Improving SAR‐Based Classification of Arctic Lake, Bay and Lagoon Ice by Accounting for Under Ice Water Salinity

Arctic lake, bay and lagoon ice regimes play a crucial role in understanding permafrost stability, hydrology, and carbon cycling in permafrost regions. This study integrates field and Synthetic Aperture Radar (SAR) data from Sentinel‐1 to improve the classification of Arctic lake, bay and lagoon ice regimes, with a particular focus on the influence of under‐ice water salinity. A May 2024 field campaign, revealed that waterbodies with a specific conductance of >4,000 µS/cm at the end of winter were often misclassified as bedfast using traditional SAR‐based classification methods. These findings underscore the limitations of relying on established approaches to differentiate floating and bedfast ice and highlight the need to account for differences in under‐ice water chemistry. To address this, we developed a novel ice regime classification, incorporating both early and late winter season SAR imagery, early summer SAR imagery to determine ice‐off timing, and a digital surface model. This enabled us to reliably classify waterbodies that are influenced by elevated under‐ice water salinities. Our approach identifies several floating ice waterbodies with moderate to high specific conductance values that were previously thought to freeze to their bed each winter. This study demonstrates that changes in radar backscatter can result from salinity‐related variations in ice and water properties, in addition to waterbody depth and ice thickness. These findings have significant implications for hydrological modeling, ecological studies, winter water availability, and community safety in the Arctic, emphasizing the need for integrating field observations with remote sensing data to better understand ice dynamics in permafrost regions.