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Ensuring the safety and operational efficiency of hydraulic infrastructures is paramount, considering the widespread consequences that damages can inflict on people, communities, and the environment. To mitigate risks and prevent significant losses, continuous surveillance is vital. While some damages might appear minor, they can jeopardize the complete operational reliability of dams, leading to substantial economic losses, especially in energy production and related activities. The rapid growth in 20th-century infrastructure development globally has made security monitoring a necessity for numerous civil structures. Rigorous inspection programs, particularly for reservoir dams, are essential for safeguarding citizens and their properties. However, individually monitoring each dam is often impractical due to the associated costs and time constraints, potentially posing safety risks. Fortunately, satellite-based differential radar interferometry (DInSAR) offers an effective and cost-efficient remote sensing solution. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques, particularly utilizing Persistent Scatterers, have proven successful in monitoring various infrastructures, natural phenomena, and geological activities. MT-InSAR provides precise measurements without the need for fieldwork, utilizing historical SAR image archives dating back to the 1990s. Technological advancements, such as the Sentinel-1 C-band with a six-day revisit time until the end of 2021, have enhanced monitoring capabilities. Additionally, commercial radar images in the X-band and the development of multi-interferometric InSAR techniques have opened new avenues for monitoring. This study showcases the adaptation and application of MT-InSAR for monitoring dams and large ponds constructed with loose materials. By assessing vertical displacements and consolidation rates, the technique identifies potential issues, aiding in further field investigations. Case studies involving dams and large reservoirs in Andalusia illustrate the effectiveness of satellite radar interferometry in monitoring their structural stability from space as a routine practice. [ABSTRACT FROM AUTHOR]

A fully automated processing system for measuring long-term ground deformation time series and deformation rates frame-by-frame using the Differential Interferometric Synthetic Aperture Radar (DInSAR) processing technique was developed and tested. Among the several factors that affect DInSAR's precision, such as temporal decorrelation and atmospheric noise, it was observed that seasonal spatial-temporal variability in radar penetration depth is the greatest contributor to the loss of precision of the long-term deformation rate measurement. This spatial-temporal signal is described for a specific region in the northern US; however, it is widely observed in multiple regions. In these regions, a gradual penetration depth increase is observed in fall and winter, and an abrupt penetration depth decrease is observed in spring. The latter effect is likely caused by rapid melting of ice and snow that, at the same time, significantly reduces interferometric coherence. Within a specific geographic region, radar penetration depth spatially varies proportionally to the elevation due to an elevation-dependent temperature gradient, producing artifacts that correlate well with the topography. This signal does not extend to high-elevation regions (above ~2500 m) that do not experience seasonal thawing, which allows for distinguishing it from the topography-dependent atmospheric signals. Without accounting for the spatial-temporal variability in radar penetration depth, deformation time series in these areas can contain either an annual periodic signal with an amplitude of over 0.1 m or, if the abrupt penetration depth decrease produced by melting is not resolved due to lower coherence, an erroneous interannual trend. Spatial-temporal variability in radar penetration depth needs to be better understood and corrected to improve the precision of long-term deformation rate products, particularly in regions susceptible to seasonal freezing and thawing. [ABSTRACT FROM AUTHOR]

This paper focuses on the automated extraction of textural features from segmented Sentinel-1A Synthetic Aperture Radar (SAR) imagery, which was captured on 25th August 2017. Textural properties play a pivotal role in discerning regions of interest in satellite imagery, essential for precise classification in diverse applications, including remote sensing, medical image analysis, biometric analysis, and document image analysis. To achieve this, the Local Adaptive Threshold (LAT) technique was employed for segmenting the foreground and background areas of the pre-processed vertical transmit-vertical receive (VV) polarized Sentinel-1A SAR data. The approach relies on second-order statistics, specifically co-occurrence measures, which evaluate the relationships between pairs of pixels within their local neighbourhood's in the input image. Four fundamental second-order statistical measures, namely correlation, energy, homogeneity, and contrast, were computed using the Grey Level Co-occurrence Matrix (GLCM). The GLCM was generated by quantizing the foreground region of the segmented grey-scale image into different levels, including 8, 16, and 64 grey levels, considering two inter-pixel distances, d=1 and d=2, and adopting an omni-directional orientation (θ = 00, 450, 900, 1350).The results underscore the effectiveness of the GLCM-based approach in computing second-order statistical texture measures from the segmented SAR image. Notably, the findings highlight that quantizing the image to Ng=8 with d=1 and considering omni-directional statistical measures (θ = 00, 450, 900, 1350) significantly enhances performance. [ABSTRACT FROM AUTHOR]

