Categorizing wetland vegetation by airborne laser scanning on Lake Balaton and Kis-Balaton, Hungary

Remote Sensing

Volumn 4, Issue 6, 2012, Pages 1617-1650

  Zlinszky, András ^a,b   Mücke, Werner ^b   Lehner, Hubert ^b   Briese, Christian ^b,c   Pfeifer, Norbert ^b  

^a MTA CENTRE FOR ECOLOGICAL RESEARCH   (Hungary)

^b VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

^c LUDWIG BOLTZMANN INSTITUTE FOR LUNG VASCULAR RESEARCH   (Austria)

Author keywords

Carex; Ecosystem health; LIDAR; Phragmites australis; Typha; Vegetation classification; Wetlands

Indexed keywords

CAREX; ECOSYSTEM HEALTH; PHRAGMITES AUSTRALIS; TYPHA; VEGETATION CLASSIFICATION;

ATMOSPHERICS; CLASSIFICATION (OF INFORMATION); DATA ACQUISITION; DECISION TREES; ECOSYSTEMS; HEALTH; LASER APPLICATIONS; OPTICAL RADAR; PHOTOGRAPHY; SURVEYS; WETLANDS;

VEGETATION;

EID: 84865025292     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs4061617     Document Type: Article

References (99)

1. Strayer, D.L.; Findlay, S.E.G. Ecology of freshwater shore zones. Aquat. Sci. 2010, 72, 127-163.
2. Ostendorp, W. Schilf ALS Lebensraum. In Artenschutzsymposium Teichrohrsänger; Landesanstalt für Umweltschutz Baden-Württemberg, Karlsruhe, Germany, 1993; Volume 68, pp. 173-280.
3. Vymazal, J. Enhancing ecosystem services on the landscape with created, constructed and restored wetlands. Ecol. Eng. 2011, 37, 1-5.
4. Schmieder, K. European lake shores in danger-Concepts for a sustainable development. Limnologica 2004, 34, 3-14.
5. Wetzel, R.G. Limnology, 3rd ed.; Academic Press: London, UK, 2001; p. 1066.
6. Segal, S. Principles on structure, zonation and succession of aquatic macrophytes. Hidrobiologia 1971, 12, 89-97.
7. van der Putten, W.H. Die-back of Phragmites australis in European wetlands: An overview of the European Research Programme on Reed Die-Back and Progression (1993-1994). Aquat. Bot. 1997, 59, 263-275.
8. Cizkova, H.; Brix, H.; Kopecky, J.; Lukavska, J. Organic acids in the sediments of wetlands dominated by Phragmites australis: Evidence of phytotoxic concentrations. Aquat. Bot. 1999, 64, 303-315.
9. Weisner, S.E.B. Effects of an organic sediment on performance of young Phragmites australis clones at different water depth treatments. Hydrobiologia 1996, 330, 189-194.
10. Zlinszky, A. A Balatoni Nádpusztulás Légifelvételes Vizsgálata; Eötvös Loránd University, Budapest, Hungary, 2007.
11. Fogli, S.; Marchesini, R.; Gerdol, R. Reed (Phragmites australis) decline in a brackish wetland in Italy. Mar. Environ. Res. 2002, 53, 465-479.
12. Kovács, M.; Turcsányi, G.; Tuba, Z.; Wolcsánszky, S.E.; Vásárhelyi, T.; Dely-Draskovics, Á.; Tóth, S.; Koltay, A.; Kaszab, L.; Szoke, P.; et al. The Decay of Reed in Hungarian Lakes. In Conservation and Management of Lakes, Salánki, J., Herodek, S., Eds.; Akadémiai Kiadó: Budapest, Hungary, 1989; pp. 461-470.
13. Hunter, P.D.; Gilvear, D.J.; Tyler, A.N.; Willby, N.J.; Kelly, A. Mapping macrophytic vegetation in shallow lakes using the Compact Airborne Spectrographic Imager (CASI). Aquat. Conserv. 2010, 20, 717-727.
