Estimation of Snow Cover Area using multi-sensor data

This dataset is part of the experiments carried out to test our methodology on the estimation of snow cover area based on the synergistic use of MODIS and Sentinel-1 data. Different parameters such as the dual polarimetric entropy, mean scattering angle, backscatter coefficients, and the interferometric coherence, are integrated with a spatially resampled Normalized Difference Snow Index (NDSI) from MODIS to estimate a composite NDSI which is then used for the determination of the SCA. The composite NDSI is derived using a machine learning-based regression. The experiments are performed for the high elevated regions of the Kunduz and Khanabad watershed of the northern Hindu Kush mountains for the peak winter and early melt season of 2019 corresponding to the months of February and March. The reference snow cover area for the evaluation of the results is generated by thresholding the NDSI derived from pan-sharpened Landsat-8 imagery.