Differential Interferograms Research Articles

A method for GB-InSAR temporal analysis considering the atmospheric correlation in time series

GB-InSAR, with high time-spatial resolution and high accuracy, shows great potential in landslide monitoring. However, the accuracy of GB-InSAR is usually reduced by the atmospheric disturbance and temporal decorrelation. PS-InSAR technology can solve those problems well and get accurate deformation information, so it has been widely adopted in space-borne SAR. For the atmospheric correction, PS-InSAR assumes that the atmospheric phase is only strongly correlated in the space domain. But for GB-InSAR, atmospheric phase shows correlation in both the time and space domains, because of the short time interval. Therefore, the calculation of linear velocity will be affected by the atmospheric disturbance when the PS-InSAR technology is applied to the GB-SAR data. To solve this problem, a PS-InSAR strategy for GB-SAR data considering the atmospheric disturbance in the time domain is proposed. The proposed method uses the differential interferograms interfered by nearby SLCs to ensure the high coherence of interferometric phase and reduces the impact of atmospheric disturbance. The coherence is used for PS selection besides the amplitude deviation index, which can increase the density of PS points. Furthermore, a method for atmospheric correction based on the wrapped phase is presented. Thus, the linear velocity is computed based on the interferogram without most atmospheric disturbance. The validation using the data of the open pit in Malanzhuang, Hebei, China, shows that the proposed method can get a deformation monitoring accuracy of sub-millimeter.

A geospatial intelligence application to support post-disaster inspections based on local exposure information and on co-seismic DInSAR results: the case of the Durres (Albania) earthquake on November 26, 2019

The current study analyzes how a geospatial intelligence application can turn into a useful operational tool in the immediate post-earthquake phase of infrastructure inspection that may have been affected by the co-seismic ground deformation due to very strong earthquake event. As a case study, the Durres (Central Albania) earthquake on November 26, 2019, has been investigated. In order to achieve this goal, free SAR images of the Sentinel-1 Copernicus satellite in both geometry of acquisition were used to create the differential interferograms and in the next step to convert them into deformation maps through phase unwrapping and convert phase to meters. Interferometric processing steps were carried out by the open and free ESA's SNAP software. Then, from open sources, data were used to identify and localize the exposure in the affected area. By combining (overlapping) the above two datasets of knowledge, a geospatial intelligence tool has been created in which for every element of the exposure that was identified, the ground deformation that the area had suffered due to the strong earthquake was also known.

METHODOLOGY FOR MONITORING DISPLACEMENTS OF BUILDINGS AND STRUCTURES USING SPACE RADAR SURVEY

The article is devoted to monitoring the deformation of structures using persistent scattereres interferometry according to the satellite Sentinel-1. The Persistant Scatterers Interferometry technique is described, which is used for processing interferometric pairs of images in SNAP and StaMPS software. As a result, differential interferograms characterizing the change in the height of individual points over a certain period of time are obtained.

Multi-wavelength phase-shifting interferometry based on a two-step phase-shifting phase retrieval algorithm with a color CMOS

By combining the advantages of multi-wavelength phase-shifting interferometry and two-step phase-shifting phase retrieval algorithm, a measured phase with high precision and a large measuring range can be retrieved rapidly from three multi-wavelength interferograms with unknown phase shifts, recorded by a single-chip color CMOS. Firstly, two normalized differential interferograms without backgrounds are obtained by means of subtraction followed by normalization between the three color interferograms. Next, the wrapped phases of a single wavelength are retrieved via the Gram–Schmidt orthonormalization approach. Finally, the unambiguous phase of the three synthetic wavelengths can be achieved by subtraction between the wrapped phases of corresponding wavelengths. To reduce the phase noise amplification introduced by the magnification of wavelengths, the phase unwrapping algorithm of reducing the noise of the three- synthetic wavelength to the level of a two-synthetic long wavelength, a single-wavelength, and a two-synthetic short wavelength are implemented in turn. Compared with conventional multi-wavelength phase shifting interferometry, only three interferograms with unknown phase shifts are needed to reconstruct the actual phase of the measured object to a high degree of measurement resolution, and with a large measurement range; this approach would be useful in dynamic phase measurement. Both simulation and experimental results validate the performance of the proposed method.

