Estimating dry biomass and plant nitrogen concentration in pre-Alpine grasslands with low-cost UAS-borne multispectral data – a comparison of sensors, algorithms, and predictor sets
Anne Schucknecht,Bumsuk Seo,Alexander Krämer,Sarah Asam,Clement Atzberger,and Ralf Kiese
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT),
82467 Garmisch-Partenkirchen, Germany
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT),
82467 Garmisch-Partenkirchen, Germany
Alexander Krämer
WWL Umweltplanung und Geoinformatik GbR, 79189 Bad Krozingen, Germany
Sarah Asam
German Remote Sensing Data Center, German Aerospace Center,
82234 Wessling, Germany
Clement Atzberger
Institute of Geomatics, University of Natural Resources and Life
Sciences (BOKU), 1190 Vienna, Austria
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT),
82467 Garmisch-Partenkirchen, Germany
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Total article views: 3,660 (including HTML, PDF, and XML)
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Total article views: 2,579 (including HTML, PDF, and XML)
Thereof 2,529 with geography defined
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Total article views: 1,081 (including HTML, PDF, and XML)
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Actual maps of grassland traits could improve local farm management and support environmental assessments. We developed, assessed, and applied models to estimate dry biomass and plant nitrogen (N) concentration in pre-Alpine grasslands with drone-based multispectral data and canopy height information. Our results indicate that machine learning algorithms are able to estimate both parameters but reach a better level of performance for biomass.
Actual maps of grassland traits could improve local farm management and support environmental...
