Abstract
Mapping sparse vegetation communities is routinely applied using techniques such as band ratios, the normalized difference vegetation index (NDVI) and spectral mixture analysis (SMA). The uncertainty of these vegetative mapping techniques is examined using the soil spectral variability defined by the spectral reference endmembers from three Landsat Thematic Mapper images: Owens Valley, California, USA; Gran Desierto, Sonora, Mexico, and Fayyum, Egypt. We find that band ratios and NDVI are not optimized for detecting vegetation given soil spectral variability. For SMA, the detection of sparse vegetation is optimized when it is detected as a residual component. Depending on the uncertainty model utilized from two to four fold improvement in mapping sparse vegetation is possible compared to NDVI and band ratios.
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7. References
Blount, G., M.O. Smith, J.B. Adams, R. Greeley, and P.R. Christensen (1990) ‘Regional aeolian dynamics and sand mixing in the Gran Desierto: evidence from Landsat thematic mapper images’, J. Geophys. Res., 95, 15463–15482.
Buck, P.E., S.C. Willis, and M.O. Smith (1986) ‘A mixture modeling approach to remote sensing of archaeological sites in Egypt using Landsat imagery’, in GSA annual meeting, Archaeological Geology Symposium, San Antonio.
Gillespie, A.R., M.O. Smith, J.B. Adams, S.C. Willis, A.F. Fischer, and D.E. Sabol (1990) ‘Interpretation of residual images: spectral mixture analysis of AVIRIS images, Owens Valley, California’, Proceedings of the Airborne Science Workshop, JPL Publ., 90-54, 243–270.
Huete, A.R., R.D. Jackson, and D.F. Post (1985) ‘Spectral response of a plant canopy with different soil backgrounds’, Remote Sensing of Environment, 17, 37–53.
Roberts, D.A., M.O. Smith, J.B. Adams, D.E. Sabol, A.R. Gillespie, and S.C. Willis (1991) ‘Isolating woody plant material and senescent vegetation from green vegetation in AVIRIS data’, Proceedings of the Airborne Science Workshop: AVIRIS, JPL Publ., 91-28, 43–50.
Roberts, D.A., M.O. Smith, D.E. Sabol, J.B. Adams, and S.L. Ustin (1992) ‘Mapping the spectral variability in photosynthetic and non-photosynthetic vegetation, soils and shade using AVIRIS’, in R.O. Green (ed.) ‘Summaries of the Third Annual JPL Airborne Geoscience Workshop, Vol I., AVIRIS Workshop’, June 1–2, 38–40.
Sabol, D.E., J.B. Adams, and M.O. Smith (1992) ‘Quantitative subpixel spectral detection of targets in multispectral images’, J. Geophys. Res., 97, 2659–2672.
Satterwhite, M.B. and P.J. Henley (1987) ‘Spectral characteristics of selected soils and vegetation in northern Nevada and their discrimination using band ratio techniques’, Remote Sensing of Environment, 23, 155–175.
Smith, M.O., S.L. Ustin, J.B. Adams, and A.R. Gilliespie (1990a) ‘Vegetation in deserts I: A regional measure of abundance from multispectral images’, Remote Sensing of Enivronment, 31, 1–26.
Smith, M.O., J.B. Adams, and A.R. Gillespie (1990b) ‘Reference endmembers for spectral mixture analysis’, Proc. 5th Australian Remote Sensing Conference, Perth, Western Australia, 8–12 October, vol. 1, 331–340.
Tucker, C.J. (1979) ‘Red and photographic infrared linear combinations for monitoring vegetation’, Remote Sensing of Environment, 8, 127–150.
Tucker, C.J. and L.D. Miller (1977) ‘Soil spectra contributions to grass canopy spectral reflectance’, Photogramm. Eng. Remote Sensing, 43, 721–726.
Ustin, S. L., J.B. Adams, CD. Elvidge, M. Rejmanek, B.N. Rock, M.O. Smith, R.W. Thomas, and R.A. Woodward (1986) ‘Thematic mapper studies of semi-arid shrub communities’, BioScience, 36, 446–452.
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© 1994 ECSC, EEC, EAEC, Brussels and Luxembourg
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Smith, M.O., Adams, J.B., Sabol, D.E. (1994). Mapping Sparse Vegetation Canopies. In: Hill, J., Mégier, J. (eds) Imaging Spectrometry — a Tool for Environmental Observations. Eurocourses: Remote Sensing, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-0-585-33173-7_12
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DOI: https://doi.org/10.1007/978-0-585-33173-7_12
Publisher Name: Springer, Dordrecht
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