SAR Methods Research Articles

Development of L-band fully polarimetric SAR algorithm for forest biomass retrieval using 7SD and random forest regression

Forest biomass is essential for carbon budgeting, biodiversity health, and climate change research. This study developed a novel L-band fully polarimetric SAR method for estimating aboveground biomass (AGB) in a forested region in India. Biomass was estimated using fully polarimetric ALOS-2/PALSAR-2 data sets and field AGB measurements. To estimate forest AGB, the algorithm employs a seven-component scattering power decomposition (7SD) and a random forest regression (RFR) machine-learning approach. By implementing the 7SD model, the seven scattering powers were extracted from ALOS-2/PALSAR-2 inverted for aboveground biomass. The field data were used to validate the biomass estimated by the model. The 7SD model estimated AGB in Shivamogga was consistent with field measured biomass. The root mean squared error (RMSE) and relative RMSE with respect to mean AGB were 21.94 Mg/ha and 19.46, respectively, which are within acceptable ranges. The 7SD model was also used for cross-validation at Tundi Forest, where the relative RMSE with respect to the mean AGB was 22.9. The scattering powers generated from L-band fully polarimetric data can be useful in tropical forest AGB estimation.

A Two-Step Phase Compensation-Based Imaging Method for GNSS-Based Bistatic SAR: Extraction and Compensation of Ionospheric Phase Scintillation

A Two-Step Phase Compensation-Based Imaging Method for GNSS-Based Bistatic SAR: Extraction and Compensation of Ionospheric Phase Scintillation

Time-series InSAR reveals new insights into land subsidence in the Yellow River Delta, China

In the past decade, the synthetic aperture radar interferometry (InSAR) technique has been extensively employed in deltas, making it possible to obtain more subsidence signals. However, the spatiotemporal nonlinearity of land subsidence often results in inaccurate estimations. Based on 72 Sentinel-1A images captured from 2016 to 2021 and the time-series persistent scatterer-interferometric SAR (PS-InSAR) method, we comprehensively analyze the temporal and spatial dynamics of recent land subsidence in the Yellow River Delta (YRD). The findings suggest a notable spatial shift in the subsidence funnel area within this delta region over the past 6 years (2016–2021), with gradual westward movement from the salt fields in the northeast to those in the central north. Additionally, with 2020 as the demarcation point, there was a notable change in magnitude, initially exhibiting acceleration at −333 mm/yr, followed by deceleration at −231 mm/yr and culminating in renewed acceleration at −413 mm/yr. The subsidence characteristics may be attributed to changes in the underground brine reserves, leading to consolidation of the confined aquifer. Furthermore, the ground subsidence trend suddenly slowed at the end of 2019, which we speculate is related to the significant reduction in human activities caused by COVID-19 prevention and control measures.

Prediction of viral protease inhibitors using proteochemometrics approach

Being widely accepted tools in computational drug search, the (Q)SAR methods have limitations related to data incompleteness. The proteochemometrics (PCM) approach expands the applicability area by using description for both protein and ligand structures. The PCM algorithms are urgently required for the development of new antiviral agents. We suggest the PCM method using the TLMNA descriptors, combining the MNA descriptors of ligands and protein sequence N-grams. Our method was validated on the viral chymotrypsin-like proteases and their ligands. We have developed an original protocol allowing us to collect a comprehensive set of 15 protein sequences and more than 9000 ligands from the ChEMBL database. The N-grams were derived from the 3D-based alignment, accurately superposing ligand-binding regions. In testing the ligand set in SAR mode with MNA descriptors, an accuracy above 0.95 was determined that shows the perspective of the antiviral drug search in virtual chemical libraries. The effective PCM models were built with the TLMNA descriptor. The strong validation procedure with pair exclusion simulated the prediction of interactions between the new ligands and new targets, resulting in accuracy estimation up to 0.89. The PCM approach shows slightly lower accuracy caused by more uncertainty compared with SAR, but it overcomes the problem of data incompleteness.

An Imaging Method for Arc Array Bistatic SAR With an Accelerated Moving Transmitter

An Imaging Method for Arc Array Bistatic SAR With an Accelerated Moving Transmitter

A Two-Step Nonstop-and-Go Phase Compensation Method for Spaceborne SAR With High-Resolution High-Squint-Angle and Wide-Swath

A Two-Step Nonstop-and-Go Phase Compensation Method for Spaceborne SAR With High-Resolution High-Squint-Angle and Wide-Swath

Improved Target Imaging Method for Arc Array Bistatic SAR with a Small Satellite Transmitter

Improved Target Imaging Method for Arc Array Bistatic SAR with a Small Satellite Transmitter

An Image Fusion Method of SAR and Optical Images, Based on Image Intensity Fields, by Reducing the Effect of Speckle Noise

An Image Fusion Method of SAR and Optical Images, Based on Image Intensity Fields, by Reducing the Effect of Speckle Noise

An Accurate and Efficient BP Algorithm Based on Precise Slant Range Model and Rapid Range History Construction Method for GEO SAR

The Geosynchronous Satellite Synthetic Aperture Radar (GEO SAR) operates at a high orbital altitude, resulting in an extended imaging time and substantial variations in slant range. Additionally, the GEO SAR satellite orbit experiences a bending effect, and the target’s movement, caused by the Earth’s rotation, is influenced by the Earth’s curvature. The back-projection (BP) algorithm has been proven to be a highly effective technique for precise imaging with GEO SAR by processing these specific echo signals. However, this approach necessitates considerable computational resources. Existing BP algorithms, such as the fast BP algorithm, do not consider the “Stop-and-Go” error present in GEO SAR. Consequently, we developed a Precise Slant Range Model that considers the motion of both the satellite and targets. The model incorporates velocity and acceleration factors to accurately represent the signal transmission from transmission to reception. Additionally, we propose a Rapid Range History Construction Method to lessen the computational burden of generating the three-dimensional range history array. By utilizing the Precise Slant Range Model and the Rapid Range History Construction Method, and employing parallel processing through aperture segmentation, we propose an Accurate and Efficient BP imaging algorithm suitable for GEO SAR applications. To validate its effectiveness, simulations were conducted using the parameters of a GEO SAR system. The results indicated that the proposed algorithm enhances the imaging quality of GEO SAR, reduces the processing time, and achieves high-precision rapid imaging, thereby improving operational efficiency.

