Exploitation of Satellite A-DInSAR Time Series for Detection, Characterization and Modelling of Land Subsidence

Bonì, Roberta; Meisina, Claudia; Cigna, Francesca; Herrera, Gerardo; Notti, Davide; Bricker, Stephanie; McCormack, H.F.; Tomás, Roberto; Béjar‐Pizarro, Marta; Mulas, J.; Ezquerro, Pablo

doi:10.3390/geosciences7020025

Cited by 24 publications

(18 citation statements)

References 45 publications

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“…Earth Observation (EO) techniques can profitably support risk reduction strategies by taking advantage of their wide area coverage associated with a high cost/benefit ratio. One of these techniques, the Persistent Scatterers Interferometry (PSI) [12], has been successfully adopted for a wide range of applications in disaster management, and it has extensively proven to be a valuable tool to detect ground deformations due to landslides [13][14][15][16][17][18], subsidence [19][20][21][22][23][24][25][26][27][28], volcanoes [29,30] and earthquakes [31].…”

Section: Introductionmentioning

confidence: 99%

Subsidence Evolution of the Firenze–Prato–Pistoia Plain (Central Italy) Combining PSI and GNSS Data

et al. 2018

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Subsidence phenomena, as well as landslides and floods, are one of the main geohazards affecting the Tuscany region (central Italy). The monitoring of related ground deformations plays a key role in their management to avoid problems for buildings and infrastructure. In this scenario, Earth observation offers a better solution in terms of costs and benefits than traditional techniques (e.g., GNSS (Global Navigation Satellite System) or levelling networks), especially for wide area applications. In this work, the subsidence-related ground motions in the Firenze–Prato–Pistoia plain were back-investigated to track the evolution of displacement from 2003 to 2017 by means of multi-interferometric analysis of ENVISAT and Sentinel-1 imagery combined with GNSS data. The resulting vertical deformation velocities are aligned to the European Terrestrial Reference System 89 (ETRS89) datum and can be considered real velocity of displacement. The vertical ground deformation maps derived by ENVISAT and Sentinel-1 data, corrected with the GNSS, show how the area affected by subsidence for the period 2003–2010 and the period 2014–2017 evolved. The differences between the two datasets in terms of the extension and velocity values were analysed and then associated with the geological setting of the basin and external factors, e.g., new greenhouses and nurseries. This analysis allowed for reconstructing the evolution of the subsidence for the area of interest showing an increment of ground deformation in the historic centre of Pistoia Town, a decrement of subsidence in the nursery area between Pistoia and Prato cities, and changes in the industrial sector close to Prato.

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Section: Introductionmentioning

confidence: 99%

Subsidence Evolution of the Firenze–Prato–Pistoia Plain (Central Italy) Combining PSI and GNSS Data

et al. 2018

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“…Retrieving processes occurring on the land surface can allow an indirect characterization of the subsurface parameters of interest. In particular, land movements obtained by Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques have been used to quantify aquifer related deformation, estimate aquifer hydraulic properties, and model hydraulic head at well locations (Galloway et al 1998;Erban et al 2014;Ezquerro et al 2014;Chaussard et al 2014;Chen et al 2016;Béjar-Pizarro et al 2017;Bonì et al 2017;Li and Zhang 2018;Choopani et al 2019;Rezaei and Mousavi 2019). Hoffmann et al (2003) exploited InSAR-derived subsidence observations to implement an inverse procedure for the estimate of the deformation time constant and inelastic skeletal storage coefficient of compacting interbeds to be used in a regional groundwater flow and aquifer-system subsidence model of the Antelope Valley (California).…”

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3D groundwater flow and deformation modelling of Madrid aquifer

