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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 74195

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Special Issue Editors

Prof. Dr. Kristy Tiampo

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Guest Editor

Cooperative Institute for Research in Environmental Sciences (CIRES) and Department of Geological Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
Interests: satellite remote sensing; SAR interferometry; InSAR and GNSS data analysis; optical data analysis; natural and anthropogenic hazard characterization and modeling
Special Issues, Collections and Topics in MDPI journals

Dr. Eric Hetland

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Guest Editor

Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48109, USA
Interests: earthquake and interseismic deformation; evolution of crustal temperatures in volcanic regions; InSAR time series; time-dependent strain rate estimation from GNSS data; cycling of seismogenic stresses

Dr. Nicolas D'Oreye

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Guest Editor

European Center for Geodynamics and Seismology, Rue Josy Welter, 19, L-7256 Walferdange, Luxembourg
Interests: SAR; SAR interferometry; InSAR; InSAR time series; GNSS, instrumentation; crustal deformations; volcanology; tectonics

Special Issue Information

Dear Colleagues,

The past twenty-five years have seen InSAR progress, from its initial development as a new and pioneering remote sensing tool for measuring Earth topography and surface deformation, to a mature technology that now provides crucial constraints on a broad and diverse range of Earth science processes. While its extensive use for mapping ground deformation with high spatial resolution and sub-centimeter precision over large areas makes it ideal for studying natural and anthropogenic hazards, such as landslides, subsidence, volcanic unrest, and earthquake processes, it also has had important impacts in environmental and land surface studies. These latter studies include, but are not limited to, applications in the fields of glaciology (e.g., ice dynamics), oceanography (e.g., wave dynamics), hydrology (e.g., flood inundation), and geomorphology (e.g., sediment erosion and deposition).

For this Special Issue, we invite contributions that illuminate the advances in SAR technology, processing and analysis, including modelling studies that have contributed to the expansion in InSAR applications for Earth observation and study. The primary goal of the Special Issue is to present overviews of both the state-of-the-art of SAR and the next generation of applications across the broad range of InSAR Earth science applications. Papers that address the expanding depth of SAR databases, the increase in resolution (both in time and space), and the growth of the number of SAR sensors orbiting the Earth are of particular interest. We welcome submissions from all areas of Earth sciences that might include, but are not limited to, techniques that take advantage of the recent and upcoming SAR satellite acquisitions, develop advanced methods for improving ionospheric and/or atmospheric artefact corrections, present innovative methods for unwrapping, investigate specific methods such as multichromatic interferometry, or investigate methods for assimilating and optimizing the associated large quantities of data and quantifying the associated error, or describe algorithms for integrating various types of satellite observations.

Dr. Kristy Tiampo
Dr. Eric Hetland
Dr. Nicolas D'Oreye
Guest Editors

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Keywords

SAR
InSAR processing
remote sensing
environmental science
hydrology
tectonics
cryosphere
glaciology
anthropogenic and natural hazards
land surface change
ocean surface processes

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30 pages, 11165 KiB

Open AccessArticle

Assessment of Mitigation Strategies for Tropospheric Phase Contributions to InSAR Time-Series Datasets over Two Nicaraguan Volcanoes

by Kirsten J. Stephens, Christelle Wauthier, Rebecca C. Bussard, Machel Higgins and Peter C. LaFemina

Remote Sens. 2020, 12(5), 782; https://doi.org/10.3390/rs12050782 - 1 Mar 2020

Cited by 17 | Viewed by 4034

Abstract

Interferometric Synthetic Aperture Radar (InSAR) studies of ground displacement are often plagued by tropospheric artifacts, which are phase delays resulting from spatiotemporal variations in the refractivity of air within the troposphere. In this study, we focus on COSMO-SkyMed (X-band) InSAR products obtained over two different types of volcanoes in Nicaragua: the Telica stratovolcano and the Masaya caldera. We examine the applicability of an empirical linear correction method and three Global Weather Models (GWMs) with different spatial and temporal resolutions for removing the tropospheric phase component. We linearly invert the tropospheric-corrected interferograms using the Small BAseline Subset (SBAS) time-series technique to produce time-series of ground displacement. Statistical assessments were performed on the corrected interferograms to examine the significance of the applied corrections on the individual interferograms and time-series results. We find that the applicability of the correction methods is highly case-dependent and that in general, the temporal resolution of GWMs influences their ability to capture turbulent tropospheric phase delays. At the two target volcanoes, our study shows that none of the GWMs are able to accurately capture the tropospheric phase delays. Our study provides a guide for researchers using InSAR data in tropical regions who wish to use tropospheric model corrections to carefully assess the applicability of the different types of tropospheric correction methods. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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20 pages, 37294 KiB

