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The atmosphere affects the propagation of radar signals by provoking unwanted signal phase changes. In interferometric applications, such as coherent change detection and displacement measurements, this effect may significantly degrade the system performances. Moreover, atmosphere-induced phase changes are both time and space variants, and therefore, they are not easy to be removed. This article proposes a novel method to remove atmospheric effects by using a parametric model of the refractive index, which is derived as an extension of the International Telecommunication Union—Radiocommunication model. The proposed algorithm has been tested on real data acquired by using a ground-based synthetic aperture radar system in conjunction with data collected by a weather station. Data have been acquired continuously for three consecutive days, approximatively every 5 min. Results have shown how the proposed method can effectively remove atmospheric effects and restore the signal phase.

Although the atmospheric compensation models developed to date have been generally robust and effective for InSAR, how to choose the right atmospheric correction method for ground-based InSAR is wo...

Differential interferometric SAR is a popular remote sensing technique to monitor deformations of the earth surface. However, the atmosphere disturbs interferograms and therefore affects the deformation estimate. Numerical weather predictions are able to hindcast the atmospheric states during SAR acquisitions which are mapped into disturbance estimates. This estimates are subtracted from interferograms to reduce the perturbation and improve the starting conditions for time series analysis. Differentielles interferometrisches SAR ist eine beliebte Fernerkundungsmethode zur Überwachung von Deformationen der Erdoberfläche. Die Atmosphäre stört jedoch die Interferogramme und beeinflusst damit die Deformationsschätzung. Numerische Wettervorhersagen sind in der Lage, die atmosphärischen Zustände bei SAR-Aufnahmen zu simulieren, die in Störungsschätzungen abgebildet werden. Diese Schätzungen werden von Interferogrammen abgezogen, um die Störung zu reduzieren und die Ausgangsbedingungen für die Zeitreihenanalyse zu verbessern.

Atmospheric phase screen (APS) is one of the main error sources of interferometric synthetic aperture radar (InSAR) measurements. In order to accurately retrieve displacement fields, it is necessary to use advanced methods to eliminate the tropospheric effect of interferograms. In this paper, the land subsidence in Kurdistan province of Iran is investigated using Sentinel-1A acquisitions on a single track for the period 2014–2018. The accurate and applicable 3D ray tracing technique is used to accurately estimate the APS. The ERA-I reanalysis data generated by European Centre for Medium Range Weather Forecasts (ECMWF) are used to implement the 3D ray tracing technique. In order to determine the effect of using the 3D ray tracing technique, the APSs are also determined using a traditional approach called, spatiotemporal filters method. To evaluate the capability of the two methods, the results are compared with the weather research and forecasting model (WRF) model. Finally, the interferograms are corrected using APSs from 3D ray tracing technique and traditional method and the subsidence rate in the study area is computed. Comparing the subsidence rates obtained from two APS estimation methods with piezometric data, GPS and precise levelling observations shows that the 3D ray tracing technique is significantly more accurate than traditional method in computing InSAR displacement fields.

Oil extraction over the years has increased tremendously resulting in land subsidence, which is a slow and gradual process and has long-term effects on ecohydrology and climate. For efficient measurement of land subsidence phenomenon due to oil extraction, an advanced PsInSAR technique was used in this study which overcame the obstacles such as temporal and geometrical decorrelation, phase delay due to atmospheric variation. The primary objective of the present study is to investigate the potential of PsInSAR technique to estimate total land subsidence in Burgan oil field, Kuwait, on a multitemporal scale from 2008 to 2011. A total of 26 datasets TerraSAR-X interferometric datasets were acquired from 31st January 2008 to 4th February 2011. Permanent Scatter Candidates (PSC) were selected based on amplitude stability index. Atmospheric Phase was estimated and removal of Atmospheric Phase Screen was carried using ensemble coherence. To measure the displacement between 31st January 2008 and 4th February 2011, a spatio-temporal displacement map was generated and overlaid on Google Earth to mark the areas of oil wells in Burgan oil field where subsidence has taken place. The total amount of subsidence was obtained from Integrated Cumulative Displacement Map, the value of which was estimated to be 10 mm/year and an average of 25–30 mm per 3 years. The land subsidence outcome of this study for three-years times was compared with already existing literature based results to show the potential of PsInSAR for subsidence mapping due to oil extraction. PsInSAR technique for land subsidence monitoring showed significant improvement in results after correcting for the atmospheric phase errors.

