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- W2134990897 abstract "Most methods applied for snow-cover mapping classify each pixel into snow and no-snow. On the other side, a sub-pixel method classifies snow into several coverage classes or onto a continuous scale. If frequent mapping is required, only low and medium spatial resolution sensors are available (200-1000 m range). Classifying pixels into snow and no-snow only may be sufficient for largescale applications. The method presented here intends to solve the problems of the current linear reflectance-to-snow-coverage sub-pixel algorithm. It gives a fast and very accurate estimate for the actual snow cover at the sub-pixel level. The method is in particularly useful for hyperspectral data. The method predicts local end-member spectra for snow and bare ground for each pixel. Vegetation end-members are predicted using a vegetation map made from another satellite image and a vegetation development model. Furthermore, a local snow end-member-spectrum predictor is used to predict a spectrum, which matches the development stage of the snow. The predictors also compensate for terrain relief effects while generating the actual end-member spectra. The prior information and the predictors allow the number of possible end-members for each pixel to be very low. An iterative algorithm is proposed in order to unmix two and three class component spectra for the prediction of the areal contribution of each class. The method has been applied to field measured spectra. Further experiments are ongoing for airborne DAIS-7915 hyperspectral data covering the Heimdalen test site in Jotunheimen, Norway. The spatial resolution of the DAIS data is reduced to 250 m simulating a medium-resolut ion sensor. The preliminary results show that the new method gives higher accuracy and reasonable computation time. However, further assessment on larger data sets is necessary to make a full evaluation of the method." @default.
- W2134990897 created "2016-06-24" @default.
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- W2134990897 date "2000-01-01" @default.
- W2134990897 modified "2023-09-27" @default.
- W2134990897 title "A NEW METHOD FOR SUB-PIXEL SNOW-COVER MAPPING USING HYPERSPECTRAL IMAGERY - FIRST RESULTS" @default.
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