Open AccessArticle

Application of DInSAR-PSI Technology for Deformation Monitoring of the Mosul Dam, Iraq

by Arsalan Ahmed Othman, Ahmed F. Al- Maamar, Diary Ali Mohammed Al-Manmi, Veraldo Liesenberg, Syed E. Hasan, Younus I. Al-Saady, Ahmed T. Shihab and Kareem Khwedim

Remote Sens. 2019, 11(22), 2632; https://doi.org/10.3390/rs11222632 - 11 Nov 2019

Cited by 24 | Viewed by 5863

Abstract

On-going monitoring of deformation of dams is critical to assure their safe and efficient operation. Traditional monitoring methods, based on in-situ sensors measurements on the dam, have some limitations in spatial coverage, observation frequency, and cost. This paper describes the potential use of Synthetic Aperture Radar (SAR) scenes from Sentinel-1A for characterizing deformations at the Mosul Dam (MD) in NW Iraq. Seventy-eight Single Look Complex (SLC) scenes in ascending geometry from the Sentinel-1A scenes, acquired from 03 October 2014 to 27 June 2019, and 96 points within the MD structure, were selected to determine the deformation rate using persistent scatterer interferometry (PSI). Maximum deformation velocity was found to be about 7.4 mm·yr⁻¹ at a longitudinal subsidence area extending over a length of 222 m along the dam axis. The mean subsidence velocity in this area is about 6.27 mm·yr⁻¹ and lies in the center of MD. Subsidence rate shows an inverse relationship with the reservoir water level. It also shows a strong correlation with grouting episodes. Variations in the deformation rate within the same year are most probably due to increased hydrostatic stress which was caused by water storage in the dam that resulted in an increase in solubility of gypsum beds, creating voids and localized collapses underneath the dam. PSI information derived from Sentinel-1A proved to be a good tool for monitoring dam deformation with good accuracy, yielding results that can be used in engineering applications and also risk management. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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26 pages, 23984 KiB

Open AccessArticle

Combining InSAR and GNSS to Track Magma Transport at Basaltic Volcanoes

by Delphine Smittarello, Valérie Cayol, Virginie Pinel, Jean-Luc Froger, Aline Peltier and Quentin Dumont

Remote Sens. 2019, 11(19), 2236; https://doi.org/10.3390/rs11192236 - 25 Sep 2019

Cited by 6 | Viewed by 4172

Abstract

The added value of combining InSAR and GNSS data, characterized by good spatial coverage and high temporal resolution, respectively, is evaluated based on a specific event: the propagation of the magma intrusion leading to the 26 May 2016 eruption at Piton de la Fournaise volcano (Reunion Island, France). Surface displacement is a non linear function of the geometry and location of the pressurized source of unrest, so inversions use a random search, based on a neighborhood algorithm, combined with a boundary element modeling method. We first invert InSAR and GNSS data spanning the whole event (propagation phase and eruption) to determine the final geometry of the intrusion. Random search conducted in the inversion results in two best-fit model families with similar data fits. Adding the same time-period GNSS dataset to the inversions does not significantly modify the results. Even when weighting data to provide even contributions, the fit is systematically better for descending than ascending interferograms, which might indicate an eastward flank motion. Then, we invert the GNSS time series in order to derive information on the propagation dynamics, validating our approach using a SAR image acquired during the propagation phase. We show that the GNSS time series can only be used to correctly track the magma propagation when the final intrusion geometry derived from InSAR and GNSS measurements is used as an a priori. A new method to extract part of a mesh, based on the representation of meshes as graphs, better explains the data and better accounts for the opening of the eruptive fissure than a method based on the projection of a circular pressure sources. Finally, we demonstrate that the temporal inversion of GNSS data strongly favors one family of models over an other for the final intrusion, removing the ambiguity inherent in the inversion of InSAR data. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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16 pages, 9039 KiB

