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Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 50975

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Special Issue Editors

Prof. Dr. Claudia Meisina

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Department of Earth and Environmental Sciences, University of Pavia, Via Adolfo Ferrata 1, 27100 Pavia, Italy
Interests: engineering geological mapping; hazard assessment (subsidence, landslide, liquefaction); geological interpretation of satellite interferometric data
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Dr. Francesco Zucca

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Department of Earth & Environmental Sciences, University of Pavia, 27100 Pavia, Italy
Interests: change analysis; multi temporal; hyperspectral; UAV; SAR; InSAR; landslides; virtual outcrops; soil moisture; 3D
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Dr. Roberta Bonì

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Guest Editor

Department of Pure and Applied Sciences, University of Urbino “Carlo Bo”, Urbino, Italy
Interests: engineering geology; remote sensing; landslides; land subsidence; InSAR; monitoring; modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The goal of this Special Issue of Remote Sensing is to collect papers (original research articles and review papers) to give insights about the use of Earth Observations (EO) for land subsidence identification, monitoring and how they impact modeling efforts for these processes.

Land subsidence represents the main reaction to superficial and deep deformations induced by multiple natural and anthropic phenomena (i.e. vadose zone processes as swelling/shrinkage of clay soils, soil consolidation, aquifer compaction, solid and fluid extraction and load-induced compaction etc.) which take place at different spatio-temporal scale. This kind of hazard affects an increasing number of worldwide regions, densely populated, causing damage to the environment and infrastructures.

Earth observations, including SAR approaches such as multi-temporal processing algorithms, represent a powerful tool for the geoscience community to investigate the land subsidence around the world, with unprecedented spatial and temporal resolution.

Authors are encouraged to submit articles about innovative research or case studies which may include, but are not limited to, the following topics:

innovative methods to use Earth Observation, such as the exploitation of the great potential contained in the displacement time series for land subsidence identification;
integrated monitoring system to measure ground deformation (land subsidence, uplift and seasonal movements);
remote sensing support to understand the land subsidence mechanisms;
land subsidence modeling.

Prof. Claudia Meisina
Prof. Francesco Zucca
Dr. Roberta Bonì
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Land subsidence
Earth observations
Monitoring
Modeling
Displacement time series

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Published Papers (12 papers)

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33 pages, 18983 KiB

Open AccessArticle

Identifying Causes of Urban Differential Subsidence in the Vietnamese Mekong Delta by Combining InSAR and Field Observations

by Kim de Wit, Bente R. Lexmond, Esther Stouthamer, Olaf Neussner, Nils Dörr, Andreas Schenk and Philip S. J. Minderhoud

Remote Sens. 2021, 13(2), 189; https://doi.org/10.3390/rs13020189 - 7 Jan 2021

Cited by 24 | Viewed by 5109

Abstract

The Mekong delta, like many deltas around the world, is subsiding at a relatively high rate, predominately due to natural compaction and groundwater overexploitation. Land subsidence influences many urbanized areas in the delta. Loading, differences in infrastructural foundation depths, land-use history, and subsurface heterogeneity cause a high spatial variability in subsidence rates. While overall subsidence of a city increases its exposure to flooding and reduces the ability to drain excess surface water, differential subsidence results in damage to buildings and above-ground and underground infrastructure. However, the exact contribution of different processes driving differential subsidence within cities in the Mekong delta has not been quantified yet. In this study we aim to identify and quantify drivers of processes causing differential subsidence within three major cities in the Vietnamese Mekong delta: Can Tho, Ca Mau and Long Xuyen. Satellite-based PS-InSAR (Persistent Scatterer Interferometric Synthetic Aperture Radar) vertical velocity datasets were used to identify structures that moved at vertical velocities different from their surroundings. The selected buildings were surveyed in the field to measure vertical offsets between their foundation and the surface level of their surroundings. Additionally, building specific information, such as construction year and piling depth, were collected to investigate the effect of piling depth and time since construction on differential vertical subsidence. Analysis of the PS-InSAR-based velocities from the individual buildings revealed that most buildings in this survey showed less vertical movement compared to their surroundings. Most of these buildings have a piled foundation, which seems to give them more stability. The difference in subsidence rate can be up to 30 mm/year, revealing the contribution of shallow compaction processes above the piled foundation level (up to 20 m depth). This way, piling depths can be used to quantify depth-dependent subsidence. Other local factors such as previous land use, loading of structures without a piled foundation and variation in piling depth, i.e., which subsurface layer the structures are founded on, are proposed as important factors determining urban differential subsidence. PS-InSAR data, in combination with field observations and site-specific information (e.g., piling depths, land use, loading), provides an excellent opportunity to study urban differential subsidence and quantify depth-dependent subsidence rates. Knowing the magnitude of differential subsidence in urban areas helps to differentiate between local and delta wide subsidence patterns in InSAR-based velocity data and to further improve estimates of future subsidence. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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21 pages, 7026 KiB

