Skip to main content
Ökologischer Betrieb
Ökologischer Betrieb
Institute of

BW Farm Economics

All publications of Gideon Tetteh

  1. 0

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2023) [Datenpublikation]. 1 ZIP archive; Version 201. Genève: Zenodo, DOI:10.5281/zenodo.15055561

  2. 1

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2023) [Datenpublikation]. 1 ZIP archive; Version 202. Genève: Zenodo, DOI:10.5281/zenodo.15309479

  3. 2

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 201. Genève: Zenodo, DOI:10.5281/zenodo.16949898

  4. 3

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 201. Genève: Zenodo, DOI:10.5281/zenodo.17122420

  5. 4

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 202. Genève: Zenodo, DOI:10.5281/zenodo.17122646

  6. 5

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 302. Genève: Zenodo, DOI:10.5281/zenodo.17197830

  7. 6

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 301. Genève: Zenodo, DOI:10.5281/zenodo.17197761

  8. 7

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 302. Genève: Zenodo, DOI:10.5281/zenodo.17190438

  9. 8

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 301. Genève: Zenodo, DOI:10.5281/zenodo.17181387

  10. 9

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2024) [Datenpublikation]. 1 ZIP archive; Version 302. Genève: Zenodo, DOI:10.5281/zenodo.17182245

  11. 10

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2025) [Datenpublikation]. 1 ZIP archive; Version 301. Genève: Zenodo, DOI:10.5281/zenodo.17181503

  12. 11

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2025) [Datenpublikation]. 1 ZIP archive; Version 302. Genève: Zenodo, DOI:10.5281/zenodo.17182293

  13. 12

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2025) [Datenpublikation]. 1 ZIP archive; Version 302/2. Genève: Zenodo, DOI:10.5281/zenodo.17197871

  14. 13

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (raster): National-scale crop type maps for Germany from combined time series of Sentinel-2 and Landsat data (2025) [Datenpublikation]. 1 ZIP archive; Version 301. Genève: Zenodo, DOI:10.5281/zenodo.17197766

  15. 14

    Tetteh GO, Schwieder M, Blickensdörfer L, Gocht A, Erasmi S (2025) Agricultural land use (vector) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2023) [Datenpublikation]. 1 ZIP archive; Version 201. Genève: Zenodo, DOI:10.5281/zenodo.17135735

  16. 15

    Schwieder M, Lobert F, Tetteh GO, Erasmi S (2025) Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the year 2023 [Datenpublikation]. 1 ZIP archive; Version 1. Genève: Zenodo, DOI:10.5281/zenodo.16941138

  17. 16

    Schwieder M, Lobert F, Tetteh GO, Erasmi S (2025) Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the year 2024 [Datenpublikation]. 1 ZIP archive; Version 1. Genève: Zenodo, DOI:10.5281/zenodo.16942505

  18. 17

    Kasiske T, Klimek S, Dauber J, Harpke A, Kühn E, Levers C, Schwieder M, Settele J, Sietz D, Tetteh GO, Musche M (2025) Identifying typical patterns of land-use and landscape structure in citizen science butterfly monitoring. Ecol Indic 180:114317, DOI:10.1016/j.ecolind.2025.114317

    https://literatur.thuenen.de/digbib_extern/dn070250.pdf

  19. 18

    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

    https://literatur.thuenen.de/digbib_extern/dn068079.pdf

  20. 19

    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) ; Version 201 [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

  21. 20

    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) ; Version 202 [Datenpublikation] [online]. 5 TIFF files, 1 PDF file, 2 CLR files. Genève: Zenodo, zu finden in <https://zenodo.org/records/10640528> [zitiert am 03.12.2024], DOI:10.5281/zenodo.10640528

  22. 21

    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

  23. 22

    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

  24. 23

    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

  25. 24

    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

  26. 25

    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

  27. 26

    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

  28. 27

    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

    https://literatur.thuenen.de/digbib_extern/dn068235.pdf

  29. 28

    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

    https://literatur.thuenen.de/digbib_extern/dn067799.pdf

  30. 29

    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

  31. 30

    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

  32. 31

    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

    https://literatur.thuenen.de/digbib_extern/dn066421.pdf

  33. 32

    Osterburg B, Ackermann A, Böhm J, Bösch M, Dauber J, Witte T de, Elsasser P, Erasmi S, Gocht A, Hansen H, Heidecke C, Klimek S, Krämer C, Kuhnert H, Moldovan A, Nieberg H, Pahmeyer C, Plaas E, Rock J, Röder N, Söder M, Tetteh GO, Tiemeyer B, Tietz A, Wegmann J, Zinnbauer M (2023) Flächennutzung und Flächennutzungsansprüche in Deutschland. Braunschweig: Johann Heinrich von Thünen-Institut, 98 p, Thünen Working Paper 224, DOI:10.3220/WP1697436258000

    https://literatur.thuenen.de/digbib_extern/dn067046.pdf

  34. 33

    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

    https://literatur.thuenen.de/digbib_extern/dn063902.pdf

  35. 34

    Tetteh GO, Gocht A, Conrad C (2020) Optimal parameters for delineating agricultural parcels from satellite images based on supervised Bayesian optimization. Comput Electron Agric 178:105696, DOI:10.1016/j.compag.2020.105696

    https://literatur.thuenen.de/digbib_extern/dn062674.pdf

  36. 35

    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

    https://literatur.thuenen.de/digbib_extern/dn062673.pdf

  37. 36

    Tetteh GO (2019) Establishment of a time-sensitive crop database of Germany based on multi-temporal Sentinel-1 and Sentinel-2 Data. In: Living Planet Symposium, Milan (Italy), May 13-17 2019.

  38. 37

    Neuenfeldt S, Rieger J, Heckelei T, Gocht A, Ciaian P, Tetteh GO (2018) A multiplicative competitive interaction model to explain structural change along farm specialisation, size and exit/entry using Norwegian farm census data [online]. IAAE, 20 p, zu finden in <http://ageconsearch.umn.edu/record/277090/files/886.pdf> [zitiert am 16.10.2018]

    Scroll to top
    Follow us
    Öffnet Webseite des BMLEH in neuem Tab
    Follow us Opens LinkedIn in new tabOpens Bluesky in new tabOpens Mastodon in new tabOpens Instagram in new tab