Differential Synthetic Aperture Radar Interferometry Results Research Articles

Retrieval of Svalbard ice flow velocities using Sentinel 1A/1B three-pass Differential SAR Interferometry

Glacier velocity is an important parameter to characterize glacier dynamics and to derive ice thickness and mass balance. The 2-pass/3-pass Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques are advantageous in estimating glacier movements. However, the 2-pass DInSAR requires an external Digital Elevation Model (DEM), whereas the 3-pass DInSAR does not. The 3-pass DInSAR technique is adopted with Sentinel-1A/1B to map the Svalbard glacier flow velocities. Furthermore, the effect of glacier surface elevation change on the 2-pass DInSAR results were revealed by comparing glacier velocity with the two time period topographic information. The coherence indicates that Sentinel-1A/1B has a high potential to infer operational glacier velocity using the 3-pass DInSAR method with an average atmospheric uncertainty of 0.24 cm/day over the studied region. The precision of the 3-pass DInSAR is analyzed by comparing 2-pass derived line-of-sight (LOS) velocity on the same dates. The 3-pass DInSAR achieves high-resolution and detailed information.

Understanding Mountain-Wave Phases in ERS Tandem DInSAR Interferogram Using WRF Model Simulation

Repeat-pass spaceborne differential synthetic aperture radar interferometry (DInSAR) is commonly used to measure surface deformation. However, the phase delay due to the atmospheric water vapor has a significant influence on the accuracy of DInSAR results. On the other hand, the signal delay in DInSAR can give the spatial variation information of water vapor during the two image acquisitions. There are some ripple-like phase signals in DInSAR, which are probably due to the mountain wave in the study area. In this paper, the weather research and forecasting (WRF) model is used to simulate the atmospheric delay and compared to the phase delay derived from DInSAR results to understand the mountain-wave phases in interferograms. The results indicate that the ripple-like phase signal in the DInSAR phase is due to different intensities of the mountain wave in two acquisitions. The WRF model can be used to explain the mechanism of mountain-wave phase in DInSAR, which may then, hopefully, be used for DInSAR atmospheric correction.

Integrating the probability integral method for subsidence prediction and differential synthetic aperture radar interferometry for monitoring mining subsidence in Fengfeng, China

Differential synthetic aperture radar interferometry (D-InSAR) is characterized mainly by high spatial resolution and high accuracy over a wide coverage range. Because of its unique advantages, the technology is widely used for monitoring ground surface deformations. However, in coal mining areas, the ground surface can suffer large-scale collapses in short periods of time, leading to inaccuracies in D-InSAR results and limiting its use for monitoring mining subsidence. We propose a data-processing method that overcomes these disadvantages by combining D-InSAR with the probability integral method used for predicting mining subsidence. Five RadarSat-2 images over Fengfeng coal mine, China, were used to demonstrate the proposed method and assess its effectiveness. Using this method, surface deformation could be monitored over an area of thousands of square kilometers, and more than 50 regions affected by subsidence were identified. For Jiulong mine, nonlinear subsidence cumulative results were obtained for a time period from January 2011 to April 2011, and the maximum subsidence value reached up to 299 mm. Finally, the efficiency and applicability of the proposed method were verified by comparing with data from leveling surveying.

Cloud Computing for Earth Surface Deformation Analysis via Spaceborne Radar Imaging: A Case Study

We present a case study on the migration to a Cloud Computing environment of the advanced differential synthetic aperture radar interferometry (DInSAR) technique, referred to as Small BAseline Subset (SBAS), which is widely used for the investigation of Earth surface deformation phenomena. In particular, we focus on the SBAS parallel algorithmic solution, namely P-SBAS, that allows the production of mean deformation velocity maps and the corresponding displacement time-series from a temporal sequence of radar images by exploiting distributed computing architectures. The Cloud migration is carried out by encapsulating the overall P-SBAS application in virtual machines running on the Cloud; moreover, the Cloud resources provisioning and configuration phases are implemented in an automatic way. Such an approach allows us to preserve the P-SBAS parallelization strategy and to straightforwardly evaluate its performance within a Cloud environment by comparing it with those achieved on a HPC in-house cluster. The results we present were achieved by using the Amazon Elastic Compute Cloud (EC2) of the Amazon Web Services (AWS) to process SAR datasets collected by the ENVISAT satellite and show that, thanks to the Cloud resources availability and flexibility, large DInSAR data volumes can be processed through the P-SBAS algorithm in short time frames and at reduced costs. As a case study, the mean deformation velocity map of the southern California area has been generated by processing 172 ENVISAT images. By exploiting 32 EC2 instances this processing took less than 17 hours to complete, with a cost of USD 850. Considering the available PB-scale archives of SAR data and the upcoming huge SAR data flow relevant to the recently launched (April 2014) Sentinel-1A and the forthcoming Sentinel-1B satellites, the exploitation of Cloud Computing solutions is particularly relevant because of the possibility to provide Cloud-based multi-user services allowing worldwide scientists to quickly process SAR data and to manage and access the achieved DInSAR results.

