SROADEX: Dataset for binary recognition and semantic segmentation of road surface areas from high resolution Aerial Orthoimages Covering Approximately 8,650 km2 of the Spanish Territory Tagged with Road Information

The data have been generated using scripts developed in Python using Open Source libraries (GDAL/OGR and MapScript) for rasterization of vector cartography representing the axes of the different types of roads (urban, interurban and rural). This cartography has been obtained from different Spanish official sources (National Geographic Institute and autonomic cartographic agencies) that we have revised and edited in a meticulous and systematic way to verify that the roads are represented on the cartography according to the orthoimages, available on January 1, 2021 in the download center of the National Center of Geographic Information (CNIG), on 16 rectangular areas (28,5 km * 18,5 km) of the Spanish territory (insular and peninsular). The dataset consists of 777599 images in png format of 256x256 pixels, organized in folders for the different trainings, separating those corresponding to training, testing and validation. The structure of the data is as follows: 1-Road-Ortho and 1-Road-Mask contain the images and ground true for training the semantic segmentation networks. 1-Road-Ortho and 2-NoRoad-Ortho contain aerial images containing or not containing vials, for the training of binary tessellation networks identifying tessellations with vials. Moreover, in each folder the structure is the same: train, test, validation containing 90%, 5% and 5% of the total images and masks of each type. 1-Road-Ortho |----Train |----Test -----Validation 1-Road-Mask |----Train |----Test -----Validation 2-NoRoad-Ortho |----Train |----Test -----Validation

本数据集通过Python开发的脚本生成，所用开源库包含GDAL/OGR与MapScript，用于对表征不同类型道路（城市道路、城际道路与乡村道路）轴线的矢量制图进行栅格化处理。本套矢量制图源自西班牙多个官方数据源（国家地理研究所及各自治区制图机构），我们已以细致且系统的方式对其开展修订与编辑工作，确保地图中呈现的道路与2021年1月1日西班牙国家地理信息中心（CNIG）下载中心提供的正射影像相符。数据集覆盖西班牙本土与岛屿的16块矩形区域，单块区域尺寸为28.5km×18.5km。
本数据集包含777599张分辨率为256×256像素的PNG格式图像，按训练、测试与验证任务分文件夹存储。数据结构设置如下：1-Road-Ortho与1-Road-Mask文件夹存放用于训练语义分割网络的图像与真值标签（ground truth）。1-Road-Ortho与2-NoRoad-Ortho文件夹存放包含或不包含道路的航空影像，用于训练二元镶嵌网络以识别含道路的镶嵌区块。各子文件夹的内部结构统一，train、test、validation子文件夹分别存放对应类别总图像与掩码数量的90%、5%与5%。具体目录结构如下：
1-Road-Ortho |----Train |----Test |----Validation
1-Road-Mask |----Train |----Test |----Validation
2-NoRoad-Ortho |----Train |----Test |----Validation