REACTIV and Sentinel-1: Advances in event-based alerts, seasonal adaptation, and polarimetric optimization for large-scale change detection

Abstract The REACTIV algorithm has emerged as a powerful tool for detecting changes in large-scale Sentinel-1 SAR time series, providing an intuitive visualization of temporal dynamics. Since its introduction, it has been widely adopted in various Earth observation applications, ranging from maritime surveillance to urban expansion monitoring. This article reviews its main applications within the remote sensing community and evaluates its contributions to SAR-based change detection. Despite its success, the algorithm in its generic form has limitations in specific contexts. To address these, we introduce three advancements: (1) an event-based alert system for detecting abrupt changes, demonstrated on refugee camp monitoring; (2) a seasonal adaptation for filtering cyclic variations, particularly useful in glacier monitoring ; (3) a polarimetric extension leveraging multivariate techniques for detecting weak signals, such as RFI and concealed vessels. These developments enhance REACTIV’s versatility, making it a more sensitive and interpretable tool for both environmental and anthropogenic change monitoring.