Open AccessArticle

Investigating Ground Subsidence and the Causes over the Whole Jiangsu Province, China Using Sentinel-1 SAR Data

by Yonghong Zhang, Hongan Wu, Mingju Li, Yonghui Kang and Zhong Lu

Remote Sens. 2021, 13(2), 179; https://doi.org/10.3390/rs13020179 - 7 Jan 2021

Cited by 18 | Viewed by 3632

Abstract

Interferometric synthetic aperture radar (InSAR) mapping of localized ground surface deformation has become an important tool to manage subsidence-related geohazards. However, monitoring land surface deformation using InSAR at high spatial resolution over a large region is still a formidable task. In this paper, we report a research on investigating ground subsidence and the causes over the entire 107, 200 km² province of Jiangsu, China, using time-series InSAR. The Sentinel-1 Interferometric Wide-swath (IW) images of 6 frames are used to map ground subsidence over the whole province for the period 2016–2018. We present processing methodology in detail, with emphasis on the three-level co-registration scheme of S-1 data, retrieval of mean subsidence velocity (MSV) and subsidence time series, and mosaicking of multiple frames of results. The MSV and subsidence time series are generated for 9,276,214 selected coherent pixels (CPs) over the Jiangsu territory. Using 688 leveling measurements in evaluation, the derived MSV map of Jiangsu province shows an accuracy of 3.9 mm/year. Moreover, subsidence causes of the province are analyzed based on InSAR-derived subsidence characteristics, historical optical images, and field-work findings. Main factors accounting for the observed subsidence include: underground mining, groundwater withdrawal, soil consolidations of marine reclamation, and land-use transition from agricultural (paddy) to industrial land. This research demonstrates not only the capability of S-1 data in mapping ground deformation over wide areas in coastal and heavily vegetated region of China, but also the potential of inferring valuable knowledge from InSAR-derived results. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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20 pages, 26393 KiB

Open AccessArticle

Surface Subsidence in Urbanized Coastal Areas: PSI Methods Based on Sentinel-1 for Ho Chi Minh City

by C. Elizabeth Duffy, Andreas Braun and Volker Hochschild

Remote Sens. 2020, 12(24), 4130; https://doi.org/10.3390/rs12244130 - 17 Dec 2020

Cited by 18 | Viewed by 4244

Abstract

In Ho Chi Minh City (HCMC), Vietnam, though at present flooding is merely a recurring nuisance, there is increasing concern that a combination of impending climate change and rapid urbanization will significantly exacerbate the situation. Given the significant measures taken in HCMC to reduce groundwater extraction and sea-level rise (SLR) inundation since the most recent subsidence studies, we aim to update and contribute to the subsidence information of HCMC with continuous temporal coverage from 2017 to 2019. In this study, we use Persistent Scatterer Interferometry (PSI) with Copernicus Sentinel-1 data and open source tools to determine current subsidence rates within the urban center of HCMC. Additionally, the scalability of this method and use of freely accessible data allows for continuous updating and monitoring of this high-vulnerability region. The observed average subsidence rates were 3.3 mm per year with a maximum local subsidence of 5.3 cm per year. These results largely align with findings of previous studies and reflect similar spatial distributed subsidence patterns. Inundation risk awareness is enhanced by not only continued improved subsidence analysis, but also incorporating latest advancements in Digital Elevation Model (DEM) accuracy. This study compares local differences between traditionally used AW3D30 DEM with the CoastalDEM. Our findings indicate that although we identify lower than previously accepted elevations in the urban core, that stabilization of subsidence is observed in this same region. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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23 pages, 5534 KiB

