*Article* **Land Subsidence Detection in the Coastal Plain of Tabasco, Mexico Using Differential SAR Interferometry**

**Zenia Pérez-Falls 1, Guillermo Martínez-Flores 1,\* and Olga Sarychikhina 2**


**\***Correspondence: gmflores@ipn.mx

**Abstract:** Land subsidence (LS) increases flood vulnerability in coastal areas, coastal plains, and river deltas. The coastal plain of Tabasco (TCP) has been the scene of recurring floods, which caused economic and social damage. Hydrocarbon extraction is the main economic activity in the TCP and could be one of the causes of LS in this region. This study aimed to investigate the potential of differential SAR interferometric techniques for LS detection in the TCP. For this purpose, Sentinel-1 SLC descending and ascending images from the 2018–2019 period were used. Conventional DInSAR, together with the differential interferograms stacking (DIS) approach, was applied. The causes of interferometric coherence degradation were analyzed. In addition, Sentinel-1 GRD images were used for delimitation of areas recurrently affected by floods. Based on the results of the interferometric processing, several subsiding zones were detected. The results indicate subsidence rates of up to −6 cm/yr in the urban centers of Villahermosa, Paraíso, Comalcalco, and other localities. The results indicate the possibility of an influence of LS on the flood vulnerability of the area south of Villahermosa city. They also sugges<sup>t</sup> a possible relationship between hydrocarbon extraction and surface deformation.

**Citation:** Pérez-Falls, Z.; Martínez-Flores, G.; Sarychikhina, O. Land Subsidence Detection in the Coastal Plain of Tabasco, Mexico Using Differential SAR Interferometry. *Land* **2022**, *11*, 1473. https://doi.org/ 10.3390/land11091473

Academic Editors: Sara Venafra, Carmine Serio and Guido Masiello

Received: 3 July 2022 Accepted: 29 August 2022 Published: 3 September 2022

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**Keywords:** land subsidence; DInSAR; differential interferograms stacking; floods; coastal plain of Tabasco
