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Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 34255

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Special Issue Editors

Dr. Massimo Fabris

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Guest Editor

Department of Civil, Environmental and Architectural Engineering-ICEA, University of Padova, 35122 Padova, Italy
Interests: geomatics; digital aerial photogrammetry; digital surface models; deformations monitoring; 3D surveys; land subsidence
Special Issues, Collections and Topics in MDPI journals

Dr. Mario Floris

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Guest Editor

Department of Geosciences, University of Padua, 35122 Padua, Italy
Interests: rainfall-induced landslides; GIS-based landslide hazard assessment; SAR interferometry applied to landslides and subsidence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ground deformation represents a growing problem that affects hundreds of millions of people worldwide. The surface changes due to landslides, volcanic activities, land subsidence, etc., can lead to structural damage of buildings and infrastructures, loss of extensive agricultural and/or natural areas, the rise of salt wedges, and the regression of coastlines, and can have a significant economic and social impact. This negative impact can be further aggravated by climate change events (e.g., sea level rise, modifications in rainfall intensity and period), particularly in low-lying coastal areas and unstable slopes.

Ground deformation monitoring plays a key role in the management of such natural hazards by providing cost-effective solutions for risk mitigation strategies.

This Special Issue of Remote Sensing is devoted to all topics related to ground (including landslides, land subsidence, coastal erosion, etc.) and structural (civil structures, e.g., buildings, bridges, dams, etc.) deformation monitoring systems using remote sensing techniques (in particular, but not limited, to InSAR) complemented with ground-based data (e.g., GNSS, precise leveling, structure from motion photogrammetry, terrestrial laser scanning), including measurements from airplanes, helicopters, and drones. This Special Issue aims to collection original contributions on this topic, focusing on both methodological aspects (including theoretical studies) and applications. The applications can concern any sector, from the natural environment (e.g., landslides, morphological changes of an area, etc.) to urban areas and structures (e.g., single buildings, old towns, bridges, dams, etc.), performed for various motivations (e.g., risk assessment, study of the state of health of a structure, cultural heritage safeguard, etc.).

Contributions in which remote sensing data are used in conjunction with data provided by other techniques to improve data quality (precision, costs and times of survey and data processing) are welcome. Papers discussing theoretical models, the results obtained from monitoring activities, the evolution in space and time of deformation processes, are also welcome. We particularly encourage the submission of manuscripts presenting new and/or innovative applications of remote sensing techniques for the monitoring and quantification of ground and structural deformations.

Prof. Dr. Massimo Fabris
Prof. Dr. Mario Floris
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

Landslides, land subsidence, volcanic deformations, coastal modifications
Climate change impact
Ground and structural deformations monitoring
Remote sensing monitoring techniques (InSAR)
Ground-based data (GNSS, leveling, SfM photogrammetry, TLS)
Time series analysis
Integrated monitoring systems

Published Papers (13 papers)

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Editorial

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6 pages, 211 KiB

Open AccessEditorial

Editorial for Special Issue “Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data”

by Massimo Fabris and Mario Floris

Remote Sens. 2023, 15(12), 3013; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15123013 - 09 Jun 2023

Viewed by 709

Abstract

Ground deformations due to landslides [...] Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

Research

Jump to: Editorial

16 pages, 6951 KiB

Open AccessArticle

Satellite SAR Interferometry and On-Site Traditional SHM to Monitor the Post-Earthquake Behavior of the Civic Tower in L’Aquila (Abruzzo Region, Italy)

by Amedeo Caprino, Silvia Puliero, Filippo Lorenzoni, Mario Floris and Francesca da Porto

Remote Sens. 2023, 15(6), 1587; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15061587 - 14 Mar 2023

Cited by 2 | Viewed by 1561

Abstract

Structural Health Monitoring (SHM) represents a very powerful tool to assess the health condition of buildings. In recent years, the growing availability of high-resolution SAR satellite images has made possible the application of multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques for structural monitoring purposes, with high precision, low costs, timesaving, and the possibility to investigate wide areas. However, a comprehensive validation of the effectiveness of MT-InSAR in this application field has not been achieved yet. For this reason, in this paper a comparison between interferometric data and on-site measurement of displacements is proposed. The application case study is the Civic Tower of the city of L’Aquila (Abruzzo Region, Italy). After the seismic events that affected the area in 2009, an on-site monitoring system was installed on the tower to detect any changes in the damage pattern in the period 2010–2013. Furthermore, images acquired by COSMO-SkyMed constellation in Stripmap mode (~3 m resolution) during the same period were processed by the Permanent Scatterer-InSAR (PSI) technique to estimate the deformation of the structure and the surrounding area. The obtained results indicate that both methods are consistent in the measurement of displacement trends of the building and a slight rotation/displacement of the tower was detected. Such evidence highlights both the huge potential and the limitations of using InSAR techniques for SHM. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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21 pages, 8080 KiB

