Imaging spectrometry for ecological applications

ITC Journal

Volumn 3, Issue 4, 2001, Pages 305-312

  Curran, Paul J ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Ecology; Foliar biochemical concentration; Geological remote sensing; NIRS; Reflectance spectra

Indexed keywords

EID: 33646258053     PISSN: 03032434     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0303-2434(01)85037-6     Document Type: Article

References (119)

1. AOAC, 1990. Method 989.03. In: K. Hilrich (Ed.), Official Methods of Analysis. Association of Official Analytical Chemists, Washington, DC, pp.74-76.
2. Aber, J.D. (Ed.), 1994. Accelerated Canopy Chemistry Program. Final Report to NASA-EOS-IWG, NASA, Washington, DC.
3. Aber, J.D., K.L. Bolster, S.D. Newman, M. Soulia & M.E. Martin, 1994. Analyses of forest foliage II: Measurement of carbon fraction and nitrogen content by end-member analysis. Journal of Near Infrared Spectroscopy 2: 15-23.
4. Asner, G.P., 1998, Biophysical and biochemical sources of variability in canopy reflectance. Remote Sensing of Environment 64: 234-253.
5. Asner, G.P., A.R. Townsend & M.C.M. Bustamante, 1999. Spectrometry of pasture condition and biogeochemistry in the Central Amazon. Geophysical Research Letters 26: 2769-2772.
6. Baret, F. & Th. Fourty, 1997. The limits of a robust estimation of canopy biochemistry. In: G. Guyot & Th. Phulpin (Eds), Physical Measurements and Signatures in Remote Sensing. A.A. Balkema, Rotterdam, pp. 413-420.
7. Batten, G.D., 1998. An appreciation of the contribution of NIR to agriculture. Journal of Near Infrared Spectroscopy 6: 105-114.
8. Berzaghi, P., J.S. Shenk & M.O. Westerhaus, 2000. LOCAL prediction with near infrared multi-product databases. Journal of Near Infrared Spectroscopy 8: 1-9.
9. Boyd, D.S. & P.J. Curran, 1998. Using remote sensing to reduce uncertainties in the global carbon budget: the potential of radiation acquired in middle infrared wavelengths. Remote Sensing Reviews 16: 293-327.
10. Boyd, D.S., T. Wicks & P.J. Curran, 2000. The use of middle infrared radiation to estimate the leaf area index of boreal forest. Tree Physiology 20: 755-760.
11. Büning-Pfaue, H., R. Hartmann, S. Kehraus & C. Urban, 1998. Near infrared spectrometric analysis of food and its achievable performance. Journal of Near Infrared Spectroscopy 6: A27-A33.
12. Burns, D.A. & E.W. Ciurczak (Eds), 1992. Handbook of Near-Infrared Analysis. Marcel Decker, New York, NY.
13. Card, D.H., D.L. Peterson & P.A. Matson, 1988. Prediction of leaf chemistry by the use of visible and near infrared reflectance spectroscopy. Remote Sensing of Environment 26: 123-147.
14. Cassis, L.A., J. Yates, W.C. Symons & R.A. Lodder, 1998. Cardiovascular near-infrared imaging. Journal of Near Infrared Spectroscopy 6: A21-A25.
15. Clark, R.N., 1991. Spectroscopy 101. The problems with NIRA. Unpublished manuscript. US Geological Survey, Denver, CO.
16. Clark, R.N., 1999. Spectroscopy of rocks and minerals, and principles of spectroscopy. In: A.N. Rencz (Ed.), Remote Sensing for the Earth Sciences. Manual of Remote Sensing, Volume 3. John Wiley & Sons, New York, NY, pp. 3-58.
17. Clark, R.N. & T.L. Roush, 1984. Reflectance spectroscopy: quantitative analysis techniques for remote sensing applications. Journal of Geophysical Research 89: 6329-6340.
18. Clevers, J.G.P.W. & R.E.E. Jongschaap, 2001. Regional mapping of carbon function by terrestrial ecosystems using the red-edge index derived from MERIS. Proceedings, 8th International Symposium, Physical Measurements and Signatures in Remote Sensing. CNES, Paris, pp. 521-527.
