The main activities of the thematic area Earth Observation (EO) and Polar Ecosystem Modeling include remote and proximal sensing, spatial analysis, thematic mapping, and geographic and environmental knowledge organization. The activity focuses on three main methodological pillars: remote and in situ observations, information organization, and representation by numerical and conceptual models. The research of this thematic area focuses on the responses of polar ecosystems to changes in air and sea temperature, in polar ice caps, in sea level height, and in persistence and thickness of snowpack and ice, also through the comparisons of climate belts. Analyses also cover permafrost evolution, coastal erosion, accretion processes, release and segregation of climate-altering gases, biogeochemical cycles, and biodiversity. The observational methodologies aim to detect environmental and climate dynamics at different spatial and temporal scales by identifying and studying multiple essential variables and their biological and geophysical interactions by integrating information from different platforms. The continuous comparison allows the combination of spatial and ecological models with observations.
The team has a group dedicated to organizing multilingual terminological knowledge, thesauri, and metadata to support data description and environmental information, focusing on polar environments. The subject area develops, by Findable Accessible Interoperable Reusable (FAIR) principles, data chains and products to support the study of terrestrial, aquatic, and cryosphere systems and the development of interoperable GIS, thematic mapping, and operational services. Figure 1: the Spegazzini Glacier (Los Glaciares National Park, Santa Cruz, Argentina, January 2010), together with the Upsala and the Perito Moreno Glaciers, feeds the Lago Argentino in the Los Glaciares National Park, in this photo, the calving-type glacier front is visible, characterized by abundant seracs, which can reach 135 m in height.
Main ERC Panels: • LS8 - Environmental Biology, Ecology and Evolution • PE10 - Earth System Science • SH7 - Human Mobility, Environment, and Space • SH2 - Institutions, Values, Environment and Space
Characterization of the atmospheric column by remote sensing techniques and study of aerosol at the interface with the ground, use of EO data and their validation with ground-based measurements. Atmospheric chemistry, microchemistry, and climate-altering microphysics (use of thematic products of fire emissions and air pollution); physics of the atmosphere by point measurements at permanent observatories in polar and high-altitude areas, both fixed and mobile (ships); bioaerosol and its quantitative and qualitative composition. Study of the spatial structure of wind over the sea at various resolutions (from tens of km to 500 m) obtained through radar echo detections from the sea surface and Synthetic Aperture Radar (SAR) satellite images, integrated with artificial intelligence (AI) techniques in a continuous comparison with ground truth and numerical modeling.
Hydrosphere
Geospatial data management for marine and maritime domains, dynamics of marine ecosystems in the Svalbard area through analysis of existing thematic products (e.g., Copernicus). Management of the IT17 macro-site in Antarctica as part of the Italian Network for Long-Term Ecological Research (LTER-Italy). Characterization and description of the soundscape of polar and mid-latitude marine areas from permanent autonomous observatories for detecting biological, anthropogenic, and geophysical components. Noise analysis and assessment of ecological dynamics of marine mammals. Distribution and density analysis of maritime traffic and interaction with large mammals. Marine traffic, detection of large mammals, and correlation with sea ice. Coastal meteorology using SAR satellite data, wind from SAR and subsequent ice identification, and AI algorithms (local filters). Techniques for detecting, through the integration of remote and in situ sensors, sea level change trends at regional scales and their connection with subsidence phenomena. Chemical-physical and biological observations by sensing and point measurements in limnological environments in polar areas.
Figure 1 - Atlantic walrus acoustic signals: Spectrogram of the sounds (series of clicks or "knocks") produced by the Atlantic walrus, Odobenus rosmarus, underwater. The graph, produced in MATLAB(c), has a temporal resolution of 0.003 s and a frequency resolution of 0.128 Hz. The acoustic recording was performed by an underwater bottom recorder positioned within Kongsfjorden - Svalbard Islands. Listen:
Figure 2 - Sentinel 3: In the image acquired by the Ocean and Land Colour Instrument (OLCI) sensor of the Sentinel 3A satellite on Aug. 28, 2021, the Svalbard Islands archipelago (79 N, 17 E) can be seen as RGB (bands 4, 6, 8, 9, and 14 combined by enhanced true color visualization. Several perennial glaciers are visible, almost uniformly covering the tops of the islands in the archipelago. Cloud formations obscure the sea view to the north and west of the image. Ny-Ålesund, on the north-western edge of the archipelago's largest island, Spitsbergen, is home to the permanent base "Dirigibile Italia", CNR"s multidisciplinary research station in the Arctic.
