Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the year 2022

GND
1165820536
ORCID
0000-0003-2103-8828
Affiliation
Johann Heinrich von Thünen-Institut
Schwieder, Marcel;
GND
1240249241
ORCID
0000-0001-5371-9930
Affiliation
Johann Heinrich von Thünen-Institut
Lobert, Felix;
GND
1151968722
ORCID
0000-0001-5430-5967
Affiliation
Johann Heinrich von Thünen-Institut
Tetteh, Gideon Okpoti;
GND
124078672
ORCID
0000-0002-6393-6071
Affiliation
Johann Heinrich von Thünen-Institut
Erasmi, Stefan

Grasslands provide a wide range of important ecosystem services. Mapping and assessing the status and use intensity of grasslands is thus important for environmental monitoring. We here provide maps with detected mowing events, as a proxy for grassland use intensity, for grassland areas across Germany for the year 2022.

The dataset contains maps of grassland mowing activity in Germany, which have been produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire grassland area, i.e. permanent grassland, potentially permanent grassland (e.g. fodder crops) and other extensive areas. They are derived from dense time series of Sentinel-2, Landsat 8 (and 9) data. Map production is based on the methods described in Schwieder et al. (2022). The algorithm used to derive the maps is available as a user-defined function for the FORCE environment (Frantz, D., 2019).

The dataset includes seven layers: (1) the number of detected mowing events, (2) the day of year (DOY) of the first to sixth detected mowing event. Ancillary data layers are available on request. The maps include all areas that have at least once been classified as permanent grassland, cultivated grassland or fallow in the maps of agricultural land use between 2017 and 2021 that are provided by Thünen Institute. Please consider to use the respective annual agricultural land use map or any other data source to generate a mask for your purpose.

We provide this dataset "as is" without any warranty regarding the quality or completeness and exclude all liability. Please refer to Schwieder et al. (2022) for the related accuracy assessment and potential limitations and / or contact the authors directly.

The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the URL to the datasets that will be provided on request. By doing so the entire map area or only the regions of interest can be accessed.
 
References

Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.

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 Sensing of Environment, 269, 112795.

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