19. Curran, P.J., 1989. Remote sensing of foliar chemistry. Remote Sensing of Environment 29: 271-278.
20. Curran, P.J., 1994. Imaging spectrometry. Progress in Physical Geography 18: 247-266.
21. Curran, P.J., 2001. Remote sensing: using the spatial domain. Environmental and Ecological Statistics 8: 331-344.
22. Curran, P.J. & J.A. Kupiec, 1995. Imaging spectrometry: a new tool for ecology. In: F.M. Danson & S.E. Plummer (Eds), Advances in Environmental Remote Sensing. John Wiley & Sons, Chichester, pp. 71-88.
23. Curran, P.J., J.L. Dungan, B.A. Macler, S.E. Plummer & D.L. Peterson, 1992. Reflectance spectroscopy of fresh whole leaves for the estimation of chemical composition. Remote Sensing of Environment 39: 153-166.
24. Curran, P.J., J.A. Kupiec & G.M. Smith, 1997. Remote sensing the biochemical composition of a slash pine canopy. IEEE Transactions on Geoscience and Remote Sensing 35: 415-420.
25. Curran, P.J., J.L. Dungan & D.L. Peterson, 2001. Estimating the biochemical concentration of leaves with reflectance spectrometry: testing the Kokaly and Clark methodologies. Remote Sensing of Environment 76: 349-359.
26. Curran, P.J., E.J. Milton, P.M Atkinson & G.M. Foody, 1998. Remote sensing from data to understanding. In: P. Longley, S. Brooks, W. Macmillan & R. McDonnell (Eds), Geocomputation: A Primer. John Wiley & Sons, Chichester, pp. 33-59.
27. Danson, F.M., 1995. Developments in the remote sensing of forest canopy structure. In: F.M. Danson & S.E. Plummer (Eds), Advances in Environmental Remote Sensing. John Wiley & Sons, Chichester, pp. 53-69.
28. Danson, F.M. & P.J. Curran, 1993. Factors affecting the remotely sensed response of coniferous forest plantations. Remote Sensing of Environment 43: 55-65.
29. Daughtry, C.S.T., C.L. Walthall, M.S. Kim, E. Brown de Colstown & J.E. McMurtrey III, 2000. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment 74: 229-239.
30. Davies, A.M.C. & P. Williams (Eds), 1996. Near Infrared Spectroscopy: The Future Waves. Proceedings, 7th International Conference on NIR Spectroscopy. NIR Publications, Chichester.
31. Dawson, T.P., 2000. The potential for estimating chlorophyll content from a vegetation canopy using the Medium Resolution Imaging Spectrometer (MERIS). International Journal of Remote Sensing 21: 2043-2051.
32. Dawson, T.P., P.J. Curran, P.R.J. North & S.E. Plummer, 1999. The propagation of foliar biochemical absorption features in forest canopy reflectance: a theoretical analysis. Remote Sensing of Environment 67: 147-159.
33. Dawson, T.P., P.J. Curran & S.E. Plummer, 1998a. LIBERTY - Modelling the effects of leaf biochemical concentration on reflectance spectra. Remote Sensing of Environment 65: 50-60.
34. Dawson, T.P., P.J. Curran & S.E. Plummer, 1998b. The biochemical decomposition of slash pine needles from reflectance spectra using neural networks. International Journal of Remote Sensing 19: 1433-1438.
35. Demarez, V. & J.P. Gastellu-Etchegorry, 2000. A modelling approach for studying forest chlorophyll content. Remote Sensing of Environment 71: 226-238.
36. Demarez, V., J.P. Gastellu-Etchegorry, E. Mougin, G. Marty, C. Proisy, E. Dufrêne & V. Le Dantec, 1999. Seasonal variation of leaf chlorophyll content of a temperate forest. Inversion of the PROSPECT model. International Journal of Remote Sensing 20: 879-894.
37. Denniss, A., 1999. Moving into the hyperspectral age. Mapping Awareness 13 (10): 47-49.
38. Dixit, L. & S. Ram, 1985. Quantitative analysis by derivative electronic spectroscopy. Applied Spectroscopy Reviews 21: 311-418.
39. Duckworth, J.H., 1998. Spectroscopic quantitative analysis. In: J. Workman Jr. & A. Springsteen (Eds), Applied Spectroscopy. A Compact Reference for Practitioners. Academic Press, San Diego, CA, pp. 93-190.
