Abstract
Change detection (CD) provides information about the changes on earth’s surface over a period of time. Many algorithms have been proposed over the years for effective CD of satellite imagery. This paper presents the steps to preprocess the captured satellite images, which can be used to perform predictive analysis of earth’s surface by CD techniques. To design a highly effective system for CD, it is recommended that algorithm designers select efficient algorithms from any given application. Thus, this paper presents and investigates the review of most appropriate literature on CD, where CD techniques have been presented into three groups; i) thresholding, ii) clustering, and iii) deep learning. The first two categories mainly rely on the traditional machine learning, whereas the last one exploits the state-of-the-art deep learning models. At the end, the standard methods are summarized based on advantages, limitation, and research gap.
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