Mapping of continuous floristic gradients in grasslands using hyperspectral imagery

Remote Sensing of Environment

Volumn 92, Issue 1, 2004, Pages 126-138

  Schmidtlein, Sebastian ^a,c   Sassin, Julia ^b  

^a UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITY OF INNSBRUCK   (Austria)

^c UNIVERSITY OF BAYREUTH   (Germany)

Author keywords

Floristic gradient; Hyperspectral; Indicator value; Plant functional type; PLS; Transition; Vegetation gradient; Vegetation mapping; Vegetation pattern

Indexed keywords

BIOCOMPATIBILITY; ECOLOGY; IMAGE SEGMENTATION; IMAGE SENSORS; PLANTS (BOTANY); REGRESSION ANALYSIS; VEGETATION;

CONTINUOUS FLORISTIC GRADIENTS; GRASSLAND SPECIES;

REMOTE SENSING;

FLORISTICS; GRASSLAND; MAPPING; SPECTRAL ANALYSIS; VEGETATION DYNAMICS;

EID: 3242715825     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2004.05.004     Document Type: Article

References (65)

1. Austin M.P., Smith T.M. A new model for the continuum concept. Vegetatio. 83:1989;35-47
2. Beaudry L., Coupé R.A., DeLong C., Pojar J. Plant indicator guide for northern B.C.: Boreal, sub-boreal, and subalpine biogeoclimatic zones (BWBS, SBS, SBPS, and northern ESSF). 1999;B.C. Ministry of Forests, Resource Branch, Victoria, BC
3. Borhidi A. Social behaviour types, the naturalness and relative ecological indicator value of the higher plants in the Hungarian flora. Acta Botanica Hungarica. 39:1995;97-181
4. Clarke K.R. Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology. 18:1993;117-143
5. Clevers J.P., Jongschaap R. Imaging spectrometry for agricultural applications. van der Meer F., de Jong S.M. Imaging spectrometry. 2001;157-199 Kluwer Academic Press, Dordrecht, Netherlands
6. Davies A.M.C. Uncertainty testing in PLS regression. Spectroscopy Europe. 13:2001;16-19
7. Dennison P.E., Roberts D.A. Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE. Remote Sensing of Environment. 87:2003;123-135
8. Dennison P.E., Roberts D.A. The effects of vegetation phenology on endmember selection and species mapping in southern California chaparral. Remote Sensing of Environment. 87:2003;295-309
9. Diekmann M. Species indicator values as an important tool in applied plant ecology - a review. Basic and Applied Ecology. 4:2003;493-506
10. Ejrnaes R. Can we trust gradients extracted by detrended correspondence analysis? Journal of Vegetation Science. 11:2000;565-572
11. Ellenberg H. Zeigerwerte der Gefäßpflanzen Mitteleuropas. Scripta Geobotanica. 9:1974;1-97
12. Ellenberg H. Vegetation ecology of central Europe. 4th ed.:1988;Cambridge University Press, Cambridge, UK. 753 pp.
13. Ellenberg H., Weber H.E., Düll R., Wirth V., Werner W., Paulißen D. Zeigerwerte von Pflanzen in Mitteleuropa. Scripta Geobotanica. 18:1991;1-248
14. Ertsen A.C.D., Alkemade J.R.M., Wassen M.J. Calibrating Ellenberg indicator values for moisture, acidity, nutrient availbility and salinity in The Netherlands. Plant Ecology. 135:1998;113-124
15. Esbensen K. Multivariate data analysis - in practice. 2000;Camo, Corvallis, OR. 598 pp.
16. Feoli E. Some aspects of classification and ordination of vegetation data in perspective. Studia Geobotanica. 4:1984;7-21
17. Foody G.M. A fuzzy sets approach to the representation of vegetation continua from remotely sensed data: An example from lowland heath. Photogrammetric Engineering and Remote Sensing. 58:1992;221-225
18. Foody G.M. Fuzzy modelling of vegetation from remotely sensed imagery. Ecological Modelling. 85:1996;3-45
19. Foody G.M. The continuum of classification fuzziness in thematic mapping. Photogrammetric Engineering and Remote Sensing. 65:1999;443-451
20. Fortin M.J., Olson R.J., Ferson S., Iverson L., Hunsaker C., Edwards G., Levine D., Butera K., Klemas V. Issues related to the detection of boundaries. Landscape Ecology. 15:2000;453-466