40. Dungan, J.L., L.F. Johnson, C.R. Billow, P.A. Matson, J. Mazzurco, J. Moen & V.C. Vanderbilt, 1996. High spectral resolution reflectance of Douglas fir grown under different fertilization treatments: experiment design and treatment effects. Remote Sensing of Environment 55: 217-228.
41. Fourty, Th. & F. Baret, 1998. On spectral estimates of fresh leaf biochemistry. International Journal of Remote Sensing 19: 1283-1297.
42. Fourty, Th., F. Baret, S. Jacquemoud, G. Schmuck & J. Verdebout, 1996. Leaf optical properties with explicit description of its biochemical composition: direct and inverse problems. Remote Sensing of Environment 56: 104-117.
43. Ganapol, B.D., L.F. Johnson, P.D. Hammer, C.A. Hlavka & D.C. Peterson, 1998. LEAFMOD: a new within-leaf radiative transfer model. Remote Sensing of Environment 63: 182-193.
44. Ganapol, B.D., L.F. Johnson, C.A. Hlavka, D.L Peterson & B. Bond, 1999. LCM2: a coupled leaf/canopy radiative transfer model. Remote Sensing of Environment 70: 153-166.
45. Gastellu-Etchegorry, J.P. & V. Bruniquel-Pinel, 2001. A modelling approach to assess the robustness of spectrometric predictive equations for canopy chemistry. Remote Sensing of Environment 76: 1-15.
46. Geladi, P. & E. Dåbakk, 1995. An overview of chemometrics applications in near infrared spectrometry. Journal of Near Infrared Spectroscopy 3: 119-132.
47. Gholz, H.L., P.J. Curran, J.A. Kupiec & G.M. Smith, 1997. Assessing leaf area and canopy biochemistry of Florida slash pine using remote sensing. In: H.L. Gholz, K. Nakane & H. Shimoda, (Eds), The Use of Remote Sensing in the Modelling of Forest Productivity. Kluwer Academic Publishers, Dordrecht, pp. 3-22.
48. Gillon, D., C. Houssard & J. Richard, 1999. Using near-IR reflectance spectroscopy to predict carbon, nitrogen and phosphorus content in hetergoneneous plant material. Oecologia 118: 173-182.
49. Gitelson, A.A. & M.N. Merzlyak, 1997. Remote estimation of chlorophyll content in higher plant leaves. International Journal of Remote Sensing 18: 2691-2697.
50. Goetz, S. J. & S.D. Prince, 1996. Remote sensing of net primary production in boreal forest stands. Agricultural and Forest Meteorology 78: 149-179.
51. Green, R.O., M.L. Eastwood, C.M. Sarture, T.G. Chrien, M. Aronsson, B.J. Chippendale, J.A. Faust, B.E. Pauri, C.J. Chovit, M. Solis, M.R. Olah & O. Williams, 1998. Imaging spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment 65: 227-248.
52. Grossman, Y.L., S.L. Ustin, S. Jacquemoud, E.W. Sanderson, G. Schmuck & J. Verdebout, 1996. Critique of stepwise multiple linear regression for the extraction of leaf biochemistry information from leaf reflectance data. Remote Sensing of Environment 56: 1-12.
53. Guyot, G. & Th. Phulpin (Eds), 1997. Physical Measurements and Signatures in Remote Sensing. A.A. Balkema, Rotterdam.
54. Hallett, R.A., J.W. Hornbeck & M.E. Martin, 1997. Predicting elements in white pine and red oak foliage with visible near-infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy 5: 77-82.
55. Hana, M., W.F. McClure, T.B. Whitaker, M.W. White & D.R. Bahler, 1997. Applying artificial neural networks: Part II. Using near infrared data to classify tobacco types and identify native grown tobacco. Journal of Near Infrared Spectroscopy 5: 19-25.
56. Heise, H.M., A. Bittner & R. Marbach, 1998. Clinical chemistry and near infrared spectroscopy: technology for non-invasive glucose monitoring. Journal of Near Infrared Spectroscopy 6: 349-359.
57. Hill, J. & J. Mégier (Eds), 1994. Imaging Spectrometry - A Tool for Environmental Observations. Kluwer Academic Publishers, Dordrecht.
