Remote sensing of forest pigments using airborne imaging spectrometer and LIDAR imagery

Remote Sensing of Environment

Volumn 82, Issue 2-3, 2002, Pages 311-321

  Blackburn, George Alan ^a  

^a LANCASTER UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CHLOROPHYLL; FORESTRY; PHOTOSYNTHESIS; SPECTROMETERS;

ROOT MEAN SQUARES ERRORS;

REMOTE SENSING;

AIRBORNE SENSING; FOREST CANOPY; LIDAR; PIGMENT; REMOTE SENSING; SPECTRAL REFLECTANCE; SPECTROMETER;

UNITED KINGDOM;

EID: 0036788865     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0034-4257(02)00049-4     Document Type: Article

References (74)

1. Adams, M. L., Philpot, W. D., & Norvell, W. A. (1999). Yellowness index: an application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation. International Journal of Remote Sensing, 20, 3663-3675.
2. Aoki, M., Yabuki, K., & Totsuka, T. (1981). An evaluation of chlorophyll content of leaves based on the spectral reflectivity in several plants. Research Reports of the National Institute of Environmental Studies of Japan, 66, 125-130.
3. Baltsavias, E. P. (1999). A comparison between photogrammetry and laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 54, 83-94.
4. Bartelink, H. H. (1997). Allometric relationships for biomass and leaf area index of beech. Annales Des Sciences Forestieres, 54, 39-50.
5. Blackburn, G. A. (1998a). Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leaves. International Journal of Remote Sensing, 19, 657-675.
6. Blackburn, G. A. (1998b). Quantifying chlorophylls and carotenoids from leaf to canopy scales: an evaluation of some hyper-spectral approaches. Remote Sensing of Environment, 66, 273-285.
7. Blackburn, G. A. (1999). Relationships between spectral reflectance and pigment concentrations in stacks of broadleaves. Remote Sensing of Environment, 70, 224-237.
8. Blackburn, G. A., & Milton, E. J. (1996). Filling the gaps: remote sensing meets woodland ecology. Global Ecology and Biogeography, 5, 175-191.
9. Blackburn, G. A., & Milton, E. J. (1997). An ecological survey of broad-leaved woodlands using airborne remote sensing and geographical information systems (GIS). International Journal of Remote Sensing, 18, 1919-1935.
10. Blackburn, G. A., & Steele, C. M. (1999). Towards the remote sensing of matorral vegetation physiology: relationships between spectral reflectance, pigment and biophysical characteristics of semi-arid bushland canopies. Remote Sensing of Environment, 70, 278-292.
11. Boochs, F., Dockter, K., Kupfer, G., & Kuhbauch, W. (1990). Shape of the red edge as a vitality indicator for plants. International Journal of Remote Sensing, 11, 1741-1754.
12. Broge, N. H., & Leblanc, E. (2000). Comparing the prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment, 76, 156-172.
13. Carter, G. A. (1994). Ratios of leaf reflectances in narrow wavebands as indicators of plant stress. International Journal of Remote Sensing, 15, 697-703.
14. Carter, G. A., Cibula, W. G., & Miller, R. L. (1996). Narrow band reflectance imagery compared with thermal imagery for early detection of plant stress. Journal of Plant Physiology, 148, 515-522.
15. Chappelle, E. W., Kim, M. S., & McMurtrey III, J. E. (1992). Ratio analysis of reflectance spectra (RARS): an algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B and the carotenoids in soybean leaves. Remote Sensing of Environment, 39, 239-247.
16. Curran, P. J. (1994). Imaging spectrometry. Progress in Physical Geography, 18, 247-266.
17. Curran, P. J., Dungan, J. L., & Gholz, H. L. (1990). Exploring the relationship between reflectance, red edge and chlorophyll content in slash pine. Tree Physiology, 7, 33-48.
