Geoinformation in Environmental Planning


Project Information

TitleSensGreen - Evaluation of recent remote sensing-based sensors and methods for the quality analysis of NATURA 2000 grassland habitat types.
FundingFederal Agency for Nature Conservation (BfN); Departmental Research Plan (3523811300)
Duration01.04.2023 – 31.03.2026
Research AssociateAnn-Kathrin Holtgrave
Project LeadProf. Dr. Birgit Kleinschmit und Dr. Michael Förster


Permanent grassland is home to more than half of all animal and plant species in Germany and thus has a high benefit for biodiversity. In addition, grassland provides a variety of other ecosystem services through its water storage capacity, buffering effect for nutrients and pollutants, prevention of soil erosion and effect as a carbon sink.

Species-rich grassland is an integral part of the habitat types (LRT) according to Annex I Fauna-Flora-Habitat (FFH) Directive and an important pillar of biodiversity protection. The importance of FFH sites is also reinforced by the fact that the European Biodiversity Strategy, which aims to significantly improve the state of biodiversity in Europe by 2030, builds on the existing NATURA 2000 network. In order to fulfil the obligations of the Habitats Directive with regard to the restoration, conservation and promotion of biodiversity, the Habitats sites must be managed, the conservation status of the LRT must be reviewed and described, and measures must be developed to improve or maintain a favourable conservation status. One focus is on the characteristics and quality parameters of the LRTs.

In the course of digitisation strategies and to achieve the digitisation goals of the federal government, the development of remote sensing-based methods should therefore help to make site management more efficient and support the existing management systems of NATURA 2000 sites. On-site inspections could also be reduced or used more efficiently as a result.

With the introduction of the hyperspectral satellite sensor EnMAP in 2022, there are new opportunities to find indicators for grassland monitoring. With hyperspectral data, all spectral characteristics of vegetation can be studied. A technically fast advancing development in drone technology can support monitoring with high resolution and be used for calibration and validation of satellite image analysis.

The aim of the project is to investigate the potentials and synergies of hyperspectral data from the EnMAP satellite and data from the Sentinel-1 & 2 satellites for the investigation of quality parameters in NATURA-2000 grasslands. The aim is to determine which quality characteristics can be reliably identified by remote sensing. The satellite data will be compared with UAV and field spectrometer data to estimate economies of scale. The focus is on FFH grassland areas whose LRT lie in the rather dry and mesophilic grassland. The output is an executable script for use in the BfN and at the state environmental offices for independent testing and practical application on other areas, including documentation on CODE-DE.