Pedosphere
Biological and geological responses of soils and vegetation cover in the Arctic region to global warming; study of cause-and-effect relationships of permafrost greening and thawing processes and the carbon cycle using EO data, field radiometry, and geospatial models; analysis of the ecosystem dynamics of polar regions at different spatial and temporal scales, including extreme environments and modeling of alpine glaciers.
Figure 2 - On the left: Image acquired by the active sensor of the satellite Sentinel 1 on April 17, 2023, visualized in RGB composite =VV+VH+VV. The Yukon Delta (Alaska) is covered by snow, highlighting the contrast between the icy delta branches and the sea ice (violet and blue). On the right: Image acquired by the passive sensor of the satellite Sentinel2 on June 9, 2022, visualized in RGB composite = 9-3-2. The Yukon Delta is totally greened by the arctic tundra (red) the characteristic wetlands appear as dark patches and a coastal plume of sedimentary origin contours the delta.
Cryosphere
Monitoring of snow cover characteristics, radiometry, and field measurements on ice and seasonal snow, by composing thematic maps from satellite data and developing operational services. Study of absorbing particles such as black carbon and organic carbon on snow cover, algal occurrence in glacial areas, and processes at the cryosphere-atmosphere interface. Paleoclimate and environmental processes analysis using long point data sets. Calibration and validation of EO data.
Figure 1 - Extract from the CNR Spectral Library "Sispec" which highlights the spectral behavior, detected in the field, of a snow surface and its snowy characteristics (shape and size of the grains)
CNR-ISP National Research Council Institute of Polar Sciences c/o Scientific Campus - Ca' Foscari University Venice - Via Torino, 155 - 30172 VENEZIA MESTRE (VE) Phone: +39 041 2348547 - E-mail: protocollo.isp AT pec.cnr.it Fax: +39 041 2348 549 - Codice Fiscale: 80054330586 - P.I.:02118311006
The main activities of the thematic area Earth Observation (EO) and Polar Ecosystem Modeling include remote and proximal sensing, spatial analysis, thematic mapping, and geographic and environmental knowledge organization. The activity focuses on three main methodological pillars: remote and in situ observations, information organization, and representation by numerical and conceptual models. 
The research of this thematic area focuses on the responses of polar ecosystems to changes in air and sea temperature, in polar ice caps, in sea level height, and in persistence and thickness of snowpack and ice, also through the comparisons of climate belts. Analyses also cover permafrost evolution, coastal erosion, accretion processes, release and segregation of climate-altering gases, biogeochemical cycles, and biodiversity. The observational methodologies aim to detect environmental and climate dynamics at different spatial and temporal scales by identifying and studying multiple essential variables and their biological and geophysical interactions by integrating information from different platforms. The continuous comparison allows the combination of spatial and ecological models with observations. 
The team has a group dedicated to organizing multilingual terminological knowledge, thesauri, and metadata to support data description and environmental information, focusing on polar environments. The subject area develops, by Findable Accessible Interoperable Reusable (FAIR) principles, data chains and products to support the study of terrestrial, aquatic, and cryosphere systems and the development of interoperable GIS, thematic mapping, and operational services. Figure 1: the Spegazzini Glacier (Los Glaciares National Park, Santa Cruz, Argentina, January 2010), together with the Upsala and the Perito Moreno Glaciers, feeds the Lago Argentino in the Los Glaciares National Park, in this photo, the calving-type glacier front is visible, characterized by abundant seracs, which can reach 135 m in height. 
Characterization of the atmospheric column by remote sensing techniques and study of aerosol at the interface with the ground, use of EO data and their validation with ground-based measurements. Atmospheric chemistry, microchemistry, and climate-altering microphysics (use of thematic products of fire emissions and air pollution); physics of the atmosphere by point measurements at permanent observatories in polar and high-altitude areas, both fixed and mobile (ships); bioaerosol and its quantitative and qualitative composition. Study of the spatial structure of wind over the sea at various resolutions (from tens of km to 500 m) obtained through radar echo detections from the sea surface and Synthetic Aperture Radar (SAR) satellite images, integrated with artificial intelligence (AI) techniques in a continuous comparison with ground truth and numerical modeling. 
