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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Annals</journal-id>
<journal-title-group>
<journal-title>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Annals</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9050</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-annals-X-G-2025-33-2025</article-id>
<title-group>
<article-title>Advances in Precision Farming: a contribute for estimating crop health and water stress by comparing UAV Multispectral and Thermal Imagery</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Aldrighettoni</surname>
<given-names>Joel</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>D'Urso</surname>
<given-names>Maria Grazia</given-names>
<ext-link>https://orcid.org/0000-0002-6770-9861</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Engineering and Applied Sciences, University of Bergamo, Bergamo 24044, Italy</addr-line>
</aff>
<pub-date pub-type="epub">
<day>10</day>
<month>07</month>
<year>2025</year>
</pub-date>
<volume>X-G-2025</volume>
<fpage>33</fpage>
<lpage>40</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2025 Joel Aldrighettoni</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-annals.copernicus.org/articles/X-G-2025/33/2025/isprs-annals-X-G-2025-33-2025.html">This article is available from https://isprs-annals.copernicus.org/articles/X-G-2025/33/2025/isprs-annals-X-G-2025-33-2025.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/X-G-2025/33/2025/isprs-annals-X-G-2025-33-2025.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/X-G-2025/33/2025/isprs-annals-X-G-2025-33-2025.pdf</self-uri>
<abstract>
<p>Current climate change is largely due to the continuing increase in the anthropogenic greenhouse effect, with major environmental repercussions, especially in agriculture. The increase of global warming, salinity of water resources and frequency of extreme weather events has devastating consequences on the primary sector, in particular on the photosynthetic activity of crops and, therefore, their agricultural yield. The current climate crisis, in fact, leads to an increase in water requirements, the proliferation of weeds, and the depletion of nutrients in the soil, necessitating the massive use of fertilisers, herbicides and pesticides, which, in turn, trigger substantial alterations in ecosystem balances. In response to these critical issues, precision agriculture (PA) constitutes a data-driven approach based on the interpretation of multispectral and thermal datasets obtained by different remote sensing techniques and the use of latest-generation sensors to recognise the state of health of crops and, therefore, optimise agricultural production with a more rational and sustainable management of resources.&lt;br /&gt;This paper presents the results of a survey campaign carried out in October 2023 on two citrus fields located in south-eastern Sicily (Italy) to highlight the health status of crops just before the harvesting period. By using multispectral and thermal sensors installed on a drone, different vegetation indices have been calculated to identify, in each field, the areas with the highest photosynthetic activity and the zones characterised by a lack of water or other nutrients, on which targeted agronomic interventions should be planned as a priority.</p>
</abstract>
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