mlsanityData to 7 Oct 2026

An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data

arXiv 2012.03690 ↗First posted 7 Dec 2020cs.CV cs.AI cs.LGcited by 4

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Abstract (arXiv)

While photovoltaic (PV) systems are installed at an unprecedented rate, reliable information on an installation level remains scarce. As a result, automatically created PV registries are a timely contribution to optimize grid planning and operations. This paper demonstrates how aerial imagery and three-dimensional building data can be combined to create an address-level PV registry, specifying area, tilt, and orientation angles. We demonstrate the benefits of this approach for PV capacity estimation. In addition, this work presents, for the first time, a comparison between automated and officially-created PV registries. Our results indicate that our enriched automated registry proves to be useful to validate, update, and complement official registries.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Dec 2020.

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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 1; 2025: 0; 2026: 1.

4 papers.