14. van der Putten, W.H. Assessing Ecological Change in European Wetlands: How to Know What Parameters Should Be Monitored to Evaluate the Die-Back of Common Reed (Phragmites Australis). In Monitoring of Ecological Change in Wetlands of Middle Europe; Aubrecht, G., Dick, G., Prentice, C., Eds.; Botanischer Arbeitsgemeinschaft am Oberösterreichisen Landesmuseum: Linz, Austria, 1993; pp. 61-68.
15. Ostendorp, W. Dieback of reeds in Europe-A critical review of literature. Aquat. Bot. 1989, 35, 5-26.
16. Hortobágyi, T.; Simon, T. Növényföldrajz, Társulástan, Ökológia, 3 ed.; Nemzeti Tankönyvkiadó Rt: Budapest, Hungary, 1981.
17. Kelly, M.; Tuxen, K.A.; Stralberg, D. Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time. Ecol. Indic. 2011, 11, 263-273.
18. Weilhoefer, C.L. A review of indicators of estuarine tidal wetland condition. Ecol. Indic. 2011, 11, 514-525.
19. Alberdi, I.; Condes, S.; Martinez-Millan, J. Review of monitoring and assessing ground vegetation biodiversity in national forest inventories. Environ. Monit. Assess. 2010, 164, 649-676.
20. Rücker, A.; Grosser, S.; Melzer, A. Geschichte und Ursachen des Röhrichtrückgangs am Ammersee (Deutschland). Limnologica 1999, 29, 11-20.
21. Hellsten, S.; Keto, A.; Suoramiemi, M.; Partanen, S. Long-term changes in the aquatic vegetation of Lake Päijänne, Southern Finland. Verh. Internat. Verein Limnol. 2006, 29, 1167-1173.
22. Csaplovics, E. Interpretation von Farbinfrarotbildern, Kartierung von Vegetationsschäden in Brixlegg, Schilfkartierung Neusiedler See. Ph.D. Thesis, Technische Universita t Wien, Vienna, Austria, 1982, Volume 23, pp. 1-192.
23. Whyte, R.S.; Trexel-Kroll, D.; Klarer, D.M.; Shields, R.; Francko, D.A. The invasion and spread of Phragmites australis during a period of low water in a Lake Erie coastal wetland. J. Coastal Res. 2008, 55, 111-120.
24. Dienst, M.; Schmieder, K.; Ostendorp, W. Effects of water level variations on the dynamics of the reed belts of Lake Constance. Limnologica 2004, 34, 29-36.
25. Laba, M.; Downs, R.; Smith, S.; Welsh, S.; Neider, C.; White, S.; Richmond, M.; Philpot, W.; Baveye, P. Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using Quickbird satellite imagery. Remote Sens. Environ. 2008, 112, 286-300.
26. Belluco, E.; Camuffo, M.; Ferrari, S.; Modenese, L.; Silvestri, S.; Marani, A.; Marani, M. Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing. Remote Sens. Environ. 2006, 105, 54-67.
27. Pengra, B.W.; Johnston, C.A.; Loveland, T.R. Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor. Remote Sens. Environ. 2007, 108, 74-81.
28. Yang, X.J. Remote sensing and GIS applications for estuarine ecosystem analysis: An overview. Int. J. Remote Sens. 2005, 26, 5347-5356.
29. Burai, P.; Lövei, G.Z.; Lénárt, C.; Nagy, I.; Enyedi, P. Mapping aquatic vegetation of the Rakamaz-Tiszanagyfalui Nagy-morotva using Hyperspectral Imagery. Acta Geographica Debrecina Landscape and Environment 2010, 4, 1-10.
30. Artigas, F.; Pechmann, I.C. Balloon imagery verification of remotely sensed Phragmites australis expansion in an urban estuary of New Jersey, USA. Landscape Urban Plan. 2010, 95, 105-112.
31. Siciliano, D.; Wasson, K.; Potts, D.C.; Olsen, R.C. Evaluating hyperspectral imaging of wetland vegetation as a tool for detecting estuarine nutrient enrichment. Remote Sens. Environ. 2008, 112, 4020-4033.
