An Overview of Covariance‐based Change Detection Methodologies in Multivariate SAR Image Time Series

Abstract

Change detection (CD) for remotely sensed images of the Earth has been a popular subject of study in the past decades. It has indeed attracted a plethora of scholars due to the various applications, in both military (activity monitoring) and civil (geophysics, disaster assessment, etc.) contexts. With the increase in the number of spatial missions with embedded synthetic aperture radar (SAR) sensors, the amount of readily available observations has now reached the “big data” era. To efficiently process and analyze this data, automatic algorithms have therefore to be developed. Notably, CD algorithms have been thoroughly investigated: the literature on the subject is dense, and a variety of methodologies can be envisioned1.