Estimation of winter soil cover by vegetation before spring-sown crops for mainland France using multispectral satellite imagery

Abstract

Winter soil cover by vegetation is associated with multiple benefits. In this study, winter soil cover rate before spring-sown crops was estimated for mainland France from multispectral imagery. For 67% and 84% of the area under spring-sown crops for years 2018 and 2019, soil cover during the previous winter was estimated through the computation of the Normalized Difference Vegetation Index (NDVI), using Sentinel-2 multispectral images. At country scale, winter soil cover rate before spring-sown crops was estimated between 37% and 48% for 2018 and between 31% and 43% for 2019, depending on the NDVI threshold for a soil to be considered covered by at least 50% of vegetation. Spatial patterns were relatively similar between the two years studied, highlighting strong heterogeneities between French departments. Cropping systems may explain some of these heterogeneities, as it has been shown that there is a large variability in the soil cover rate between spring-sown crops, but also depending on the previous crop. Winter soil cover rate was higher for crops associated with livestock production, such as maize silage (between 59% and 74% of plots covered before this crop). It was also shown that winter soil cover could be ensured by other means than cover crops: temporary grasslands were the previous crop with the highest soil cover, probably due to late ploughing. For these reasons, mixed systems combining livestock and crop productions may be a solution to increase winter soil cover before spring-sown crops.

Keywords

• agriculture
• remote sensing
• cover crops
• cropping systems
• global agronomy