Monitoring of large-scale landslides in Zongling, Guizhou, China, with improved distributed scatterer interferometric SAR time series methods

The Zongling landslide (Nayong, Guizhou, China) is dominated by a unique karst landscape area with many landslide masses. In this paper, an improved Interferometric Point Target Analysis (IPTA) method is proposed to identify and monitor the Zongling landslide. In this method, the Anderson-Darling test is applied to distributed scatterer (DS) selection, and DS and persistent scatterer (PS) are combined to improve the density of measurement points in vegetation area. Moreover, this method is also characterized by the appropriate combination of differential interferograms produced by a small baseline subsets and the employment of the phase triangulation algorithm to estimate the optimal phase. Combining 105 scenes of C-band Sentinel-1A ascending and descending data acquired during 2014–2018, the method is applied to retrieve time series displacement for the large-scale landslide in Zongling Town. Finally, three accelerating landslides are identified from our result, which is consistent with ALOS PALSAR differential interferometry synthetic aperture radar (DInSAR) results and field investigation. The influencing factors and deformation mechanism of the Zongling landslide are also analysed. Our monitoring results will help the local government to conduct regular inspections and strengthen disaster prevention in mountain areas.

Accurate frequency estimation for removal of orbital fringes in SAR interferograms

ABSTRACT Differential interferogram of space-borne SAR data may be affected by residual orbital fringes resulting from errors in the orbit (i.e. baseline) determination that hinder subsequent InSAR applications (deformation or elevation measurements). In this paper, an easy-to-use method was developed to remove the orbit errors in complex SAR interferogram in the radar coordinate system by accurately estimating the frequencies of the orbital ramp phase. The method first finds an approximate integer frequency by searching for the peak of the sum of the Fourier spectra of all the rows of the interferogram. It then uses the 100-order Burg spectral estimation algorithm to estimate the power spectrum for each row of the interferogram, and calculates the high-resolution power spectrum over the frequency range Hz. Finally, the method obtains the exact frequency of the orbital ramp phase in the row direction by searching for the peak of the sum of the high-resolution power spectra of all rows. By performing the same operations on all columns of the interferogram, the exact frequency in the column direction can be obtained. The orbital ramp phase can be calculated using these exact frequencies and be removed from the interferogram. Validation tests demonstrate that our method can accurately estimate the frequencies of the orbital ramp phase in the row and column directions, and eliminate the orbital ramp fringes from the simulated and actual interferograms. The proposed method only needs to calculate the high-resolution spectrum in a small frequency range, so the burden of calculation is light. The proposed method is easy to use since phase unwrapping or a priori satellite orbit information is not required.

The Extraction of Ocean Tidal Loading from ASAR Differential Interferograms

The spatiotemporal crustal non-tectonic deformation caused by ocean tidal loading (OTL) can reach the centimeters scale in coastal land areas. The temporal variation of the site OTL displacements can be estimated by the global positioning system (GPS) technique, but its spatial variation needs to be further determined. In this paper, in order to analyze the spatial characteristics of the OTL displacements, we propose a multi-scale decomposition method based on signal spatial characteristics to derive the OTL displacements from differential interferometric synthetic aperture radar (D-InSAR) measurements. The method was tested using long-term advanced synthetic aperture radar (ASAR) data and GPS reference site data from the Los Angeles Basin in the United States, and we compared the results with the FES2014b tide model. The experimental results showed that the spatial function of the OTL displacements in an ASAR image can be represented as a higher-order polynomial function, and the spatial trends of the OTL displacements determined by the InSAR and the GPS techniques are basically consistent with the FES2014b tide model. The root-mean-square errors of the differences between the spatial OTL displacements of these two methods and the FES2014b tide model are less than 0.8 mm. The results indicate that the OTL displacement extracted from InSAR data can accurately reflect the spatial characteristics of the OTL effect, which will help to improve the spatial resolution and accuracy of the OTL displacement in coastal areas.

