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Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat 8 time series for the years 2017 - 2020

Schwieder, Marcel; Wesemeyer, Maximilian; Frantz, David; Pfoch, Kira; Erasmi, Stefan; Pickert, Jürgen; Nendel, Claas; Hostert, Patrick

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 years 2017 to 2020.

The algorithm used to derive the maps is described in Schwieder, et al. (accepted) and is available as a user-defined function for the FORCE (Frantz, D., 2019) environment (https://github.com/davidfrantz/force-udf/tree/main/python/ts/mowingDetection). The here provided GeoTiffs contain a band with the number of detected mowing events per pixel for the repsective year. In the products, only stable grassland areas that were consistently classified as grassland within three years (2017 - 2019) were considered, based on crop maps provided by Blickensdörfer et al. (2021). Note that grassland uses (pasture, mowed, mixed) were not separated prior to analysis. The maps for 2018, 2019, and 2020 were validated in different regions of Germany, with accuracies - in terms of Mean Absolute Percentage Error - ranging from 35% to 40% (for more details see Schwieder et al. accepted). The maps may thus give an indication of extensively or intensively grassland use.

Please contact the authors, if you are interested in additional products e.g., regarding the estimated mowing dates.

All satellite data were downloaded, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software FORCE - Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019; https://force-eo.readthedocs.io/en/latest/ last accessed: 15. October 2021).

 

References:

Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., & Hostert, P.. (2021). National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data (2017, 2018 and 2019) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5153047 

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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