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<p>This study investigates landslide-triggering factors in the Glandrood watershed using a descriptive-analytical approach. Emphasis is placed on extreme climatic variables, including daily temperature differentials and maximum 24-hour precipitation. Landslide displacements from 2013 to 2023 were monitored using Differential Interferometric Synthetic Aperture Radar (DInSAR) and Sentinel-1 imagery, revealing vertical displacement rates ranging from − 10 to 6.9&#xa0;cm. The most significant subsidence occurred in southern areas with low vegetation density. Statistical analysis using the Pearson correlation coefficient showed a strong positive relationship between vertical displacement and climatic extremes, with correlation values of 0.555 for precipitation and 0.494 for temperature differentials (p-value = 0.00). These results indicate that increased precipitation and temperature fluctuations significantly elevate the risk of slope instability. The findings contribute to geophysical modeling and inform proactive mitigation strategies for landslide-prone regions. This research highlights the importance of integrating remote sensing and climatic data to enhance spatial information science and support sustainable land management in vulnerable zones.</p>

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Investigating the effects of climatic elements on landslides using multi-temporal DInSAR technology and statistical analysis

  • 期刊论文

  • 发表日期：

    2025年11月11日

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  • Ali Gilanipoor,
  • Sadroddin Motevalli,
  • GholamReza Janbaz Ghobadi,
  • Khabat Derafshi

摘要

This study investigates landslide-triggering factors in the Glandrood watershed using a descriptive-analytical approach. Emphasis is placed on extreme climatic variables, including daily temperature differentials and maximum 24-hour precipitation. Landslide displacements from 2013 to 2023 were monitored using Differential Interferometric Synthetic Aperture Radar (DInSAR) and Sentinel-1 imagery, revealing vertical displacement rates ranging from − 10 to 6.9 cm. The most significant subsidence occurred in southern areas with low vegetation density. Statistical analysis using the Pearson correlation coefficient showed a strong positive relationship between vertical displacement and climatic extremes, with correlation values of 0.555 for precipitation and 0.494 for temperature differentials (p-value = 0.00). These results indicate that increased precipitation and temperature fluctuations significantly elevate the risk of slope instability. The findings contribute to geophysical modeling and inform proactive mitigation strategies for landslide-prone regions. This research highlights the importance of integrating remote sensing and climatic data to enhance spatial information science and support sustainable land management in vulnerable zones.