{"slug": "openpvmapper-a-multi-source-nationwide-database-of-rooftop-photovoltaic-systems", "title": "OpenPVMapper: A Multi-source, Nationwide Database of Rooftop Photovoltaic Systems in France", "summary": "Researchers have released OpenPVMapper, a nationwide database of rooftop photovoltaic installations in mainland France containing 1,135,850 installations totaling approximately 15.01 GWp of installed capacity, built by aggregating deep learning-based aerial imagery detection, OpenStreetMap, and probabilistic building-level data. The database achieves 74-75% precision based on manual review of 1,862 installations and is released under a CC-BY license with full source code.", "body_md": "arXiv:2607.25153v1 Announce Type: new\nAbstract: 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.", "url": "https://wpnews.pro/news/openpvmapper-a-multi-source-nationwide-database-of-rooftop-photovoltaic-systems", "canonical_source": "https://arxiv.org/abs/2607.25153", "published_at": "2026-07-29 04:00:00+00:00", "updated_at": "2026-07-29 04:22:30.078901+00:00", "lang": "en", "topics": ["artificial-intelligence", "computer-vision", "machine-learning", "ai-research"], "entities": ["OpenPVMapper", "OpenStreetMap"], "alternates": {"html": "https://wpnews.pro/news/openpvmapper-a-multi-source-nationwide-database-of-rooftop-photovoltaic-systems", "markdown": "https://wpnews.pro/news/openpvmapper-a-multi-source-nationwide-database-of-rooftop-photovoltaic-systems.md", "text": "https://wpnews.pro/news/openpvmapper-a-multi-source-nationwide-database-of-rooftop-photovoltaic-systems.txt", "jsonld": "https://wpnews.pro/news/openpvmapper-a-multi-source-nationwide-database-of-rooftop-photovoltaic-systems.jsonld"}}