AI 中文总结
研究旨在创建法国屋顶光伏系统数据库。核心方法是整合多源数据，包括深度学习检测管道、OpenStreetMap等。主要贡献是建成含超百万装置、约15GWp容量的数据库，精度约74%-75%，且可扩展，还开源发布。
AI 中文摘要
屋顶光伏（PV）系统占光伏并网连接的绝大部分，但目前尚无关于这些系统的开放、全面的安装级数据集。公共注册机构仅汇总高于容量阈值的数据，基于遥感的检测工作虽广泛，但通常局限于单一方法、有限地理范围或单一时间点。我们引入OpenPVMapper，这是一个法国大陆全国性的多源屋顶光伏装置数据库，通过整合和协调互补来源构建而成，包括基于深度学习的全国航空图像检测管道、OpenStreetMap和概率性建筑级检测数据集。由此产生的数据库包含1,135,850个装置，总装机容量约为15.01GWp，每个装置都记录了其来源、检测方法以及（如有）手动验证标志。对1,862个装置的分层样本进行人工审核后，数据库的总体精度约为74%-75%，独立来源的相互印证带来了显著的、量化的精度提升。通过整合独立来源而非依赖单一检测方法，OpenPVMapper达到了任何单一来源都无法独自提供的置信水平，并且随着更多可用来源的出现仍可扩展。它在开放（CC-BY）许可下发布，并附带用于构建它的完整源代码。
英文摘要
Rooftop photovoltaic (PV) systems account for the vast majority of PV grid connections, yet no open, comprehensive, installation-level dataset of these systems exists: public registries aggregate data only above a capacity threshold, and remote sensing-based detection efforts, while extensive, are typically confined to a single method, a limited geographic scope, or a single point in time. We introduce OpenPVMapper, a nationwide, multi-source database of rooftop PV installations in mainland France, built by aggregating and reconciling complementary sources: a deep learning-based detection pipeline deployed on nationwide aerial imagery, OpenStreetMap and a probabilistic building-level detection dataset. The resulting database contains 1,135,850 installations, totaling approximately 15.01~GWp of installed capacity, each documented with its provenance, detection method, and, where available, a manual validation flag. Manual review of a stratified sample of 1,862 installations places the database's overall precision at approximately 74--75\%, with corroboration across independent sources bringing a substantial, quantified precision gain. By aggregating independent sources rather than relying on any single detection method, OpenPVMapper reaches a level of confidence beyond what any one source could provide on its own, while remaining extensible to further sources as they become available. It is released under an open (CC-BY) license alongside the full source code used to build it.
Comments14 pages, 5 tables, 7 figures
