## 1 Introduction  
Long-term records of vegetation indices (VI) from satellite constellations like NOAA, Aqua/Terra or SPOT played a major role in monitoring of terrestrial ecosystems and their interaction with the atmosphere for the last decades. First observations date back to the early 1980s and, since then, regular acquisitions continued to facilitate new applications and findings. With time series of about ten years long, it became first feasible to quantify phenology, global vegetation activity and their gradual changes [1]. When around two decades of time series became available, links between candidate drivers of change were established. The Earth was found to become greener, especially in the Northern Hemisphere, and human-induced greenhouse effects appeared to play a large role in this process [2, 3]. These findings further put satellite records at the forefront serving as main information sources for land-status monitoring [4]. With even longer series becoming available, first studies about non-monotonicity of vegetation trends were published. Trends were not any longer considered as a linearly developing equilibrium, but turning points were taken into account [5, 6, 7]. These studies further revealed that temporal trends can be composed of multiple segments with different, sometimes even opposing, behavior [8], and major shifts, derived from these datasets, from greening to browning were suggested and debated [9, 10, 11]. This temporal evolution combined with the improved analysis techniques of time series illustrate that today even shifts in the type of processes--and their associated length scales--can be captured and analyzed. Currently, analysis can be performed on datasets of more than thirty years of fortnightly VI composites. This time span corresponds to more than a human generation and covers climatic relevant changes. In addition, such a time span combined with a complete terrestrial surface cover allows assessment of ecosystem dynamics instead of ecosystem states. The current datasets can therefore be used to detect and interpret major changes in terrestrial ecosystems, which might results in sustained interruption or improvement of their functioning. Temporal dynamics of terrestrial ecosystems consist of continuous (gradual) changes, discontinuous (abrupt) changes, and more rarely, no change. Within a temporal framework of decades, abrupt negative changes may, for example, be induced by short-lived processes like wildfires, harvesting or diseases, while rainfall events or reduced snow cover may trigger sudden greening of vegetation. Gradual changes occur over a longer period and include adaptation processes of vegetation to variations in oceanic oscillations, or persistent climate changes like decrease in yearly rainfall or raise of atmospheric CO\({}_{2}\) concentrations. The least complicated type of change is gradual throughout the time series. In long time span datasets, such changes are referred to as monotonic \"greening\" or \"browning\", depending on the direction of change. The magnitude of gradual change over the past decades has been quantified in various studies [2, 12, 13]. It is, however, likely that such long-term trends are composed of consecutive segments with gradual change, separated from each other by a relatively short period of abrupt change, or any combination thereof [8]. Such interruptions in the gradual trends have in the literature been referred to as change points, break points or turning points. Their existence has been demonstrated extensively, including methods to describe how they affect the temporal trend [14, 15, 16, 17, 18]. The capacity to characterize major change types spatially and temporally currently forms a gap in our knowledge, but is critical for understanding their impact within a global change context.