58. Hlavka, C.A., D.L. Peterson, L.F. Johnson & B. Ganapol, 1997. Analysis of forest foliage spectra using a multivariate mixture model. Journal of Near Infrared Spectroscopy 5: 167-173.
59. Jacquemoud, S. & F. Baret, 1990. PROSPECT: a model of leaf optical properties spectra. Remote Sensing of Environment 34: 75-91.
60. Jacquemoud, S., S.L. Ustin, J. Verdebout, G. Schmuck, G. Andreoli & B. Hosgood, 1996. Estimating leaf biochemistry using the PROSPECT leaf optical properties model. Remote Sensing of Environment 56: 194-202.
61. Jacquemoud, S. & S.L. Ustin, 2001. Leaf optical properties: a state of the art. 8th International Symposium Physical measurements and signatures in Remote Sensing. CNES, Paris, pp. 223-232.
62. Jago, R.A., M.E.J. Cutler & P.J. Curran, 1999. Estimating canopy chlorophyll concentration from field and airborne spectra. Remote Sensing Environment 68: 206-216.
63. Joffre, R., D. Gillion, P. Dardenne, R. Agneessens & R. Biston, 1992. The use of near-infrared reflectance spectroscopy in litter decomposition studies. Annales de Sciences Forestieres 49: 481-488.
64. Johnson, L.F., C.A. Hlavka & D.L. Peterson, 1994. Multivariate analysis of AVIRIS data for canopy biochemical estimation along the Oregon transect. Remote Sensing of Environment 47: 216-230.
65. Johnson, L.F. & C.R. Billow, 1996. Spectrometric estimation of total nitrogen concentration in Douglas-fir foliage. International Journal of Remote Sensing 17: 489-500.
66. Kokaly, R.F., 2001. Investigating a physical basis for spectroscopic estimates of leaf nitrogen concenctration. Remote Sensing of Environment 75: 153-161.
67. Kokaly, R.F. & R.N. Clark, 1999. Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote Sensing of Environment 67: 267-287.
68. Kruse, F.A., 1999. Visible-infrared sensors and case studies. In: A.N. Rencz (Ed.), Remote Sensing for the Earth Sciences. Manual of Remote Sensing, Volume 3. John Wiley & Sons, New York, NY, pp. 567-611.
69. Kruse, F.A., A.B. Lefkoff, J.W. Boardman, K.B. Heidebrecht, A.T. Shapiro, P.J. Barloon & A.F.H. Goetz, 1993. The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment 44: 145-163.
70. Kupiec, J.A. & P.J. Curran, 1995. Decoupling the effect of the canopy and foliar biochemical concentration in AVIRIS spectra. International Journal of Remote Sensing 16: 1731-1739.
71. Lister, S.J., M.S. Dhanoa, P.O.M. Omondi & I. Mueller-Harvey, 1997. Kenyan elephant feed preferences explored by near infrared spectroscopy. Journal of Near Infrared Spectroscopy 5: 99-111.
72. Lucas, N.S. & P.J. Curran, 1999. Forest ecosystem simulation modelling: the role of remote sensing. Progress in Physical Geography 23: 391-423.
73. Lucas, N.S., P.J. Curran, S.E. Plummer & F.M. Danson, 2000. Estimating the stem carbon production of a coniferous forest using ecosystem simulation model driven by the remotely sensed red edge. International Journal of Remote Sensing 21: 619-631.
74. Marten, G., J. Shenk & F.E. Barton II, 1989. Near Infrared Reflectance Spectroscopy (NIRS): analysis of forage quality. Technical Report 643. United States Department of Agriculture, Washington, DC.
75. Martin, M.E., 1994. Measurements of foliar chemistry using laboratory and airborne high spectral resolution visible and infrared data. Unpublished PhD thesis. University of New Hampshire, Durham, NH.
76. Martin, M.E., S.D. Newman, J.D. Aber & R.G. Congalton, 1998. Determining forest species composition using high spectral resolution remote sensing data. Remote Sensing of Environment 65: 249-254.
77. Martin, M.E. & J.D. Aber, 1997. High spectral resolution remote sensing of forest canopy lignin, nitrogen and ecosystem process. Ecological Applications 7: 431-443.
78. Martinsen, P., P. Schaare & M. Andrews, 1999. A versatile near infrared imaging spectrometer. Journal of Near Infrared Spectroscopy 7: 17-25.
