Application of Euclidean norm in multi-temporal remote sensing image change detection

This paper explores a methodology for computing the amount of changes that have occurred within an area by using remotely sensed technologies and Euclidean norm. The discussion concentrates on the formulation of a standard procedure that, using the Euclidean norm, can define the likelihood of changes detected from remotely sensed data. Furthermore, an example of how Euclidean norm can be employed in change detection and the selection of change threshold is presented. The example, which is carried out on a multitemporal remote-sensing data set, also confirms the effectiveness of the proposed system. And it indicates that the neighborhood has quite influence on the change detection of pixels information and can be regarded as an important factor to be introduced into quantitative model.