An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data
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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.
- 2021Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmarkcited by 22
- 2022Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature datacited by 8
- 2024Space-scale Exploration of the Poor Reliability of Deep Learning Models: the Case of the Remote Sensing of Rooftop Photovoltaic Systemscited by 4
- 2026Nationally Consistent, Locally Incomplete: A Bayesian Remote-Sensing Audit of Rooftop Photovoltaic Registriescited by 0
- 2026Nationally Consistent, Locally Incomplete: A Bayesian Remote-Sensing Audit of Rooftop Photovoltaic Registries14 Sep 2026
- 2024Space-scale Exploration of the Poor Reliability of Deep Learning Models: the Case of the Remote Sensing of Rooftop Photovoltaic Systems31 Jul 2024
- 2022Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature data5 Jun 2022
- 2021Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark1 Dec 2021