Spatiotemporal Ocean Tidal Loading in InSAR Measurements Determined by Kinematic PPP Solutions of a Regional GPS Network

The coastal crustal deformation caused by ocean tidal loading (OTL) varies spatially and temporally, and this spatiotemporal variation in satellite-based interferometric synthetic aperture radar (InSAR) measurements needs to be determined. In this article, we propose a spatiotemporal modeling method to estimate the OTL displacements in InSAR measurements using the kinematic precise point positioning (PPP) solutions of a regional GPS network. We tested the method through an experiment using 25 Sentinel-1B images and long-term observations of 172 GPS reference sites from Southern California. The experimental results suggest that there are significant OTL and solid Earth tide effects in the differential InSAR interferogram, which is greater than 40 mm. We find that the spatial characteristics of OTL variations can be expressed as a high-order polynomial in the two variables of latitude and longitude, and the spatiotemporally modeled PPP tidal estimates of the high-density GPS sites can provide high precision OTL correction for all the pixels in the interferogram. In the last part of the study, we show that the spatial large-scale signals in the differential interferograms of Sentinel-1B data are mainly atmospheric delay, solid Earth tidal, and OTL effect, and demonstrate the importance of the tidal correction in the InSAR measurements.

Minimizing Height Effects in MTInSAR for Deformation Detection Over Built Areas

Removing the topographic component in the interferometric synthetic aperture radar (InSAR) phase is conventionally conducted using an external digital elevation model (DEM). However, with an increasing spatial resolution of SAR data, the external DEM is becoming less qualified for this purpose, resulting in notable phase residues and even decorrelation in differential interferograms. Although topographic residuals can be parameterized and estimated by multi-temporal InSAR (MTInSAR) techniques, its accuracy is limited by several factors. Instead of providing accurate height information, shortening the length of baselines is an alternative for DEM phase mitigation. We propose here an MTInSAR processing framework that can retrieve the deformation time series without the estimation of topographic residuals. Within the framework, we generate a set of pseudo interferograms with near-zero baselines by integer combination and take these pseudo interferograms as observations of MTInSAR model, where deformation becomes the only signal that needs to be parameterized. The deformation time series is then retrieved directly from wrapped phases by ridge estimation with an integer ambiguity detector. It is noted that although atmospheric artifacts might be magnified during the combination, their differential components at arcs constructed with neighboring points that are not significantly enlarged. The proposed method is particularly suitable for infrastructure deformation monitoring in urban areas where no accurate external DEM is available. It also has promising potential for retrieving deformation from SAR data stacks with short acquisition intervals since the combination can enlarge the signal of interests in pseudo-observations. Semisynthetic and real data tests indicate that the proposed method has satisfied performance on DEM error mitigation and deformation time series estimation.

The 2017 Noneruptive Unrest at the Caldera of Cerro Azul Volcano (Galápagos Islands) Revealed by InSAR Observations and Geodetic Modelling

An unrest event occurred at the Cerro Azul volcano, Galápagos Islands, South America, in March 2017, leading to significant surface deformation on the southern Isabela Island, without eruption or surface rupture. We collected single-look complex synthetic aperture radar (SAR) images sensed by the Sentinel-1A satellite, obtaining eight differential interferograms, of which four showed extensive surface displacement during the co-unrest period. Geodetic data indicated that the unrest continued from 18 March to 25 March, reaching a negative peak displacement of −32.9 cm in the caldera and a positive peak displacement of 41.8 cm on the south-east plain in the line-of-sight direction. A joint magma source deformation model, consisting of a Mogi source below the caldera and a sill source south-east of the caldera, was inverted by the Markov chain Monte Carlo method combined with the Metropolis–Hasting algorithm, acquiring the best fit with the four interferograms. The magma transport mechanism of the event was explained by magma overflowing from the compressive Mogi to the tensile sill source, resulting in the observed “∞”-shaped deformation fields. Additionally, we investigated previous events with eruption rifts and lava lakes in 1979, 1998, and 2008, and proposed a potential hazard of tectonic volcanic activity for further volcanic susceptibility research in the Cerro Azul area.

