Million-AID Dataset

Million-AID is a large-scale benchmark dataset containing a million instances for RS scene classification. There are 51 semantic scene categories in Million-AID. And the scene categories are customized to match the land-use classification standards, which greatly enhance the practicability of the constructed Million-AID. Different form the existing scene classification datasets of which categories are organized with parallel or uncertain relationships, scene categories in Million-AID are organized with systematic relationship architecture, giving it superiority in management and scalability. Specifically, the scene categories in Million-AID are organized by the hierarchical category network of a three-level tree: 51 leaf nodes fall into 28 parent nodes at the second level which are grouped into 8 nodes at the first level, representing the 8 underlying scene categories of agriculture land, commercial land, industrial land, public service land, residential land, transportation land, unutilized land, and water area. The scene category network provides the dataset with excellent organization of relationship among different scene categories and also the property of scalability. The number of images in each scene category ranges from 2,000 to 45,000, endowing the dataset with the property of long tail distribution. Besides, Million-AID has superiorities over the existing scene classification datasets owing to its high spatial resolution, large scale, and global distribution.

Million-AID 是一个包含百万实例的大规模基准数据集，用于遥感场景分类。该数据集涵盖 51 个语义场景类别。场景类别经过精心设计，以符合土地利用分类标准，极大地提升了构建的 Million-AID 的实用性。与现有场景分类数据集不同，其类别组织呈现平行或不确定的关系，Million-AID 中的场景类别则以系统性的关系架构进行组织，从而在管理和可扩展性方面展现出优越性。具体而言，Million-AID 中的场景类别按照三级树形结构的层级类别网络进行组织：51 个叶子节点归属于第二层的 28 个父节点，这些父节点进一步组成了第一层的 8 个节点，分别代表农业用地、商业用地、工业用地、公共服务用地、住宅用地、交通用地、未利用用地和水域这 8 个基本的场景类别。场景类别网络为数据集提供了不同场景类别之间关系的优秀组织结构，以及可扩展性的特性。每个场景类别中的图像数量介于 2,000 到 45,000 之间，赋予了数据集长尾分布的特性。此外，Million-AID 在空间分辨率、规模和全球分布方面相较于现有场景分类数据集具有显著优势。