This field deals with quantitative, physical and statistical based retrieval of land surface parameters relevant for multiple monitoring applications and earth system modelling.
Activities are ongoing to advance foundations for quantitative land remote sensing and to improve in-situ data collection and analysis for development, calibration and validation of the next generation remote sensing data and products.
Particular attention is paid to the use of innovative in-situ and laboratory based measurements (terrestrial LIDAR, sensor webs), unmanned airborne vehicles (UAVs), radiative transfer models, vegetation indices, data assimilation methods, linking soil-vegetation-atmosphere transfer models, soil spectroscopy and calibration and validation procedures. Our sensing scientific research is underpinned by our long-term expertise in using advanced earth observation techniques (i.e. imaging spectroscopy and LIDAR) in combination with ecological and dynamic vegetation models for applications. Some examples are biodiversity assessment at habitat and ecosystem level, assessing vegetation characteristics and carbon stocks and combining sensing techniques with crop growth models for precision farming.