Performance Assessment of the Sen4CAP Mowing Detection Algorithm on a Large Reference Data Set of Managed Grasslands

2021 
Grassland use intensity has an impact on their ecological value as habitats. The precocity and frequency of mowing events are major factors of grassland use intensity. Grassland mowing detection through remote sensing can thereby be a great asset for large scale habitat monitoring. A grassland mowing product, based on Sentinel-1 and Sentinel-2 time series, was developed recently in the frame of ESA's Sentinels for Common Agricultural Policy (Sen4CAP) project. The aim of this study is to assess the performances of this Sen4CAP mowing algorithm on managed grasslands in Belgium. Based on a large reference data set, collected through field observations in 2019, this study shows that the product detects 79% mowing events in managed grasslands and that its confidence level estimation is strongly correlated to the detection precision. Overall, the Sen4CAP grassland mowing product represents a great potential for grassland use intensity assessment in the context of large scale monitoring of biodiversity habitat.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    13
    References
    0
    Citations
    NaN
    KQI
    []