Open AccessArticle

Source Characteristics of the 28 September 2018 Mw 7.4 Palu, Indonesia, Earthquake Derived from the Advanced Land Observation Satellite 2 Data

by Yongzhe Wang, Wanpeng Feng, Kun Chen and Sergey Samsonov

Remote Sens. 2019, 11(17), 1999; https://doi.org/10.3390/rs11171999 - 24 Aug 2019

Cited by 17 | Viewed by 4879

Abstract

On 28 September 2018, an Mw 7.4 earthquake, followed by a tsunami, struck central Sulawesi, Indonesia. It resulted in serious damage to central Sulawesi, especially in the Palu area. Two descending paths of the Advanced Land Observation Satellite 2 (ALOS-2) synthetic aperture radar (SAR) data were processed with interferometric synthetic aperture radar (InSAR) and pixel tracking techniques to image the coseismic deformation produced by the earthquake. The deformation measurement was used to determine the fault geometry and the coseismic distributed slip model with a constrained least square algorithm based on the homogeneous elastic half-space model. We divided the fault into four segments (named AS, BS, CS and DS, from the north to the south) in the inversion. The BS segment was almost parallel to the DS segment, the CS segment linked the BS and DS segments, and these three fault segments formed a fault step-over system. The Coulomb failure stress (CFS) change on the causative fault was also calculated. Results show that the maximum SAR line-of-sight (LOS) and horizontal deformation were −1.8 m and 3.6 m, respectively. The earthquake ruptured a 210-km-long fault with variable strike angles. The ruptured pattern of the causative fault is mainly a sinistral slip. Almost-pure normal characteristics could be identified along the fault segment across the Palu bay, which could be one of the factors resulting in the tsunami. The main slip area was concentrated at the depths of 0–20 km, and the maximum slip was 3.9 m. The estimated geodetic moment of the earthquake was 1.4 × 10²⁰ Nm, equivalent to an earthquake of Mw 7.4. The CFS results demonstrate that the fault step-over of 5.3 km width did not terminate the rupture propagation of the main shock to the south. Two M>6 earthquakes (the 23 January 2005 and the 18 August 2012) decreased CFS along CS segment and the middle part of DS segment of the 2018 main shock. This implies that the stress release during the previous two earthquakes may have played a vital role in controlling the coseismic slip pattern of the 2018 earthquake. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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28 pages, 2223 KiB

Open AccessArticle

Spatio–Temporal Analysis of Deformation at San Emidio Geothermal Field, Nevada, USA Between 1992 and 2010

by Elena C. Reinisch, Michael Cardiff, John Akerley, Ian Warren and Kurt L. Feigl

Remote Sens. 2019, 11(16), 1935; https://doi.org/10.3390/rs11161935 - 19 Aug 2019

Cited by 2 | Viewed by 3187

Abstract

Although subsidence has been observed at the San Emidio geothermal field in Nevada using interferometric synthetic aperture radar since the early 1990s, the spatial extent and temporal evolution of the subsidence have not heretofore been quantified. Furthermore, the weather conditions and geographic location of San Emidio negatively affect interferometric image quality, causing low correlation amongst pairs. To address this, we introduce a new method for selecting pairs in areas of low correlation and small deformation signal using a minimum spanning tree method with a measure of image quality as the weighting criterion. We validate our pair selection approach by comparing our data products to SqueeSAR

^{TM}

data products from a previous study at San Emidio. We also develop a deformation model which characterizes the spatial extent of subsidence at San Emidio in terms of volume change of the reservoir. After applying this deformation model to our data set of interferometric pairs, we examine the temporal relationship of the observed deformation with production and injection operations associated with geothermal power production. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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17 pages, 4790 KiB