Ionospheric correction of ALOS‐2 full‐aperture ScanSAR interferometric data for surface deformation measurement in Beijing

Ionospheric disturbance is one of the most serious factors that limit the accuracy of deformation measurement of interferometric synthetic aperture radar (InSAR) especially for spaceborne SAR systems in low frequency such as L-band. Especially in imaging modes with a large coverage, ScanSAR mode for example, ionospheric disturbance phase screen almost submerges other useful geographical information. In this study, two ALOS-2 (L-band) full-aperture ScanSAR images (October 2015 and October 2016) are used to study ground deformation in Beijing from 2015 to 2016. The split range-spectrum technique is adopted to extract ionospheric distortion. The authors splice the differential interferograms of adjacent subswaths by resampling them to perform the overall ionospheric extraction. Also non-local filtering is used to improve the coherence of interferograms. Spatial deformation distribution that was obtained by differential interferometric synthetic aperture radar (D-InSAR) technique using the two ALOS-2 ScanSAR images is highly consistent with the result obtained by persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technique using Sentinel Tops mode images (October 2015–February 2017). The comparison results show the effectiveness of the ionospheric distortion extraction method used in this study. Moreover, the spatial distribution is also highly consistent with the results before 2014, which means that the deformation trend in Beijing continues.

Demonstration of Time-Series InSAR Processing in Beijing Using a Small Stack of Gaofen-3 Differential Interferograms

More and more synthetic aperture radar (SAR) satellites in orbit provide abundant data for remote sensing applications. In August 2016, China launched a new Earth observation SAR satellite, Gaofen-3 (GF-3). In this paper, we utilize a small stack of GF-3 differential interferograms to map land subsidence in Beijing (China) using the time-series SAR interferometry (InSAR) technique. The small stack of differential interferograms is generated with 5 GF-3 SAR images from March 2017 to January 2018. Orbit errors are carefully addressed and removed during differential InSAR (DInSAR) processing. Truncated singular-value decomposition (TSVD) is applied to strengthen the robustness of deformation rate estimation. To validate the results of GF-3 data, an additional deformation measurement using 26 Sentinel-1B images from March 2017 to February 2018 is carried out using the persistent scatterer interferometry (PSI) technique. By implementing a cross-comparison, we find that the retrieved results from GF-3 images and Sentinel-1 images are spatially consistent. The standard deviation of vertical deformation rate differences between two data stacks is 11.24 mm/y in the study area. The results shown in this paper demonstrate the reasonable potential of GF-3 SAR images to monitor land subsidence.

Modeling and Robust Estimation for the Residual Motion Error in Airborne SAR Interferometry

Due to the limited accuracy of the current navigation systems, uncompensated motion errors during airborne synthetic aperture radar (SAR) preprocessing, i.e., the residual motion error (RME), cause undesirable phase errors in the final interferogram. Especially in airborne repeat-pass interferometric SAR (InSAR), the removal of RME is critical for topographic mapping. In this letter, based on the geometry of a single-baseline interferogram, a model is first developed for describing the relationship between the time-varying baseline parameters and the interferometric phase errors. A robust estimation is then employed to estimate the RME-induced phase errors. The performance of the proposed method was validated by the use of P- and L-band single-baseline interferograms acquired by the airborne E-SAR system. The results showed that the phase artifacts in the initial differential interferograms can be greatly mitigated. In addition, the corrected interferograms acquired in the P- and L-bands were used to estimate the digital elevation model (DEM). After correction, the root-mean-square errors (RMSEs) of the two DEMs with respect to the light detection and ranging (LiDAR) DEM were 2.6 and 4.6 m, respectively, which are improvements of 48.0% and 63.8%. Furthermore, even in the case of low coherence, the proposed method can still work well.

