Large-scale tree species maps for tree species diversity monitoring across scales – challenges and opportunities

Numerous studies have shown the immense potential of Sentinel-2 satellite data for tree species classification across temperate forest ecosystems. However, key challenges such as the classification of minor tree species and detection of admixture species remain. In particular, when mapping tree species classes at a national scale, heterogeneous landscapes, different forest management practices and differences in phenology introduce additional uncertainties. Nevertheless, detailed information on tree species composition, including minor species, is crucial for nature conservation, biodiversity monitoring, and the development of forest management strategies opting for enhanced resilience. At the same time, spatially explicit information on model uncertainties and domains are often lacking in state-of-art national tree species maps. Here, we aim to provide new insight in mapping minor tree species relevant for nature conservation and forest resilience at the landscape scale in Germany by combining diverse reference data sources such as forest management maps, biotope mapping data, and regional forest inventories with Sentinel-2 timeseries and periodic forest masks. The obtained tree species maps are complemented by spatially explicit uncertainty maps and areas of model applicability, allowing for a transparent and species-specific assessment of the classification results. Subsequently, these outputs will be used to derive tree species composition and tree species diversity measures across different spatial scales. We compare our findings to existing tree species maps and aim to quantify tree species diversity measures in relation to in-situ inventory plots across different landscape regions in Germany. Additionally, the generation of periodic tree species maps enables the analysis of temporal changes and shifts in tree species composition and biodiversity, especially in view of the drastic changes and stresses that forests in Germany have been exposed to in recent years as a result of climate change. This study contributes to a more comprehensive understanding of the potential and the limitations of remotely sensed tree species maps for monitoring biodiversity and supporting conservation planning across spatial and temporal scales.