Open AccessEditor’s ChoiceArticle

Remote Sensing Monitoring of the Pietrafitta Earth Flows in Southern Italy: An Integrated Approach Based on Multi-Sensor Data

by Davide Mazza, Antonio Cosentino, Saverio Romeo, Paolo Mazzanti, Francesco M. Guadagno and Paola Revellino

Remote Sens. 2023, 15(4), 1138; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15041138 - 19 Feb 2023

Cited by 5 | Viewed by 1906

Abstract

Earth flows are complex gravitational events characterised by a heterogeneous displacement pattern in terms of scale, style, and orientation. As a result, their monitoring, for both knowledge and emergency purposes, represents a relevant challenge in the field of engineering geology. This paper aims to assess the capabilities, peculiarities, and limitations of different remote sensing monitoring techniques through their application to the Pietrafitta earth flow (Southern Italy). The research compared and combined data collected during the main landslide reactivations by different ground-based remote sensors such as Robotic Total Station (R-TS), Terrestrial Synthetic Aperture Radar Interferometry (T-InSAR), and Terrestrial Laser Scanner (TLS), with data being derived by satellite-based Digital Image Correlation (DIC) analysis. The comparison between R-TS and T-InSAR measurements showed that, despite their different spatial and temporal resolutions, the observed deformation trends remain approximately coherent. On the other hand, DIC analysis was able to detect a kinematic process, such as the expansion of the landslide channel, which was not detected by the other techniques used. The results suggest that, when faced with complex events, the use of a single monitoring technique may not be enough to fully observe and understand the processes taking place. Therefore, the limitations of each different technique alone can be solved by a multi-sensor monitoring approach. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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19 pages, 7694 KiB

Open AccessArticle

Study on the Development Law of Mining-Induced Ground Cracks under Gully Terrain

by Yanjun Zhang, Xugang Lian, Yueguan Yan, Yuanhao Zhu and Huayang Dai

Remote Sens. 2022, 14(23), 5985; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14235985 - 25 Nov 2022

Cited by 4 | Viewed by 1225

Abstract

Coal seam mining in the gully area easily causes ground cracks and even induces landslides, which endanger the safety of mining areas. In this paper, combined with the mining conditions of a mining area in southern Shanxi Province, China, ground crack mapping, crack width dynamic monitoring, and the numerical simulation method are used to study the static and dynamic evolution law and the formation mechanism of ground cracks in the gully area. The research shows that ground cracks mainly include dynamic in-plane cracks and boundary cracks. The dynamic in-plane cracks show the characteristics of “opening first and closing later”. The boundary cracks show the characteristics of “only opening and not closing”. It is found that the closure of the dynamic in-plane cracks will decrease (compared with plain areas). The development of ground cracks experiences three stages: the initial formation stage, the dynamic development stage, and the gradually stable stage. The “goaf–surface” structure model and force chain arch structure model are established to more intuitively analyze the formation mechanism of ground cracks. The research results have a specific reference value for preventing ground disasters caused by underground coal mining and land ecological restoration. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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14 pages, 2498 KiB

Open AccessArticle

M_split Estimation Approach to Modeling Vertical Terrain Displacement from TLS Data Disturbed by Outliers

by Robert Duchnowski and Patrycja Wyszkowska

Remote Sens. 2022, 14(21), 5620; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14215620 - 07 Nov 2022

Cited by 2 | Viewed by 966

Abstract

Terrestrial laser scanning (TLS) is a modern measurement technique that provides a point cloud in a relatively short time. TLS data are usually processed using different methods in order to obtain the final result (infrastructure or terrain models). M_split estimation is a modern method successfully applied for such a purpose. This paper addresses the possible application of the method in processing TLS data from two different epochs to model a vertical displacement of terrain resulting, for example, from landslides or mining damages. M_split estimation can be performed in two variants (the squared or absolute method) and two scenarios (two point clouds or one combined point cloud). One should understand that point clouds usually contain outliers of different origins. Therefore, this paper considers the contamination of TLS data by positive or/and negative outliers. The results based on simulated data prove that absolute M_split estimation provides better results and overperforms conventional estimation methods (least-squares or robust M-estimation). In practice, the processing of point clouds separately seems to be a better option. This paper proved that M_split estimation is a compelling alternative to conventional methods, as it can be applied to process TLS data disturbed by outliers of different types. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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21 pages, 5977 KiB

