In this paper, we introduce an image analysis approach for spatio-temporal segmentation, quantification and visualization of movement or contraction patterns in 2D+t or 3D+t microscopy recordings of biological tissues. The imaging pipeline is applied to time lapse images of the embryonic development of the red flour beetleTribolium castaneumrecorded with light-sheet fluorescence microscopy (LSFM). We are particularly interested in the dynamics of extra-embryonic membranes, and provide quantitative evidence of the existence of contraction waves during late stages of development. These contraction waves are a novel observation of which neither origin, nor function are yet known. The proposed pipeline relies on particle image velocimetry (PIV) for quantitative movement analysis, surface detection, tissue cartography, and an algorithmic approach to detect characteristic movement dynamics. This approach locates contraction waves in 2D+t and 3D+t reliably and efficiently and allows the automated quantitative analysis, such as the area involved in the contractile behavior, contraction wave duration and frequency, path of contractile area, or the relation to the spatio-temporal velocity distribution. The pipeline will be used in the future to conduct a large-scale characterization and quantification of contraction wave behavior inTribolium castaneumdevelopment and can be adapted easily to the identification and segmentation of characteristic tissue dynamics in other systems of interest.