Open AccessArticle

Ground Deformation Analysis of Bolvadin (W. Turkey) by Means of Multi-Temporal InSAR Techniques and Sentinel-1 Data

by Mumin Imamoglu, Fatih Kahraman, Ziyadin Cakir and Fusun Balik Sanli

Remote Sens. 2019, 11(9), 1069; https://doi.org/10.3390/rs11091069 - 6 May 2019

Cited by 47 | Viewed by 6178

Abstract

Surface deformations were observed in Bolvadin, located in the province of Afyon (western Turkey) in the last decade which occurred without any destructive earthquakes. In this study, ground deformation of the Bolvadin region is analyzed by means of multi-temporal interferometric synthetic aperture radar (InSAR) technique with Sentinel-1 synthetic aperture radar (SAR) data. Sentinel-1 data acquired in ascending and descending orbits between October 2014 and October 2018 are processed with the Sentinel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS) open source software tools. Deformation velocity maps and line-of-sight (LOS) displacement time series are produced and compared with geology, groundwater level and the water surface area of Eber Lake nearby. Deformation velocity maps reveal significant subsidence in most of the town and surrounding regions, which is confirmed by field observations that show severe damage to the settlements and infrastructure of the town. The most severe subsidence is observed to be in the southern part of Bolvadin with rates up to 35 mm/year, which is characterized by the presence of soft alluvial deposits. Composed of slope debris/talus and conglomerate, the northeastern part of the deforming region experiences a relatively lower rate of subsidence. A strong correlation between LOS displacement time series and groundwater level exists both in the short and long term. Moreover, short term variations in LOS displacement time series also show high similarity with seasonal variations in the water surface area of Eber Lake located a few km southeast of the town. We conclude that the primary cause of subsidence is most probably the overexploitation of groundwater and hydrological changes because of (1) the strong correlation of subsidence with lithological units, (2) the similarity between deformation rate and groundwater level changes, (3) the correspondence of seasonal variations in water surface area and short-term deformation rate oscillations, and (4) the absence of InSAR velocity contrast across the active faults. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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21 pages, 29399 KiB

Open AccessArticle

Estimation of Tropospheric and Ionospheric Delay in DInSAR Calculations: Case Study of Areas Showing (Natural and Induced) Seismic Activity

by Wojciech Milczarek, Anna Kopeć and Dariusz Głąbicki

Remote Sens. 2019, 11(6), 621; https://doi.org/10.3390/rs11060621 - 14 Mar 2019

Cited by 12 | Viewed by 5095

Abstract

The article presents a proposal to make simultaneous allowance for both ionospheric and tropospheric corrections in differential synthetic aperture radar interferometry (DInSAR) measurements. Atmospheric delay in the interferometric phase may cause the detection of terrain-surface changes to be impossible or significantly distorted. This fact remains of special importance in the case of surface changes that show limited amplitude and spatial range. Two areas were chosen to verify the validity of the proposed solution. The first area includes terrains affected by underground copper-ore mining activity (Poland), which shows high induced seismic activity. Mining tremors recorded in this area cause the terrain surface to locally subside. The authors analyzed three tremors that were recorded in 2016, 2017, and 2019. Each of the tremors exceeded a magnitude of Mw 4.0. The second area is located in the coastal region of Chile, in the Cardenal Caro province. In this case, the authors focused on a series of three earthquakes recorded on 11 March 2010. The strongest of the earthquakes was of Mw 7.0 magnitude. In the first case, calculations were based on obtained data from the Sentinel 1 satellites, and in the second case from the ALOS-1 satellite. It is demonstrated that simultaneous allowance for both the tropospheric and ionospheric corrections significantly improves the final results. The authors were also able to use the analyzed cases to demonstrate that implementation of the corrections does not have negative influence on the range and magnitude of local ground-surface deformations. At the same time, such implementation minimizes local displacement fluctuations and reduces displacement values in areas affected by deformations. The examples used in the article served to show that tropospheric correction is mainly responsible for global corrections (i.e., within the whole analyzed spatial range), while ionospheric correction reduces local fluctuations. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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21 pages, 6405 KiB

