Mapping is a core approach used to investigate and display spatial dynamics of biological diversity and habitats. In the Netherlands, agricultural lands occupy nearly two-thirds of the land surface and provide the greatest potential for habitat restoration; particularly in grassland-based dairy production systems, which comprise the largest share of these agricultural lands. When a crop rotation is applied to a long-term grassland, the resulting disruption of ecological complexity requires years–if not decades–to restore, even after reconversion. The availability of high-quality land-use data for measuring the spatio-temporal distribution of grassland legacies is thus essential for monitoring the dynamics of biodiversity in production grasslands. In this study, we reflect on the Basic Crop Registration (BRP) of the Netherlands, an open spatial data infrastructure developed for parcel-level crop registration and examine how it shapes our spatio-temporal understanding of land use. The BRP serves as an administrative basis for numerous national and local-level regulatory and financial arrangements, mainly aimed at agricultural actors. In this study, we repurposed BRP data to introduce a new perspective on depicting the stability of grasslands in a high-intensity agricultural region. We used this data to map the frequency of grassland-to-cropland conversions using 17 years of longitudinal crop records in southwest Friesland, Netherlands. The legacy effects of grassland-to-cropland conversion were investigated in a field study, where significant differences were found between new and long-term grasslands in plant community composition, soil organic matter content, bulk density, soil penetration resistance, and pH. In our analysis of BRP data, we discovered a significant number of grasslands that were recently converted from cropland but that were recorded as long-term grasslands. This affected approximately 12% of the study area from 2005–2021, which prevents the accurate tracking of grassland stability over time. This misclassification also adds uncertainty to the temporal context of the decline in grassland-dependent species in the region. However, using a spatially-explicit mapping approach, these misclassifications can be corrected and help produce an effective measure of grassland stability with potential as an agroecosystem monitoring tool for researchers, land-use planners, and policymakers.