NDVI trends observed over 30 years for different land cover types and biogeographical regions in Europe based on the novel TIMELINE NDVI product

Remote sensing allows for spatially and timely continuous monitoring of the Earth’s surface. The analysis of remote sensing time-series can help to understand ongoing environmental changes. Especially the monitoring of past and current vegetation status and phenology may allow to identify possible long-term patterns and trends, which might be related to climate change. The availability of multi-decadal remote sensing time-series, such as from the Advanced Very High Resolution Radiometer (AVHRR), can be used to analyze long-term vegetation change over large areas. In the TIMELINE project (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long-Term Dynamics In our Natural Environment) of the German Remote Sensing Data Center (DFD) at the German Aerospace Center (DLR), a time-series of daily, 10-day, and monthly NDVI composites based on AVHRR data at 1 km resolution covering Europe and northern Africa has been generated. In this study, we used the TIMELINE monthly NDVI composites from the 30-year period 1989-2018 to derive long-term vegetation trends using Mann-Kendall trend test and Theil-Sen slope estimator. We analyzed annual and seasonal trends for spring, summer, and autumn for different land cover classes within the individual biogeographical regions in Europe. Our results show different NDVI trends for individual regions and land cover classes in Europe. The novel TIMELINE NDVI product allows to analyze European-wide trends at a spatial resolution of 1 km. The results of this study can thus assist to further understand vegetation dynamics and possible impacts of climate change on different land cover classes and within different regions in Europe.