Open AccessArticle

Spatial Analysis of Land Subsidence in the San Luis Potosi Valley Induced by Aquifer Overexploitation Using the Coherent Pixels Technique (CPT) and Sentinel-1 InSAR Observation

by María Inés Navarro-Hernández, Roberto Tomás, Juan M. Lopez-Sanchez, Abraham Cárdenas-Tristán and Jordi J. Mallorquí

Remote Sens. 2020, 12(22), 3822; https://doi.org/10.3390/rs12223822 - 21 Nov 2020

Cited by 19 | Viewed by 4053

Abstract

The San Luis Potosi metropolitan area has suffered considerable damage from land subsidence over the past decades, which has become visible since 1990. This paper seeks to evaluate the effects of groundwater withdrawal on land subsidence in the San Luis Potosi Valley and the development of surface faults due to the differential compaction of sediments. For this purpose, we applied the Coherent Pixels Technique (CPT), a Persistent Scatterer Interferometry (PSI) technique, using 112 Sentinel-1 acquisitions from October 2014 to November 2019 to estimate the deformation rate. The results revealed that the deformation areas in the municipality of Soledad de Graciano Sánchez mostly exhibit subsidence values between −1.5 and −3.5 cm/year; whereas in San Luis Potosi these values are between −1.8 and −4.2 cm/year. The PSI results were validated by five Global Navigation Satellite System (GNSS) benchmarks available, providing a data correlation between the results obtained with both techniques of 0.986. This validation suggests that interferometric derived deformations agree well with results obtained from GNSS data. The strong relationship between trace fault, land subsidence,e and groundwater extraction suggests that groundwater withdrawal is resulting in subsidence induced faulting, which follows the pattern of structural faults buried by sediments. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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21 pages, 12800 KiB

Open AccessArticle

Ground Deformation of Wuhan, China, Revealed by Multi-Temporal InSAR Analysis

by Yakun Han, Jingui Zou, Zhong Lu, Feifei Qu, Ya Kang and Jiangwei Li

Remote Sens. 2020, 12(22), 3788; https://doi.org/10.3390/rs12223788 - 18 Nov 2020

Cited by 29 | Viewed by 3488

Abstract

Wuhan, the largest city in central China, has experienced rapid urban development leading to land subsidence as well as environmental concerns in recent years. Although a few studies have analyzed the land subsidence of Wuhan based on ALOS-1, Envisat, and Sentinel-1 datasets, the research on long-term land subsidence is still lacking. In this study, we employed multi-temporal InSAR to investigate and reveal the spatiotemporal evolution of land subsidence over Wuhan with ALOS-1, Envisat, and Sentinel-1 images from 2007–2010, 2008–2010, 2015–2019, respectively. The results detected by InSAR were cross-validated by two independent SAR datasets, and leveling observations were applied to the calibration of InSAR-derived measurements. The correlation coefficient between the leveling and InSAR has reached 0.89. The study detected six main land subsidence zones during the monitoring period, with the maximum land subsidence velocity of −46 mm/a during the 2015–2019 analysis. Both the magnitude and the extent of the land subsidence have reduced since 2017. The causes of land subsidence are discussed in terms of urban construction, Yangtze river water level changes, and subsurface water level changes. Our results provide insight for understanding the causes of land subsidence in Wuhan and serve as reference for city management for reducing the land subsidence in Wuhan and mitigating the potential hazards. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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18 pages, 9823 KiB

Open AccessArticle

Reservoir Induced Deformation Analysis for Several Filling and Operational Scenarios at the Grand Ethiopian Renaissance Dam Impoundment

by Austin Madson and Yongwei Sheng

Remote Sens. 2020, 12(11), 1886; https://doi.org/10.3390/rs12111886 - 10 Jun 2020

