Sensing & measuring
We aim to advance quantitative remote sensing and in-situ measurement techniques. This way, we aim to more accurately retrieve land-surface parameters, improve calibration and validation of Earth-observation products. In addition, it allows us to support applications such as biodiversity monitoring, carbon assessment and precision farming through integration with ecological and vegetation models.
In this research theme, we develop methods to measure and analyse land-surface parameters using both remote sensing and ground-based observations. We work on improving the accuracy of satellite and airborne data by collecting high-quality field measurements and by developing better calibration and validation procedures.
Techniques
Our work makes use of advanced tools such as terrestrial LiDAR, sensor networks, unmanned airborne vehicles (UAVs), radiative transfer models, vegetation indices and soil spectroscopy. By linking these measurements with soil–vegetation–atmosphere models and data assimilation techniques, we can better understand how land surfaces function and change.
Applications
We apply these methods to real-world challenges, including monitoring biodiversity, assessing vegetation characteristics and carbon stocks, and supporting precision farming through improved crop-growth modelling.
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Research themes
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