A multi-site, multi-year labeled polygon dataset for agricultural land use and land cover mapping in central and northern Benin

Accurate land use and land cover (LULC) mapping in West African agricultural landscapes is severely constrained by the scarcity of high-quality, geo-referenced reference data. In the central and northern regions of Benin, this limitation is particularly acute due to the high spatial heterogeneity of the landscape, the small size of agricultural plots, the diversity of farming practices, and the logistical challenges of conducting field surveys in remote agro-pastoral areas. This data article addresses this gap by describing a multi-site, multi-annual dataset of geo-referenced labeled polygons for agricultural LULC mapping, produced within the framework of the EU DeSIRA OBSYDYA Project.
The dataset integrates complementary sources of reference information across six pilot sites in central and northern Benin, each covering a 50 × 50 km2 observation window. Annual field campaigns conducted between 2022 and 2024 provided the primary reference information for annual crops, while a dedicated field campaign documented areas occupied by natural formations. Additional polygons were delineated by direct visual interpretation of SPOT 6/7 pansharpened imagery and, for built-up surfaces, complemented with OpenStreetMap (OSM) data. All polygons were subsequently subjected to expert visual validation and geometric and topological quality control. The nomenclature comprises 13 land cover classes adapted to the local agricultural context, including annual crop types (leguminous/oleaginous crops, cereals, cotton, roots/tubers, and other crops), perennial agroforestry systems (fruit tree crops and other tree crops), natural formations (dense forest, open forest, and shrubby savanna), and non-agricultural classes (built-up surfaces, bare soil, and water).
The dataset contains 33 065 labeled polygons representing 18 189.32 ha of labeled surface across 18 site-year combinations, with a growing spatial coverage over the three years (9 027 polygons in 2022, 9 932 in 2023, and 14 106 in 2024).
The dataset constitutes a solid and unique reference base for central and northern Benin, serving three complementary purposes: the operational production of annual agricultural LULC maps within the OBSYDYA project using the MORINGA processing chain [1]; the design, training, and evaluation of deep learning models for LULC classification; and, more broadly, the benchmarking of supervised classification approaches for the monitoring of agricultural dynamics in Sudanian West Africa.