This paper proposes the remote sensing time series approach WLMO (Water-Land MOnitor) to monitor spatiotemporal shoreline changes. The approach uses a hierarchical classification system based on temporal MNDWI-trajectories with the goal to accommodate typical uncertainties in remote sensing shoreline extraction techniques such as existence of clouds and geometric mismatches between images. Applied to a dense Landsat time series between 1984 and 2014 for the two Namibian coastal lagoons at Walvis Bay and Sandwich Harbour the WLMO was able to identify detailed accretion and erosion progressions at the sand spits forming these lagoons. For both lagoons a northward expansion of the sand spits of up to 1000 m was identified, which corresponds well with the prevailing northwards directed ocean current and wind processes that are responsible for the material transport along the shore. At Walvis Bay we could also show that in the 30 years of analysis the sand spit’s width has decreased by more than a half from 750 m in 1984–360 m in 2014. This ongoing cross-shore erosion process is a severe risk for future sand spit breaching, which would expose parts of the lagoon and the city to the open ocean. One of the major advantages of WLMO is the opportunity to analyze detailed spatiotemporal shoreline changes. Thus, it could be shown that the observed long-term accretion and erosion processes underwent great variations over time and cannot a priori be assumed as linear processes. Such detailed spatiotemporal process patterns are a prerequisite to improve the understanding of the processes forming the Namibian shorelines. Moreover, the approach has also the potential to be used in other coastal areas, because the focus on MNDWI-trajectories allows the transfer to many multispectral satellite sensors (e.g. Sentinel-2, ASTER) available worldwide. Keywords: Coastal lagoons, Spatiotemporal dynamics, Remote sensing, Time series, Shoreline.