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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLVIII-4-W13-2025-17-2025</article-id>
<title-group>
<article-title>Creating a Dataset of Spatial Parameters of Ground-Mounted Photovoltaic Systems Utilising Orthophotos and the Segment Anything Model</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Albert</surname>
<given-names>Johannes</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Schymik</surname>
<given-names>Chantal</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gärtner</surname>
<given-names>Philipp</given-names>
<ext-link>https://orcid.org/0000-0002-5746-096X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wehner</surname>
<given-names>Claudius</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Siegismund</surname>
<given-names>Jan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Klingner</surname>
<given-names>Stephan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Application Lab for Artificial Intelligence and Big Data at the German Environment Agency, Leipzig, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>11</day>
<month>07</month>
<year>2025</year>
</pub-date>
<volume>XLVIII-4/W13-2025</volume>
<fpage>17</fpage>
<lpage>24</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2025 Johannes Albert et al.</copyright-statement>
<copyright-year>2025</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.html">This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-4-W13-2025/17/2025/isprs-archives-XLVIII-4-W13-2025-17-2025.pdf</self-uri>
<abstract>
<p>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.</p>
</abstract>
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