MONITORING LANDSLIDES IN THE MUSSOORIE REGION, UTTARAKHAND USING MULTI-TEMPORAL SAR INTERFEROMETRY WITH SENTINEL-1 IMAGES

Abstract. Occurrence of landslide events are common in the lesser Himalayan region which lie in a tectonically active zone with unstable slopes. The Mussoorie region is situated in the lesser Himalayas and is one of most visited tourist sites of the Uttarakhand state. The region is facing social and economic crisis due to the damage caused by multiple landslide events, which requires continuous monitoring for better planning and rescue operations. This study shows the time series analysis of landslide events occurring in the Mussoorie region using the Persistent Scatterer Interferometry (PSI) technique on Sentinel-1 synthetic aperture radar (SAR) images. The processing steps required to process the Sentinel-1 data stacks using both differential SAR interferometry (DInSAR) and PSI are presented. 13 Sentinel-1A C-band interferometric wide swath (IW) images covering a time period of one year are used for PSI processing, resulting in the generation of 12 differential interferograms. The PSI approach extracted 5593 measurement points in the study area. The one dimensional line of sight (1D LOS) time series displacement estimates obtained from PSI processing show a maximum velocity of −55.7 mm year−1 in the radar line of sight (LOS) direction, indicating subsidence. The displacement map further used to characterize the landslide susceptible zones show higher displacement magnitude for areas near Jabarkhet, Bhataghat, Bansagad and Raipur range. Use of more Sentinel-1 images and better DInSAR processing algorithms can improve the displacement estimation and pattern detection.

TIME SERIES ANALYSIS OF SURFACE DEFORMATION OF BENGALURU CITY USING SENTINEL-1 IMAGES

Abstract. Persistent Scatterer Interferometry (PSI) is an advanced technique to map ground surface displacements of an area over a period. The technique can measure deformation with a millimeter-level accuracy. It overcomes the limitations of Differential Synthetic Aperture Radar Interferometry (DInSAR) such as geometric, temporal decorrelation and atmospheric variations between master and slave images. In our study, Sentinel-1A Interferometric Wide Swath (IW) mode descending pass images from May 2016 to December 2017 (23 images) are used to identify the stable targets called persistent scatterers (PS) over Bengaluru city. Twenty-two differential interferograms are generated after topographic phase removal using the SRTM 30 m DEM. The main objective of this study is to analyze urban subsidence in Bengaluru city in India using the multi-temporal interferometric technique such as PSI. The pixels with Amplitude Stability Index ≥ 0.8 are selected as initial PS candidates (PSC). Later, the PSCs having temporal coherence > 0.5 are selected for the time series analysis. The number of PSCs that are identified after final selection are reduced from 59590 to 54474 for VV polarization data and 15611 to 15596 for VH polarization data. It is interesting to note that a very less number of PSC are identified in cross-polarized images (VH). A high number of PSC have identified in co-polarized (VV) images as the vertically oriented urban targets produce a double bounce, which results in a strong return towards the sensor. The velocity maps obtained using VV and VH polarizations show displacement in the range of ± 20 mm year−1. The subsidence and the upliftment observed in the city shows a linear trend with time. It is observed that the eastern part of Bengaluru city shows more subsidence than the western part.