Open AccessArticle

An Integrated InSAR and GNSS Approach to Monitor Land Subsidence in the Po River Delta (Italy)

by Massimo Fabris, Mattia Battaglia, Xue Chen, Andrea Menin, Michele Monego and Mario Floris

Remote Sens. 2022, 14(21), 5578; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14215578 - 04 Nov 2022

Cited by 10 | Viewed by 2932

Abstract

Land subsidence affects many areas of the world, posing a serious threat to human structures and infrastructures. It can be effectively monitored using ground-based and remote sensing techniques, such as the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). GNSS provides high precision measurements, but in a limited number of points, and is time-consuming, while InSAR allows one to obtain a very large number of measurement points, but only in areas characterized by a high and constant reflectivity of the signal. The aim of this work is to propose an approach to combine the two techniques, overcoming the limits of each of them. The approach was applied in the Po River Delta (PRD), an area located in Northern Italy and historically affected by land subsidence. Ground-based GNSS data from three continuous stations (CGNSS) and 46 non-permanent sites (NPS) measured in 2016, 2018, and 2020, and Sentinel-1 and COSMO-SkyMed SAR data acquired from 2016 to 2020, were considered. In the first phase of the method, InSAR processing was calibrated and verified through CGNSS measurements; subsequently, the calibrated interferometric data were used to validate the GNSS measurements of the NPS. In the second phase, the datasets were integrated to provide an efficient monitoring system, extracting high-resolution deformation maps. The results showed a good agreement between the different sources of data, a high correlation between the displacement rate and the age of the emerged surfaces composed of unconsolidated fine sediments, and high land subsidence rates along the coastal area (up to 16–18 mm/year), where the most recent deposits outcrop. The proposed approach makes it possible to overcome the disadvantages of each technique by providing more complete and detailed information for a better understanding of the ongoing phenomenon. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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14 pages, 5235 KiB

Open AccessArticle

Surface Subsidence Monitoring Induced by Underground Coal Mining by Combining DInSAR and UAV Photogrammetry

by Yafei Zhang, Xugang Lian, Linlin Ge, Xiaoyu Liu, Zheyuan Du, Wenfu Yang, Yanru Wu, Haifeng Hu and Yinfei Cai

Remote Sens. 2022, 14(19), 4711; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14194711 - 21 Sep 2022

Cited by 10 | Viewed by 2156

Abstract

Surface subsidence caused by coal mining has become an important factor that affects and restricts the sustainable development of mining districts. It is necessary to use appropriate methods for effective subsidence monitoring. It is hard to monitor large gradient ground deformations with a high accuracy by using differential interferometric synthetic aperture radar (DInSAR) technology. Unmanned aerial vehicle (UAV) photogrammetry is limited in that it monitors the basin edge by subtracting two DEMs (digital elevation models). Therefore, in this paper we propose a combination of DInSAR and UAV photogrammetry to complement the two data advantages and to achieve a high-precision monitoring of mining subsidence areas. The subsidence of coal panel 81,403 in the Yangquan coal mine was obtained using DInSAR and UAV photogrammetry technologies. The appropriate fusion points were selected for the two datasets and the agreement between the fusion data and the leveling data was verified. The results indicated that the combination of DInSAR and UAV technology could monitor the settlement more accurately than the single use of DInSAR or UAV technology. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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18 pages, 18039 KiB

Open AccessArticle

Surface Deformation Analysis of the Houston Area Using Time Series Interferometry and Emerging Hot Spot Analysis

by Shuhab D. Khan, Otto C. A. Gadea, Alyssa Tello Alvarado and Osman A. Tirmizi

Remote Sens. 2022, 14(15), 3831; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14153831 - 08 Aug 2022