79. Massart, D.L., B.G.M. Vandeginste, L.M.C. Buydens, S. de Jong, P.J. Lewi & J. Smeyers-Verbeke(Eds), 1998. Handbook of Chemometrics and Qualimetrics. Elsevier, Amsterdam.
80. Matson, P., L.F. Johnson, C. Billow, J. Miller & R. Pu, 1994. Seasonal patterns and remote spectral estimation of canopy chemistry across the Oregon transect. Ecological Applications 4: 280-298.
81. McClure, W.F., S.L. Ranford, M.J. Hammersley & A.M.C. Davies, 1991. Black holes in near infrared spectroscopy. Applied Spectroscopy 45: 14A-14B.
82. McGlone, V.A., H. Abe & S. Kawano, 1997. Kiwifruit firmness by near infrared light scattering. Journal of Near Infrared Spectroscopy 5: 83-89.
83. Méthy, M., R. Joffre & J.M. Ourcival, 1998. Two ways of assessing absorbance of fresh leaves from near-infrared reflectance spectroscopy. International Journal of Remote Sensing 19: 1741-1750.
84. Montalvo Jr, J.G., S.E. Buco & H.H. Ramey Jr, 1994. Studies to measure cotton fibre length, strength, micronaire and colour by vis/NIR reflectance spectroscopy. Part II: Principal components regression. Journal of Near Infrared Spectroscopy 2: 185-198.
85. Morgan, E. (Ed.), 1991. Chemometrics: Experimental Design. John Wiley & Sons, London.
86. Newman, S.D., M.E. Soulia, J.D. Aber, B. Dewey & A. Ricca, 1994. Analyses of forest foliage I: Laboratory procedures for proximate carbon fractionation and nitrogen determination. Journal of Near Infrared Spectroscopy 2: 5-14.
87. Osborne, B.G., T. Fearn & P.H. Hindle, 1993. Practical NIR Spectroscopy with Application in Food and Beverage Analysis (2nd Edn). Longman, Harlow.
88. Otto, M. (Ed.), 1999. Chemometrics. John Wiley & Sons, Chichester.
89. Penuelas, J., F. Baret & I. Filella, 1995. Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica 31: 221-230.
90. Peterson, D.L., 1991. Report, Workshop Remote Sensing of Plant Biochemical Content: Theoretical and Empirical Studies. NASA Ames Research Center, Moffett Field, CA.
91. Peterson, D.L., 2000. NIRS in space? NIRS News 11(2): 10-12.
92. Peterson, D.L., J.D. Aber, P.A. Matson, D.H. Card, N.A. Swanberg, C.A. Wessman & M.A. Spanner, 1988. Remote sensing of forest canopy leaf biochemical contents. Remote Sensing of Environment 24: 85-108.
93. Peterson, D.L. & G.S. Hubbard, 1992. Scientific issues and potential remote sensing requirements for plant biochemical content. Journal of Imaging Science and Technology 36: 446-456.
94. Ponzoni, F.J. & J.L. de M. Gonçalves, 1999. Spectral features associated with nitrogen, phosphorous, and potassium deficiencies in Eucalyptus salinga seedling leaves. International Journal of Remote Sensing 20: 2249-2264.
95. Rees, G., 1999. The Remote Sensing Data Book. Cambridge University Press, Cambridge.
96. Running, S.W., 1990. Estimating terrestrial primary productivity combining remote sensing and ecosystem simulation. In: R.J. Hobbs & H.A. Mooney (Eds), Remote Sensing of Biosphere Functioning. Springer-Verlag, New York, NY, pp. 65-86.
97. Salgo, A., J. Nagy, É. Mikó & I. Boros, 1998. Application of near infrared spectroscopy in the sugar industry. Journal of Near Infrared Spectroscopy 6: A101-A106.
98. Schowengerdt, R.A., 1997. Remote Sensing: Models and Methods for Image Processing (2nd Edn). Academic Press, San Diego, CA.
99. Sinnaeve, G., P. Dardenne & R. Agneessens, 1994. Global or local? A choice for NIR calibration in analyses of forage quality. Journal of Near Infrared Spectroscopy 2: 163-175.
