Present-day land subsidence rates, surface faulting hazard and risk in Mexico City with 2014–2020 Sentinel-1 IW InSAR

Cigna, Francesca; Tapete, Deodato

doi:10.1016/j.rse.2020.112161

Cited by 145 publications

(105 citation statements)

References 69 publications

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“…Since the initial development of spaceborne synthetic aperture radar (SAR) systems and the demonstration of the SAR interferometric capability, the technique has reached its maturity for the detection of earthquake-induced ground displacements (Cornou et al 2020;Bacques et al 2020), among other geohazards (Delgado Blasco et al 2019;Papageorgiou et al 2019;Aslan et al 2020;Cigna and Tapete 2020;Vassilakis et al 2020). In the last decade, Earth Observation (EO) satellite missions are providing a richness of data at improved spatial resolution and coverage, as well as reduced revisit time, while the latest generation of SAR sensors ensures the millimeter precision of interferometric measurements (Gisinger et al 2019).…”

Section: Spaceborne Imaging Geodesymentioning

confidence: 99%

On rapid multidisciplinary response aspects for Samos 2020 M7.0 earthquake

et al. 2021

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Following the M 7.0 earthquake that struck the Greek island of Samos and Turkey's western coast, causing extensive damage and casualties, we combined existing knowledge geodatabases concerning historical seismicity and rupture zones with seismological and geodetic measurements as well as with modelling and in situ observations, to provide an assessment of rapid response to the seismic event. In this paper, we demonstrate that in the frame of the gradual provision of information from the individual scientific disciplines, taking into account their respective potential and limitations, a multidisciplinary approach is able to address more efficiently rapid response issues in order to allow effective preliminary interpretation of the earthquake activity, even within the first 24 h of the event. It focuses on the assessment of the timely provision of information by each discipline, evaluating the access to primary data sources as well as the maturity of the techniques in terms of accuracy and rapid data processing. Within a period of less than a week, several constraints were partially compensated for, allowing the delivery of more robust results and interpretation. The study highlights the readiness level of the various domains that has been significantly improved over the past years, including rapid seismological solutions, systematic availability of free and open Earth Observation data and on-demand online processing through dedicated platforms. Their combination with routinely applied inversion modelling and timely in situ observation is leading to improved operational response levels. Supplementary Information The online version contains supplementary material available at 10.1007/s11600-021-00578-6.

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Section: Spaceborne Imaging Geodesymentioning

confidence: 99%

On rapid multidisciplinary response aspects for Samos 2020 M7.0 earthquake

et al. 2021

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“…More specifically, subsidence may causes lowering of the earth's land surface by natural or human induced activities, most importantly mobilization of solid or fluid underground materials are the main causes (Herrera-García et al, 2021). In general, there is a downward motion of the rock and soil surface in an almost vertical direction or sometimes with a slight angle that is known as LS (Cigna and Tapete, 2021). This phenomenon occurs suddenly or sometimes gradually due to a number of natural as well as anthropogenic factors.…”

Section: Introductionmentioning

confidence: 99%

“…Like other natural geo-hazard phenomena, this incident also causes life loss and huge economic losses. Essentially, land loss causes devastating damage to property and infrastructure, such as construction, communication with transport networks, drainage systems, underground pipelines, and many more (Cigna and Tapete, 2021). LS not only affected environmental changes but also impacts on social and economic activities.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

et al. 2021

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The optimal prediction of land subsidence (LS) is very much difficult because of limitations in proper monitoring techniques, field-base surveys and knowledge related to functioning and behavior of LS. Thus, due to the lack of LS susceptibility maps it is almost impossible to identify LS prone areas and as a result it influences severe economic and human losses. Hence, preparation of LS susceptibility mapping (LSSM) can help to prevent natural and human catastrophes and reduce the economic damages significantly. Machine learning (ML) techniques are becoming increasingly proficient in modeling purpose of such kinds of occurrences and they are increasing used for LSSM. This study compares the performances of single and hybrid ML models to preparation of LSSM for future prediction of performance analysis. In this study, the spatial prediction of LS was assessed using four ML models of maximum entropy (MaxEnt), general linear model (GLM), artificial neural network (ANN) and support vector machine (SVM). Alongside, the possible numbers of novel ensemble models were integrated through the aforementioned four ML models for optimal analysis of LSSM. An inventory LS map was prepared based on the previous occurrences of LS points and the dataset were divvied into 70:30 ratios for training and validating of the modeling process. To identify the robust and best LSSMs, receiver operating characteristic-area under curve (ROC-AUC) curve was employed. The ROC-AUC result indicated that ANN model gives the highest ROC-AUC (0.924) in training accuracy. The highest AUC (0.823) of the LSSMs was determined based on validation datasets identified by SVM followed by ANN-SVM (0.812).

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“…Geohazard maps. Geological instability hazard maps were produced based on the angular distortion 33,39,40 , which was calculated as the ratio of the subsidence horizontal gradient between two adjacent pixels to the horizontal distance between them, equivalent to 15 m of pixel size. The subsidence horizontal gradient was calculated from the Sentinel-1 LOS displacement maps for the cumulative periods of 10.2016-10.2017, 10.2016-10.2018, 10.2016-10.2019, and 10.2016-07.2020.…”

Section: Methodsmentioning

confidence: 99%

A decade-long silent ground subsidence hazard culminating in a metropolitan disaster in Maceió, Brazil

Vassileva

Al-Halbouni

Motagh

et al. 2021

Sci Rep

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Ground subsidence caused by natural or anthropogenic processes affects major urban areas worldwide. Sinkhole formation and infrastructure fractures have intensified in the federal capital of Maceió (Alagoas, Brazil) since early 2018, forcing authorities to relocate affected residents and place buildings under demolition. In this study, we present a 16-year history (2004–2020) of surface displacement, which shows precursory deformations in 2004–2005, reaching a maximum cumulative subsidence of approximately 200 cm near the Mundaú Lagoon coast in November 2020. By integrating the displacement observations with numerical source modelling, we suggest that extensive subsidence can be primarily associated with the removal of localized, deep-seated material at the location and depth where salt is mined. We discuss the accelerating subsidence rates, influence of severe precipitation events on the aforementioned geological instability, and related hazards. This study suggests that feedback destabilization mechanisms may arise in evaporite systems due to anthropogenic activities, fostering enhanced and complex superficial ground deformation.

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Present-day land subsidence rates, surface faulting hazard and risk in Mexico City with 2014–2020 Sentinel-1 IW InSAR

Cited by 145 publications

References 69 publications

On rapid multidisciplinary response aspects for Samos 2020 M7.0 earthquake

On rapid multidisciplinary response aspects for Samos 2020 M7.0 earthquake

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

A decade-long silent ground subsidence hazard culminating in a metropolitan disaster in Maceió, Brazil

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