Hyperspectral data as provided by the proposed EnMAP imager offer considerable potential for the extraction of detailed information on sediment properties, soil erosion status, and land degradation, and thus, serves also for precision farming activities. In particular, the amount of organic matter and iron content, particle size distribution, clay mineralogy and its distribution, cation exchange capacity and calcium carbonate content, can be determined with high-spectral reflectance data.

 

 

 

The following goals and scientific/application tasks have been identified:

• Monitoring land degradation processes by providing regular maps of soil status such as organic matter, CaCO₃, and iron content, infiltration rate, salinity, and physical crusting development

• Calibration of remote sensing-based soil condition indices against soil reference samples to better link spectral parameters with soil development models;

• Identification and quantification of various pollutants through their specific spectral signatures or specific features linked to change in chemical composition of the polluted soil

• Development of new algorithms and optimisation of existing modelling approaches for mapping coherent indicators of the erosional state of soils; and

• Improvement of regular up-dates of green and dry vegetation cover estimates in semi-arid and sub-humid ecosystems for land degradation purposes taking into account highly variable background substrates.