr.usgs.gov/USGS-NGP%20Lidar%20Guidelines%20and%20Base%20Specification%20v13(ILMF).pdf [Accessed 24 April 2012]
   Google Scholar
• Virtual Geomatics (VG4D) . 2011 . VG4D production manager [online] Available from:http://www.virtualgeomatics.com/solutions2.html [Accessed 24 April 2012]
   Google Scholar
• Willers , J. 2008 . A post-processing step error correction algorithm for overlapping LiDAR strips from agricultural landscapes . Computers and Electronics in Agriculture , 64 ( 2 ) : 183 – 193 .
   Web of Science ®Google Scholar
• Zhang , K. and Cui , Z. 2007 . Airborne LiDAR data processing and analysis tools ALDPAT 1.0, software manual , Miami , FL : National Center for Airborne Laser Mapping, Florida International University .
   Google Scholar