Cited by 14 | Viewed by 9250

Abstract

Cities in the northern Gulf of Mexico, such as Houston, have experienced one of the fastest rates of subsidence, with groundwater/hydrocarbon withdrawal being considered the primary cause. This work reports substantial ground subsidence in a few parts of Greater Houston and adjoining areas not reported before. Observation of surface deformation using interferometric synthetic aperture radar (InSAR) data obtained from Sentinel-1A shows total subsidence of up to 9 cm in some areas from 2016 to 2020. Most of the area within the Houston city limits shows no substantial subsidence, but growing suburbs around the city, such as Katy in the west, Spring and The Woodlands in the north and northwest, and Fresno in the south, show subsidence. In this study, we performed emerging hot spot analysis on InSAR displacement products to identify areas undergoing significant subsidence. To investigate the contributions of groundwater to subsidence, we apply optimized hot spot analysis to groundwater level data collected over the past 31 years from over 71,000 water wells and look at the correlation with fault surface deformation patterns. To evaluate the contribution of oil/gas pumping, we applied optimized hot spot analysis to known locations of oil and gas wells. The high rate of water pumping in the suburbs is the main driver of subsidence, but oil/gas withdrawal plays an important role in areas such as Mont Belvieu. Displacement time series shows that the Clodine, Hockley, and Woodgate faults are active, whereas the Long Point Fault shows no motion, although it was once very active. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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19 pages, 7163 KiB

Open AccessArticle

Recognition of Landslide Triggering Mechanisms and Dynamics Using GNSS, UAV Photogrammetry and In Situ Monitoring Data

by Tina Peternel, Mitja Janža, Ela Šegina, Nejc Bezak and Matej Maček

Remote Sens. 2022, 14(14), 3277; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14143277 - 07 Jul 2022

Cited by 11 | Viewed by 2025

Abstract

Detecting the mechanism of landslides and evaluating their dynamics is challenging, especially concerning composite landslides. For this purpose, several investigation and monitoring techniques should be implemented to obtain reliable information on landslide characteristics (e.g., geological and hydrogeological conditions and type of landslide processes), kinematics (displacement rate), and potential triggering mechanisms (e.g., change in groundwater table and precipitation). The Urbas landslide in northwest Slovenia has been studied for decades through geological, geotechnical, geodetic, and remote sensing investigations. However, due to the complexity of the landslide and the short duration of continuous monitoring, no assessment of its dynamics has been made. To meet this need, this study analysed continuous and periodic monitoring of landslide displacements using data from the global navigation satellite system (GNSS), a wire extensometer, unmanned aerial vehicle (UAV) photogrammetry, and hydrometeorological sensing (groundwater table, precipitation). The results of this study show that the dynamics of the Urbas landslide differ along the landslide area, depending on local geological and hydrogeological conditions. Consequently, certain parts of the landslide are at different evolutionary states and respond differently to the same external triggers. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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14 pages, 7560 KiB

Open AccessArticle

Evaluation of Tidal Effect in Long-Strip DInSAR Measurements Based on GPS Network and Tidal Models

by Wei Peng, Qijie Wang, Yunmeng Cao, Xuemin Xing and Wenjie Hu

Remote Sens. 2022, 14(12), 2954; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14122954 - 20 Jun 2022

Cited by 2 | Viewed by 1644

Abstract

A long-strip differential interferometric synthetic aperture radar (DInSAR) measurement based on multi-frame image mosaicking is currently the realizable approach to measure large-scale ground deformation. As the spatial range of the mosaicked images increases, the nonlinear variation of ground ocean tidal loading (OTL) displacements is more significant, and using plane fitting to remove the large-scale errors will produce large tidal displacement residuals in a region with a complex coastline. To conveniently evaluate the ground tidal effect on mosaic DInSAR interferograms along the west coast of the U.S., a three-dimensional ground OTL displacements grid is generated by integrating tidal constituents’ estimation of the GPS reference station network and global/regional ocean tidal models. Meanwhile, a solid earth tide (SET) model based on IERS conventions is used to estimate the high-precision SET displacements. Experimental results show that the OTL and SET in a long-strip interferogram can reach 77.5 mm, which corresponds to a 19.3% displacement component. Furthermore, the traditional bilinear ramp fitting methods will cause 7.2~20.3 mm residual tidal displacement in the mosaicked interferograms, and the integrated tidal constituents displacements calculation method can accurately eliminate the tendency of tidal displacement in the long-strip interferograms. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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30 pages, 18192 KiB

Open AccessArticle

A New Deep Learning Neural Network Model for the Identification of InSAR Anomalous Deformation Areas

by Tian Zhang, Wanchang Zhang, Dan Cao, Yaning Yi and Xuan Wu

Remote Sens. 2022, 14(11), 2690; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14112690 - 03 Jun 2022

