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Grassland is a land cover in the area of conflict between agriculture and conservation, where intensification of land use is a major threat to grassland biodiversity. Grassland use intensity is a key factor for the conservation value of grassland, and detailed spatial data on grassland use intensity is needed to improve strategies for biodiversity conservation. A new remote sensing-based approach using multi-temporal high resolution RapidEye satellite data was developed in the present study that makes a large-scale assessment of grassland use intensity possible. RapidEye is a constellation of five satellites with 6.5m spatial resolution, which allows frequent and timely image acquisition targeted at specific growing seasons. Semi-natural grassland, extensively used grassland, intensively used grassland and tilled grassland could be reliably differentiated at the management plot level in a study area in southern Germany. Various combinations of images from different observation dates have been tested as classification input and their overall classification accuracies were validated by field data. Best results were achieved using a combination of five multi-temporal scenes with an overall accuracy of 85.7%. A three-scene combination resulted in an overall accuracy of 82.2%. The analysis showed that seasonal aspects are very important when selecting adequate observation dates. Grassland use intensity was also assessed on peatlands using a peat soil map, since land use intensity significantly affects greenhouse gas emissions from peatlands. The results demonstrate the potential of targeted multi-spectral, high spatial resolution remote sensing for the large-scale monitoring of dynamic habitats, which is of vital importance to support various environmental conservation schemes through improved monitoring and reporting capabilities.