Boundary and area information could be used to study various interesting relations of multiple disasters such as "magnitude-area" relation for earthquakes. In this paper, a new method using InSAR-derived interferograms to determine the boundary of the crustal deformation area is introduced. Although InSAR has been widely used in crustal deformation monitoring, little is known about boundary detection using interferograms. The proposed method conducted Atmospheric Phase Screen (APS) correction to the interferograms based on Numerical Weather Prediction (NWP) model offered by Generic Atmospheric Correction Online Service for InSAR (GACOS). Moreover, this study proposed a suggestion to identify points in the interferograms at which the deformation changes smoothly that could be determined as the far-field boundary. Here we used a pair of Sentinel-1A images to investigate the deformation boundary associated with the 2017 Iran Sangsefid earthquake as an example. It was experimentally shown that the proposed method provided an inspiring scheme for boundary detection based on InSAR interferograms.

In this study, we investigated the potential use of polarimetric information to detect the land morphological changes without APS compensation. We proposed to use the APS independent descriptor and the covariance matrix likelihood ratio for APS. We validated the proposed technique by selecting the soil accumulated zone for a land elevation as a part of the restoration work at the landslide affected slope. The 24-hour processed time-series result reveals that both the APS independent descriptor and the likelihood-ratio are in agreement with the APS-compensated DInSAR result. The proposed idea shows the reasonable capability of detecting the land morphological change without APS compensation.

In this paper, the ground stability of the city of Constanta and surrounding areas (in Romania) is analyzed using the persistent scatterer interferometry technique, applied to Sentinel-l SAR data spanning an interval of two years. Two deformation maps are computed: one where the atmospheric phase screen is estimated and removed using ERA-Interim data and spatial filtering, and another using only spatial filtering.

Differential Interferometry SAR (DInSAR) is an advanced technique to retrieve ground deformation in the geoscience community. Atmospheric Phase Screen (APS) is one of the largest challenges limiting the application of DInSAR especially in mountainous areas. In this paper we propose an approach based on an empirical linear model for compensating stratified atmospheric phase delay in differential interferograms. Compared with conventional empirical linear model, the influence of turbulent APS is taken into consideration in our work. With this, the modelled stratified APS is more accurate. We test our algorithm using Envisat dataset and Sentinel dataset over Tenerife island (Spain). The performance of the approach is compared with Global Atmospheric Models (GAMs).

This paper reports the results of an experimental campaign carried out with a Ground Based Synthetic Aperture Radar (GB-SAR), aimed at monitoring the behaviour of an Alpine glacier. The apparatus is an Ibis-L® system, a commercial interferometric radar operating at Ku-band. It has been installed in a valley in front of the Planpincieux glacier, located on the Italian side of the Mont Blanc massif, about 3 km far from the glacier surface. The images, acquired with a temporal frequency of approximately five minutes, were processed correcting the atmospheric effect using a simple model which takes into account the variation of the atmospheric parameters with the altitude. The study enhances the importance of a satisfactory evaluation of the atmospheric behaviour to achieve an estimate of the deformation, and finally evaluates the mean velocity of the glacier in the order of 20-30 cm per day.

International audience; Spatial and temporal variations of pressure, temperature, and water vapor content in the atmosphere introduce significant confounding delays in interferometric synthetic aperture radar (InSAR) observations of ground deformation and bias estimates of regional strain rates. Producing robust estimates of tropospheric delays remains one of the key challenges in increasing the accuracy of ground deformation measurements using InSAR. Recent studies revealed the efficiency of global atmospheric reanalysis to mitigate the impact of tropospheric delays, motivating further exploration of their potential. Here we explore the effectiveness of these models in several geographic and tectonic settings on both single interferograms and time series analysis products. Both hydrostatic and wet contributions to the phase delay are important to account for. We validate these path delay corrections by comparing with estimates of vertically integrated atmospheric water vapor content derived from the passive multispectral imager Medium-Resolution Imaging Spectrometer, onboard the Envisat satellite. Generally, the performance of the prediction depends on the vigor of atmospheric turbulence. We discuss (1) how separating atmospheric and orbital contributions allows one to better measure long-wavelength deformation and (2) how atmospheric delays affect measurements of surface deformation following earthquakes, and (3) how such a method allows us to reduce biases in multiyear strain rate estimates by reducing the influence of unevenly sampled seasonal oscillations of the tropospheric delay.

Ground-based synthetic aperture radar (GBSAR) is a powerful tool used in monitoring structures, such as bridges and dams. However, despite the extremely short range of GBSAR interferometry, the atmosphere effects cannot be neglected. The permanent scatterer technique is an effective operational tool that utilizes a long series of SAR data and detects information with high accuracy. An algorithm based on the permanent scatterer technique is developed in accordance with the phase model used in GBSAR interferometry. In this study, atmospheric correction is carried out on a real campaign (Geheyan Dam, China). The atmosphere effects created using this method, which utilizes SAR data, can be reduced effectively compared to when plumb line data are used.

