Coverage and Rainfall Response of Biological Soil Crusts Using Multi-Temporal Sentinel-2 Data in a Central European Temperate Dry Acid Grassland

Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) global drylands. They consist of poikilohydric organisms capable adjusting their metabolic activities depending on the water availability. However, they, with them, ecosystem functions, endangered by climate change land-use intensification. Remote sensing (RS)-based studies estimated BSC cover drylands through various multispectral indices, few them correlated BSCs’ activity response to rainfall. allocation BSCs is not limited only as there areas beyond where smaller patches have developed under intense human impact frequent disturbance. Yet, those were addressed RS-based studies, raising question whether methods extensive can be transferred easily. Our temperate study area, ‘Lieberoser Heide’ northeastern Germany, home country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating Sentinel-2 (S2) data, indices derived from topographic information spatiotemporally map for first time Central Europe. further monitored rainfall events over period around five years (June 2015 end December 2020). Therefore, we combined datasets gridded NDVI measure photosynthetic daily data conducted detection analysis. With an overall accuracy 98.9%, our proved satisfactory. Detected changes between dry wet found significant. emphasizes transferability established climate. consider provide essential impulses so biocrust mapping future will