Work within TERENO is centered on agricultural research and application of remote sensing data combined with in-situ data. Therefore many tasks concentrate on monitoring varying parameters and providing high quality input for further use in research and prototype applications.
The site was developed as Durable Environmental Multidisciplinary Monitoring Information Network –DEMMIN® by DLR Neustrelitz, starting in 2000 and belongs to the German observatory network TERENO since 2011. The DEMMIN® test field is considered as a rather heterogeneous and intense agricultural area with highly diverse soil properties from soils developed on glacial substrates. Single crops cover large surfaces. Bare soils are only exposed over entire fields before sowing and after harvesting of rotating crops such as wheat, rape and corn.
Monitoring infrastructure includes 40 agrometeorological stations owned by GFZ and DLR, 62 soil moisture stations (GFZ), a tower crane (GFZ) for forest observations and a lysimeter operated by DLR. To complete this measurement setup an eddy-covariance (EC) system and an automated hyperspectral radiometer are planned.
One scientific key parameter within this observatory is evapotranspiration (ET). ET is dependent on water-soil-plant interaction and therefore spatially variable, which makes remote sensing data a mandatory input for high resolution modeling.
As a result of the unique measurement infrastructure the research area is promoted as intensive monitoring zone and the open data policy offers benefits to related projects. Connected projects often concentrate on single parameters related to ET or agricultural topics, like estimating surface soil moisture from remote sensing data, identifying soil properties, phenology and plants properties or water availability.
Foresthype – Hyperspectral data for the characterization of forest attributes (DLR)
Development of new methods for biodiversity monitoring of forest biotopes, using hyperspectral remote sensing data.
The project "Global Agricultural Monitoring. The German experiment "(GLAM. DE) is dedicated to the challenge of developing local, viable services in the agricultural sector.
Soil Pattern Analysis
Using multispectral and multitemporal remote sensing data for detection of soil patterns and categorizing them into temporal stable and unstable types. An organic carbon map of surface soils was derived based on this pattern for all agricultural areas within the region.
EORAP Detection and classification of crop growing patterns
The project EORAP (Earth Observation for the retrieval of agronomical parameters) focusses since 2014 on the analysis of plant pattern / heterogeneities in agricultural crops. This can be based on temporary ( nutrients , disease , bad weather , among others ) and permanent ( soil type , relief , failure management ) causes and effects directly the local yield potential. The recognition and classification of plants occurring patterns can help to optimize fertilizers and farm management strategies of each crop adapted to the structures and thus contribute to sustainable and resource efficient management.
AgriFusion Data Fusion for yield potential maps
The aim of the AgriFusion project is to generate yield potential maps by merging yield mapping, remote sensing data, digital relief analysis and management data.