Reclaimed airports usually have fragile geological structures and are susceptible to the uneven ground settlements caused by filling-material consolidation, underground construction, and dynamic loading from takeoff and landing of aircrafts. Therefore, deformation monitoring is of great significance to the safe operation of reclaimed airports. This study adopts an improved permanent-scatterer interferometric synthetic-aperture radar strategy to map the spatiotemporal deformation of Shenzhen Bao'an International Airport in China using ascending and descending Envisat/ASAR data acquired from 2007 to 2010 and Sentinel-1 data from 2015 to 2019. The results show that uneven settlements of the airport concentrate in the new reclaimed land. Then we explore the settlement characteristics of each functional area. Furthermore, we separate out the dynamicload settlement of runway No. 2 and confirm the settlements caused by dynamic load. This study provides new ideas for studying deformation in similar fields, and technical references for the future construction of Shenzhen Airport. [ABSTRACT FROM AUTHOR]

Subsidence in coastal deltas is a challenging issue globally, influenced by both climate and anthropogenic pressures. Owing to its rich economic value, the Godavari Delta on the east coast of India attracts the human population and is therefore a hub of developmental activities. We quantified the line of sight (LOS) rate of land deformation in the Godavari Delta, India, for two different periods using the time series interferometric analysis of Advanced Land Observing Satellite Phase Arrayed L-band Synthetic Aperture Radar (ALOS PALSAR) (2007–2011) and C-band Sentinel-1A (2017–2020) datasets. This approach was based on the Small Baseline Subset (SBAS) algorithm, which constructed 76 (ALOS) and 333 (Sentinel-1A) pairs of interferograms. The results indicated that the majority of deltas had varying LOS deformation rates in both periods. The southern and northern coastline of the deltas showed subsidence (-10 to -20 mm/yr) and uplift (5 mm to 7 mm/yr), respectively, from 2007 to 2011. The uplift (11 mm/yr) during 2017–2020 was attributed to coastal erosion and accretion during the study period. Statistical analyses showed that the majority of the coastline experienced erosion from 2006 to 2011, ranging from 0 ‐30 m/yr. Conversely, during 2017–2019, accretion ranging from 0-30 m/yr was dominant. The Kakinada spit has recently experienced an uplift of 8 mm/yr. Many factors contributing to deformation, such as groundwater fluctuations, rainfall, land use and land cover (LULC) changes, and water quality, were explored. Groundwater level variations were strongly correlated with the rate of deformation. A direct relationship was also observed between water recharge through rainfall and the ground deformation rate. The subsidence rate was estimated as 0 to ‐8 mm/yr from 2007-2011 and -10 to -20 mm/yr for 2017–2020 in the Godavari Delta. Increased urban areas and land conversion from the LULC analysis were the causative factors of subsidence in this region. Thus, the Godavari Delta will become highly vulnerable, as the region has shown various LOS deformation rates. Studies on land subsidence are highly relevant for effective coastal management planning and management. • First study to explore the ground deformation in Godavari delta. • Role of freshwater influence and land use are discussed. • Brought out the human interventions in the Godavari delta. • Needed for environmental management of the Godavari delta. [ABSTRACT FROM AUTHOR]

In recent years, a second generation of Synthetic Aperture Radar (SAR) satellite sensor has been designed and, partially, put into operation, leading to an important breakthrough in Earth Science studies. The common characteristics of such new systems are, indeed, a reduced revisit time (as short as a few days) and, in most cases, an improved spatial resolution (as small as a few meters), providing scientists with unprecedented data for the mapping and monitoring of natural and human-induced hazards. This paper provides an overview on the new observational capability offered by the second generation of SAR sensors, especially in the field of ground deformation analysis for mitigating the risk associated with natural and human-induced hazards. In particular, we exploit the high resolution X-band data acquired by the COSMO-SkyMed (CSK) constellation to show how deformation phenomena characterized by limited spatial extent and extremely fast dynamics can be detected and investigated in details. Whenever possible, we compare the achieved results with those obtained by using data collected by the first generation ERS-1/2 and ENVISAT systems. A comparison with one ALOS satellite dataset is also included. Most of the results, based on the application of Differential SAR Interferometry (DInSAR) techniques, highlight how this technology is not anymore just a sophisticated tool for remotely studying surface deformation phenomena, but it is becoming an operational system for near-real time deformation monitoring. Moreover, we also show how the improved spatial resolution extends the possibility to exploit SAR image amplitude, instead of phase, for direct comparison with optical data and for imaging large deformation episodes, typically associated with strong seismic events, for which DInSAR may fail. [ABSTRACT FROM AUTHOR]

The article looks at developments in the use of radar remote sensing. Topics discussed include the basics of radar and interferometric synthetic aperture radar (InSAR) imaging and the revolution of InSAR technology on monitoring natural hazards and characterizing natural resources. Also highlighted are some of the emerging InSAR technologies, including multi-aperture InSAR, SqueeSAR and SAR Tomography.