18. Curran, P. J., Dungan, J. L., Macler, B. A., & Plummer, S. E. (1991). The effect of a red leaf pigment on the relationship between red-edge and chlorophyll concentration. Remote Sensing of Environment, 35, 69-75.
19. Danson, F. M., & Curran, P. J. (1993). Factors affecting the remotely sensed response of coniferous forest plantations. Remote Sensing of Environment, 43, 55-65.
20. Danson, F. M., & Plummer, S. E. (1995). Red-edge response to forest leaf-area index. International Journal of Remote Sensing, 16, 183-188.
21. Datt, B. (1998). Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a+b and total carotenoid content in eucalyptus leaves. Remote Sensing of Environment, 66, 111-121.
22. Datt, B. (1999a). A new reflectance index for remote sensing of chlorophyll content in higher plants: tests using eucalyptus leaves. Journal of Plant Physiology, 154, 20-26.
23. Datt, B. (1999b). Visible/near infrared reflectance and chlorophyll content in eucalyptus leaves. International Journal of Remote Sensing, 20, 2741-2759.
24. Daughtry, C. S. T., Walthall, C. L., Kim, M. S., Brown de Colstoun, E., & McMurtrey, J. E. (2000). Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment, 74, 229-239.
25. Dawson, T. P., & Curran, P. J. (1998). A new technique for interpolating the reflectance red edge position. International Journal of Remote Sensing, 19, 2133-2139.
26. Demarez, V., & Gastellu-Etchegorry, P. (2000). A modelling approach for studying forest chlorophyll content. Remote Sensing of Environment, 71, 226-238.
27. Demarez, V., Gastellu-Etchegorry, P., Mougin, E., Marty, G., Proisy, C., Dufrene, E., & Le Dantec, V. (1999). Seasonal variation of leaf chlorophyll content of a temperate forest. Inversion of the PROSPECT model. International Journal of Remote Sensing, 20, 879-894.
28. Elvidge, C. D., & Chen, Z. (1995). Comparison of broad-band and narrow-band red and near-infrared vegetation indices. Remote Sensing of Environment, 54, 38-48.
29. Filella, I., & Peñuelas, J. (1994). The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status. International Journal of Remote Sensing, 15, 1459-1470.
30. Filella, I., Serrano, L., Serra, J., & Peñuelas, J. (1995). Evaluating wheat nitrogen status with canopy reflectance indices and discriminant analysis. Crop Science, 35, 1400-1405.
31. Gamon, J. A., & Surfus, J. S. (1999). Assessing leaf pigment content and activity with a reflectometer. New Phytologist, 143, 105-117.
32. Gitelson, A. A., Kaufman, Y. J., & Merzlyak, M. N. (1996). Use of a green channel in remote sensing of vegetation from EOS-MODIS. Remote Sensing of Environment, 58, 289-298.
33. Gitelson, A. A., & Merzlyak, M. N. (1994). Quantitative estimation of chlorophyll-a using reflectance spectra: experiments with autumn chestnut and maple leaves. Journal of Photochemistry and Photobiology. B, Biology, 22, 247-252.
34. Gitelson, A. A., & Merzlyak, M. N. (1996). Signature analysis of leaf reflectance spectra: algorithm development for remote sensing of chlorophyll. Journal of Plant Physiology, 148, 494-500.
35. Gitelson, A. A., & Merzlyak, M. N. (1997). Remote estimation of chlorophyll content in higher plant leaves. International Journal of Remote Sensing, 18, 2691-2697.
36. Gitelson, A. A., Merzlyak, M. N., & Lichtenthaler, H. K. (1996). Detection of red edge position and chlorophyll content by reflectance measurements near 700 nm. Journal of Plant Physiology, 148, 501-508.
37. Gomes Pereira, L. M., & Janssen, L. L. F. (1999). Suitability of laser data for DTM generation: a case study in the context of road planning and design. ISPRS Journal of Photogrammetry and Remote Sensing, 54, 244-253.