Open AccessArticle

Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion

by Thomas Fuhrmann and Matthew C. Garthwaite

Remote Sens. 2019, 11(3), 241; https://doi.org/10.3390/rs11030241 - 24 Jan 2019

Cited by 168 | Viewed by 16721

Abstract

Interferometric synthetic aperture radar (InSAR) technology has been widely applied to measure Earth surface motions related to natural and anthropogenic crustal deformation phenomena. With the widespread uptake of data captured by the European Space Agency’s Sentinel-1 mission and other recently launched or planned space-borne SAR missions, the usage of the InSAR technique to detect and monitor Earth surface displacements will increase even more in the coming years. However, InSAR can only measure a one-dimensional motion along the radar line of sight (LOS), which makes interpretation and communication of InSAR measurements challenging, and can add ambiguity to the modelling process. Within this paper, we investigate the implications of the InSAR LOS geometry using simulated and observed deformation phenomena and describe a methodology for multi-geometry data fusion of LOS InSAR measurements from many viewing geometries. We find that projecting LOS measurements to the vertical direction using the incidence angle of the satellite sensor (and implicitly assuming no horizontal motions are present) may result in large errors depending on the magnitude of horizontal motion and on the steepness of the incidence angle. We quantify these errors as the maximum expected error from simulated LOS observations based on a Mogi deformation model. However, we recommend to use LOS observations from several image geometries wherever data are available, in order to solve for vertical and E–W oriented horizontal motion. For an anthropogenic deformation phenomenon observed in seven independent InSAR analyses of Envisat SAR data from the Sydney region, Australia, we find that the strong horizontal motion present could lead to misinterpretation of the actual motion direction when projecting LOS measurements to vertical (uplift instead of subsidence). In this example, the difference between multi-geometry data fusion and vertical projection of LOS measurements (at an incidence angle of 33.8°) reach up to 67% of the maximum vertical displacement rate. Furthermore, the position of maximum vertical motion is displaced horizontally by several hundred metres when the LOS measurements are projected. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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19 pages, 6951 KiB

Open AccessArticle

Sentinel-1 and Ground-Based Sensors for Continuous Monitoring of the Corvara Landslide (South Tyrol, Italy)

by Mehdi Darvishi, Romy Schlögel, Christian Kofler, Giovanni Cuozzo, Martin Rutzinger, Thomas Zieher, Isabella Toschi, Fabio Remondino, Abraham Mejia-Aguilar, Benni Thiebes and Lorenzo Bruzzone

Remote Sens. 2018, 10(11), 1781; https://doi.org/10.3390/rs10111781 - 10 Nov 2018

Cited by 25 | Viewed by 7634

Abstract

The Copernicus Sentinel-1 mission provides synthetic aperture radar (SAR) acquisitions over large areas with high temporal and spatial resolution. This new generation of satellites providing open-data products has enhanced the capabilities for continuously studying Earth surface changes. Over the past two decades, several studies have demonstrated the potential of differential synthetic aperture radar interferometry (DInSAR) for detecting and quantifying land surface deformation. DInSAR limitations and challenges are linked to the SAR properties and the field conditions (especially in mountainous environments) leading to spatial and temporal decorrelation of the SAR signal. High temporal decorrelation can be caused by changes in vegetation (particularly in nonurban areas), atmospheric conditions, or high ground surface velocity. In this study, the kinematics of the complex and vegetated Corvara landslide, situated in Val Badia (South Tyrol, Italy), are monitored by a network of three permanent and 13 monthly measured benchmark points measured with the differential global navigation satellite system (DGNSS) technique. The slope displacement rates are found to be highly unsteady and reach several meters a year. This paper focuses firstly on evaluating the performance of DInSAR changing unwrapping and coherence parameters with Sentinel-1 imagery, and secondly, on applying DInSAR with DGNSS measurements to monitor an active and complex landslide. To this end, 41 particular SAR images, coherence thresholds, and 2D and 3D unwrapping processes give various results in terms of reliability and accuracy, supporting the understanding of the landslide velocity field. Evolutions of phase changes are analysed according to the coherence, the changing field conditions, and the monitored ground-based displacements. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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14 pages, 5971 KiB

Open AccessArticle

Bias Removal for Goldstein Filtering Power Using a Second Kind Statistical Coherence Estimator

by Xin Tian, Mi Jiang, Ruya Xiao and Rakesh Malhotra

Remote Sens. 2018, 10(10), 1559; https://doi.org/10.3390/rs10101559 - 28 Sep 2018

Cited by 7 | Viewed by 3268

Abstract

The adaptive Goldstein filter driven by InSAR coherence is one of the most famous frequency domain-based filters and has been widely used to improve the quality of InSAR measurement with different noise features. However, the filtering power is biased to varying degrees due to the biased coherence estimator and empirical modelling of the filtering power under a given coherence level. This leads to under- or over-estimation of phase noise over the entire dataset. Here, the authors present a method to correct filtering power on the basis of the second kind statistical coherence estimator. In contrast with regular statistics, the new estimator has smaller bias and variance values, and therefore provides more accurate coherence observations. In addition, a piece-wise function model determined from the Monte Carlo simulation is used to compensate for the nonlinear relationship between the filtering parameter and coherence. This method was tested on both synthetic and real data sets and the results were compared against those derived from other state-of-the-art filters. The better performance of the new filter for edge preservation and residue reduction demonstrates the value of this method. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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18 pages, 17272 KiB