21. Gamon J.A., Field C.B., Roberts D.A., Ustin S.L., Valentini R. Functional patterns in annual grassland during a AVIRIS overflight. Remote Sensing of Environment. 44:1993;239-253
22. Grossman Y.L., Ustin S.L., Jacquemond S., Sanderson E.W., Schmuck G., Vandebout J. Critique of stepwise linear regression for the extraction of leaf biochemistry information from leaf reflectance data. Remote Sensing of Environment. 56:1996;182-193
23. Guyot G., Baret F., Jacquemoud S. Imaging spectroscopy for vegetation studies. Toselli F., Bodechtel J. Imaging spectroscopy: Fundamentals and prospective applications. 1992;145-165 Kluwer Academic Publications, Dordrecht, Netherlands
24. Hansen P.M., Schjoerring J.K. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sensing of Environment. 86:2003;542-553
25. Hill M.O., Gauch H.G. Detrended correspondence analysis: An improved ordination technique. Vegetatio. 42:1980;47-58
26. Hill M.O., Mountford J.O., Roy D.B., Bunce R.G.H. Ellenberg's indicator values for British plants. 1999;Institute of Terrestrial Ecology, Huntingdon, UK. 46 pp.
27. Hubbel S.P. The unified neutral theory of biodiversity and biogeography. 2001;Princeton University Press, Princeton, NJ
28. Jacobsen, A. (2000). Analysing airborne optical remote sensing data from a hyperspectral scanner and implications for environmental mapping and monitoring - results from a case study of casi data and Danish semi-natural, dry grasslands. PhD thesis. Rønde: National Environmental Research Institute, Denmark, 148 pp.
29. Kennedy R.E., Cohen W.B., Takao G. Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery. Remote Sensing of Environment. 62:1997;277-291
30. Klinka K., Krajina V.J., Ceska A., Scagel A.M. Indicator plants of coastal B.C. 1989;University of British Columbia, Vancouver, BC. 288 pp.
31. Kojić M., Popović R., Karadžć B. Vaskularne biljke Srbije kao indikatori staništa. 1997;Institut za istraivanja u poljoprivredi 'Srbija', Institut za biološka istraivanja 'Siniša Stanković', Beograd, Yuguslavia. 160 pp.
32. Kubinyi H. Evolutionary variable selection in regression and PLS analyses. Journal of Chemometrics. 10:1996;119-133
33. Kumar L., Schmidt K.S., Dury S., Skidmore A.K. Imaging spectrometry and vegetation science. van der Meer F., de Jong S.M. Imaging spectrometry. 2001;111-155 Kluwer Academic Press, Dordrecht, Netherlands
34. Landolt E. Ökologische Zeigerwerte der Schweizer Flora. Veröffentlichungen des Geobotanischen Institutes der Eidg, Technischen Hochschule, Stiftung Rübel in Zürich. 64:1977;1-208
35. Lavorel S., Garnier E. Predicting changes in community composition and ecosystem functioning from plant traits: Revisiting the Holy Grail. Functional Ecology. 16:2002;545-556
36. Lepš J., Šmilauer P. Multivariate analysis of ecological data using CANOCO. 2003;Cambridge University Press, Cambridge, UK. 269 pp.
37. Lewis M.M. Numeric classification as an aid to spectral mapping of vegetation communities. Plant Ecology. 136:1998;133-149
38. Martens H., Martens M. Modified jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR). Food Quality and Preference. 11:2000;5-16
39. McCune B., Mefford M.J. PC-ORD. Multivariate analysis of ecological data. Version 4.27. 1999;MjM Software, Gleneden Beach, OR, USA
40. Minchin P.R. An evaluation of the relative robustness of techniques for ecological ordination. Vegetatio. 69:1987;89-107
41. Nakajima T., Tanaka M. Algorithms for radiative intensity calculations in moderately thick atmospheres using truncation approximation. Journal of Quantitative Spectroscopy & Radiative Transfer. 40:1988;51-69
42. Oberdorfer, E. (Ed.) (1993-1998). Süddeutsche Pflanzengesellschaften. 5 Vols. Jena: Fischer.
