Investigation of the utility of spectral vegetation indices for determining information on coniferous forests

Remote Sensing of Environment

Volumn 66, Issue 3, 1998, Pages 250-272

  McDonald, A J ^a,c   Gemmell, F M ^a   Lewis, P E ^b  

^a UNIVERSITY OF LEICESTER   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SOFTWARE; LIGHT REFLECTION; MATHEMATICAL MODELS; MONTE CARLO METHODS; RAY TRACING;

LEAF AREA INDEX; NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI);

VEGETATION;

COMPARATIVE STUDY; CONIFEROUS FOREST; DATA QUALITY; VEGETATION INDEX;

EID: 0032311806     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0034-4257(98)00057-1     Document Type: Article

References (77)

1. Abuelgasim A.A., Strahler A.H. Modeling bidirectional radiance measurements collected by the Advanced Solid-state Array Spectroradiometer (ASAS) over Oregon transect conifer forests. Remote Sens. Environ. 47:1994;261-275.
2. Anderson G.L., Hanson J.D., Haas R.H. Evaluating Landsat Thematic mapper derived vegetation indices for estimating above-ground biomass on semiarid rangeland. Remote Sens. Environ. 45:1993;165-175.
3. Asrar G., Myneni R.M., Kanemasu E.T. Estimation of plant canopy attributes from spectral reflectance measurements. Theory and Applications of Optical Remote Sensing. 1989;252-296 Wiley, New York.
4. Bannari, A., Morin, D., and He, D. C. (1994), High spatial and spectral resolution remote sensing for the management of urban environment. In First International Airborne Remote Sensing Conference, Strasbourg, France, Vol. III, pp. 247- 260.
5. Bannari A., Morin D., Bonn F., Huete A.R. A review of vegetation indices. Remote Sens. Rev. 13:1995;95-120.
6. Baret F., Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote. Sens. Environ. 35:1991;161-173.
7. Baret F., Jaquemoud S., Hanocq J.F. The soil line concept in remote sensing. Remote Sens. Rev. 7:1993;65-82.
8. Burgess D.W., Lewis P., Muller J.-P.A.L. Topographic effects in AVHRR NDVI data. Remote Sens. Environ. 54:1995;223-232.
9. Cavayas, F., and Teillet, P. M. (1985), Geometric model simulations of conifer canopy reflectance. In Proceedings of the 3rd International Colloquium on Spectral Signatures of Objects in Remote Sensing, pp. 183-189.
10. Chen J.M. Evaluation of vegetation indices and a modified simple ratio for boreal applications. Can. J. Remote Sens. 22:1996;229-242.
11. Chen J.M., Leblanc S.G. A four-scale bidirectional reflectance model based on canopy architecture. IEEE Trans. Geosci. Remote Sens. 35:1997;1316-1337.
12. Cihlar J., Manak D., Voisin N. AVHRR bidirectional reflectance effects and compositing. Remote Sens. Environ. 48:1994;77-88.
13. Cohen W.B., Spies T.A. Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat TM and SPOT imagery. Remote Sens. Environ. 41:1992;1-17.
14. Cooksley, G. (1997), The importance of geometric structure in forest canopy reflectance modelling, MSc thesis, University of London (unpublished).
15. Crist E.P., Cicone R.C. A physically based transformation of Thematic mapper data - The TM Tasseled Cap. IEEE Trans. Geosci. Remote Sens. 22:1984;256-263.
16. Curran P. Multispectral remote sensing of vegetation amount. Prog. Phys. Geogr. 4:1980;315-341.
17. Curran P.J., Williamson H.D. GLAI estimation using measurements of red, near-infrared, and middle infrared radiance. Photogramm. Eng. Remote Sens. 53:1987;181-186.
18. Elvidge C.D., Chen Z. Comparison of broad-band and narrow-band red and near-infrared vegetation indices. Remote Sens. Environ. 54:1995;38-48.
19. Escadafel R. Remote sensing of arid soil surface color with Landsat Thematic mapper. Adv. Space Res. 9:1989;1159-1163.
20. Franklin J., Michaelsen J., Strahler A.H. Spatial analysis of density dependent pattern in coniferous forest stands. Vegetatio. 64:1985;29-36.
21. Franklin J. Thematic Mapper analysis of conifer forest structure and composition. Int. J. Remote Sens. 7(10):1986;1287-1301.
22. Friedl M.A., Davis F.W., Michaelsen J., Moritz M.A. Scaling and uncertainty in the relationship between the NDVI and land surface biophysical variables. an analysis using the scene simulation model and data from FIFE Remote Sens. Environ. 54:1995;233-246.
23. Gemmell F.M. Effects of forest cover, terrain and scale on timber volume estimation with thematic mapper data in a Rocky Mountain site. Remote Sens. Environ. 51:1995;291-315.
24. Gemmell F. An investigation of terrain effects on the inversion of a forest reflectance model. Remote Sens. Environ. 65:1998;155-169.
