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Grassland yield estimations – potentials and limitations of remote sensing in comparison to process-based modeling and field measurements

Reinermann, Sophie ; Boos, Carolin 1; Kaim, Andrea; Schucknecht, Anne 1; Asam, Sarah; Gessner, Ursula; Annuth, Sylvia H.; Schmitt, Thomas M. ORCID iD icon 1; Koellner, Thomas; Kiese, Ralf ORCID iD icon 1
1 Institut für Meteorologie und Klimaforschung Atmosphärische Umweltforschung (IMKIFU), Karlsruher Institut für Technologie (KIT)

Abstract:

Grasslands make up the majority of agricultural land and provide fodder for livestock. Information on grass-
land yield is very limited, as fodder is directly used at farms. However, data on grassland yields would be needed to inform politics and stakeholders on grassland ecosystem services and interannual variations. Grassland yield patterns often vary on small scales in Germany, and estimations are further complicated by missing information on grassland management. Here, we compare three different approaches to estimate annual grassland yield for a study region in southern Germany. We apply (i) a novel approach based on a model derived from field samples, satellite data and mowing information (RS); (ii) the biogeochemical process-based model LandscapeDNDC (LDNDC); and (iii) a rule set approach based on field measurements and spatial information
on grassland productivity (RVA) to derive grassland yields per parcel for the Ammer catchment area in 2019. All three approaches reach plausible results of annual yields of around 4–9 t ha−1 and show overlapping as well as diverging spatial patterns. For example, direct comparisons show that higher yields were derived with LDNDC compared to RS and RVA, in particular related to the first cut and for grasslands mown only one or two times per year. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000185944
Veröffentlicht am 21.10.2025
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Atmosphärische Umweltforschung (IMKIFU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2025
Sprache Englisch
Identifikator ISSN: 1726-4189
KITopen-ID: 1000185944
HGF-Programm 12.11.22 (POF IV, LK 01) Managed ecosystems as sources and sinks of GHGs
Erschienen in Biogeosciences
Verlag Copernicus Publications
Band 22
Heft 18
Seiten 4969–4992
Vorab online veröffentlicht am 25.09.2025
Nachgewiesen in Web of Science
Scopus
OpenAlex
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