Cited by 7 | Viewed by 2513

Abstract

The identification and early warning of potential landslides can effectively reduce the number of casualties and the amount of property loss. At present, interferometric synthetic aperture radar (InSAR) is considered one of the mainstream methods for the large-scale identification and detection of potential landslides, and it can obtain long-term time-series surface deformation data. However, the method of identifying anomalous deformation areas using InSAR data is still mainly manual delineation, which is time-consuming, labor-consuming, and has no generally accepted criterion. In this study, a two-stage detection deep learning network (InSARNet) is proposed and used to detect anomalous deformation areas in Maoxian County, Sichuan Province. Compared with the most commonly used detection models, it is demonstrated that the InSARNet has a better performance in the detection of anomalous deformation in mountainous areas, and all of the quantitative evaluation indexes are higher for InSARNet than for the other models. After the anomalous deformation areas are identified using the proposed model, the possible relationship between the anomalous deformation areas and potential landslides is investigated. Finally, the fact that the automatic and rapid identification of potential landslides is the inevitable trend of future development is discussed. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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29 pages, 57631 KiB

Open AccessArticle

Analysis of the Periodic Component of Vertical Land Motion in the Po Delta (Northern Italy) by GNSS and Hydrological Data

by Eleonora Vitagliano, Enza Vitale, Giacomo Russo, Leonardo Piccinini, Massimo Fabris, Domenico Calcaterra and Rosa Di Maio

Remote Sens. 2022, 14(5), 1126; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14051126 - 24 Feb 2022

Cited by 3 | Viewed by 1884

Abstract

Nowadays, several methodologies, implemented for satellite or terrestrial surveys, reveal that daily and weekly site-positioning time series can exhibit linear trends plus seasonal oscillations. Such periodic components affect the evaluation of subsidence rates and, thus, they must be recognized and properly modelled. In this work, the periodic component of vertical land motion in Po Delta (Northern Italy) is estimated by a multi-component and multi-source procedure recently proposed by some of the authors for studying land subsidence in delta areas. First, land vertical motion data, acquired in the central part of the Po Delta over a six-year time interval, were compared with hydro-meteorological and climate datasets collected from nineteen stations distributed over the entire Delta. Then, four physically based models of the test site were implemented to verify the water pressure- and water mass-dependent processes inferred from the analytical phase. Modelling results show that the annual ground oscillation is better explained by soil moisture change, although river water mass variation gives a relevant contribution to land deformation, especially in the wet periods. Finally, to account for intra-annual processes, the joint contributions of all the inferred sources were treated as a nonlinear problem and solved applying the generalized reduced gradient method. The obtained combination is well supported by statistical parameters and provides the best agreement with the geodetic observations. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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15 pages, 21822 KiB

Open AccessArticle

Multitemporal and Multisensor InSAR Analysis for Ground Displacement Field Assessment at Ischia Volcanic Island (Italy)

by Lisa Beccaro, Cristiano Tolomei, Roberto Gianardi, Vincenzo Sepe, Marina Bisson, Laura Colini, Riccardo De Ritis and Claudia Spinetti

Remote Sens. 2021, 13(21), 4253; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13214253 - 22 Oct 2021

Cited by 11 | Viewed by 3568

Abstract

Volcanic islands are often affected by ground displacement such as slope instability, due to their peculiar morphology. This is the case of Ischia Island (Naples, Italy) dominated by the Mt. Epomeo (787 m a.s.l.), a volcano-tectonic horst located in the central portion of the island. This study aims to follow a long temporal evolution of ground deformations on the island through the interferometric analysis of satellite SAR data. Different datasets, acquired during Envisat, COSMO-SkyMed and Sentinel-1 satellite missions, are for the first time processed in order to obtain the island ground deformations during a time interval spanning 17 years, from November 2002 to December 2019. In detail, the multitemporal differential interferometry technique, named small baseline subset, is applied to produce the ground displacement maps and the associated displacement time series. The results, validated through the analysis and the comparison with a set of GPS measurements, show that the northwestern side of Mt. Epomeo is the sector of the island characterized by the highest subsidence movements (maximum vertical displacement of 218 mm) with velocities ranging from 10 to 20 mm/yr. Finally, the displacement time series allow us to correlate the measured ground deformations with the seismic swarm started with the Mw 3.9 earthquake that occurred on 21 August 2017. Such correlations highlight an acceleration of the ground, following the mainshock, characterized by a subsidence displacement rate of 0.12 mm/day that returned to pre-earthquake levels (0.03 mm/day) after 6 months from the event. Full article

(This article belongs to the Special Issue Ground and Structural Deformations Monitoring Systems Integrating Remote Sensing and Ground-Based Data)

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