Automation of change detection procedures for nuclear safeguards-related monitoring purposes

Abstract

Against the background of nuclear safeguards applications using commercially available satellite imagery, a two-steps attempt for change detection and analysis was realized in general. Beginning with the wide-area monitoring on the basis of medium-resolution satellite data for the pre-scanning of significant changes within the nuclear-related locations, the areas of interest could then be explicitly analyzed by change detection and analysis methods using high-resolution satellite data. The change pixels were detected by using the multivariate alteration detection (MAD) transformation, producing a set of mutually orthogonal difference images (the so-called MAD variates). The decision thresholds for the change pixels were set by applying a probability mixture model to the MAD variates based on an EM algorithm. By means of eCognition a second, object-oriented procedure was implemented in order to create an automated workflow for the multiscale extraction of the (change) objects and (change) features for the subsequent post-classification of the areas of interest. Regarding the necessity of automation for extensive monitoring tasks the processing aspects of standardization and transferability took the centre stage of the investigations.