Chiara Di Muro

Ms. Chiara Di Muro

Department of Earth Sciences, University of Naples Federico II, Naples, Campania, Italy
orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 May 2023 in Applied Sciences
Verified
Journal Article
Open access
PDF file
Mohammad Amin KhaliliMohammad Amin Khalili
Mohammad Amin Khalili
GBGiuseppe Bausilio
Giuseppe Bausilio
CMChiara Di Muro
Chiara Di Muro
SZSebastiano Perriello Zampelli
Sebastiano Perriello Zampelli
Diego Di MartireDiego Di Martire
Diego Di Martire
Landslides pose significant risks to towns and villages in Southern Italy, including the San Marco dei Cavoti hamlet (Benevento, Campania), where settlements have expanded into areas threatened by landslides, leading to property damage, disruption to the social fabric and loss of life. This study aims to investigate the surface deformations in the area using Differential Interferometry SAR (DInSAR) analysis on COSMO-SkyMed radar imagery and to assess the potential implications for landslide activity. The DInSAR analysis methodology allowed us to obtain high-precision results presented as time series diagrams and maps of cumulative displacement for the study area. Furthermore, the displacement rates derived from the DInSAR analysis were decomposed into vertical and horizontal components to provide better insights into the slope processes and their potential impacts on the San Marco dei Cavoti hamlet. Our significant findings revealed active slope movements and the uphill enlargement of previously inventoried landslides threatening the San Marco dei Cavoti hamlet. These insights contribute to a better understanding of the landslide dynamics in the region and highlight the areas that may require further investigation or intervention measures. In conclusion, this study demonstrates the effectiveness of DInSAR analysis in providing valuable insights into landslide dynamics and informing potential mitigation measures for at-risk communities. This technique could be applied to other landslide-prone regions to support informed decision-making and enhance the safety and resilience of affected communities.