In spaceborne SAR (Synthetic Aperture Radar) , the pulse compression of LFM (Linear Frequency Modulated) signal would be affected by the system phase error which changes in the space environment. Therefore a method of in-orbit phase pre-distortion for LFM signal based on polynomial fitting is put forward, in which the system phase error is obtained by in-orbit calibration, the phase compensation parameters are obtained by polynomial fitting on ground, and by uploading phase compensation parameters, LFM signal with compensation phase is generated by in-orbit calculation. The basis of the theory is described, as well as the realizing flow of the method is presented. Also, hardware requirements and advantages of the method are analyzed. The method is compared with other methods, and is verified to be efficient by the simulation and experiments in real system. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) is a special type of active microwave sensor, which has got a wide range of applications in remote sensing. However, the performance of SAR systems may be affected by radio frequency interference (RFI) in several geographic regions. A novel singular value decomposition method is proposed for radio frequency interference suppression applied to SAR. This method decomposes the singular vectors of the received signal with RFI into interference subspace and signal subspace. The orthogonality of the two subspaces is used to suppress the RFI. The point-target simulation is used to show the working principle of the proposed algorithm. The experimental results based on SAR real data are also shown to verify the proposed algorithm. [ABSTRACT FROM AUTHOR]

Deceptive jamming technology against inverse synthetic aperture radar is matured now, which is meaningful in military application. But the research on anti-jamming technology for inverse synthetic aperture radar (ISAR) is still not a mature technology. Through the analysis on the theory of deceptive jamming technology against ISAR, a new method for anti-jamming against ISAR based on linear frequency modulation signal's frequency slope-varying is presented. The false target echo energy is suppressed due to frequency modulation slope mis-matching. Doppler domain averaging is adopted for improving the quality of the ISAR image, which helps automatic target recognition. Simulation result based on simulating data shows the validity of the new algorithm. [ABSTRACT FROM AUTHOR]

Experimental real and synthetic aperture radar are developed from the base-band digital unit to the analogue RF parts, based on solid state units, using pulse compression for radar imaging. Proper QPSK code is found for matched filter. [ABSTRACT FROM AUTHOR]

Delineating management zones is important in agriculture for implementing site-specific practices. We delineated within-field homogeneous zones over a corn and a wheat field using high spatial resolution multi-temporal airborne C-band synthetic aperture radar (SAR) imagery with an object-based fuzzy k-means classification approach. Image objects were generated by a segmentation procedure implemented in eCognition® software, and were classified as basic processing units using SAR data. Results were evaluated using analysis of variance and variance reduction of soil electrical conductivity (EC), leaf area index (MI), and crop yield. The object-based approach provided better results than a pixel-based approach. The variance reduction in LAI, and soil EC varied with SAR acquisition time and incidence angle. Although the variance reduction of yield was not as significant as that of MI and EC, average yield among the delineated zones were different in most cases. The SAR data classification produced interpretable patterns of soil and crop spatial variability, which can be used to infer within-field management zones. [ABSTRACT FROM AUTHOR]

The article reports on GeoSar's interferometric synthetic aperture radar data (IFSAR) as topographic mapping system in equatorial regions. Geosar technology is developed by NASA's Jet Propulsion Laboratory, U.S. Department of Defense's Defense Advanced Research Projects Agency, Califonia Department of Conservation, and Fugro EarthData, Inc. It cam collect data from an altitude of 40,000 ft. at an airspeed of over 350 mph. Its system operates two frequencies namely X-band and P-band whose wavelengths have a bandwidth of 160 MHz. It also maps drainage features, canopies and wetland habitats in equatorial regions.