32. Schmidt, K.S.; Skidmore, A.K. Spectral discrimination of vegetation types in a coastal wetland. Remote Sens. Environ. 2003, 85, 92-108.
33. Wehr, A.; Lohr, U. Airborne laser scanning-An introduction and overview. ISPRS J. Photogramm. 1999, 54, 68-82.
34. Kobler, A.; Pfeifer, N.; Ogrinc, P.; Todorovski, L.; Ostir, K.; Dzeroski, S. Repetitive interpolation: A robust algorithm for DTM generation from aerial laser scanner data in forested terrain. Remote Sens. Environ. 2007, 108, 9-23.
35. Kraus, K.; Pfeifer, N. Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS J. Photogramm. 1998, 53, 193-203.
36. Fricker, G.A.; Saatchi, S.S.; Meyer, V.; Gillespie, T.W.; Sheng, Y. Application of semi-automated filter to improve waveform lidar sub-canopy elevation model. Remote Sens. 2012, 4, 1494-1518.
37. Jochem, A.; Hollaus, M.; Rutzinger, M.; Höfle, B., Estimation of aboveground biomass in Alpine forests: A semi-empirical approach considering canopy transparency derived from airborne lidar data. Sensors 2011, 11, 278-295.
38. Eysn, L.; Hollaus, M.; Schadauer, K.; Pfeifer, N. Forest delineation based on airborne LIDAR data. Remote Sens. 2012, 4, 762-783.
39. Lindberg, E.; Hollaus, M. Comparison of methods for estimation of stem volume, stem number and basal area from Airborne Laser Scanning data in a hemi-boreal forest. Remote Sens. 2012, 4, 1004-1023.
40. Garcia, M.; Riano, D.; Chuvieco, E.; Salas, J.; Danson, F.M. Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules. Remote Sens. Environ. 2011, 115, 1369-1379.
41. Riano, D.; Chuvieco, E.; Ustin, S.L.; Salas, J.; Rodriguez-Perez, J.R.; Ribeiro, L.M.; Viegas, D.X.; Moreno, J.M.; Fernandez, H. Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging. Int. J. Wildland Fire 2007, 16, 341-348.
42. Mitchell, J.J.; Glenn, N.F.; Sankey, T.T.; Derryberry, D.R.; Anderson, M.O.; Hruska, R.C. Small-footprint Lidar estimations of sagebrush canopy characteristics. Photogramm. Eng. Remote Sensing 2011, 77, 521-530.
43. Streutker, D.R.; Glenn, N.F. LiDAR measurement of sagebrush steppe vegetation heights. Remote Sens. Environ. 2006, 102, 135-145.
44. Sankey, T.T.; Bond, P. LiDAR-based classification of sagebrush community types. Rangeland Ecol. Manag. 2011, 64, 92-98.
45. Nayegandhi, A.; Brock, J.C.; Wright, C.W.; O'Connell, M.J. Evaluating a small footprint, waveform-resolving lidar over coastal vegetation communities. Photogramm. Eng. Remote Sensing 2006, 72, 1407-1417.
46. Mücke, W.; Hollaus, M.; Briese, C. Application and Analysis of Airborne Laser Scanning Data on Reed Beds. In International Symposium on Advanced Methods of Monitoring Reed Habitats in Europe; Csaplovics, E., Schimdt, J., Eds.; Rhombos-Verlag, Berlin, Germany, 2010.
47. Cobby, D.M.; Mason, D.C.; Horritt, M.S.; Bates, P.D. Two-dimensional hydraulic flood modelling using a finite-element mesh decomposed according to vegetation and topographic features derived from airborne scanning laser altimetry. Hydrol. Process. 2003, 17, 1979-2000.
48. Straatsma, M.W.; Baptist, M. Floodplain roughness parameterization using airborne laser scanning and spectral remote sensing. Remote Sens. Environ. 2008, 112, 1062-1080.