38. Gougeon, F. A. (1995). A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution images. Canadian Journal of Remote Sensing, 21, 274-284.
39. Horler, D. N. H., Dockray, M., & Barber, J. (1983). The red edge of plant leaf reflectance. International Journal of Remote Sensing, 4, 273-288.
40. Jago, R. A., Cutler, M. E. J., & Curran, P. J. (1999). Estimating canopy chlorophyll concentration from field and airborne spectra. Remote Sensing of Environment, 68, 217-224.
41. Jacquemond, S., & Baret, F. (1990). PROSPECT: a model of leaf optical properties spectra. Remote Sensing of Environment, 34, 75-91.
42. Koukoulas, S. (2001). Analysing the spatial structure of semi-natural deciduous woodlands through high-resolution airborne imagery and Geographical Information Systems. PhD thesis, Department of Geography, King's College, University of London, UK.
43. Koukoulas, S., & Blackburn, G. A. (2001). Introducing new indices for accuracy evaluation of classified images representing semi-natural woodland environments. Photogrammetric Engineering and Remote Sensing, 67, 499-510.
44. Kim, M. S., Daughtry, C. S. T., Chappelle, E. W., McMurtrey, J. E., & Walthall, C. L. (1994). The use of high spectral resolution bands for estimating absorbed photosynthetically active radiation. ISPRS Sixth International Colloquium on Physical Measurements and Signatures in Remote Sensing, Val d'Isère, France, 17-21 January 1994 (pp. 299-306). Paris: European Space Agency.
45. Lefsky, M. A., Cohen, W. B., Acker, S. A., Parker, G. G., Spies, T. A., & Harding, D. (1999). Lidar remote sensing of the canopy structure and biophysical properties of Douglas-Fir Western Hemlock Forests. Remote Sensing of Environment, 70, 339-361.
46. Lefsky, M. A., Harding, D., Parker, G., & Shugart, H. H. (1999). Lidar remote sensing of forest canopy and stand attributes. Remote Sensing of Environment, 67, 83-98.
47. Lichtenthaler, H. K. (1987). Chlorophylls and carotenoids: pigments of photosynthetic membranes. Methods in Enzymology, 148, 350-382.
48. Lichtenthaler, H. K., Gitelson, A. A., & Lang, M. (1996). Non-destructive determination of chlorophyll content of leaves of a green and an aurea mutant of tobacco by reflectance measurements. Journal of Plant Physiology, 148, 483-493.
49. Mariotti, M., Ercoli, L., & Masoni, A. (1996). Spectral properties of iron-deficient corn and sunflower leaves. Remote Sensing of Environment, 58, 282-288.
50. Means, J. E., Acker, S. A., Harding, D. J., Blair, J. B., Lefsky, M. A., Cohen, W. B., Harmon, M. E., & McKee, W. A. (1999). Use of large-footprint scanning airborne LIDAR to estimate forest stand characteristics in the Western Cascades of Oregon. Remote Sensing of Environment, 67, 298-308.
51. Milton, E. J., Blackburn, G. A., Rollin, E. M., & Danson, F. M. (1994). Measurement of the spectral directional reflectance of forest canopies: a review of methods and a practical application. Remote Sensing Reviews, 10, 285-298.
52. Moran, J. A., Mitchell, A. K., Goodmanson, G., & Stockburger, K. A. (2000). Differentiation among effects of nitrogen fertilization treatments on conifer seedlings by foliar reflectance: a comparison of methods. Tree Physiology, 20, 113-1120.
53. Munden, R., Curran, P. J., & Catt, J. A. (1994). The relationship between red edge and chlorophyll concentration in the Broadbalk winter wheat experiment at Rothamsted. International Journal of Remote Sensing, 15, 705-709.
54. Naesset, E. (1997). Estimating timber volume of forest stands using airborne laser scanner data, Remote Sensing of Environment, 61, 246-253.
55. Nilsson, M. (1996). Estimation of tree heights and stand volume using an airborne LIDAR system. Remote Sensing of Environment, 56, 1-7.
