Echelon approach to characterize and understand spatial structures of change in multitemporal remote sensing imagery

Most existing methods for change analysis aim at providing measurements tha t can be used to locate changes of phenomena of interest. This paper goes o ne step further and investigates a method that can be used to characterize and understand the spatial behavior of change by decomposing the change int ensity image into a tree of entities called echelons, Such a tree can be ex tremely helpful in discovering connections between changes, Also, features can be computed from this tree and used in successive manual or automatic a nalysis, Results on synthetic and real-world change interpretation problems illustrate the power of the discussed method.