Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat time series for the years 2017 - 2021

Grasslands provide a wide range of ecosystem services within agricultural landscapes. 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 2021. 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). Each annual 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. The mowing events map therefore contains a substantial overestimation of grassland areas. 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 provided URL to the datasets (right click on the respective data set --> “copy link address”). By doing so the entire map area or only the regions of interest can be accessed. _______________________________________________________________________________________________________ Mailing list If you do not want to miss the latest updates, please enroll to our mailing list. _______________________________________________________________________________________________________ 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. _____________________________________________________________________________Grassland mowing events across Germany © 2022 by Schwieder, Marcel; Lobert, Felix; Tetteh, Gideon Okpoti; Erasmi, Stefan; licensed under CC BY 4.0. Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (MonViA, Monitoring of biodiversity in agricultural landscapes).草地在农业景观中能够提供多样化的生态系统服务。因此，对草地的现状与利用强度开展制图与评估，对环境监测工作具有重要意义。本数据集提供2017至2021年德国全境草地的割草事件识别图，以此作为草地利用强度的替代指标。 本数据集包含德国草地割草活动的制图成果，该系列制图自2017年起由瑟能研究所（Thünen Institute）依托卫星数据逐年制作完成。制图范围覆盖全部草地类型，包括永久草地、潜在永久草地（如饲料作物种植区）及其他低集约度区域。制图数据源自哨兵2号（Sentinel-2）、陆地卫星8号（Landsat 8）及陆地卫星9号（Landsat 9）的高密度时间序列影像。制图方法参考Schwieder等人（2022）发表的研究成果，用于生成该制图成果的算法可作为用户自定义函数在FORCE平台（FORCE）中调用。 每份年度数据集包含7个图层：(1) 识别到的割草事件总次数；(2) 第1至第6次割草事件对应的年积日（day of year, DOY）。辅助数据图层可按需申请获取。本制图覆盖2017至2021年间瑟能研究所发布的农业土地利用图中，曾至少一次被归类为永久草地、人工草地或休耕地的全部区域。因此，割草事件制图存在草地面积显著高估的情况，建议使用者根据自身研究需求，结合对应年度农业土地利用图或其他数据源生成掩膜，以修正该偏差。 本数据集按"现状"提供，不对其质量与完整性作出任何保证，且不承担相关责任。相关精度评估与潜在局限性细节，请参考Schwieder等人（2022）的研究，或直接联系作者咨询。 该制图成果以云优化GeoTIFF（Cloud Optimized GeoTIFF）格式存储，支持按需下载完整数据集或仅选取目标区域。使用者可通过提供的数据集链接（右键对应数据集→"复制链接地址"），直接在QGIS、R、Python或其他兼容软件中访问全部数据，既可获取全制图区域数据，也可仅下载感兴趣的区域数据。 _______________________________________________________________________________________________________ 邮件订阅 若希望获取最新动态，请订阅我们的邮件列表。 _______________________________________________________________________________________________________ 参考文献 Frantz, D. (2019). FORCE——Landsat与Sentinel-2的分析就绪数据及拓展功能. 《遥感》(Remote Sensing), 11, 1124. Schwieder, M., Wesemeyer, M., Frantz, D., Pfoch, K., Erasmi, S., Pickert, J., Nendel, C., & Hostert, P. (2022). 基于Sentinel-2与Landsat 8联合时间序列的德国全境草地割草事件制图. 《环境遥感》(Remote Sensing of Environment), 269, 112795. _____________________________________________________________________________德国全境草地割草事件数据集 © 2022 作者：Marcel Schwieder、Felix Lobert、Gideon Okpoti Tetteh、Stefan Erasmi；采用CC BY 4.0协议授权。 本数据集由德国联邦食品与农业部资助，作为联合项目"农业景观生物多样性监测"（MonViA，Monitoring of biodiversity in agricultural landscapes）的一部分完成。