Coseismic Deformation Field of the Mw 7.3 12 November 2017 Sarpol-e Zahab (Iran) Earthquake: A Decoupling Horizon in the Northern Zagros Mountains Inferred from InSAR Observations

The study of crustal deformation fields caused by earthquakes is important for a better understanding of seismic hazard and growth of geological structures in tectonically active areas. In this study, we present, using interferometric measurements constructed from Sentinel-1 Terrain Observation with Progressive Scan (TOPS) data and ALOS-2 ScanSAR, coseismic deformation and source model of the Mw 7.3, 12 November 2017 earthquake that hit northwest of the Zagros Mountains in the region between Iran–Iraq border. This was one of the strongest seismic events to hit this region in the past century, and it resulted in an uplift area of about 3500 km2 between the High Zagros Fault (HZF) and Mountain Front Fault (MFF) with a maximum amount of 70 cm south of Miringe fault. A subsidence over an area of 1200 km2 with a maximum amount of 35 cm occurred near Vanisar village at the hanging wall of the HZF. Bayesian inversion of interferometric synthetic aperture radar (InSAR) observations suggests a source model at a depth between 14 and 20 km that is consistent with the existence of a decoupling horizon southwest edge of the northern portion of the Zagros Mountains near the MFF. Moreover, we present evidence for a number of coseismically induced rockslides and landslides, the majority of them which occurred along or close to pre-existing faults, causing decorrelation in differential interferograms. Exploiting the offset-tracking technique, we estimated surface motion by up to 34 and 10 m in horizontal and vertical directions, respectively, due to lateral spreading on a big coseismic-induced landslide near Mela-Kabod. Field observations also revealed several zones of en echelon fractures and crack zones developed along a pre-existing fault passing through Qasr-e Shirin City, which exhibited secondary surface slip by up to 14 cm along its strike.

Atmospheric Effect Correction for InSAR With Wavelet Decomposition-Based Correlation Analysis Between Multipolarization Interferograms

This paper presents a wavelet decomposition-based correlation analysis (WDCA) method to correct atmospheric effects for interferometric synthetic aperture radar interferometry. The main idea is based on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge that the atmospheric effects are independent of the polarizations. This provides the possibility to find the identical atmospheric phases (ATPs) from the two different polarimetric interferograms. To achieve this goal, differential interferometry is performed with different topographic data so that the obtained differential interferograms (D-Infs) have different topographic errors. A polynomial incorporating topographic information is then used to remove the orbit error phase. Thus, the ATPs are the only identical components in the obtained D-Infs. A forward wavelet transform is then utilized to perform multiresolution analysis for the two obtained D-Infs. After this, we apply correlation analysis to identify the wavelet coefficients attributed to the atmospheric effects. The corrected D-Infs are then obtained by down-weighting the wavelet coefficients during inverse wavelet transform. The performance of the WDCA method was tested with L-band ALOS-1 PALSAR dual-polarization SAR images acquired over Southern California and Qilian mountain test sites characterized by different topographic conditions. For the Southern California test site, two interferometric pairs with long and short baselines (750 and 50 m) were formulated. The results show that the WDCA method can work well for both of the interferometric pairs, and the root-mean-square errors (RMSEs) of the obtained DEMs with respect to the Shuttle Radar Topography Mission digital elevation model (DEM) are 7.86 and 13.78 m, and show a decrease of 34.7% and 80.4% for the long- and short-baseline cases, respectively. For the Qilian mountain test site, the corrected interferogram can provide a DEM with an RMSE of 19.73 m, which is an improvement of 22.3% with respect to the DEM containing the atmospheric signals. In addition, the above two experiments show that compared with the existing topographic information-based wavelet method, this approach can remove not only the topography-dependent ATP but also the turbulent ATP.

Evaluation of the Multilook Size in Polarimetric Optimization of Differential SAR Interferograms

The interferometric coherence is a measure of the correlation between two SAR images and constitutes a commonly used estimator of the phase quality. Its estimation requires a spatial average within a 2-D window, usually named as multilook. The multilook processing allows reducing noise at the expenses of a resolution loss. In this letter, we analyze the influence of the multilook size while applying a polarimetric optimization of the coherence. The same optimization algorithm has been carried out with different multilook sizes and also with the nonlocal SAR filter filter, which has the advantage of preserving the original resolution of the interferogram. Our experiments have been carried out with a single pair of quad-polarimetric RADARSAT-2 images mapping the Mount Etna's volcanic eruption of May 2008. Results obtained with this particular data set show that the coherence is increased notably with respect to conventional channels when small multilook sizes are employed, especially over low-vegetated areas. Conversely, very decorrelated areas benefit from larger multilook sizes but do not exhibit an additional improvement with the polarimetric optimization.