49. Johansen, K.; Tiede, D.; Blaschke, T.; Arroyo, L.A.; Phinn, S. Automatic geographic object based mapping of streambed and riparian zone extent from LiDAR data in a temperate rural urban environment, Australia. Remote Sens. 2011, 3, 1139-1156.
50. Rosso, P.H.; Ustin, S.L.; Hastings, A. Use of lidar to study changes associated with Spartina invasion in San Francisco Bay marshes. Remote Sens. Environ. 2006, 100, 295-306.
51. Collin, A.; Long, B.; Archambault, P. Salt-marsh characterization, zonation assessment and mapping through a dual-wavelength LiDAR. Remote Sens. Environ. 2010, 114, 520-530.
52. Knight, J.M.; Dale, P.E.R.; Spencer, J.; Griffin, L. Exploring LiDAR data for mapping the micro-topography and tidal hydro-dynamics of mangrove systems: An example from southeast Queensland, Australia. Estuar. Coast. Shelf Sci. 2009, 85, 593-600.
53. Jenkins, R.B.; Frazier, P.S. High-resolution remote sensing of upland swamp boundaries and vegetation for baseline mapping and monitoring. Wetlands 2010, 30, 531-540.
54. Morris, J.T.; Porter, D.; Neet, M.; Noble, P.A.; Schmidt, L.; Lapine, L.A.; Jensen, J.R. Integrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization. Int. J. Remote Sens. 2005, 26, 5221-5234.
55. Gilvear, D.; Tyler, A.; Davids, C. Detection of estuarine and tidal river hydromorphology using hyper-spectral and LiDAR data: Forth estuary, Scotland. Estuar. Coast. Shelf Sci. 2004, 61, 379-392.
56. Mather, P.M. Computer Processing of Remotely Sensed Images; John Wiley & Sons Ltd.: Chichester, UK, 2006; p. 324.
57. Onojeghuo, A.O.; Blackburn, G.A. Optimising the use of hyperspectral and LiDAR data for mapping reedbed habitats. Remote Sens. Environ. 2011, 115, 2025-2034.
58. Geerling, G.W.; Labrador-Garcia, M.; Clevers, J.; Ragas, A.M.J.; Smits, A.J.M. Classification of floodplain vegetation by data fusion of spectral (CASI) and LiDAR data. Int. J. Remote Sens. 2007, 28, 4263-4284.
59. Arroyo, L.A.; Johansen, K.; Armston, J.; Phinn, S. Integration of LiDAR and QuickBird imagery for mapping riparian biophysical parameters and land cover types in Australian tropical savannas. For. Ecol. Manage. 2010, 259, 598-606.
60. Höfle, B.; Pfeifer, N. Correction of laser scanning intensity data: Data and model-driven approaches. ISPRS J. Photogramm. 2007, 62, 415-433.
61. Lehner, H.; Briese, C. Radiometric calibration of full-waveform airborne laser scanning data based on natural surfaces. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2010, 38, 360-365.
62. Habib, A.F.; Kersting, A.P.; Shaker, A.; Yan, W.Y. Geometric calibration and radiometric correction of LiDAR data and their impact on the quality of derived products. Sensors 2011, 11, 9069-9097.
63. Höfle, B.; Vetter, M.; Pfeifer, N.; Mandlburger, G.; Stotter, J. Water surface mapping from airborne laser scanning using signal intensity and elevation data. Earth Surf. Process. Landf. 2009, 34, 1635-1649.
64. Moffiet, T.; Mengersen, K.; Witte, C.; King, R.; Denham, R. Airborne laser scanning: Exploratory data analysis indicates potential variables for classification of individual trees or forest stands according to species. ISPRS J. Photogramm. 2005, 59, 289-309.