Subsidence monitoring in the Ordos basin using integrated SAR differential and time-series interferometry techniques

ABSTRACTRecent researches have illustrated with the image tracking method that Ordos, China is suffering from a significant drop in earth surface level. However, such method can lead to bias in terms of its accuracy. In this paper, land displacement in Ordos between 8 January 2007 and 19 January 2011 was mapped using L-band ALOS Phased Array type L-band Synthetic Aperture Radar (PALSAR) data. Twenty PALSAR images were utilized to generate both Differential Synthetic Aperture Radar Interferometry (DInSAR) and time-series InSAR (TS-InSAR) results. Several locations in the eastern Ordos experiencing rapid land subsidence were identified. The subsidence rates ranging from −30 mm year−1 to 30 mm year−1 were measured in line-of-sight direction. The comparison between TS-InSAR and DInSAR results, although showing good agreement in general, reveals some gaps in time-series map near Qu Jia Liang coalmine mainly due to sudden changes within the four-year period. DInSAR result was exploited to fill these gaps after removing the tropospheric stratification phase delay and the verification step was conducted over the relatively stable region identified by TS-InSAR analysis. At last, the refined DInSAR result was converted into time-series velocity map and superimposed to TS-InSAR outcome to generate a final product.

An On-Demand Web Tool for the Unsupervised Retrieval of Earth’s Surface Deformation from SAR Data: The P-SBAS Service within the ESA G-POD Environment

This paper presents a web tool for the unsupervised retrieval of Earth’s surface deformation from Synthetic Aperture Radar (SAR) satellite data. The system is based on the implementation of the Differential SAR Interferometry (DInSAR) algorithm referred to as Parallel Small BAseline Subset (P-SBAS) approach, within the Grid Processing on Demand (G-POD) environment that is a part of the ESA’s Geohazards Exploitation Platform (GEP). The developed on-demand web tool, which is specifically addressed to scientists that are non-expert in DInSAR data processing, permits to set up an efficient on-line P-SBAS processing service to produce surface deformation mean velocity maps and time series in an unsupervised manner. Such results are obtained by exploiting the available huge ERS and ENVISAT SAR data archives; moreover, the implementation of the Sentinel-1 P-SBAS processing chain is in a rather advanced status and first results are already available. Thanks to the adopted strategy to co-locate both DInSAR algorithms and computational resources close to the SAR data archives, as well as the provided capability to easily generate the DInSAR results, the presented web tool may contribute to drastically expand the user community exploiting the DInSAR products and methodologies.

Polarimetric Optimization of Temporal Sublook Coherence for DInSAR Applications

The application of differential synthetic aperture radar interferometry (DInSAR) techniques has been traditionally limited to the single-polarimetric case. The launch of satellites with polarimetric capabilities has triggered the synergy between polarimetric and interferometric algorithms, leading to a significant improvement in final DInSAR products. During the last years, the different polarimetric optimization techniques available have been successfully applied to the so-called classical phase quality estimators, i.e., the coherence and the amplitude dispersion estimators. In this context, a new estimator to evaluate the pixels' phase quality, referred to as temporal sublook coherence (TSC), has recently demonstrated to provide promising results in DInSAR applications. The nature of this estimator, which is based on exploiting the spectral properties of pointlike scatterers through the coherence evaluation of different sublooks of the image spectrum, allows its adaptation to the existing polarimetric optimization methods. This letter presents the benefits of extending the TSC estimator to work with fully polarimetric data. For this purpose, a fully polarimetric data set consisting of ten X-band ground-based SAR (GB-SAR) images is employed. The final DInSAR results obtained by means of TSC polarimetric optimization are compared with the ones obtained with its classical single-polarimetric approach, achieving up to more than a twofold increase in the pixels' density.

Land subsidence in the Cerro Prieto Geothermal Field, Baja California, Mexico, from 1994 to 2005: An integrated analysis of DInSAR, leveling and geological data

Cerro Prieto is the oldest and largest Mexican geothermal field in operation and has been producing electricity since 1973. The large amount of geothermal fluids extracted to supply steam to the power plants has resulted in considerable deformation in and around the field. The deformation includes land subsidence and related ground fissuring and faulting. These phenomena have produced severe damages to the local infrastructure such as roads, irrigation canals and other facilities. In this paper, the technique of Differential Synthetic Aperture Radar Interferometry (DInSAR) is applied using C-band ENVISAR ASAR data acquired between 2003 and 2006 to determine the extent and amount of land subsidence in the Mexicali Valley near Cerro Prieto Geothermal Field. The DInSAR results were compared with published data from precise leveling surveys (1994–1997 and 1997–2006) and detailed geological information in order to improve understanding of the temporal and spatial distributions of anthropogenic subsidence in the Mexicali Valley. The leveling and DInSAR data were modeled to characterize the observed deformation in terms of fluid extraction. The results confirm that the tectonic faults control the spatial extent of the observed subsidence. These faults likely act as groundwater flow barriers for aquifers and reservoirs. The shape of the subsiding area coincides with the Cerro Prieto pull-apart basin. In addition, the changes in spatial pattern and rate of the subsidence are correlated with the development of the Cerro Prieto Geothermal Field.

ALOS PALSAR D-InSAR for land subsidence mapping in Jakarta, Indonesia

Differential synthetic aperture radar interferometry (D-InSAR) is a technique capable of detecting land surface deformation. In this research, we use Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) data to investigate land subsidence in Jakarta during 2007 and 2008. It is found that four northern areas in the city exhibit clear indications of land subsidence. The location of the centre of subsidence is estimated, and the subsidence volume is evaluated for each area using the unwrapping method as a further process of using D-InSAR results. The subsidence depth and volume around the centre are estimated to be 10–22 cm and 0.2 × 105 – 4.2 × 105 m3, respectively, in the study time period. Comparison with ground survey data indicates that the D-InSAR analysis gives reliable estimates of the subsidence in an urban environment.