SCIA

The main purpose of SCIA is the development and optimization of methods for the generation of products related to the Cryosphere. The project foresees the development of a robust processing chain of PRISMA hyperspectral data for the estimation of snow and glacier parameters in Alpine areas, through a combined use of satellite images, field data and radiative transfer models, which will also allow to evaluate the quality of the obtained products. SCIA aims at demonstrating that innovative algorithms for the generation of products related to a set of geophysical parameters of the cryosphere in the Alpine environment can be developed using PRISMA data. The image spectroscopy measurements provided by PRISMA will allow to investigate radiometrically complex surfaces and to obtain some geophysical parameters currently achievable only through airborne hyperspectral sensors. The possibility, for example, to recognize the three phases of water and the type of impurities on snow and ice allows to obtain a series of products currently non-existent and characterized by high innovativeness and important potential applications, also in view of the synergies with the next hyperspectral space missions.  The proposed research follows the valuable experiences obtained in the context of studies conducted with airborne hyperspectral sensors (e,g, AVIRIS), which have demonstrated the possibility of generating a series of geophysical parameters of the cryosphere with a high level of maturity and credibility of the proposed methodologies.  SCIA is articulated in three different phases and foresees a first part of pre-processing of PRISMA L1A data (acquired in different sites and in correspondence of ground campaigns), a phase of optimization/development/validation of algorithms for the generation of products (snow and ice geophysical parameters) and a phase of demonstrative character on the potentiality of PRISMA products for applications related to glacial and proglacial dynamics and snow processes and hydrological modeling, which are two aspects of strategic importance for policies in Alpine areas. The expected results of this project are therefore the development of processing methods and algorithms based on PRISMA hyperspectral data and the understanding of how the generated products can foster cryosphere-related applications.  The proposing team consists of EURAC Research, CNR-IREA, UNIMIB, ARPA VDA and the University of California, Los Angeles (UCLA) as a foreign partner. This team has extensive and documented experience in the field of processing multi-source remote sensing, optical hyperspectral, thermal and SAR data for cryosphere-related studies.

Responsible person: Claudia Notarnicola, claudia.notarnicola@eurac.edu

The SCIA project spans over a period of 24 months and is leaded by EURAC Research. The other partners are IREA-CNR, the University of Milan Bicocca (UNIMIB), Arpa Valle D’Aosta (ARPA-VdA) and the California University, Los Angeles (UCLA).

The main objectives of the project are the developments of products for the cryosphere by exploiting the hyperspectral images from PRISMA satellite.

EURAC is responsible for the following work packages:

WP1101: Project coordination. Management of the project activities and coordination among partners. Eurac as project lead will be also the interface towards ASI.

WP1102: Dissemination. It includes participation to meetings, conferences and writing of peer-reviewed papers.

WP2101: Snow and ice albedo. The aim is to develop products for mapping snow and ice albedo. First the images will be classified to identify different classes such as sow, ice, soils and other. Then the albedo is derived applying the specific signatures of each surface.

WP2102: Snow grain size. The grain size will be derived by using the approach of Nolin&Dozier (2000) that uses the characteristics of the snow in the spectrum 0.7-3.0µm.

WP2103: Three phases of water. To obtain the three phases of water, a decoupling approach will be used to disentangle the features of water vapour, water and ice. The results will be maps of water vapour and absorption coefficients from water and ice.

WP2104: Validation strategy. Starting from satellite, auxiliary and ground data available, the objectives are the harmonization of ground data collected in the different validation areas, execution of measurement campaigns to increase the set of validation data related to the different parameters, the development and implementation of a protocol for the validation of the snow parameters using the validation data collected and the analysis and evaluation of the accuracy of the products developed within the project. Model simulations will be used as well to check the robustness of the satellite estimates.

The main activities of 2023 are related to the development of algorithms for snow parameters retrieval. This activity has been done in parallel to the preprocessing activity of the satellite images, that aims to provide reliable inputs to derive the snow products from PRISMA bottom of atmosphere (BOA) reflectances. Another important activity involved the acquisition of in situ data by means of extensive field campaigns that made it possible to collect a lot of data, useful for validating the algorithms developed within the project. For the coming year (2024), the main activities will include the algorithms development finalization as well as activities related to algorithms validation with the data collected during measurement campaigns.