25. Gilabert M.A., Segarra D., Meliá J. Simulation of citrus orchard reflectance by means of a geometrical canopy model. Int. J. Remote Sens. 15:1994;2559-2582.
26. Gong P., Pu R., Miller J.R. Coniferous forest leaf area index estimation along the oregon transect using compact airborne spectrographic imager data. Photogramm. Eng. Remote Sens. 61:1995;1107-1117.
27. Guyot G., Gu X. Effect of radiometric corrections on NDVI-determined from SPOT-HRV and Landsat-TM data. Remote Sens. Environ. 49:1994;169-180.
28. Hafley W.I., Scheuner H.T. Statistical distributions for fitting diameter and height data in even aged stands. Can. For. J. Res. 7:1977;481-489.
29. Hall F.G., Townshend J.R., Engman E.T. Status of remote sensing algorithms for estimation of land surface state parameters. Remote Sens. Environ. 51:1995;138-156.
30. Horler D.N.H., Ahern F.J. Forestry information content of Thematic Mapper data. Int. J. Remote Sens. 7:1986;405-428.
31. Huete A.R. A soil-adjusted vegetation index (SAVI). Remote Sens. Environ. 25:1988;295-309.
32. Huete A.R. Soil influences in remotely sensed vegetation canopy spectra. Asrar G. Theory and Applications of Optical Remote Sensing. 1989;107-141 Wiley, New York.
33. Huete A.R., Jackson R.D. Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands. Remote Sens. Environ. 23:1987;213-232.
34. Huete A.R., Jackson R.D., Post E.F. Spectral response of a plant canopy with different soil backgrounds. Remote Sens. Environ. 17:1985;37-53.
35. Huete A.R., Liu H.Q., Batchily K., van Leeuwen W. A comparison of vegetation indices over a global set of TM images for EOS-MODIS. Remote Sens. Environ. 59:1997;440-451.
36. Jackson R.D. Spectral indices in n-space. Remote Sens. Environ. 13:1983;409-421.
37. Jasinski M.F. Sensitivity of the normalized difference vegetation index to subpixel canopy cover, soil albedo and pixel scale. Remote Sens. Environ. 32:1990;169-187.
38. Jensen J.R. Biophysical Remote Sensing. Ann. Assoc. Am. Geogr. 73:1983;111-132.
39. Johnston R.J. Multivariate Statistical Analysis in Geography. A Primer on the General Linear Model:1978;Longman, London.
40. Jordan C.F. Derivation of leaf area index from quality of light on the forest floor. Ecology. 50:1969;663-666.
41. Kaufman Y.J., Sendra C. Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery. Int. J. Remote Sens. 9:1988;1357-1381.
42. Kaufman Y.J., Tanré D. Atmospherically resistant vegetation index (ARVI) for EOS-MODIS. IEEE Trans. Geosci. Remote Sens. 30:1992;261-270.
43. Kauth, R. J., and Thomas, G. S. (1976), The Tassled Cap - a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. In Proceedings of the Symposium on Machine Processing of Remotely Sensed Data, Purdue University, West Lafayette, IN pp. 4B-41- 4B-50.
44. Lacaze B., Caselles V., Coll C.et al. DeMon - integrated approaches to desertification mapping and monitoring in the Mediterranean basin. Hill J. Final Report of the Demon-1 Project. 1996;European Commission, Brussels, Belgium.
45. Leblon B., Granberg H., Charland S.-D. Shadowing effects on SPOT-HRV and high spectral resolution reflectances in Christmas tree plantations. Int. J. Remote Sens. 17:1996;277-289.
46. Leprieur C., Verstraete M.M., Pinty B. Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data. Remote Sens. Rev. 10:1994;265-284.
47. Leprieur C., Kerr Y.H., Pichon J.M. Critical assessment of vegetation indices from AVHRR in a semi-arid environment. Int. J. Remote Sens. 17:1996;2549-2563.
48. Lewis, P. (1996), A botanical plant modelling system for remote sensing simulation studies. Ph.D. thesis, University of London.
49. Lewis P., Muller J.-P. The advanced radiometric ray tracer. ARARAT for plant canopy reflectance simulation Int. Arch. Photogramm. Remote Sens. 29:1992;26-34.
50. Li X., Strahler A.H. Geometric optical modeling of a conifer forest canopy. IEEE Trans. Geosci. Remote Sens. 23:1985;705-721.
51. Li X., Strahler A.H. Geometric-optical bi-directional reflectance modeling of the discrete crown vegetation canopy. effect of crown shape and mutual shadowing IEEE Trans. Geosci. Remote Sens. 30:1992;276-292. a.
52. Li, X., and Strahler, A. H. (1992b), Mutual shadowing and directional reflectance of a rough surface: A geometrical-optical model. In Proceedings of the International Geoscience and Remote Sensing symposium (IGARSS92), Houston, TX, pp. 766-768.