65. Brandtberg, T. Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidar. ISPRS J. Photogramm. 2007, 61, 325-340.
66. Chust, G.; Galparsoro, I.; Borja, A.; Franco, J.; Uriarte, A. Coastal and estuarine habitat mapping, using LIDAR height and intensity and multi-spectral imagery. Estuar. Coast. Shelf Sci. 2008, 78, 633-643.
67. Brzank, A.; Heipke, C.; Goepfert, J.; Soergel, U. Aspects of generating precise digital terrain models in the Wadden Sea from lidar-water classification and structure line extraction. ISPRS J. Photogramm. 2008, 63, 510-528.
68. Virág, Á. A Balaton Múltja és Jelene, 1st ed.; Egri nyomda: Eger, Hungary, 1998; p. 904.
69. Dömötörfy, Z.; Reeder, D.; Pomogyi, P. Changes in the macro-vegetation of the Kis-Balaton Wetlands over the last two centuries: a GIS perspective. Hydrobiologia 2003, 506, 671-679.
70. Kárpáti, I.; Szeglet, P.; Tóth, I. Die Vegetationskarte der Bozsauer-Bucht. BFB-Bericht 1987, 63, 63-68.
71. Kárpáti, I.; Szeglet, P.; Kárpáti, V. Vegetationskarte des Naturschutzgebietes Kisbalaton und seine Primärproduktion. BFB-Bericht 1983, 47, 183-196.
72. Lang, M.W.; McCarty, G.W. LIDAR intensity for improved detection of inundation below the forest canopy. Wetlands 2009, 29, 1166-1178.
73. Clevering, O.A.; Lissner, J. Taxonomy, chromosome numbers, clonal diversity and population dynamics of Phragmites australis. Aquat. Bot. 1999, 64, 185-208.
74. Engloner, A.I. Structure, growth dynamics and biomass of reed (Phragmites australis)-A review. Flora 2009, 204, 331-346.
75. Poulin, B.; Lefebvre, G.; Mauchamp, A. Habitat requirements of passerines and reedbed management in southern France. Biol. Conserv. 2002, 107, 315-325.
76. Zlinszky, A.; Tóth, V.; Pomogyi, P.; Timár, G. Initial report of the AIMWETLAB project: Simultaneous airborne hyperspectral, LIDAR and photogrammetric survey of the full shoreline of Lake Balaton, Hungary. Geographia Technica 2011, 11, 101-117.
77. Mandlburger, G.; Otepka, J.; Karel, W.; Wagner, W.; Pfeifer, N. Orientation and processing of airborne laser scanning data (OPALS)-Concept and first results of a comprehensive ALS software. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2009, 38, 55-60.
78. Wagner, W.; Ullrich, A.; Ducic, V.; Melzer, T.; Studnicka, N. Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner. ISPRS J. Photogramm. 2006, 60, 100-112.
79. Wagner, W.; Hollaus, M.; Briese, C.; Ducic, V. 3D vegetation mapping using small-footprint full-waveform airborne laser scanners. Int. J. Remote Sens. 2008, 29, 1433-1452.
80. Lehner, H.; Kager, H.; Roncat, A.; Zlinszky, A. Consideration of Laser Pulse Fluctuations and Automatic Gain Control in Radiometric Calibration of Airborne Laser Scanning Data. In Proceedings of 6th ISPRS Student Consortium and WG VI/5 Summer School, Fayetteville State University, NC, USA, 30 July-6 August 2011.
81. Hollaus, M.; Mandlburger, G.; Pfeifer, N.; Mücke, W. Land cover dependent derivation of digital surface models from airborne laser scanning data. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2010, 38, 222-226.
82. Lillesand, T.M.; Kiefer, R.W.; Chipman, J.W. Remote Sensing and Image Interpretation: International Edition, 5th ed.; John Wiley & Sons: New York, NY, USA, 2003; p. 704.