43. Ohmann J.L., Gregory M.J. Predictive mapping of forest composition and structure with direct gradient analysis and nearest-neighbor imputation in coastal Oregon, USA. Canadian Journal of Forest Research. 32:2002;725-741
44. Oppelt N., Mauser W. Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data. International Journal of Remote Sensing. 25:2004;145-159
45. Palmer M.W. How should one count species? Natural Areas Journal. 15:1995;124-135
46. Purves, W. K., Orians, G. H., Heller, H. C., & Sadava, D. (1998). LIFE: The science of biology, (5th Ed.). Sunderland (Mass.): Sinauer Associates, and W. H. Freeman and Company.
47. Raunkiaer C. The life forms of plants and statistical plant geography. 1934;Clarendon, Oxford, UK
48. Ray T.W., Murray B.C. Nonlinear spectral mixing in desert vegetation. Remote Sensing of Environment. 55:1996;59-64
49. Reichelt G., Wilmanns O. Vegetationsgeographie. 1973;Westermann, Braunschweig, Germany. 210 pp.
50. Rennwald, E. (2000). Verzeichnis und Rote Liste der Pflanzengesellschaften Deutschlands - Schriftenreihe für Vegetationskunde, vol. 35. Bundesamt für Naturschutz, Bonn-Bad Godesberg, 800 pp.
51. Ripple W.J. Spectral reflectance relationships to leaf water stress. Photogrammetric Engineering & Remote Sensing. 52:1986;1669-1675
52. Roberts D.A., Green R.O., Adams J.B. Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS. Remote Sensing of Environment. 62:1997;223-240
53. Schaffers A.P., Sýkora K.V. Reliability of Ellenberg indicator values for moisture, nitrogen and soil reaction: A comparison with field measurements. Journal of Vegetation Science. 11:2000;225-244
54. Smith M.-L., Ollinger S.V., Martin M.E., Aber J.D., Hallett R.A., Goodale C.L. Direct estimation of aboveground forest productivity through hyperspectral remote sensing of canopy nitrogen. Ecological Applications. 12:2002;1286-1302
55. Ter Braak C.J.F. Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis. Ecology. 67:1986;1167-1179
56. Ter Braak C.J.F., Juggins S. Weighted averaging partial least squares regression (WA-PLS): An improved method for reconstructing environmental variables from species assemblages. Hydrobiologia. 269/270:1993;485-502
57. Thenkabail P.S., Smith R.B., De Pauw E. Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sensing of Environment. 71:1999;158-182
58. Thompson K.J., Hodgson K.G., Grime J.P., Rorison I.H., Band S.R., Spencer R.E. Ellenberg numbers revisited. Phytocoenologia. 23:1993;277-289
59. Tompkins S., Mustard J.F., Pieters C.M., Forsyth D.W. Optimization of endmembers for spectral mixture analysis. Remote Sensing of Environment. 59:1997;472-489
60. Townsend P.A. A quantitative fuzzy approach to assess mapped vegetation classifications for ecological applications. Remote Sensing of Environment. 72:2000;253-267
61. Van de Ven C.M., Weiss S.B. Mapping arid vegetation species distributions in the White Mountains, eastern California, using AVIRIS, topography, and geology. AVIRIS Proceedings: May 20 and 21, 1991:2001;Jet Propulsion Laboratory, Pasadena, CA
62. Wessman C.A., Bateson C.A., Benning T.L. Detecting fire and grazing patterns in tallgrass prairie using spectral mixture analysis. Ecological Applications. 7:1997;493-511
63. White J.D., Trotter C.M., Brown J., Scott N. Nitrogen concentration in New Zealand vegetation foliage derived from laboratory and field spectroscopy. International Journal of Remote Sensing. 21:2000;2525-2531
64. Wold H. Partial least squares. Kotz S., Johnson N.L. Encyclopedia of Statistical Sciences. vol. 6:1985;581-591 Wiley, New York
65. Yoder B.J., Pettigrew-Crosby R.E. Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400-9,500 nm) at leaf and canopy scales. Remote Sensing of Environment. 53:1995;199-211