Abstract

ABSTRACT Remote sensing change detection (RSCD) is the process of identifying changes between scenes of the same location acquired at different times. This is an active research area with a broad range of applications. Many change detection methods have been described in the literature, ranging from simple differencing to machine learning techniques. Faced with this large number of suggested techniques, researchers have tried to classify them into different categories to simplify and systematize the topic. A number of different categorization schemes have been proposed, based on various dimensions, aspects or features of the techniques considered. Nevertheless, using these schemes to understand the different techniques and to select suitable techniques for a specific remote sensing change detection project remains a hard task for practitioners. In this context, we provide a critical study of proposed categorization schemes in order to extract the main dimensions used for their construction. Then, based on the obtained set of dimensions, we propose a new definition for the concept of a remote sensing change detection technique, which provides greater clarity and better guidance for researchers and practitioners. We then expand upon this description to incorporate non-computational aspects of RSCD in order to propose a comprehensive conceptual framework for remote sensing change detection projects.

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