83. Ressl, C.; Pfeifer, N.; Mandlburger, G. Applying 3D Affine Transformation and Least Squares Matching for Airborne Laser Scanning Strips Adjustment without GNSS/IMU Trajectory Data. In Proceedings of ISPRS Workshop Laser Scanning 2011, Calgary, AB, Canada, 29-31 August 2011.
84. Briese, C.; Höfle, B.; Lehner, H.; Wagner, W.; Pfenningbauer, M.; Ullrich, A. Calibration of full-waveform airborne laser scanning data for object classification. Proc. SPIE 2008, 6950, 6950H.
85. Stevens, J.P.; Blackstock, T.H.; Howe, E.A.; Stevens, D.P. Repeatability of Phase I habitat survey. J. Environ. Manage. 2004, 73, 53-59.
86. Vanden Borre, J. User Requirements towards the Integration of Remote Sensing in Natura 2000 Monitoring. Results of the Work Package 2200; Belgian Science Policy: Brussels, Belgium, 2009.
87. Gibbs, J.P. Importance of small wetlands for the persistance of local-populations of wetland-associated animals. Wetlands 1993, 13, 25-31.
88. Standovár, T.; Primack, R. A Természetvédelmi Biológia Alapjai, 1st ed.; Nemzeti Tankönyvkiadó Rt: Budapest, Hungary, 2001; p. 541.
89. Wang, C.; Menenti, M.; Stoll, M.P.; Belluco, E.; Marani, M., Mapping mixed vegetation communities in salt marshes using airborne spectral data. Remote Sens. Environ. 2007, 107, 559-570.
90. Pal, M.; Mather, P.M. An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sens. Environ. 2003, 86, 554-565.
91. Verrelst, J.; Geerling, G.W.; Sykora, K.V.; Clevers, J. Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data. Int. J. Appl. Earth Obs. Geoinf. 2009, 11, 83-94.
92. Holmgren, J.; Persson, A.; Soderman, U. Species identification of individual trees by combining high resolution LIDAR data with multi-spectral images. Int. J. Remote Sens. 2008, 29, 1537-1552.
93. Hartfield, K.A.; Landau, K.I.; van Leeuwen, W.J.D. Fusion of high resolution aerial multispectral and LiDAR data: land cover in the context of urban mosquito habitat. Remote Sens. 2011, 3, 2364-2383.
94. Hollaus, M.; Mücke, W.; Höfle, B.; Dorigo, W.; Pfeifer, N.; Wagner, W.; Bauerhansl, C.; Regner, B. Tree Species Classification Based on Full-Waveform Airborne Laser Scanning Data. In Proceedings of Silvilaser 2009, College Station, TX, USA, 14-16 October 2009.
95. Surveying and Mapping Authority of the Republic of Slovenia. Technical Documentation: Laser Scanning and Aerial Photography; Ministry of the Environment and Spatial Planning: Ljubljana, Slovenia, 2010; p. 23.
96. Flood, M. Laser altimetry: From science to commercial lidar mapping. Photogramm. Eng. Remote Sensing 2001, 67, 1209-1211.
97. Briese, C.; Mandlburger, G.; Pfeifer, N. Airborne Laser Scanning-High Quality Digital Terrain Modelling. In Proceedings of Geo-Sibir, III International Scientific Congress, Novosibirsk, Russia, 23-27 April 2007; pp. 79-92.
98. Fritzmann, P.; Hoefle, B.; Vetter, M.; Sailer, R.; Stoetter, J.; Bollmann, E. Surface classification based on multi-temporal airborne LiDAR intensity data in high mountain environments: A case study from Hintereisferner, Austria. Zeitschrift Fur Geomorphologie 2011, 55, 105-126.
99. Oberleitner, I.; Dick, G. Feuchtgebietsinventar Österreich-Grundlagenerhebung, 1st ed.; Umweltbundesamt: Vienna, Austria, 1996; pp. 1-41.