Using Dual-Polarization Interferograms to Correct Atmospheric Effects for InSAR Topographic Mapping

Atmospheric effect represents one of the major error sources for interferometric synthetic aperture radar (InSAR), particularly for the repeat-pass InSAR data. In order to further improve the practicability of InSAR technology, it is essential to study how to estimate and eliminate the undesired impact of atmospheric effects. In this paper, we propose the multi-resolution weighted correlation analysis (MRWCA) method between the dual-polarization InSAR data to estimate and correct atmospheric effects for InSAR topographic mapping. The study is based on the a priori knowledge that atmospheric effects is independent of the polarization. To find the identical atmospheric phase (ATP) signals of interferograms in different polarizations, we need to remove the other same or similar phase components. Using two different topographic data, differential interferometry was firstly performed so that the obtained differential interferograms (D-Infs) have different topographic error phases. A polynomial fitting method is then used to remove the orbit error phases. Thus, the ATP signals are the only identical components in the final obtained D-Infs. By using a forward wavelet transform, we break down the obtained D-Infs into building blocks based on their frequency properties. We then applied weighted correlation analysis to estimate the wavelet coefficients attributed to the atmospheric effects. Thus, the ATP signals can be obtained by the refined wavelet coefficients during inverse wavelet transform (IWT). Lastly, we tested the proposed method by the L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR dual-polarization SAR data pairs covering the San Francisco (USA) and Moron (Mongolia) regions. By using Ice, Cloud, and land Elevation Satellite (ICESat) data as the reference data, we evaluated the vertical accuracy of the InSAR digital elevation models (DEMs) with and without atmospheric effects correction, which shows that, for the San Francisco test site, the corrected interferogram could provide a DEM with a root-mean-square error (RMSE) of 7.79 m, which is an improvement of 40.5% with respect to the DEM without atmospheric effects correction. For the Moron test site, the corrected interferogram could provide a DEM with an RMSE of 10.74 m, which is an improvement of 30.2% with respect to the DEM without atmospheric effects correction.

Satellite SAR interferometry for the improved assessment of the state of activity of landslides: A case study from the Cordilleras of Peru

In Peru landslides have been causing damages and casualties annually due to the high mountain relief and distinct seasonal precipitation distribution. Satellite Synthetic Aperture Radar (SAR) interferometry represents one possibility for mapping surface deformation at fine spatial resolution over large areas in order to characterize aspects of terrain motion and potentially hazardous processes. We present land surface motion maps derived from satellite SAR interferometry (InSAR) for a part of the Santa River Basin between the Cordilleras Blanca and Negra around the city of Carhuaz in Peru. Using both Persistent Scatterer Interferometry (PSI) and differential SAR Interferograms (DInSAR) from ALOS-1 PALSAR-1, ENVISAT ASAR, ALOS-2 PALSAR-2 and Sentinel-1 we mapped 42 landslides extending over 17,190,141 m2 within three classes of activity (i.e. 0–2 cm/a, 2–10 cm/a and >10 cm/a). A geomorphological inventory of landslides was prepared from optical satellite imagery and field experience and compared to the InSAR-based slope-instability inventory. The two approaches provide slightly different information about landslide spatial and temporal activity patterns, but altogether they can be combined for the assessment of the state of activity of landslides and possibly the development of hazard maps, which are not systematically available in this region. We conclude that ALOS PALSAR (1 and 2) and Sentinel-1 data have a high potential to derive high-quality surface deformation information of landslides in many mountainous regions worldwide due to their global and frequent acquisition strategies.