International audience—A time series issued from modern synthetic aperture radar satellite imaging sensors is a huge dataset composed by many hundreds of million pixels when observing large-scale earth structures such as big forests or glaciers. A concise monitoring of these large scale structures for anomaly spotting thus requires loading and analyzing huge spatio/polarimetric multi-temporal image series. The contributions of the present paper for the sake of parsimonious analysis of such huge datasets are associated with a framework having two main processing stages. The first stage is the derivation of an index called geometric multi-wavelet total variation for fast and robust anomaly spotting. This index is useful for identifying signif...