Open AccessArticle

Method Combining Probability Integration Model and a Small Baseline Subset for Time Series Monitoring of Mining Subsidence

by Hongdong Fan, Lu Lu and Yahui Yao

Remote Sens. 2018, 10(9), 1444; https://doi.org/10.3390/rs10091444 - 10 Sep 2018

Cited by 44 | Viewed by 4118

Abstract

Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) has high accuracy for monitoring slow surface subsidence. However, in the case of a large-scale mining subsidence areas, the monitoring capabilities of TS-InSAR are poor, owing to temporal and spatial decorrelation. To monitor mining subsidence effectively, a method known as Probability Integration Model Small Baseline Set (PIM-SBAS) was applied. In this method, mining subsidence with a large deformation gradient was simulated by a PIM. After simulated deformation was transformed into a wrapped phase, the residual wrapped phase was obtained by subtracting the simulated wrapped phase from the actual wrapped phase. SBAS was used to calculate the residual subsidence. Finally, the mining subsidence was determined by adding the simulated deformation to the residual subsidence. The time series subsidence of the Nantun mining area was derived from 10 TerraSAR-X (TSX) images for the period 25 December 2011 to 2 April 2012. The Zouji highway above the 9308 workface was the target for study. The calculated maximum mining subsidence was 860 mm. The maximum subsidence for the Zouji highway was about 145 mm. Compared with the SBAS method, PIM-SBAS alleviates the difficulty of phase unwrapping, and may be used to monitor large-scale mining subsidence. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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29 pages, 13236 KiB

Open AccessReview

The role of Interferometric Synthetic Aperture Radar in Detecting, Mapping, Monitoring, and Modelling the Volcanic Activity of Piton de la Fournaise, La Réunion: A Review

by Nicole Richter and Jean-Luc Froger

Remote Sens. 2020, 12(6), 1019; https://doi.org/10.3390/rs12061019 - 22 Mar 2020

Cited by 27 | Viewed by 6701

Abstract

Synthetic Aperture Radar (SAR) remote sensing plays a significant role in volcano monitoring despite the measurements’ non real-time nature. The technique’s capability of imaging the spatial extent of ground motion has especially helped to shed light on the location, shape, and dynamics of subsurface magmatic storage and transport as well as the overall state of activity of volcanoes worldwide. A variety of different deformation phenomena are observed at exceptionally active and frequently erupting volcanoes, like Piton de la Fournaise on La Réunion Island. Those offer a powerful means of investigating related geophysical source processes and offer new insights into an active volcano’s edifice architecture, stability, and eruptive behavior. Since 1998, Interferometric Synthetic Aperture Radar (InSAR) has been playing an increasingly important role in developing our present understanding of the Piton de la Fournaise volcanic system. We here collect the most significant scientific results, identify limitations, and summarize the lessons learned from exploring the rich Piton de la Fournaise SAR data archive over the past ~20 years. For instance, the technique has delivered first evidence of the previously long suspected mobility of the volcano’s unsupported eastern flank, and it is especially useful for detecting displacements related to eruptions that occur far away from the central cone, where Global Navigation Satellite System (GNSS) stations are sparse. However, superimposed deformation processes, dense vegetation along the volcano’s lower eastern flank, and turbulent atmospheric phase contributions make Piton de la Fournaise a challenging target for applying InSAR. Multitemporal InSAR approaches that have the potential to overcome some of these limitations suffer from frequent eruptions that cause the replacement of scatterers. With increasing data acquisition rates, multisensor complementarity, and advanced processing techniques that resourcefully handle large data repositories, InSAR is progressively evolving into a near-real-time, complementary, operational volcano monitoring tool. We therefore emphasize the importance of InSAR at highly active and well-monitored volcanoes such as Mount Etna, Italy, Kīlauea Volcano, Hawai’i, and Piton de la Fournaise, La Réunion. Full article

(This article belongs to the Special Issue InSAR for Earth Observation)

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