Based on parallel digital signal processing (DSP) technology, the design and implementation of a real-time quick look system is presented. Many kinds of quick look imaging algorithms of spaceborne synthetic aperture radar (SAR) are compared. According to certain parameters of spaceborne SAR system, an optimized real-time imaging algorithm is proposed. The system is used to fulfill 1/4 of range resolution and four-look of azimuth real-time imaging of L band spaceborne SAR Data. Finally, the results of image quality measures are given. [ABSTRACT FROM AUTHOR]

The first aim of this paper is to show how the joint use of Digital Surface Models (DSMs) coming from different sources may improve the understanding of an urban environment. More specifically, we consider loser and radar three-dimensional data over the same urban area and show that they can be profitably combined to improve building extraction. We exploit the better vertical and horizontal accuracy of the laser DSM, assumed to be available only for a small area, to ease the deformation of Interferometric Synthetic Aperture Radar (INSAR) DSM with built structures. To achieve this, we propose a method based on subsequent steps of geometrical correction, and mainly on a simple "stretching step" that uses laser data as a reference to adjust INSAR-derived building footprints. We show quantitative results obtained from two different urban areas, using different laser and radar data sets, to assess advantages and drawbacks of the proposed method. [ABSTRACT FROM AUTHOR]

A complete, high-resolution coastline of Antarctica, extracted from an orthorectified mosaic of Radarsat-1 synthetic aperture radar (SAR) images through a sequence of automated image processing algorithms, is presented. A locally adaptive thresholding method is used to segment the orthorectified SAR images; while image-object formation and labeling, and edge-tracing techniques are used to process the segmented images into vector-based cartographic products of coastline, defined here as the boundary between continental ice or rock exposures and sea ice covered ocean. The absolute accuracy of planimetric positioning of the resultant coastline is estimated to better than 130 m, and its spatial resolution (25 m) is adequate for supporting cartographic and scientific applications at 1:50,000 scale. This radar-image-derived coastline gives an accurate description of geometric shape and glaciological characteristics of the Antarctic coasts and also provides a precise benchmark for future change-detection studies. [ABSTRACT FROM AUTHOR]

The magnitude 6.8 Nisqually earthquake occurred on 28 February 2001 at a depth of 50-60 km within the subducting Juan de Fuca plate. The fault parameters are estimated from moment tensor solutions and by comparing the surface displacements from Global Positioning System (GPS) data and from satellite interferometry, with predictions from elastic deformation models. The simple deformation model calculates the coseismic surface displacements caused by an earthquake on an extensional rectangular fault in a uniform half-space. Continuous GPS stations within 200 km of the epicenter resolved horizontal displacements as great as 9 mm (210°) and vertical displacements as great as 13 mm of subsidence near the epicenter. The near-vertical displacements were also determined from a differential interferogram created from synthetic aperture radar (InSAR) data from RADARSAT, the only satellite data available for the event. A maximum vertical subsidence of approximately 20 mm is observed 30 km east of the epicenter. The GPS, InSAR, and moment tensor solutions provide a consistent solution for the rupture parameters of the Nisqually earthquake. The fault has a strike of 180° and a dip of 20° and is centered at 47.10° N and 122.67° W (4 km east and 6 km south of the epicenter) or has a strike of 360° and a dip of 70° and is centered at 47.10° N and 122.69° W (2 km east and 6 km south). The trade-off between fault area and rupture displacement is not resolved by our data, but a good fit is found with the main rupture having an area of 230 km2 and an along-strike length of 23 km and downdip width of 10 km. The rupture area is centered at a depth of 51 km with a scalar moment of 2.0 x 1019 N m and, with the given area, an average rupture displacement of 1.4 m. To refine the interpretation of the GPS and InSAR data, a 3D heterogeneous numerical model was generated having realistic shear moduli structure, a 3D model of the... [ABSTRACT FROM AUTHOR]

Copyright of Atmosphere - Ocean (Canadian Meteorological & Oceanographic Society) is the property of Canadian Meteorological & Oceanographic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Atmosphere - Ocean (Canadian Meteorological & Oceanographic Society) is the property of Canadian Meteorological & Oceanographic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Finding appropriate class-separating metric and labeling rules is crucial in the construction of image classifiers. In this paper a Divergence-Chebyshev Neighbors Pursuit (DCNP) algorithm is proposed for rapid Polarimetric Synthetic Aperture Radar (PolSAR) image classification. First, an information-theoretic divergence is defined to measure the similarity of polarimetric features between pixels. Then a divergence-Chebyshev distance is defined to reveal the affinity of pixels in both the polarization and spatial domains. Moreover, inspired by human's learning characteristic that the knowledge is learned little by little, the DCNP algorithm is designed to progressively determine the labels of unknown pixels. Some experiments are conducted on several real PolSAR image datasets and the results show that our method can achieve accurate classification with a small number of labeled data, and outperforms its counterparts in terms of several guidelines. • A simple PolSAR image classifier based on KNNC is proposed. • A divergence-chebyshev distance is defined to reveal the affinity of pixels. • A DCNP algorithm is proposed to progressively classify pixels. [ABSTRACT FROM AUTHOR]

