Institut für
BW Betriebswirtschaft
Alle Publikationen von Marcel Schwieder
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Tetteh GO, Schwieder M, Pham V-D, Blickensdörfer L, Gocht A, Neuenfeldt S, van der Linden S, Erasmi S (2024) Agrarflächennutzung aus dem All kartiert: Daten zur Quantifizierung von Klimaschutzmaßnahmen. In: Köchy M (ed) Agrarforschung zum Klimawandel : Konferenz der Deutschen Agrarforschungsallianz, 11.-14.03.2024, Potsdam, unter der Schirmherrschaft des Bundesministeriums für Ernährung und Landwirtschaft ; Programm und Beiträge, Stand: 7. Mai 2024. Braunschweig: DAFA, p 61, DOI:10.3220/DAFA1713767287000
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Schwieder M, Tetteh GO, Blickensdörfer L, Gocht A, Erasmi S (2024) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) [Datenpublikation] [online]. 5 TIFF files, 1 PDF file, 2 CLR files. Genève: Zenodo, zu finden in <https://zenodo.org/records/10617623> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10617623
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Schwieder M, Tetteh GO, Blickensdörfer L, Gocht A, Erasmi S (2024) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2022) ; Version v201 [Datenpublikation] [online]. 6 TIFF files, 1 PDF file, 2 CLR files. Genève: Zenodo, zu finden in <https://zenodo.org/records/10628809> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10628809
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Schwieder M, Tetteh GO, Blickensdörfer L, Gocht A, Erasmi S (2024) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2022) ; Version v202 [Datenpublikation] [online]. 1 TIFF file, 1 PDF file, 2 CLR files. Genève: Zenodo, zu finden in <https://zenodo.org/records/10645427> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10645427
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Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2024) Agricultural land use (vector) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) [Datenpublikation] [online]. 2 PDF files, 5 FGB files, 1 SLD file. Genève: Zenodo, zu finden in <https://zenodo.org/records/10619783> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10619783
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Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2024) Agricultural land use (vector) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2022) [Datenpublikation] [online]. 1 FGB file, 1 PDF file, 1 SLD file. Genève: Zenodo, zu finden in <https://zenodo.org/records/10621629> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10621629
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Kasiske T, Dauber J, Dieker P, Harpke A, Klimek S, Kühn E, Levers C, Schwieder M, Settele J, Musche M (2024) Assessing landscape-level effects of permanent grassland management and landscape configuration on open-land butterflies based on national monitoring data. Biodiv Conserv 33(8-9):2381-3404, DOI:10.1007/s10531-024-02861-6
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Schwieder M, Lobert F, Tetteh GO, Erasmi S (2024) Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the year 2022 [Datenpublikation] [online]. 1 TIFF file. Genève: Zenodo, zu finden in <https://zenodo.org/records/10610283> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10610283
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Schwieder M, Lobert F, Tetteh GO, Erasmi S (2024) Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the years 2017 - 2021 [Datenpublikation] [online]. 5 TIFF files. Genève: Zenodo, zu finden in <https://zenodo.org/records/10609590> [zitiert am 07.03.2024], DOI:10.5281/zenodo.10609590
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Weber D, Schwieder M, Ritter L, Koch T, Psomas A, Huber N, Ginzler C, Boch S (2024) Grassland-use intensity maps for Switzerland based on satellite time series: Challenges and opportunities for ecological applications. Remote Sensing Ecol Conserv 10(3):312-327, DOI:10.1002/rse2.372
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Weber D, Schwieder M, Huber N, Ginzler C, Boch S (2024) Kartierung der Grünlandnutzung aus dem All - methodisches Vorgehen und ökologische Anwendung für die Schweiz. N+L Inside(1):35-39
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Erasmi S, Muro J, Brög T, Blickensdörfer L, Fuß R, Gocht A, Don A, Schwieder M (2024) KlimaFern - Fernerkundung für eine Verbesserung der Klimaberichterstattung. In: Köchy M (ed) Agrarforschung zum Klimawandel : Konferenz der Deutschen Agrarforschungsallianz, 11.-14.03.2024, Potsdam, unter der Schirmherrschaft des Bundesministeriums für Ernährung und Landwirtschaft ; Programm und Beiträge, Stand: 7. Mai 2024. Braunschweig: DAFA, p 60, DOI:10.3220/DAFA1713767287000
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Pham V-D, Tetteh GO, Thiel F, Erasmi S, Schwieder M, Frantz D, van der Linden S (2024) Temporally transferable crop mapping with temporal encoding and deep learning augmentations. Int J Appl Earth Observ Geoinf 129:103867, DOI:10.1016/j.jag.2024.103867
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Frank C, Hertzog LR, Klimek S, Schwieder M, Tetteh GO, Böhner HGS, Röder N, Levers C, Katzenberger J, Kreft H, Kamp J (2024) Woody semi-natural habitats modulate the effects of field size and functional crop diversity on farmland birds. J Appl Ecol 61(5):987-999, DOI:10.1111/1365-2664.14604
