Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: Comparing multispectral and hyperspectral observations

G. P. Asner, K. B. Heidebrecht

Research output: Contribution to journalArticle

261 Citations (Scopus)

Abstract

Remote measurements of the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil are critical to understanding climate and land-use controls over the functional properties of arid and semi-arid ecosystems. Spectral mixture analysis is a method employed to estimate PV, NPV and bare soil extent from multispectral and hyperspectral imagery. To date, no studies have systematically compared multispectral and hyperspectral sampling schemes for quantifying PV, NPV and bare soil covers using spectral mixture models. We tested the accuracy and precision of spectral mixture analysis in arid shrubland and grassland sites of the Chihuahuan Desert, New Mexico, USA using the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). A general, probabilistic spectral mixture model, Auto-MCU, was developed that allows for automated sub-pixel cover analysis using any number or combination of optical wavelength samples. The model was tested with five different hyperspectral sampling schemes available from the AVIRIS data as well as with data convolved to Landsat TM, Terra MODIS, and Terra ASTER optical channels. Full-range (0.4-2.5 μm) sampling strategies using the most common hyperspectral or multispectral channels consistently over-estimated bare soil extent and under-estimated PV cover in our shrubland and grassland sites. This was due to bright soil reflectance relative to PV reflectance in visible, near-IR, and shortwave-IR channels. However, by utilizing the shortwave-IR 2 region (SWIR2; 2.0-2.3 μm) with a procedure that normalizes all reflectance values to 2.03 μm, the sub-pixel fractional covers of PV, NPV and bare soil constituents were accurately estimated. AVIRIS is one of the few sensors that can provide the spectral coverage and signal-to-noise ratio in the SWIR2 to carry out this particular analysis. ASTER, with its 5-channel SWIR2 sampling, provides some means for isolating bare soil fractional cover within image pixels, but additional studies are needed to verify the results.

Original languageEnglish (US)
Pages (from-to)3939-3958
Number of pages20
JournalInternational Journal of Remote Sensing
Volume23
Issue number19
DOIs
StatePublished - Jan 1 2002
Externally publishedYes

Fingerprint

arid region
bare soil
vegetation
carbon
soil
reflectance
pixel
spectrometer
ASTER
sampling
shrubland
grassland
soil cover
Landsat thematic mapper
signal-to-noise ratio
vegetation cover
MODIS
imagery
desert
sensor

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Cite this

Spectral unmixing of vegetation, soil and dry carbon cover in arid regions : Comparing multispectral and hyperspectral observations. / Asner, G. P.; Heidebrecht, K. B.

In: International Journal of Remote Sensing, Vol. 23, No. 19, 01.01.2002, p. 3939-3958.

Research output: Contribution to journalArticle

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