100. Smith, G.M. & P.J. Curran, 1995. The estimation of foliar biochemical content of a slash pine canopy from AVIRIS imagery. Canadian Journal of Remote Sensing 21: 234-244.
101. Smith, G.M. & P.J. Curran, 1996. The signal-to-noise ratio (SNR) required for the estimation of foliar biochemical concentrations. International Journal of Remote Sensing 17: 1031-1058.
102. Smith, G.M. & P.J. Curran, 1999. Methods for estimating image signal-to-noise ratio (SNR). In: P.M. Atkinson & N.J. Tate (Eds), Advances in Remote Sensing and GIS Analysis. John Wiley & Sons, Chichester, pp. 61-74.
103. Sollinger, S. & M. Voges, 1997. Simultaneous determination of the main constituents of viscose spinning solutions by visible near infrared spectroscopy. Journal of Near Infrared Spectroscopy 5: 135-148.
104. Sørensen, L.K. & R. Jepsen, 1997. Detection of cheese batches exposed to Clostridium tyrobutyricum spoilage by near infrared spectroscopy. Journal of Near Infrared Spectroscopy 5: 91-97.
105. Staenz, K., 1992. A decade of imaging spectrometry in Canada. Canadian Journal of Remote Sensing 18: 187-197.
106. Thygesen, L.G., 1994. Determination of dry matter content and basic density of Norway spruce by near infrared reflectance and transmittance spectroscopy. Journal of Near Infrared Spectroscopy 2: 127-135.
107. Thyholta, K. & T. Isaksson, 1997. Near infrared spectroscopy of dry extracts from high moisture food products on solid support - a review. Journal of Near Infrared Spectroscopy 5: 179-193.
108. Treitz, P.M. & P.J. Howarth, 1999. Hyperspectral remote sensing for estimating biophysical parameters of forest ecosystems. Progress in Physical Geography 23: 359-390.
109. Tsai, F. & W. Philpot, 1998. Derivative analysis of hyperspectral data. Remote Sensing of Environment 66: 41-51.
110. Ustin, S.L., M.D. Smith, S. Jacquemoud, M. Verstraete & N. Govaerts, 1999. Geobotany: vegetation mapping for Earth sciences. In: A.N. Rencz (Ed.), Remote Sensing for the Earth Sciences. Manual of Remote Sensing, Volume 3. John Wiley & Sons, New York, NY, pp. 189-248.
111. Verstraete, M.M., B. Pinty & R.B. Myeni, 1996. Potentials and limitations of information extraction on the terrestrial biosphere from satellite remote sensing. Remote Sensing of Environment 58: 201-214.
112. Wessman, C.A., 1994. Remote sensing and the estimation of ecosystem parameters and functions. In: J. Hill & J. Mégier (Eds), Imaging Spectrometry - a Tool for Environmental Observations. Kluwer Academic Publishers, Dordrecht, pp. 39-56.
113. Westad, F. & H. Martens, 2000. Variable selection in near infrared spectroscopy based on significance testing in partial least squares regression. Journal of Near Infrared Spectroscopy 8: 117-124.
114. Williams, P.C. & K. Norris, 1987. Near infrared technology in the agricultural and food industries. American Association of Cereal Chemists Inc., St. Paul, MN.
115. Workman Jr., J. & A. Springsteen, (Eds), 1998. Applied Spectroscopy. A Compact Reference for Practitioners. Academic Press, San Diego, CA.
116. Wozny, C.E., D.W. Noid & B.G. Sumpter, 2000. A dynamical method for calculating the near infrared spectra of molecules and macromolecules. Journal of Near Infrared Spectroscopy 8: 133-150.
117. Wülder, M., 1998. Optical remote sensing techniques for the assessment of forest inventory and biophysical parameters. Progress in Physical Geography 22: 449-476.
118. Yoder, B.J. & R.E. Pettigrew-Crosby, 1995. Predicting nitrogen and chlorophyll content and concentration from reflectance spectra (400-2500 nm) at leaf and canopy scales. Remote Sensing of Environment 53: 199-211.
119. Zagolski, F., V. Pinel, J. Romier, D. Alcayde, J. Fontanari, J.P. Gastellu-Etchegorry, G. Giordana, G. Marty, E. Mougin & R. Joffre, 1996. Forest chemistry with high spectral resolution remote sensing. International Journal of Remote Sensing 17: 1107-1128.