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Risk assessment of land subsidence and associated faulting in Mexico City using InSAR

Author

Listed:
  • Enrique Antonio Fernández-Torres

    (Universidad Nacional Autónoma de México
    Universidad Nacional Autónoma de México)

  • Enrique Cabral-Cano

    (Universidad Nacional Autónoma de México)

  • David Alberto Novelo-Casanova

    (Universidad Nacional Autónoma de México)

  • Darío Solano-Rojas

    (Universidad Nacional Autónoma de México)

  • Emre Havazli

    (California Institute of Technology)

  • Luis Salazar-Tlaczani

    (Universidad Nacional Autónoma de México)

Abstract

Land subsidence and associated faulting have affected Mexico City (CDMX), Mexico, for more than 100 years. However, despite the extensive research on land subsidence in CDMX, very few investigations focus on characterizing its socioeconomic risk due to land subsidence. In this article, we present Mexico City’s socioeconomic risk map due to land subsidence and associated faulting, combining our data from a land subsidence characterization based on InSAR processing with a socioeconomic vulnerability assessment. Our results show two high subsidence velocity areas. The largest area is located in the northeast sector of CDMX and the neighboring State of Mexico suburbs, where the maximum subsidence rate reaches up to 423 mm/year. We also found that 40.4% of the total cumulative length of land subsidence-associated faults correspond to high 15.6% and very high 24.8% classes of subsidence horizontal gradient. Our results demonstrate a spatial correlation between areas of high subsidence rate and horizontal gradient with high and very high socioeconomic vulnerability zones. Under this scenario, 9% of the urbanized areas, about 70.7 km2, are exposed to high and very high land subsidence socioeconomic risk where approximately 12.6% of the CDMX population lives.

Suggested Citation

  • Enrique Antonio Fernández-Torres & Enrique Cabral-Cano & David Alberto Novelo-Casanova & Darío Solano-Rojas & Emre Havazli & Luis Salazar-Tlaczani, 2022. "Risk assessment of land subsidence and associated faulting in Mexico City using InSAR," 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. 112(1), pages 37-55, May.
  • Handle: RePEc:spr:nathaz:v:112:y:2022:i:1:d:10.1007_s11069-021-05171-0
    DOI: 10.1007/s11069-021-05171-0
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    1. Hamidreza Gharechaee & Aliakbar Nazari Samani & Shahram Khalighi Sigaroodi & Abolfazl Baloochiyan & Maryam Sadat Moosavi & Jason A. Hubbart & Seyed Mohammad Moein Sadeghi, 2023. "Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran," Land, MDPI, vol. 12(4), pages 1-20, April.

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