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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-4-W8-2025-257-2026</article-id>
<title-group>
<article-title>Assessment of Land Subsidence Risk Changes in Agricultural Lands Using Remote Sensing Data (Golestan Province)</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Garshasbi</surname>
<given-names>Fateme</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>Ashournejad</surname>
<given-names>Qadir</given-names>
<ext-link>https://orcid.org/0000-0002-0319-6921</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>Safarrad</surname>
<given-names>Taher</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Dept. of Geography and Urban Planning, Faculty of Humanities and Social Sciences, University of Mazandaran, Babolsar, Iran</addr-line>
</aff>
<pub-date pub-type="epub">
<day>29</day>
<month>05</month>
<year>2026</year>
</pub-date>
<volume>X-4/W8-2025</volume>
<fpage>257</fpage>
<lpage>264</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Fateme Garshasbi et al.</copyright-statement>
<copyright-year>2026</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-4-W8-2025/257/2026/isprs-annals-X-4-W8-2025-257-2026.html">This article is available from https://isprs-annals.copernicus.org/articles/X-4-W8-2025/257/2026/isprs-annals-X-4-W8-2025-257-2026.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/X-4-W8-2025/257/2026/isprs-annals-X-4-W8-2025-257-2026.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/X-4-W8-2025/257/2026/isprs-annals-X-4-W8-2025-257-2026.pdf</self-uri>
<abstract>
<p>Land subsidence is one of the most significant environmental threats in agricultural areas, directly affecting soil stability and crop productivity. This study assessed changes in land subsidence in the agricultural lands of Golestan Province between 2015 and 2023. Sentinel-1 radar data were processed using the SBAS method and interferometry techniques to extract vertical ground displacements, while environmental and agricultural indicators, including NDVI, SMI, slope, and aspect, were integrated to analyze subsidence risk. The results indicated a substantial increase in both the intensity and extent of subsidence in 2023, with the average risk rising from 0.397 in 2015 to 0.750 in 2023, while risk dispersion decreased, leaving nearly all agricultural areas at high risk. Correlation analysis also revealed that agricultural activities play a significant role in accelerating subsidence (correlation coefficient = 0.71). Pixel frequency analysis and distribution charts further indicated spatial expansion of risk and homogenization of high-risk areas. These findings can inform sustainable agricultural land management and help predict areas prone to subsidence.</p>
</abstract>
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