A 4-band (RGBN) Crop Segmentation Dataset for Oilseed Rape and Wheat
Abstract
Oilseed Rape and Wheat Segmentation Dataset (RGBN) DescriptionThis dataset provides high-resolution 4-band (RGBN) imagery and pixel-level labels for crop classification. Data Format Imagery: 4-band GeoTIFF (Red, Green, Blue, Near-Infrared). Patch Size: 512 x 512 pixels. Labels: 8-bit grayscale raster masks. Class Definitions 0: Background 1: Oilseed Rape 2: Wheat 3: Other Crops Dataset StructureThe data is organized into three subsets (Datasets A, B, and C) in Pascal VOC format: JPEGImages: Original 4-band image patches. SegmentationClass: Pixel-level labels (0-3). ImageSets/Segmentation: Text files for training and validation splits. Data GenerationInitial labels were generated using Maximum Likelihood Classification (MLC). All boundaries were then manually inspected and corrected in ArcGIS 10.8 to ensure high geometric precision.
Fields of Study & Subjects
Smart Agriculture and AI
Remote Sensing in Agriculture
Remote-Sensing Image Classification
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 3 February 2026
- Language
- EN
- Document type
- Dataset