A crowdsourced dataset of aerial images with annotated solar photovoltaic arrays and installation metadata

Photovoltaic (PV) energy generation plays a crucial role in the energy transition. Small-scale PV installations are deployed at an unprecedented pace, and their integration into the grid can be challenging since stakeholders often lack quality data about these installations. Overhead imagery is increasingly used to improve the knowledge of distributed PV installations with machine learning models capable of automatically mapping these installations. However, these models cannot be easily transferred from one region or data source to another due to differences in image acquisition. To address this issue known as domain shift and foster the development of PV array mapping pipelines, we propose a dataset containing aerial images, annotations, and segmentation masks. We provide installation metadata for more than 28,000 installations. We provide ground truth segmentation masks for 13,000 installations, including 7,000 with annotations for two different image providers. Finally, we provide ground truth annotations and associated installation metadata for more than 8,000 installations. Dataset applications include end-to-end PV registry construction, robust PV installations mapping, and analysis of crowdsourced datasets. This dataset contains the complete records associated with the article "A crowdsourced dataset of aerial images of solar panels, their segmentation masks, and characteristics", currently under review. These complete records consist of RGB overhead imagery, segmentation masks, and characteristics of PV installations. The data records are organized as follows: bdappv/ Root data folder google / ign: One folder for each campaign img/: Folder containing all the images presented to the users. This folder contains 28807 images for Google and 17325 images for IGN. mask/: Folder containing all segmentations masks generated from the polygon annotations of the users. This folder contains 13303 masks for Google and 7686 masks for IGN. metadata.csv The .csv file with the characteristics of the installations.

光伏（Photovoltaic，PV）发电在能源转型中发挥着至关重要的作用。小型光伏装置正以前所未有的速度部署，但其并网颇具挑战，因为相关方往往缺乏这类装置的高质量数据。航空影像正日益被用于提升对分布式光伏装置的认知，结合机器学习模型实现这类装置的自动测绘。然而，由于图像采集方式存在差异，这些模型难以在不同区域或数据源间迁移，这一问题被称为域偏移（domain shift）。为解决该问题并推动光伏阵列测绘流程的发展，我们构建了一个包含航空影像、标注信息与分割掩码的数据集。

我们提供了超过28000个光伏装置的安装元数据；为13000个装置提供了真值分割掩码，其中7000个装置配有来自两家不同图像提供商的标注。此外，我们还为超过8000个装置提供了真值标注与对应的安装元数据。

本数据集的应用场景包括端到端光伏登记系统构建、鲁棒性光伏装置测绘，以及众包数据集分析。本数据集对应于目前处于审稿阶段的论文"A crowdsourced dataset of aerial images of solar panels, their segmentation masks, and characteristics"的完整数据集，包含RGB航空影像、分割掩码以及光伏装置的特征信息。

数据记录的组织形式如下：
bdappv/：根数据文件夹
google / ign：对应每个采集项目的子文件夹
img/：存放所有向用户展示的图像的文件夹，其中Google源包含28807张图像，IGN源包含17325张图像。
mask/：存放由用户多边形标注生成的所有分割掩码的文件夹，其中Google源包含13303个掩码，IGN源包含7686个掩码。
metadata.csv：包含光伏装置特征信息的CSV文件。

搜集汇总

背景与挑战

背景概述

该数据集是一个众包的航拍图像数据集，包含标注的太阳能光伏阵列和安装元数据，旨在支持光伏阵列的自动映射和分析。数据集提供了超过28,000个安装的元数据和13,000个分割掩码，适用于计算机视觉和光伏安装研究。