53. Markham B.L., Barker J.L. Landsat MSS and TM post-calibration dynamic ranges, exoatmospheris reflectances and At-satellite temperatures. EOSAT Landsat Tech. Notes. 1:1986;5-8.
54. Myneni R.B., Asrar G. Atmospheric effects and spectral vegetation indices. Remote Sens. Environ. 47:1994;390-402.
55. Myneni R.B., Keeling C.D., Tucker C.J., Asrar G., Nemani R.R. Increased plant growth in the northern latitudes from 1981 to 1991. Nature. 386:1997;698-702.
56. Nilson T., Peterson U. A forest canopy reflectance model and a test case. Remote Sens. Environ. 37:1991;131-142.
57. Pinty B., Verstraete M.M. GEMI. a non-linear index to monitor global vegetation from satellites Vegetatio. 101:1992;15-20.
58. Plummer, S. E., North, P. R., and Briggs, S. A. (1994), The angular vegetation index: an atmospherically resistant index for the second along track scanning radiometer (ATSR-2). In Proceedings of the Sixth International Symposium on Physical Measurements and Signatures in Remote Sensing, Val d'Isère, France, CNES, Jan. 17-21, 1994, pp. 717-722.
59. Privette J.L., Emery W.J., Schimel D.S. Inversion of a vegetation reflectance model with NOAA AVHRR data. Remote Sens. Environ. 58:1996;187-200.
60. Qi, J., Moran, M. S., Huete, A. R., Jackson, R. D., and Chehbouni, A. (1991), View-atmosphere soil effect on vegeta- tion indices derived from SPOT images. In Proceedings of the 5th International Symposium on Physical Measurements and Signatures in Remote Sensing, Courchevel, France, pp. 785-790.
61. Qi J., Huete A.R., Moran M.S., Chehbouni A., Jackson R.D. Interpretation of vegetation indices derived from multi-temporal SPOT images. Remote Sens. Environ. 44:1993;89-101.
62. Qi J., Chehbouni A., Huete A.R., Kerr Y.H., Sorooshian S. A modified soil adjusted vegetation index. Remote Sens. Environ. 48:1994;119-126.
63. Qi J., Moran M.S., Cabot F., Dedieu G. Normalization of sun/view angle effects using spectral albedo-based vegetation indices. Remote Sens. Environ. 52:1995;207-217.
64. Rahman H., Verstraete M.M., Pinty B. Coupled Surface-Atmosphere Reflectance (CSAR) model. 1. Model description and inversion on synthetic data. J. Geophys. Res. 98:1993;20,779-20,789.
65. Richardson A.J., Wiegand C.L. Distinguishing vegetation from soil background information. Photogramm. Eng. Remote Sens. 43:1977;1541-1552.
66. Ripple W.J., Wang S., Isaacson D.L., Paine D.P. A preliminary comparison of Landsat Thematic Mapper and SPOT-1 HRV multispectral data for estimating coniferous forest volume. Int. J. Remote Sens. 12(9):1991;1971-1977.
67. Rondeaux G., Steven M., Baret F. Optimization of soil-adjusted vegetation indices. Remote. Sens. Environ. 55:1996;95-107.
68. Rouse, J. W., Haas, R. H., Shell, J. A., and Deering, D. W. (1973), Monitoring vegetation systems in the Great Plains with ERTS-1. In Third Earth Resources Technology Satellite Symposium, Vol. 1, pp. 309-317.
69. Schaaf C.B., Strahler A.H. Validation of bidirectional and hemispherical reflectances from a geometric-optical model using ASAS imagery and pyranometer measurements of a spruce forest. Remote Sens. Environ. 49:1994;138-144.
70. Schaaf C.B., Li X., Strahler A.H. Topographic effects on bidirectional and hemispherical reflectances calculated with a geometric-optical canopy model. IEEE Trans. Geosci. Remote Sens. 6:1994;1186-1193.
71. Tanré D., Holben B.N., Kaufman Y.J. Atmospheric correction algorithm for NOAA-AVHRR products. theory and application IEEE Trans. Geosci. Remote Sens. 30:1992;231-248.
72. Teillet P.M., Fedosejevs G. On the dark target approach to atmospheric correction of remotely sensed data. Can. J. Remote Sens. 21:1995;374-385.
73. Teillet P.M., Staenz K., Williams D.J. Effects of spectral, spatial, and radiometric characteristics on remote sensing vegetation indices of forested regions. Remote Sens. Environ. 61:1997;139-149.
74. Vermote E.F., Tanré D., Deuzé J.L., Herman M., Morcrette J.J. Second simulation of the satellite signal in the solar spectrum, 6S. an overview IEEE Trans. Geosci. Remote Sens. 35:1997;675-686.
75. Verstraete M.M., Pinty B. The potential contribution of satellite remote sensing to the understanding of arid lands processes. Vegetatio. 91:1991;59-72.
76. Verstraete M.M., Pinty B. Designing optimal spectral indexes for remote sensing applications. IEEE Trans. Geosci. Remote Sens. 34:1996;1254-1265.
77. Wulder M.A., LeDrew E.F., Franklin S.E., Lavigne M.B. Aerial image texture information in the estimation of northern deciduous and mixed wood forest leaf area index (LAI). Remote Sens. Environ. 64:1998;64-76.