Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate 1 . Seasonal snow coveris the most dynamic element of the cryosphere. It responds rapidly to atmospheric conditions on timescales of days to weeks and, in fact, exhibits the greatest seasonal variation of any geophysical element on Earth's surface 2 . While large changes in snow cover are useful as indicators of climate change, snow also affects other components of the Earth system at different scales. The aim of the study is to track the use of different data and a differentiated approach to track the state of the snow cover. The object of research is the snow cover and its condition around Vitosha, Rila and Pirin mountains. The objects are mapped according to data of the European Space Agency (ESA) -Copernicus program. Data from different spectral snow mapping are obtained, which can be used to estimate results for quantitative changes in snow cover and wet snow cover. The data used are of high spatial resolution. The snow mapping system has sufficient temporal and spatial resolution. The research also emphasizes the possibilities that field data provide for validating the results of satellite data. Field data were collected from three different areas of interest in mountainous conditions. These are data from a mobile spectrometer Sekonic C-800 with a wavelength of 380 to 780nm and a thermal camera with a wavelength of 8 -14 μm. A differentiated approach was used in spectral mapping based on data from spectral indices such as Normalized Difference Forest Snow Index (NDFSI), Normalized Difference Snow Index (NDSI) and Normalized Difference Vegetation Index (NDVI). The study doesn't make a detailed characterization of each of the example areas, but demonstrates the use and combination of the integrated methodology for monitoring a database from different ranges of the Electromagnetic Spectrum.