SYSU-HiRoads: A Large-Scale Multi-Level Road Dataset for Remote Sensing

SYSU-HiRoads is a large-scale, multi-level road dataset designed to support research on road surface segmentation, road network reconstruction, and fine-grained road hierarchy classification from high-resolution remote sensing imagery. The dataset is derived from GF-2 satellite imagery covering Henan Province, China, with a spatial resolution of 0.8 meters. It spans approximately 3,631 km² and consists of 1,079 image tiles, each with a size of 1024 × 1024 pixels. SYSU-HiRoads provides aligned multi-source annotations, including: (1) Pixel-level road masks for dense road surface segmentation; (2) Vector-level road centerlines for topology-preserving network reconstruction; and (3) Three-level hierarchical road labels for fine-grained classification. The dataset bridges the gap between segmentation-oriented and network-oriented road benchmarks by jointly providing raster-level and vector-level representations with hierarchical attributes. SYSU-HiRoads is publicly released to facilitate research in remote sensing, geospatial artificial intelligence, urban studies, and intelligent transportation systems.SYSU-HiRoads 是一款大规模多层级道路数据集，旨在支撑高分辨率遥感影像下的路面分割、路网重建及细粒度道路层级分类研究。 该数据集源自覆盖中国河南省的高分二号（GF-2）卫星影像，空间分辨率为0.8米，覆盖总面积约3631平方千米，包含1079张尺寸为1024×1024像素的影像瓦片。 SYSU-HiRoads 提供对齐后的多源标注，具体包含以下三类：(1) 用于密集路面分割的像素级道路掩码；(2) 用于支撑保留拓扑结构的路网重建的矢量级道路中心线；(3) 用于细粒度分类的三级层级道路标签。 该数据集同时提供栅格级与矢量级表征并附带层级属性，填补了面向分割与面向路网的道路基准数据集之间的空白。SYSU-HiRoads 已公开发布，以推动遥感、地理空间人工智能、城市研究以及智能交通系统领域的相关研究。