Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model

The rapid expansion of renewable energy sources poses significant challenges in reconciling energy development with competing interests. This underscores the necessity for precise spatial data to facilitate effective balancing, management, or evaluation of compliance with regulatory frameworks. This...

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Main Authors: J. Albert, C. Schymik, P. Gärtner, C. Wehner, J. Siegismund, S. Klingner
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.pdf
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author J. Albert
C. Schymik
P. Gärtner
C. Wehner
J. Siegismund
S. Klingner
author_facet J. Albert
C. Schymik
P. Gärtner
C. Wehner
J. Siegismund
S. Klingner
author_sort J. Albert
collection DOAJ
description The rapid expansion of renewable energy sources poses significant challenges in reconciling energy development with competing interests. This underscores the necessity for precise spatial data to facilitate effective balancing, management, or evaluation of compliance with regulatory frameworks. This paper presents a zero-shot approach for extracting parameters of ground-mounted photovoltaic systems in Germany based on digital orthophotos. This allows for the accurate identification and delineation of essential spatial parameters, including the ground coverage ratio of photovoltaic modules, the row spacing between module rows, and their exact orientation. The results of this study are twofold. First, the developed technical pipeline successfully achieves high-quality segmentation of photovoltaic module rows, with over 71 % of the results demonstrating satisfactory to flawless segmentation. Second, the resulting dataset is made available for further analysis and can serve as a starting point for the development of additional AI models aimed at monitoring the dynamics of photovoltaic systems.
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institution Kabale University
issn 1682-1750
2194-9034
language English
publishDate 2025-07-01
publisher Copernicus Publications
record_format Article
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
spelling doaj-art-e003354fe1ce48e5b3f5b43e65f889542025-08-20T03:49:50ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342025-07-01XLVIII-4-W13-2025172410.5194/isprs-archives-XLVIII-4-W13-2025-17-2025Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything ModelJ. Albert0C. Schymik1P. Gärtner2C. Wehner3J. Siegismund4S. Klingner5Application Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, GermanyApplication Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, GermanyApplication Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, GermanyApplication Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, GermanyApplication Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, GermanyApplication Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, GermanyThe rapid expansion of renewable energy sources poses significant challenges in reconciling energy development with competing interests. This underscores the necessity for precise spatial data to facilitate effective balancing, management, or evaluation of compliance with regulatory frameworks. This paper presents a zero-shot approach for extracting parameters of ground-mounted photovoltaic systems in Germany based on digital orthophotos. This allows for the accurate identification and delineation of essential spatial parameters, including the ground coverage ratio of photovoltaic modules, the row spacing between module rows, and their exact orientation. The results of this study are twofold. First, the developed technical pipeline successfully achieves high-quality segmentation of photovoltaic module rows, with over 71 % of the results demonstrating satisfactory to flawless segmentation. Second, the resulting dataset is made available for further analysis and can serve as a starting point for the development of additional AI models aimed at monitoring the dynamics of photovoltaic systems.https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.pdf
spellingShingle J. Albert
C. Schymik
P. Gärtner
C. Wehner
J. Siegismund
S. Klingner
Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model
title_full Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model
title_fullStr Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model
title_full_unstemmed Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model
title_short Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model
title_sort creating a dataset of spatial parameters of ground mounted photovoltaic systems utilising orthophotos and the segment anything model
url https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.pdf
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