Cited by 8 | Viewed by 5092

Abstract

Addressing seasonal water uncertainties and increased power generation demand has sparked a global rise in large-scale hydropower projects. To this end, the Blue Nile impoundment behind the Grand Ethiopian Renaissance Dam (GERD) will encompass an areal extent of ~1763.3 km² and hold ~67.37 Gt (km³) of water with maximum seasonal load changes of ~27.93 (41% of total)—~36.46 Gt (54% of total) during projected operational scenarios. Five different digital surface models (DSMs) are compared to spatially overlapping spaceborne altimeter products and hydrologic loads for the GERD are derived from the DSM with the least absolute elevation difference. The elastic responses to several filling and operational strategies for the GERD are modeled using a spherically symmetric, non-rotating, elastic, and isotropic (SNREI) Earth model. The maximum vertical and horizontal flexural responses from the full GERD impoundment are estimated to be 11.99 and 1.99 cm, regardless of the full impoundment period length. The vertical and horizontal displacements from the highest amplitude seasonal reservoir operational scenarios are 38–55% and 34–48% of the full deformation, respectively. The timing and rate of reservoir inflow and outflow affects the hydrologic load density on the Earth’s surface, and, as such, affects not only the total elastic response but also the distance that the deformation extends from the reservoir’s body. The magnitudes of the hydrologic-induced deformation are directly related to the size and timing of reservoir fluxes, and an increased knowledge of the extent and magnitude of this deformation provides meaningful information to stakeholders to better understand the effects from many different impoundment and operational strategies. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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17 pages, 6508 KiB

Open AccessArticle

Satellite-Based Monitoring and Modeling of Ground Movements Caused by Water Rebound

by Agnieszka A. Malinowska, Wojciech T. Witkowski, Artur Guzy and Ryszard Hejmanowski

Remote Sens. 2020, 12(11), 1786; https://doi.org/10.3390/rs12111786 - 1 Jun 2020

Cited by 15 | Viewed by 3447

Abstract

The presented research aimed to evaluate the spatio-temporal distribution of ground movements caused by groundwater head changes induced by mining. The research was carried out in the area of one of the copper ore and anhydrite mines in Poland. To determine ground movements, classical surveying results and the persistent scatter Satellite Radar Interferometry (PSInSAR) method were applied. The mining operation triggered significant subsidence, reaching 1.4 m in the years 1944–2015. However, subsidence caused by groundwater pumping was about 0.3 m. After mine closure, an ongoing groundwater rebound was observed. Hence, land uplift occurred, reaching no more than 29 mm/y. The main part of the investigation concerned developing a novel method for uplift prediction. Therefore, an attempt was made to comparatively analyze the dynamics of ground movements correlated with the mine life and hydrogeological condition. These analyses allowed the time factor for the modeling of land uplift to be determined. The investigation also revealed that in the next six years, the uplift will reach up to 12 mm/y. The developed methodology could be applied in any post-mining area where groundwater-rebound-related uplift is observed. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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19 pages, 46820 KiB

Open AccessArticle

Multi-Component and Multi-Source Approach for Studying Land Subsidence in Deltas

by Eleonora Vitagliano, Umberto Riccardi, Ester Piegari, Jean-Paul Boy and Rosa Di Maio

Remote Sens. 2020, 12(9), 1465; https://doi.org/10.3390/rs12091465 - 5 May 2020

Cited by 9 | Viewed by 3140

Abstract

The coupled effects of climate change and land sinking make deltas and coastal areas prone to inundation and flooding, meaning that reliable estimation of land subsidence is becoming crucial. Commonly, land subsidence is monitored by accurate continuous and discrete measurements collected by terrestrial and space geodetic techniques, such as Global Navigation Satellite System (GNSS), Interferometry Synthetic Aperture Radar (InSAR), and high precision leveling. In particular, GNSS, which includes the Global Positioning System (GPS), provides geospatial positioning with global coverage, then used for deriving local displacements through time. These site-positioning time series usually exhibit a linear trend plus seasonal oscillations of annual and semi-annual periods. Although the periodic components observed in the geodetic signal affect the velocity estimate, studies dealing with the prediction and prevention of risks associated with subsidence focus mainly on the permanent component. Periodic components are simply removed from the original dataset by statistical analyses not based on the underlying physical mechanisms. Here, we propose a systematic approach for detecting the physical mechanisms that better explain the permanent and periodic components of subsidence observed in the geodetic time series. It consists of three steps involving a component recognition phase, based on statistical and spectral analyses of geodetic time series, a source selection phase, based on their comparison with data of different nature (e.g., geological, hydro-meteorological, hydrogeological records), and a source validation step, where the selected sources are validated through physically-based models. The application of the proposed procedure to the Codigoro area (Po River Delta, Northern Italy), historically affected by land subsidence, allowed for an accurate estimation of the subsidence rate over the period 2009–2017. Significant differences turn out in the retrieved subsidence velocities by using or not periodic trends obtained by physically based models. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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28 pages, 17025 KiB

