Abstract
Accurate snow spectral albedo measurements from satellite data can essentially help to determine the changes over the snow surface area. In the current study, spectral snow albedo is measured over the northern region of Pakistan using spatio-temporal imagery datasets taken by Landsat satellite series equipped with TM and ETM+ sensors. An Automatic Cloud Cover Assessment (ACCA) algorithm is used to mask cloudy pixels from further processing. Furthermore, an image independent model, Second Simulation of the Satellite Signal in the Solar Spectrum (6S) is used in the current research work to atmospherically correct the satellite data. The snow cover albedo of northern Pakistan is estimated using pixel values prior to correction, ACCA output values, and 6S model output values. The results of the study show that highest albedo values are estimated using Landsat band 4 data with albedo model. The results of the study also show that the albedo values measured (band 4) in the year 1992 (0.989) are reduced in the year 2000 (0.931). It is expected that the results of the study could be utilized to predict climatic variations for spring runoff estimation.