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PSInSAR-Based Time-Series Coastal Deformation Estimation Using Sentinel-1 Data

Author

Listed:
  • Muhammad Ali

    (Dipartimento di Ingegneria, Università degli Studi di Napoli Parthenope, 80133 Napoli, Italy)

  • Alessandra Budillon

    (Dipartimento di Ingegneria, Università degli Studi di Napoli Parthenope, 80133 Napoli, Italy)

  • Zeeshan Afzal

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China)

  • Gilda Schirinzi

    (Dipartimento di Ingegneria, Università degli Studi di Napoli Parthenope, 80133 Napoli, Italy)

  • Sajid Hussain

    (School of Remote sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

Abstract

Coastal areas are highly dynamic regions where surface deformation due to natural and anthropogenic activities poses significant challenges. Synthetic Aperture Radar (SAR) interferometry techniques, such as Persistent Scatterer Interferometry (PSInSAR), provide advanced capabilities to monitor surface deformation with high precision. This study applies PSInSAR techniques to estimate surface deformation along coastal zones from 2017 to 2020 using Sentinel-1 data. In the densely populated areas of Pasni, an annual subsidence rate of 130 mm is observed, while the northern, less populated region experiences an uplift of 70 mm per year. Seawater intrusion is an emerging issue causing surface deformation in Pasni’s coastal areas. It infiltrates freshwater aquifers, primarily due to excessive groundwater extraction and rising sea levels. Over time, seawater intrusion destabilizes the underlying soil and rock structures, leading to subsidence or gradual sinking of the ground surface. This form of surface deformation poses significant risks to infrastructure, agriculture, and the local ecosystem. Land deformation varies along the study area’s coastline. The eastern region, which is highly reclaimed, is particularly affected by erosion. The results derived from Sentinel-1 SAR data indicate significant subsidence in major urban districts. This information is crucial for coastal management, hazard assessment, and planning sustainable development in the region.

Suggested Citation

  • Muhammad Ali & Alessandra Budillon & Zeeshan Afzal & Gilda Schirinzi & Sajid Hussain, 2025. "PSInSAR-Based Time-Series Coastal Deformation Estimation Using Sentinel-1 Data," Land, MDPI, vol. 14(3), pages 1-17, March.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:536-:d:1605247
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    References listed on IDEAS

    as
    1. Shubham Awasthi & Divyesh Varade & Sutapa Bhattacharjee & Hemant Singh & Sana Shahab & Kamal Jain, 2022. "Assessment of Land Deformation and the Associated Causes along a Rapidly Developing Himalayan Foothill Region Using Multi-Temporal Sentinel-1 SAR Datasets," Land, MDPI, vol. 11(11), pages 1-21, November.
    2. Manzoor Hussain Memon & Rafiq Ahmed, 2022. "Multi-topographical landscape: comparative vulnerability of climate-induced disaster-prone rural area of Pakistan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1575-1602, March.
    Full references (including those not matched with items on IDEAS)

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