Open AccessArticle

Inferring the Creep Settlement Behavior of Rockfill in Reclaimed Lands by Advanced SAR Interferometry and Numerical Modeling: An Example from Arabian Gulf

by Michele Di Lisa, Hossam Eldin A. Ali, Paolo Mazzanti and Serena Moretto

Remote Sens. 2020, 12(3), 527; https://doi.org/10.3390/rs12030527 - 6 Feb 2020

Cited by 4 | Viewed by 4834

Abstract

Satellite Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) is becaming a key-technique for monitoring ground deformations. The potential of A-DInSAR for settlement monitoring is exploited in this paper through the investigation of a reclaimed land in Dubai (UAE). Time histories of displacements were obtained from COSMO-SkyMed satellite images over the period between 2011 to 2016, allowing to derive the long-term deformation of the entire artificial island. Special attention was paid on long-term settlement of the hydraulically-placed rockfill of the peripheral rubble-mound revetments. The A-DInSAR results have been compared with results derived from numerical analyses and with field surveys, proving the relation between observed and modeled displacements. The study has also revealed that rockfill long-term settlement (creep) rate is significantly dependent on the aging (time since placement). In the analyzed time-frame (2011–2016) it has been observed that recently placed rockfill experienced creep rate up to ten times higher than the creep rate measured for similar rockfill structures placed 30 years earlier. Furthermore, it has been demonstrated that static compression by preloading and dynamic or impact densification induced by wave forces proved to have also a significant impact on reducing the creep rate of the rockfill. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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19 pages, 4340 KiB

Open AccessArticle

Improvement of Persistent Scatterer Interferometry to Detect Large Non-Linear Displacements with the 2π Ambiguity by a Non-Parametric Approach

by Fumitaka Ogushi, Masashi Matsuoka, Marco Defilippi and Paolo Pasquali

Remote Sens. 2019, 11(21), 2467; https://doi.org/10.3390/rs11212467 - 23 Oct 2019

Cited by 4 | Viewed by 3345

Abstract

Persistent scatterer interferometry (PSI) is commonly applied to monitor surface displacements with millimetric precision. However, this technique still has trouble estimating non-linear displacements because the algorithm is designed for the slow and linear displacements. Additionally, there is a variety of non-linear displacement types, and finding an appropriate displacement model for PSI is still assumed to be a fairly large task. In this paper, the conventional PSI technique is extended using a non-parametric non-linear approach (NN-PSI), and the performance of the extended method is investigated by simulations and actual observation data processing with TerraSAR-X. In the simulation, non-linear displacements are modeled by the magnitudes and periods of the displacement, and the evaluation of NN-PSI is conducted. According to the simulation results, the maximum magnitude of the displacement that can be estimated by NN-PSI is two and a half times the magnitude of the SAR sensor’s wavelength (2.5

λ

that is roughly equivalent to 8 cm for X-band, 14 cm for C-band, and 60 cm for L-band), and the period of the displacement is about three months. However, this displacement cannot be reconstructed by the conventional PSI due to the limitation, known as the 2

π

displacement ambiguity. The result of the observation data processing shows that a large displacement with the 2

π

ambiguity can be estimated by NN-PSI as the simulation results show, but the conventional PSI cannot reconstruct it. In addition, a different approach, Small BAseline Subset (SBAS), is applied to the same data to ensure the accuracy of results, and the correlation between NN-PSI and SBAS is 0.95, while that between the conventional PSI and SBAS is −0.66. It is concluded that NN-PSI enables the reconstruction of non-linear displacements by the non-parametric approach and the expansion of applications to measure surface displacements that could not be measured due to the limitations of the traditional PSI methods. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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17 pages, 9230 KiB

Open AccessArticle

Ground Deformations Controlled by Hidden Faults: Multi-Frequency and Multitemporal InSAR Techniques for Urban Hazard Monitoring

by Federica Murgia, Christian Bignami, Carlo Alberto Brunori, Cristiano Tolomei and Luca Pizzimenti

