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Spectral libarary of glacier surface reflectances

On 02.09, 03.09 and 04.09 of the year 2002, nearly 600 spectra were acquired from horizontal parts of Hintereisferner using the FieldSpec® Pro FR spectrometer.

For snow, firn and ice the following classification scheme was used: New Wet Snow (NWS), Old Dirty Snow (ODS), Old Clean Snow (OCS), Firn (FI), Clean Ice (CI) and Dirty Ice (DI). Per location, approximately 6-7 measurements together with 2 reference measurements were made. The spectrometer has a spectral sampling interval of 1.0nm in the spectral interval 350nm - 2500nm. The whole process of acquiring multiple measurements on different parts of a glacier is very time consuming and most of all laborious. Therefore the amount of available spectral glacier data is minimal. Such ground measurements form the ultimate basis for creating groundthruth databases for glacier surfaces. Our measurements of these surfaces were compared to albedo curves constructed by Zeng et al. (1984).

These spectral databases are generally used to unravel the often widely varying signals detected by satellites for specific surfaces. One might argue that as long as both ground and satellite acquisitions have not been done at the same time, the comparison of spectral measurements cannot be done.

Nevertheless, the measurements done at Hintereisferner in 2002 show great resemblance to typical reflection patterns of snow, firn and ice. In non-glacier studies, satellite images are interpreted spectrally using spectral libraries for e.g. certain stone or vegetation covers. These spectral libraries are even implemented in to the most common remote sensing software packages.

Therefore we think that this dataset is very valuable and may be the basis of a new spectral library that is to be constructed for glacier surfaces. As remote sensing techniques are becoming more popular and inevitable in land surface analysis, more of these datasets have to be acquired. They have to be compared and a standard has to be developed for their correct acquisition and the optimal atmospheric circumstances. Only then, glacier surfaces can be correctly interpreted by fine-tuning spectral data from satellite images.

Related information

Reported by

University of Turku
Department of Geography, University of Turku
20014 Turku
Finland
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