Bonì

Meisina

Teatini

et al. 2020

Journal of Hydrology

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A novel methodological approach to calibrate and validate three-dimensional (3D) finite element (FE) groundwater flow and geomechanical models has been implemented using Advanced Differential Interferometric SAR (A-DInSAR) data. In particular, we show how A-DInSAR data can be effectively used to (1) constrain the model setup in evaluating the areal influence of the wellfield and (2) characterise the aquifer system, specifically the storage coefficient values, which represents a fundamental step in managing groundwater resources. The procedure has been tested to reconstruct the surface vertical and horizontal movements caused by the Manzanares-Jarama wellfield located northwest of Madrid (Spain). The wellfield was used to supply freshwater during major droughts over the period between 1994 and 2010. Previous A-DInSAR outcomes obtained by ERS-1/2 and ENVISAT acquisitions clearly revealed the seasonality of the land displacements associated to the withdrawal and recovery cycles that characterized the wellfield development. A time-lag of about one month, which is in the order of the time span between two SAR acquisitions, between the hydraulic head changes and the displacements has been detected in this site by a wavelet analysis of A-DInSAR and piezometer time series. The negligible delay between the forcing factor and the system response and the complete subsidence recovery when piezometric head recovers supported the understanding of a minor role played by the pore pressure propagation within clay layers and the almost perfectly elastic behavior of the system (viscosity is negligible), respectively. The developed geomechanical model satisfactorily reproduces the pumping-induced deformations with a Root Mean Square Error (RMSE) between observed and simulated land displacements in the order of 0.1-0.3 mm. The results give insights about the approach benefits in deeply understanding the spatio-temporal aquifersystem response to the management of this strategic water resource for Madrid.

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“…Bonì et al [3] tackle the use of satellite InSAR methods and SAR data from the methodological point of view, and present three case studies in Italy, Spain, and the UK, where approaches to analysing and interpreting InSAR results for land subsidence detection, characterisation, and modelling are exploited with a focus on the relationship of surface deformation with groundwater level change and exploitation of aquifer resources. Using various stacks of C-, L-and X-band satellite SAR imagery, as well as different InSAR image processing methods (i.e., SqueeSAR TM , StaMPS, Stable Points Network or SPN, and Interferometric Point Target Analysis or IPTA), the authors showcase InSAR time series post-processing methods such as principal component analysis to identify and separate linear, non-linear, and seasonal movements, transient and inelastic aquifer deformation, and accelerating and decelerating subsidence trends.…”

Section: Data Methods and Geohazard Domainsmentioning

confidence: 99%

Observing Geohazards from Space

Cigna

2018

Geosciences

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Abstract:With a wide spectrum of imaging capabilities-from optical to radar sensors, low to very high resolution, continental to local scale, single-image to multi-temporal approaches, yearly to sub-daily acquisition repeat cycles-Earth Observation (EO) offers several opportunities for the geoscience community to map and monitor natural and human-induced Earth hazards from space. The Special Issue "Observing Geohazards from Space" of Geosciences gathers 12 research articles on the development, validation, and implementation of satellite EO data, processing methods, and applications for mapping and monitoring of geohazards such as slow moving landslides, ground subsidence and uplift, and active and abandoned mining-induced ground movements. Papers published in this Special Issue provide novel case studies demonstrating how EO and remote sensing data can be used to detect and delineate land instability and geological hazards in different environmental contexts and using a range of spatial resolutions and image processing methods. Remote sensing datasets used in the Special Issue papers encompass satellite imagery from the ERS-1/2, ENVISAT, RADARSAT-1/2, and Sentinel-1 C-band, TerraSAR-X and COSMO-SkyMed X-band, and ALOS L-band SAR missions; Landsat 7, SPOT-5, WorldView-2/3, and Sentinel-2 multi-spectral data; UAV-derived RGB and near infrared aerial photographs; LiDAR surveying; and GNSS positioning data. Techniques that are showcased include, but are not limited to, differential Interferometric SAR (InSAR) and its advanced approaches such as Persistent Scatterers (PS) and Small Baseline Subset (SBAS) methods to estimate ground deformation, Object-Based Image Analysis (OBIA) to identify landslides in high resolution multi-spectral data, UAV and airborne photogrammetry, Structure-from-Motion (SfM) for digital elevation model generation, aerial photo-interpretation, feature extraction, and time series analysis. Case studies presented in the papers focus on landslides, natural and human-induced subsidence, and groundwater management and mining-related ground deformation in many local to regional-scale study areas in

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Exploitation of Satellite A-DInSAR Time Series for Detection, Characterization and Modelling of Land Subsidence

Cited by 24 publications

References 45 publications

Subsidence Evolution of the Firenze–Prato–Pistoia Plain (Central Italy) Combining PSI and GNSS Data

Subsidence Evolution of the Firenze–Prato–Pistoia Plain (Central Italy) Combining PSI and GNSS Data

3D groundwater flow and deformation modelling of Madrid aquifer

Observing Geohazards from Space

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