SPVPANELEX: Dataset containing aerial orthoimages (covering 257.93 km2 of the Spanish territory, with a spatial resolution of 0.5 m) labelled with photovoltaic panel information for binary recognition and semantic segmentation

The data have been generated using scripts developed in Python with Open-Source libraries (GDAL/OGR and MapScript) to rasterize of vector cartography representing the photovoltaic (PV) panels instalations in urban, industrial, and rural areas. This PV panels cartography has been generated by manual digitalizing the PV panels found latest aerial orthofotographs available on June 1, 2021 from Plano Nacional de Ortofotografía Aérea (PNOA), produced by the National Geographic Institute of Spain, using the Web Map Service PNOA-MA. The dataset consists of 239,680 images of 256 × 256 pixels in size, in png format, labelled with Class_1: “Contains PV panel” and Class_2: “Does not contain PV panel”, that were pre-divided with a split criterion of 70:10:20%. in train, validation and test folders, respectively. The structure of the data is as follows: 1-Panels-Ortho and 1-Panels-Mask contain the images featuring PV panels and their corresponding ground truth mask for training the semantic segmentation networks. 1-Panels-Ortho and 2-NoPanels-Ortho contain images containing and not containing PV panels, for the training of binary recognition models of PV panels. Moreover, in each folder the structure is the same: train, test, validation containing 70%, 10% and 20% of the total images and masks of each type. 1-Panels-Ortho |----Train |----Test -----Validation 1-Panels-Mask |----Train |----Test -----Validation 2-NoPanels-Ortho |----Train |----Test -----Validation

本数据集依托基于Python开发的脚本与GDAL/OGR、MapScript等开源库生成，用于对表征城市、工业及乡村区域光伏（photovoltaic, PV）面板安装情况的矢量制图进行栅格化处理。该光伏面板矢量制图由研究人员通过手动数字化的方式生成，所用影像为西班牙国家地理研究院于2021年6月1日发布的最新航空正射影像，该影像源自西班牙国家正射影像图计划（Plano Nacional de Ortofotografía Aérea, PNOA），并通过其网络地图服务PNOA-MA获取。

数据集共包含239680张尺寸为256×256像素的PNG格式图像，标注分为两类：Class_1为"包含光伏面板"，Class_2为"不包含光伏面板"。数据集已预先按照70:10:20的比例划分为训练集、验证集与测试集三个文件夹。

数据集的目录结构如下：
1-Panels-Ortho与1-Panels-Mask文件夹分别存放光伏面板影像及其对应的真值掩码，用于语义分割网络的训练；
1-Panels-Ortho与2-NoPanels-Ortho文件夹分别存放包含与不包含光伏面板的影像，用于光伏面板二元识别模型的训练。
各子文件夹内部均遵循统一的划分规则：训练集、测试集、验证集分别包含对应类型总图像与掩码的70%、10%与20%，具体层级结构如下：
1-Panels-Ortho
├─ Train
├─ Test
└─ Validation
1-Panels-Mask
├─ Train
├─ Test
└─ Validation
2-NoPanels-Ortho
├─ Train
├─ Test
└─ Validation

搜集汇总

背景与挑战

背景概述

该数据集包含西班牙高分辨率航空影像，专门标注光伏面板信息，适用于光伏面板的二元识别和语义分割任务。数据集已预分割为训练、验证和测试集，包含近24万张图像。