The accuracy of InSAR DEMs is affected by the temporal decorrelation of SAR images which is due to atmosphere, land use/cover, soil moisture, and roughness changes. Elimination of the temporal decorrelation of the master and slave image improves the DEMs accuracy. In this study, the Independent Component Analysis was applied before interferometric process. It was observed that using three ICA entries, ICA independent sources can be interpreted as background and changed images. ICA when performed on the master and slave images using the same couple of additional images produces two background images which enable the production of high quality DEMs. However, limitations exist in the proposed approach.

An algorithm is described which simulates atmospheric phase screen (PS) distorted by von Karman atmospheric turbulence by using Zernike expansion of randomly weighted Karhunen-Loeve function. The statistics of the PS generated by using power spectrum method which is most commonly used for generating PS poorly match up with the theoretical structure function, especially at low spatial frequency, while the algorithm described in the this paper can compensate for this shortcoming. And the accuracy of the PS is verified by comparing with the theoretical results. Furthermore, comparing with the existed methods which also use the Zernike expansion to simulate PS, algorithm presented in this paper is more accurate because the effects of the finite outer scale L0.is included

When studying geophysical processes through Differential SAR Interferometry (DInSAR), it is often necessary to estimate and subtract signals due to atmospheric inhomogeneities. To this end, stochastic models are often used to describe atmospheric phase delays in DInSAR data. As a first approximation, these can be modelled as isotropic, though this is a simplification, because SAR interferograms often exhibit anisotropic atmospheric signals. In view of this, it is increasingly advocated the use of anisotropic models for atmospheric phase estimation. However, anisotropic models lead to increased computational complexity in estimating the correlation function parameters with respect to the isotropic case. Moreover, performances can degrade when use is made of interferograms with only a few sparse points usable for computations, such as in the case of persistent scatterers interferometry (PSI) applications, especially when this estimation has to be done in an automated way on several tens of interferograms. In the present work we critically analyse the main aspects connected with the use of anisotropic models for DInSAR atmospheric delays, and we evaluate the advantage given by anisotropic modeling of atmospheric phase in the case of sparse grids of points. Through analysis of APS simulated data, we observe that a slight increase in the performances of reconstruction approaches can be obtained when sufficient sampling densities are available; based on these results, some recommendations for operational atmospheric phase estimation procedures are proposed.

The paper provides a theoretical model for the Geosynchronous SAR focused data, including clutter and atmosphere decorrelation effects. The focused data model is exploited to generate realistic GEOSAR demonstrative products, on the basis of the preliminary design of a regional GEOSAR system. The provided demo products are useful for a preliminary evaluation of the expected system performances.

SAR interferometry has long been regarded as an effective tool for wide-area topographic mapping in hilly and mountainous areas. However, quality of InSAR DEM product is usually affected by atmospheric disturbances and decorrelation-induced voids, especially for data acquired in repeat-pass mode. In this paper, we proposed an approach for improved topographic mapping by optimal fusion of multi-orbit InSAR DEMs with correction of atmospheric phase screen (APS). An experimental study with high-resolution TerraSAR-X and COSMO-SkyMed datasets covering a mountainous area was carried out to demonstrate the effectiveness of the proposed approach. Validation with a reference DEM of scale 1:50,000 indicated that vertical accuracy of the fused DEM can be better than 5 m.

As a component of interferometric phase, atmospheric phase influences accuracy of millimetric land deformation measurement. Though Atmospheric Phase Screen (APS) can be estimated by Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology, they are pseudo without consideration of actual atmospheric state and topography. This paper researches into ineffective separation of atmospheric phase in PS-InSAR methods when applied to extended cloudy area, and proposes an improved PS-InSAR processing flow by introducing Weather Research Forecast (WRF) simulations to remove atmospheric phase before interferometric phase analysis of PSI technique to obtain accurate land deformation velocity.

The paper evaluates the effects of Atmospheric Phase Screen on focused Geosynchronous SAR data. We derive theoretical models for the resolution, the interferometric de-correlation and the induced clutter in presence of an APS, whose joint time and space power spectrum is modeled as an extension of the Kolmogorov power law. Finally we provide some statistics gathered from a GB RADAR experiment.

We propose an efficient method for the azimuth compression and Atmospheric Phase Screen estimation of Geosynchronous SAR data. The method is based on the iterative processing of sub-apertures of increasing size, allowing to gradually refine the quality of the focused data and of the estimated APS. The whole processing can be easily parallelized. Results over simulated data are shown. © 2013 IEEE.