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Lobert F, Löw J, Schwieder M, Gocht A, Schlund M, Hostert P, Erasmi S (2023) A deep learning approach for deriving winter wheat phenology from optical and SAR time series at field level. Remote Sens Environ 298:113800, DOI:10.1016/j.rse.2023.113800
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Schwieder M, Tetteh GO, Blickensdörfer L, Gocht A, Erasmi S (2023) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) [Datenpublikation] [online]. 5 TIFF-Dateien, 2 Textdateien. Braunschweig: Thünen-Atlas, zu finden in <https://www.openagrar.de/receive/openagrar_mods_00087489> [zitiert am 10.07.2023], DOI:10.3220/DATA20230707103051-0
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Schwieder M, Tetteh GO, Blickensdörfer L, Gocht A, Erasmi S (2023) Agricultural land use (vector) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) [Datenpublikation] [online]. 5 Geopackages, 2 Textdateien. Braunschweig: Thünen-Atlas, zu finden in <https://www.openagrar.de/receive/openagrar_mods_00087490> [zitiert am 10.07.2023], DOI:10.3220/DATA20230707103117-0
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Tetteh GO, Schwieder M, Erasmi S, Conrad C, Gocht A (2023) Comparison of an optimised multiresolution segmentation approach with deep neural networks for delineating agricultural fields from Sentinel-2 images. J Photogramm Remote Sensing Geoinf Sci 91(4):295-312, DOI:10.1007/s41064-023-00247-x
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Holtgrave A-K, Förster M, Rossi M, Morel J, Ali I, Burchard-Levine V, Raya Serano MD, Fastnacht F, Rocchini D, Schwieder M, Hostert P, Kleinschmit B (2023) Remote sensing indices for environmental grassland monitoring in Europe. In: Brückner D, Kietzmann K (eds) Book of abstracts : 52nd Annual Meeting of the Ecological Society of Germany, Austria and Switzerland ; Leipzig - 12-16 September 2023. Berlin: Gesellschaft für Ökologie, p 697
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Kasiske T, Klimek S, Dauber J, Dieker P, Harpke A, Kühn E, Musche M, Schwieder M, Settele J (2023) Testing the effects of grassland mowing regimes and landscape configuration on butterflies at large spatial scales. In: Brückner D, Kietzmann K (eds) Book of abstracts : 52nd Annual Meeting of the Ecological Society of Germany, Austria and Switzerland ; Leipzig - 12-16 September 2023. Berlin: Gesellschaft für Ökologie, p 389
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Oliveira HFM, Fandos G, Zangrandi PL, Bendini HN, Silva DC, Muylaert RL, Marinho-Filho JS, Fonseca LMG, Rufin P, Schwieder M, Domingos FMCB (2022) Crops, caves, and bats: deforestation and mining threaten an endemic and endangered bat species (Lonchophylla: Phyllostomidae) in the Neotropical savannas. Hystrix 33(2):157-165, DOI:10.4404/hystrix-00541-2022
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Schwieder M, Wesemeyer M, Frantz D, Pfoch K, Erasmi S, Pickert J, Nendel C, Hostert P (2022) Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series. Remote Sens Environ 269:112795, DOI:10.1016/j.rse.2021.112795
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Blickensdörfer L, Schwieder M, Pflugmacher D, Nendel C, Erasmi S, Hostert P (2022) Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany. Remote Sens Environ 269:112831, DOI:10.1016/j.rse.2021.112831
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Lobert F, Röder N, Gocht A, Schwieder M, Erasmi S (2022) Mowing detection from combined Sentinel-1, Sentinel-2, and Landsat 8 time series on fallow cropland with transfer learning. Publikationen der DGPF eV 30:117-126
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Lobert F, Holtgrave A-K, Schwieder M, Pause M, Gocht A, Vogt J, Erasmi S (2021) Detection of mowing events from combined Sentinel-1, Sentinel-2, and Landsat 8 time series with machine learning. Grassl Sci Europe 26:123-125
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Buddeberg M, Schwieder M, Orthofer A, Kowalski K, Pfoch K, Hostert P, Bach H (2021) Estimating grassland biomass from Sentinel 2 - a study on model transferability. Grassl Sci Europe 26:211-213
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Tetteh GO, Gocht A, Erasmi S, Schwieder M, Conrad C (2021) Evaluation of sentinel-1 and sentinel-2 feature sets for delineating agricultural fields in heterogeneous landscapes. IEEE Access 9:116702-116719, DOI:10.1109/ACCESS.2021.3105903
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Wesemeyer M, Schwieder M, Pickert J, Hostert P (2021) Identifying areas of homogeneous grassland management based on iterative segmentation of Sentinel-1 and Sentinel-2 data. Grassl Sci Europe 26:208-210
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Lobert F, Holtgrave A-K, Schwieder M, Pause M, Vogt J, Gocht A, Erasmi S (2021) Mowing event detection in permanent grasslands: Systematic evaluation of input features from Sentinel-1, Sentinel-2, and Landsat 8 time series. Remote Sens Environ 267:112751, DOI:10.1016/j.rse.2021.112751
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Schwieder M, Buddeberg M, Kowalski K, Pfoch K, Bartsch J, Bach H, Pickert J, Hostert P (2020) Estimating grassland parameters from Sentinel-2: A model comparison study. J Photogramm Remote Sensing Geoinf Sci 88:379-390, DOI:10.1007/s41064-020-00120-1
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Tetteh GO, Gocht A, Schwieder M, Erasmi S, Conrad C (2020) Unsupervised parameterization for optimal segmentation of agricultural parcels from satellite images in different agricultural landscapes. Remote Sensing 12(18):3096, DOI:10.3390/rs12183096
