Earth Observation

EnMAP, Tandem-L and co.

Large data volumes, powerful computing capacities and innovative AI-based evaluation techniques are opening up new possibilities that were unimaginable just a few years ago. And the potential of satellite data continues to grow, particularly with regard to spatial and, above all, temporal resolution. The DLR EnMAP mission and the proposed Tandem-L mission are also opening up entirely new possibilities.

EnMAP โ€“ the first German hyperspectral satellite mission

Conventional multispectral sensors record the radiation reflected by Earth in a few very wide channels โ€“ in relation to wavelength. Launched this year, the EnMAP Earth observation satellite, on the other hand, records Earth in 230 channels and provides the precise spectral fingerprints of objects on the surface. This makes it possible to derive important quantitative information, such as the nutrient supply of arable crops or the water quality of lakes. The data from EnMAP will be used in many fields of research, such as geology, agriculture and forestry, soil science and research into coastal areas and inland waters.

Tandem-L โ€“ a proposed mission to monitor dynamic processes

The proposed Tandem-L mission will comprise two radar satellites. Their L-band radar instruments will easily penetrate clouds and treetops using signals with a wavelength of 24 centimetres. The mission aims to measure important dynamic parameters such as forest biomass, soil moisture, glacier movements, deformations of Earth’s surface and much more. Among other things, the mission will record the three-dimensional structure of areas of vegetation and ice, allowing the carbon content of global forest areas to be better determined. The Tandem L concept enables weekly mapping of the entire planet. The techniques and technologies involved in Tandem-L will form the basis for future generations of satellite SAR systems. Thanks to its data products, the mission will be a milestone in remote sensing.

Links:

German Aerospace Center (DLR)
German Remote Sensing Data Center
Nils Sparwasser ยท Email nils.sparwasser@dlr.de