Grassland-use intensity maps for Switzerland

A rule-based algorithm [(Schwieder et al., 2022)](https://doi.org/10.1016/j.rse.2021.112795) was used to produce annual maps for 2018–2021 of grassland-management events, i.e. mowing and/or grazing, for Switzerland using Sentinel-2 and Landsat 8 satellite time series. All satellite images were processed with the [FORCE](https://force-eo.readthedocs.io) framework. The resulting maps provide information on the number and timing of grassland-management events at a spatial resolution of 10 m × 10 m for the whole of Switzerland. For the final maps, permanent grasslands were masked using a variety of land-use layers, according to [Huber et al. (2022)](https://doi.org/10.1002/rse2.298) but replacing the crop mask with the agricultural-use data from the cantons. We assessed the detection of management events based on independent reference data, which we acquired from daily time series of publicly available webcams that are widely distributed across Switzerland. We further tested the ecological relevance of the generated intensity measures in relation to nationwide biodiversity data (see Weber et al., 2023; IN REVIEW).本研究采用基于规则的算法[(Schwieder等，2022)](https://doi.org/10.1016/j.rse.2021.112795)，借助哨兵-2（Sentinel-2）与陆地卫星8号（Landsat 8）卫星时序影像，生成了瑞士2018至2021年的草地管理事件年度分布图，涵盖刈割和/或放牧两类管理活动。所有卫星影像均通过FORCE框架完成处理。 所生成的分布图以10 m×10 m的空间分辨率，提供了瑞士全境草地管理事件的发生次数与时间节点信息。针对最终成果图，研究依据[Huber等(2022)](https://doi.org/10.1002/rse2.298)的方法，通过多类土地利用图层对永久草地进行掩膜处理，并以各州农业用地数据替换其中的作物掩膜。 本研究基于独立参考数据对草地管理事件的检测效果开展了评估，该参考数据来源于广泛分布于瑞士全境的公开网络摄像头每日时序影像。此外，本研究还结合全国性生物多样性数据，对所生成的管理强度指标的生态学相关性进行了检验（详见Weber等，2023；待刊）。