Examination of the synthetic aperture radar imagery and of the hydraulic characteristics of Maya lowland swamps has led Kevin 0. Pope and Bruce H. Dahlin (‘Ancient Maya Wetland Agriculture: New Insight from Ecological and Remote Sensing Research,’ Journal of Field Archaeology 16 [1989] 87-106) to conclude that there is no connection between lattice patterns in the imagery and raised fields in the swamps. They further conclude that there are no significant numbers of raised fields in periodic swamps. We examine the arguments and points raised and find them tenuous at best, and disingenuous at worst. We conclude that the SAR imagery does indeed indicate raised field and canal systems and that they exist in the large periodic swamps of the Maya lowlands. [ABSTRACT FROM AUTHOR]

• We clarified the urban morphological roles in water detection from SAR images. • Our model captures the spatial heterogeneity of radar's double-bounce effect. • Neighboring building density could contribute to radar's multiple bounces. • Our model can be applied to another city that shares similar urban forms. Satellite remote sensing is an effective method for extracting water bodies on a large scale. Radar imagery, such as synthetic aperture radar (SAR) imagery, can penetrate clouds and provide opportunities for water body identification when in situ observations are difficult to obtain because of severe weather conditions. However, when using SAR images in urban areas to extract water bodies, the radar's double-bounce effect results in complicated backscatter patterns of water near urban features such as buildings due to the side-looking properties of SAR sensors and the vertical urban structures. Therefore, the objective of this study is to propose a reliable urban water extraction framework for SAR images that integrates urban surface morphological features for controlling radar's multiple bounces. Statistical (logistic regression) and machine-learning (random forest) models were used to explore how radar's double-bounce effect influences the prediction performance of urban water extraction. Our findings indicate that when extracting urban water bodies, urban water's backscatter values could be significantly interfered by the neighboring building density above a threshold height that contributes to radar's multiple bounces. Without model calibration, our framework incorporating urban surface morphology demonstrates high prediction ability with an Area Under the Curve (AUC) of 0.914 and with 97.0% of urban water cells correctly identified by testing in another city sharing similar urban forms. In summary, our study provides a better understanding of the role of the urban surface morphology in the double-bounce effect in SAR images, specifically for differentiating urban water and land, thereby improving the accuracy of urban water extraction and enhancing the feasibility of further applications of SAR imagery under complex urban landscapes. [ABSTRACT FROM AUTHOR]

• The landslide deformation is obtained by using Ground-based radar 8 km far away. • We present a GBR deformation extraction method in a complicated environment. • A 3D sliding distribution is achieved by combining two methods of measurement. • The present and future stability state of landslide is inferred. On Oct. 11 and Nov. 3, 2018, two large-scale landslides occurred in the same location in Baige Village, Tibet, and massive rocks fell and encroached into the Jingsha River. These landslides posed a severe risk to the upstream and downstream areas. The occurrence, development and evolution of landslides are accompanied by a large number of changes in measurable variables. The deformation data are one of most important parameters for characterizing change and development trends of a landslide. This paper is centered on the results derived from ground-based radar and space-borne Synthetic Aperture Radar (SAR) images in the post-event phase to monitor the Baige landslides and to assess their residual risk. Two technologies play important roles in identifying and characterizing impending catastrophic slope failures: ground-based radar reveals the horizontal deformation, and satellite SAR images reveal the azimuth and range offset deformation. By combining satellite and ground-based SAR observations, we obtained high-precision three-dimensional (3D) deformation results and found that the vast majority of the instability regions mainly occur in the source area of the slope failures and that the direction of collapse converges from all sides to the middle. Additional information from UAV orthophoto maps and GNSS measurements also reveal that several cracks are distributed on the trailing edge of the landslide and are still moving. The comprehensive results revealed that the moving rock mass has still been remarkably active after the two landslide events. This study combined ground-based and space-borne SAR data to develop a long-term monitoring and stability evaluation process for implementation after a large landslide disaster. Based on the distribution characteristics of the 3D deformation fields, the present and future stability of the Baige Landslide was analyzed. [ABSTRACT FROM AUTHOR]