56. Ourcival, J. M., Joffre, R., & Rambal, S. (1999). Exploring the relationships between reflectance and anatomical and biochemical properties in Quercus ilex leaves. New Phytologist, 143, 351-364.
57. Peñuelas, J., Baret, F., & Filella, I. (1995). Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica, 31, 221-230.
58. Peñuelas, J., Filella, I., & Gamon, J. A. (1995). Assessment of photosynthetic radiation-use efficiency with spectral reflectance. New Phytologist, 141, 291-296.
59. Peñuelas, J., Filella, I., Lloret, P., Muñoz, F., & Vilajeliu, M. (1995). Reflectance assessment of mite effects on apple trees. International Journal of Remote Sensing, 16, 2727-2733.
60. Pinar, A., & Curran, P.J. (1996). Grass chlorophyll and the reflectance red edge. International Journal of Remote Sensing, 17, 351-357.
61. Pinz, A., & Bischof, H. (1990). Constructing a neural network for the interpretation of the species of trees in aerial photographs. In Proceedings of 10th International Conference in Pattern Recognition, Atlantic City, N.J, June 16-21 (pp. 755-757). Washington, DC: IEEE Computer Society.
62. Pollock, R. J. (1996). The automatic recognition of individual trees in aerial images of forests based on a synthetic tree crown image model. PhD thesis, University of British Columbia, Vancouver, Canada.
63. Sampson, P. H., Mohammed, G. H., ZarcoTejada, P. J., Miller, J. R., Noland, T. L., Irving, D., Treitz, P. M., Colombo, S. J., & Freemantle, J. (2000). The bioindicators of forest condition project: a physiological remote sensing approach. Forestry Chronicle, 76, 941-952.
64. Schepers, J. S., Blackmer, T. M., Wilhelm, W. W., & Resende, M. (1996). Transmittance and reflectance measurements of corn leaves from plants with different nitrogen and water supply. Journal of Plant Physiology, 148, 523-529.
65. Strahler, A., Woodcock, C., & Smith, J. (1986). On the nature of models in remote sensing. Remote Sensing of Environment, 20, 121-139.
66. Vane, G., & Goetz, A. F. H. (1993). Terrestrial imaging spectrometry: current status, future trends. Remote Sensing of Environment, 44, 117-126.
67. Verstraete, M. M., Pinty, B., & Curran, P. J. (1999). MERIS potential for land applications. International Journal or Remote Sensing, 20, 1747-1756.
68. Wehr, A., & Lohr, U. (1999). Airborne Laser Scanning - an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54, 68-82.
69. Weltz, M. A., Ritchie, J. C., & Fox, H. D. (1994). Comparison of laser and field measurements of vegetation height and canopy cover. Water Resources Research, 30, 1311-1319.
70. Wulder, M., LeDrew, E., Franklin, S., & Lavigne, M. (1998). Aerial image texture information in the estimation of northern broadleaved and mixed forest leaf area index (LAI). Remote Sensing of Environment, 64, 64-76.
71. Wulder, M., Niemann, K. O., & Goodenough, D. G. (2000). Local maximum filtering for the extraction of tree locations and basal area from high spatial resolution imagery. Remote Sensing of Environment, 73, 103-114.
72. Yamada, N., & Fujimura, S. (1991). Nondestructive measurement of chlorophyll pigment content in plant leaves from three-color reflectance and transmittance. Applied Optics, 30, 3964-3973.
73. Yoder, B. J., & Pettigrew-Crosby, R. E. (1995). Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400-2500 nm) at leaf and canopy scales. Remote Sensing of Environment, 53, 199-211.
74. Young, A., & Britton, G. (1990). Carotenoids and stress. In R.G. Alscher, & J. R. Cumming (Eds.), Stress responses in plants: adaptation and acclimation mechanisms (pp. 87-112). New York: Wiley-Liss.