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Eck, TF, Deering, DW, Vierling, LA (1997). Arctic tundra albedo and its estimation from spectral hemispheric reflectance. INTERNATIONAL JOURNAL OF REMOTE SENSING, 18(17), 3535-3549.

Abstract
We present the results of a held experiment in which the nearly complete bidirectional reflectance distribution function of Alaskan arctic tundra sites early in the growing season is measured by the PARABOLA instrument. The spectral hemispheric reflectances were computed by angular integration of these measurements for three wavebands: red (650-670 nm), near-infrared (810-840 nm) and shortwave infrared (1620-1690 nm). Total albedo was then estimated by weighting the spectral hemispheric reflectances by the fraction of total solar inadiance in three broadband spectral regions (300-700, 700-1300 and 1300-4000 nm) and representing each spectral region by the narrowband PARABOLA measurements. These calculations resulted in albedo estimates with a mean relative error of 15.7 per cent as compared to pyranometer measured albedo. Since vegetation reflectance varies signifrcantly over each of the three broadband regions, additional reflectance weighting factors were computed from a combination of high spectral resolution canopy reflectance data and corresponding computed spectral solar irradiance. This additional reflectance weighting resulted in a reduction in the mean relative error to 7.5 per cent relative to pyranometer measured albedo. It is noted that the three spectral bands of the PARABOLA instrument data reported here are similar to those of the spectral wavebands planned for future Advanced Very High Resolution Radiometer (AVHRR) sensors on National Oceanic and Atmospheric Administration (NOAA) satellites. Therefore the results and techniques presented here may be useful for future global albedo estimation utilizing AVHRR sensors. The analysis presented here may also be applied to albedo estimation from satellite sensors with higher spectral resolution and more complete spectral coverage, such as the future orbiting MODIS sensor, in which the errors of spectral reflectance weighting will be reduced considerably due to a more complete sampling of the reflected spectrum.

DOI:

ISSN:
0143-1161

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