Abstract
The cryosphere has a relevant role for understanding the changes on our planet. Because of its importance, cryosphere has been investigated by addressing different remote sensing instruments and techniques. Even though many products and studies exist from multispectral and radar images, the exploitation of hyperspectral images is still in an early phase because of the limited availability of these sensors up to now. The study of the cryosphere by means of remote sensing hyperspectral data in the domain of reflected solar radiation (400-2500 nm) can contribute to determine key surface parameters such as albedo, grain size, liquid water content, concentration of organic and inorganic impurities, distribution of debris cover on glaciers, proglacial lakes and their surface characteristics. In this context, PRISMA data represent a unique opportunity for the development and optimization of algorithms for the estimation of physical parameters of snow and ice and are particularly well suited for investigations in complex morphologies such as alpine areas.
In this contribution, we present the main activities undertaken within the SCIA project founded by the Italian Space Agency. The main goal of the project is the development and optimization of algorithms to generate products useful for monitoring the cryosphere in different geographic and climatic context, with particular focus on mountainous alpine areas. The overall methodology is based on the jointly exploitation of satellite images, in-situ measurements, and radiative transfer modeling.
Particular attention will be initially paid on the generation of surface reflectance corrected for topography and including adjacency effects. We will present simulations performed by using radiative transfer models and the influences of the snow parameters on surface reflectance. Preliminary algorithms for detecting snow parameters, such as albedo, grain size and light absorbing impurities will be also presented at different scales. For assessing processes due to glacial-lakes interaction we will show some examples of deglaciation processes revealed by the amount of suspended solids into the lake. By exploiting the state-of-the-art solutions of hypersharpening (fusion of PAN and hyperspectral images) we map lakes in terms of number, size and shape and to compute the chromaticity coordinates and the dominant wavelengths to support the analysis of lake water properties. Finally, some examples of debris covered glacier are also addressed. Although the high level of accuracy and automation achieved to map ice and snow by satellite sensors, the recognition of supra-glacial debris is still an issue when the glacier snout is debris covered, and more in general, for those glaciers that are partially or totally debris-covered, the exploitation of spectroscopic method help the detection of such conditions.
In summary, imaging spectroscopy is promising for the detection of all these parameters and the possibilities offered by PRISMA to detect subtle spectral features can open new perspectives in the remote sensing of the cryosphere.