Abstract
We present NordFKB, a fine-grained benchmark dataset for geospatial AI in Norway, derived from the authoritative, highly accurate, national Felles KartdataBase (FKB). The dataset contains high-resolution orthophotos paired with detailed annotations for 36 semantic classes, including both per-class binary segmentation masks in GeoTIFF format and COCO-style bounding box annotations. Data is collected from seven geographically diverse areas, ensuring variation in climate, topography, and urbanization. Only tiles containing at least one annotated object are included, and training/validation splits are created through random sampling across areas to ensure representative class and context distributions. Human expert review and quality control ensures high annotation accuracy. Alongside the dataset, we release a benchmarking repository with standardized evaluation protocols and tools for semantic segmentation and object detection, enabling reproducible and comparable research. NordFKB provides a robust foundation for advancing AI methods in mapping, land administration, and spatial planning, and paves the way for future expansions in coverage, temporal scope, and data modalities.
Abstract (translated)
我们介绍了NordFKB，这是一个针对挪威地理空间AI的细粒度基准数据集，源自权威且高度准确的国家级Felles KartdataBase（FKB）。该数据集包含了高分辨率正射影像，并附有36个语义类别的详细注释，包括以GeoTIFF格式提供的每类别二值分割掩模和COCO风格的边界框标注。数据来自七个地理多样化的地区，确保了气候、地形和城市化等方面的多样性。只有包含至少一个已标注对象的数据块被纳入，并通过跨区域随机采样创建训练/验证拆分，以保证语义类和上下文分布的一致性。人工专家审查和质量控制确保了注释的准确性。 除了数据集之外，我们还发布了一个基准测试仓库，提供了用于语义分割和目标检测的标准评估协议和工具，从而实现可重复性和可比较性的研究。NordFKB为地图绘制、土地管理和空间规划领域的AI方法的发展提供了一个坚实的基础，并为未来扩展覆盖范围、时间跨度以及数据模式铺平了道路。
URL
https://arxiv.org/abs/2512.09913
