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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-1-W3-2023-47-2023</article-id>
<title-group>
<article-title>GEOMETRIC PROCESSING OF VERY HIGH-RESOLUTION SATELLITE IMAGERY: QUALITY ASSESSMENT FOR 3D MAPPING NEEDS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Farella</surname>
<given-names>E. M.</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>Remondino</surname>
<given-names>F.</given-names>
<ext-link>https://orcid.org/0000-0001-6097-5342</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>Cahalane</surname>
<given-names>C.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Qin</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Loghin</surname>
<given-names>A. M.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Di Tullio</surname>
<given-names>M.</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Haala</surname>
<given-names>N.</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mills</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>3D Optical Metrology Unit, Bruno Kessler Foundation (FBK), Trento, Italy</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Department of Geography, Rhetoric House, Maynooth University, Co. Kildare, Ireland</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Geospatial Data Analytics Laboratory, The Ohio State University, Columbus, USA</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Department of Geodesy and Geoinformation, Vienna University of Technology, Austria</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>Federal Office of Metrology and Surveying (BEV), Vienna, Austria</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>GMatics, Rome, Italy</addr-line>
</aff>
<aff id="aff7">
<label>7</label>
<addr-line>Institute for Photogrammetry, University of Stuttgart, Germany</addr-line>
</aff>
<aff id="aff8">
<label>8</label>
<addr-line>School of Engineering, Newcastle University, United Kingdom</addr-line>
</aff>
<pub-date pub-type="epub">
<day>19</day>
<month>10</month>
<year>2023</year>
</pub-date>
<volume>XLVIII-1/W3-2023</volume>
<fpage>47</fpage>
<lpage>54</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2023 E. M. Farella et al.</copyright-statement>
<copyright-year>2023</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-1-W3-2023/47/2023/isprs-archives-XLVIII-1-W3-2023-47-2023.html">This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-1-W3-2023/47/2023/isprs-archives-XLVIII-1-W3-2023-47-2023.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVIII-1-W3-2023/47/2023/isprs-archives-XLVIII-1-W3-2023-47-2023.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-1-W3-2023/47/2023/isprs-archives-XLVIII-1-W3-2023-47-2023.pdf</self-uri>
<abstract>
<p>In recent decades, the geospatial domain has benefitted from technological advances in sensors, methodologies, and processing tools to expand capabilities in mapping applications. Airborne techniques (LiDAR and aerial photogrammetry) generally provide most of the data used for this purpose. However, despite the relevant accuracy of these technologies and the high spatial resolution of airborne data, updates are not sufficiently regular due to significant flight costs and logistics. New possibilities to fill this information gap have emerged with the advent of Very High Resolution (VHR) optical satellite images in the early 2000s. In addition to the high temporal resolution of the cost-effective datasets and their sub-meter geometric resolutions, the synoptic coverage is an unprecedented opportunity for mapping remote areas, multi-temporal analyses, updating datasets and disaster management. For all these reasons, VHR satellite imagery is clearly a relevant study for National Mapping and Cadastral Agencies (NMCAs). This work, supported by EuroSDR, summarises a series of experimental analyses carried out over diverse landscapes to explore the potential of VHR imagery for large-scale mapping.</p>
</abstract>
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