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as tectonic movements, landslide monitoring and digital elevation model extraction. One of its major limitation is the atmospheric effect, and in particular the high water vapour spatial and temporal variability which introduces an unknown delay in the signal propagation. This paper describes the general approach and some results achieved in the framework of an ESA funded project devoted to the mapping of the water vapour with the aim to mitigate its effect in InSAR applications. Ground based (microwave radiometers, radiosoundings, GPS) and spaceborne observations (AMSR-E, MERIS, MODIS) of columnar water vapour were compared with Numerical Weather Prediction model runs in Central Italy during a 15-day experiment. A dense network of GPS receivers was deployed close to Como, in Northern Italy, to complement the operational network in order to derive Zenith Total Delay as well as Slant Delay which can support InSAR processing. A comparison with Atmospheric Phase Screens (APS) derived from a sequence of Envisat multi pass interferometric acquisitions processed using the Permanent Scatters technique on the two test sites has been also performed. The acquired experimental data and their comparison give a valuable idea of what can be done to gather information on water vapour, which, besides InSAR applications, plays a fundamental role in weather prediction and radio propagation studies. The work has been carried out in the framework of an ESA funded project, named “Mitigation of Electromagnetic Transmission errors induced by Atmospheric Water Vapour Effects” (METAWAVE). This paper presents the general approach an the various methodologies exploited in the project, together with the overall intercomparison of the results. In deep details on the comparison with the InSAR APS maps derived by the PS technique, as well as on GPS receiver processing and water vapour tomography are reported in two companion papers.

The PSInSAR technique, invented by Ferretti et. al. [1], [2], [3] ten years ago, meanwhile has proven it's capability for very precise measurement of surface deformations. To achieve this, the influence of the atmospheric phase screen (APS) has to be removed. We investigated the APS for two series of TerraSAR-X high resolution spotlight data of a scene in Bavaria. Our approach was to consider the APS as composed of a phase ramp, a part stratified with height and a turbulent component. We estimated the turbulent component via kriging. The variograms show for short distances a regime which is not visible for lower resolutions. In this paper we discuss the choice of appropriate variogram models with respect to our data.

It is well know that atmospheric phase screen(APS) effect in Small Baseline Subset (SBAS) D-InSAR processing to obtain ground deformation in long time series leads to additional interferometry phase and the unreliable result. To solve the problem above, MODIS product provide a mean to stimulate atmospheric field of SAR data for reducing the APS effect in D-InSAR processing. In this paper, 12 ENVISAT ASAR images are used to process SBAS method and 6 MODIS MOD05_L2 products are used to process atmosphere correction. A case study in the Jiaxing-Huzhou plain in Zhejiang province, China shows successfully stimulate the atmospheric field of SAR data and analysis its effect on SBAS application.

To overcome the shortage of conventional least squares (LS) DInSAR technique which can only obtain the optimal deformation under ideal condition, we propose an advanced LS algorithm to retrieve ground deformation over large areas. In this algorithm, two extensions are derived. First, the atmospheric phase screen (APS) is removed from the differential interferometric phases by temporal low-pass filtering. Second, topographic errors are considered in the linear model to be separated from deformation. The proposed algorithm has been tested with an ALOS PALSAR data set relative to southern Jiangsu Province, covering the cities of Suzhou and Wuxi, East China. Finally, leveling data validate the results.

In the above-named article [ibid., vol. 8, no. 3, pp. 537-541, May 2011], an error in equation (4) appears. In it, the value 0.2589 is corrected to 77.6. The error concerns only the transcription of (4), and not the results presented in the letter, where the proper formulation was indeed used. The authors would like to thank the reviewer who helped correct this.

Motivated by prospective synthetic aperture radar (SAR) satellite missions, this paper addresses the problem of differential SAR tomography (D-TomoSAR) in urban areas using spaceborne bistatic or pursuit monostatic acquisitions. A bistatic or pursuit monostatic interferogram is not subject to significant temporal decorrelation or atmospheric phase screen and, therefore, ideal for elevation reconstruction. We propose a framework that incorporates this reconstructed elevation as deterministic prior to deformation estimation, which uses conventional repeat-pass interferograms generated from bistatic or pursuit monostatic pairs. By means of theoretical and empirical analyses, we show that this framework is, in the pursuit monostatic case, both statistically and computationally more efficient than the standard D-TomoSAR. In the bistatic case, its theoretical bound is no worse by a factor of 2. We also show that reasonable results can be obtained by using merely six TerraSAR-X add-on for digital elevation measurements (TanDEM-X) pursuit monostatic pairs, if additional spatial prior is introduced. The proposed framework can be easily extended for multistatic configurations or external sources of scatterer’s elevation.