Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.5194/bg-22-4969-2025 |
Lizenz  |
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| Titel (primär) | Grassland yield estimations – potentials and limitations of remote sensing in comparison to process-based modeling and field measurements |
| Autor | Reinermann, S.; Boos, C.; Kaim, A.
; Schucknecht, K.; Asam, S.; Gessner, U.; Annuth, S.H.; Schmitt, T.M.; Koellner, T.; Kiese, R. |
| Quelle | Biogeosciences |
| Erscheinungsjahr | 2025 |
| Department | CLE |
| Band/Volume | 22 |
| Heft | 18 |
| Seite von | 4969 |
| Seite bis | 4992 |
| Sprache | englisch |
| Topic | T5 Future Landscapes |
| Abstract | Grasslands make up the majority of agricultural land and provide fodder for livestock. Information on grassland 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. The mowing frequency was found to be the most important influencing factor for grassland yields of all three approaches. There were no significant differences found in the effect of abiotic influencing factors, such as climate or elevation, on grassland yields derived from the different approaches. The potentials and limitations of the three approaches are analyzed and discussed in depth, such as the level of detail of required input data or the capability of regional and interannual yield estimations. For the first time, three different approaches to estimate grassland yields were compared in depth, resulting in new insights into their potentials and limitations. Grassland productivity maps provide the basis for the long-term analyses of climate and management impacts and comprehensive studies of the functions of grassland ecosystems. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=30481 |
| Reinermann, S., Boos, C., Kaim, A., Schucknecht, K., Asam, S., Gessner, U., Annuth, S.H., Schmitt, T.M., Koellner, T., Kiese, R. (2025): Grassland yield estimations – potentials and limitations of remote sensing in comparison to process-based modeling and field measurements Biogeosciences 22 (18), 4969 - 4992 10.5194/bg-22-4969-2025 |
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