Remote Sens. 2019, 11(19), 2246; https://doi.org/10.3390/rs11192246 - 26 Sep 2019

Cited by 9 | Viewed by 3007

Abstract

This work focuses on the study of land subsidence processes by means of multi-temporal and multi-frequency InSAR techniques. Specifically, we retrieve the long-term evolution (2003–2018) of the creeping phenomenon producing ground fissuring in the Ciudad Guzmán (Jalisco state, Mexico) urban area. The city is located on the northern side of the Volcan de Colima area, one of the most active Mexican volcanoes. On September 21 2012, Ciudad Guzmán was struck by ground fissures of about 1.5 km of length, causing the deformation of the roads and the propagation of fissures in adjacent buildings. The field surveys showed that fissures follow the escarpments produced during the central Mexico September 19 1985 Mw 8.1 earthquake. We extended the SAR (Synthetic Aperture Radar) interferometric monitoring starting with the multi-temporal analysis of ENVISAT and COSMO-SkyMed datasets, allowing the monitoring of the observed subsidence phenomena affecting the Mexican city. We processed a new stack of Sentinel-1 TOPSAR acquisition mode images along both descending and ascending paths and spanning the 2016–2018 temporal period. The resulting long-term trend observed by satellites, together with data from volcanic bulletin and in situ surveys, seems to suggest that the subsidence is due to the exploitation of the aquifers and that the spatial arrangement of ground deformation is controlled by the position of buried faults. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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27 pages, 5753 KiB

Open AccessArticle

Ground Subsidence Susceptibility (GSS) Mapping in Grosseto Plain (Tuscany, Italy) Based on Satellite InSAR Data Using Frequency Ratio and Fuzzy Logic

by Silvia Bianchini, Lorenzo Solari, Matteo Del Soldato, Federico Raspini, Roberto Montalti, Andrea Ciampalini and Nicola Casagli

Remote Sens. 2019, 11(17), 2015; https://doi.org/10.3390/rs11172015 - 27 Aug 2019

Cited by 39 | Viewed by 5772

Abstract

This study aimed at evaluating and mapping Ground Subsidence Susceptibility (GSS) in the Grosseto plain (Tuscany Region, Italy) by exploiting multi-temporal satellite InSAR data and by applying two parallel approaches; a bivariate statistical analysis (Frequency Ratio) and a mathematical probabilistic model (Fuzzy Logic operator). The Grosseto plain experienced subsidence and sinkholes due to natural causes in the past and it is still suffering slow-moving ground lowering. Five conditioning subsidence-related factors were selected and managed in a GIS environment through an overlay pixel-by-pixel analysis. Firstly, multi-temporal ground subsidence inventory maps were prepared in the study area by starting from two inventories referred to distinct temporal intervals (2003–2009 and 2014–2019) derived from Persistent Scatterers Interferometry (PSI) data of ENVISAT and SENTINEL-1 satellites. Then, the susceptibility modelling was performed through the Frequency Ratio (FR) and Fuzzy Logic (FL) approaches. These analyses led to slightly different scenarios which were compared and discussed. Results show that flat areas on alluvial and colluvial deposits with thick sedimentary cover (higher than 20 m) on the bedrock in the central and eastern sectors of the plain are the most susceptible to land subsidence. The obtained FR- and FL-based GSS maps were finally validated with a ROC (Receiver Operating Characteristic) analysis, in order to estimate the overall performance of the models. The AUC (Area Under Curve) values of ROC analysis of the FR model were higher than the ones of FL model, suggesting that the former is a better and more appropriate predictor for subsidence susceptibility analysis in the study area. In conclusion, GSS maps provided a qualitative overview of the subsidence scenarios and may be helpful to predict and preliminarily identify high-risk areas for environmental local authorities and decision makers in charge of land use planning in the study area. Finally, the presented methodologies to derive GSS maps are easily reproducible and could also be applied and tested in other test sites worldwide, in order to check the modeling performance in different environmental settings. Full article

(This article belongs to the Special Issue Earth Observations for Land Subsidence Identification, Monitoring and Their Contribute to Modeling)

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