A sensitive UPLC-MS/MS method for the simultaneous assay and trace level genotoxic impurities quantification of SARS-CoV-2 inhibitor-Molnupiravir in its pure and formulation dosage forms using fractional factorial design

Two potential genotoxic impurities were identified (PGTIs)-viz. 4-amino-1-((2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)tetrahydrofuran-2-yl)pyrimidin-2(1H)-one (PGTI-1), and 1-(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)tetrahydrofuran-2-yl)pyrimidin-2,4(1H,3H)-one (PGTI-II) in the Molnupiravir (MOPR) synthetic routes. COVID-19 disease was treated with MOPR when mild to moderate symptoms occurred. Two (Q)-SAR methods were used to assess the genotoxicity, and projected results were positive and categorized into Class-3 for both PGTIs. A simple, accurate and highly sensitive ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) method was optimized for the simultaneous quantification of the assay, and these impurities in MOPR drug substance and formulation dosage form. The multiple reaction monitoring (MRM) technique was utilized for the quantification. Prior to the validation study, the UPLC-MS method conditions were optimised using fractional factorial design (FrFD). The optimized Critical Method Parameters (CMPs) include the percentage of Acetonitrile in MP B, Concentration of Formic acid in MP A, Cone Voltage, Capillary Voltage, Collision gas flow and Desolvation temperature were determined from the numerical optimization to be 12.50 %, 0.13 %, 13.6 V, 2.6 kV, 850 L/hr and 375 °C, respectively. The optimized chromatographic separation achieved on Waters Acquity HSS T3 C18 column (100 mm × 2.1 mm, 1.8 µm) in a gradient elution mode with 0.13% formic acid in water and acetonitrile as mobile phases, column temperature kept at 35 °C and flow rate at 0.5 mL/min. The method was successfully validated as per ICH guidelines, and demonstrated excellent linearity over the concentration range of 0.5–10 ppm for both PGTIs. The Pearson correlation coefficient of each impurity and MOPR was found to be higher than 0.999, and the recoveries were in between the range of 94.62 to 104.05% for both PGTIs and 99.10 to 100.25% for MOPR. It is also feasible to utilise this rapid method to quantify MOPR accurately in biological samples.

Morphological Analysis of Anak Krakatau Volcano after 22 December 2018 Eruption using Differential Interferometry Synthetic Aperture Radar (DInSAR)

Anak Krakatau Volcano is an active volcano located in the Krakatau Complex, Sunda Strait, Indonesia. On 22 December 2018, the volcano experienced a major eruption that led to a tsunami that devastated the shores of the islands of Java and Sumatra and killed up to 437 people. The eruption also destroyed the volcano’s body and change its shape drastically and forming a large crater in the southwestern part. After that eruption, the volcano continues to grow up. This research aims to analyze the deformation of the Anak Krakatau Volcano post-2018 eruption by using the differential interferometry SAR method (DInSAR). In order to support the analysis, we additionally compare the DInSAR result with tectonic-volcanic activity. Sentinel 1-A type SLC satellite imagery data from 5 June 2019 to 7 January 2020; consisting of 19 images or 18 pairs as master and slave were used to producing a deformation map. DInSAR result shows the volcano was generally experiencing deflation during the period, ranging from -1.03 to -4.81 cm (-3.01 cm average). However, inflation also occurred ranging from 0 to 5.99 cm, correlating with shallow and deep volcanic activity and followed by eruptions in October 2019 when the highest activities were observed. Furthermore, coherence value should be highly considered along with DInSAR processing, and this research allows that coherence to be acceptable.

Short communication: Potential of Sentinel-1 interferometric synthetic aperture radar (InSAR) and offset tracking in monitoring post-cyclonic landslide activities on Réunion

Abstract. This study examines the results of an interferometric synthetic aperture radar (InSAR) and SAR offset tracking (OT) study in Cirque de Salazie (CdS), Réunion Island, France, within the context of the RENOVRISK project, a multidisciplinary programme to study the cyclonic risks in the south-western Indian Ocean. Despite numerous landslides in this territory, CdS is one of the more densely populated areas on Réunion Island. One of the aims of the project is to assess whether Sentinel-1 SAR methods can be used to measure landslide motion and/or accelerations due to post-cyclonic activity in CdS. We concentrate on the post-2017 cyclonic activity. We use the Copernicus Sentinel-1 data, acquired between 30 October 2017 and 6 November 2018. Sentinel-1 is a C-band SAR, and its signal can be severely affected by the presence of changing vegetation between two SAR acquisitions, particularly in CdS, where the vegetation canopy is well developed. This is why C-band radars such as the ones on board RADARSAT or Envisat, characterized by low acquisition frequency (24 and 36 d, respectively), could not be routinely used in CdS to measure landslide motion with InSAR in the past. In this study, we use InSAR and OT techniques applied to Sentinel-1 SAR. We find that C-band SAR on board Sentinel-1 can be used to monitor landslide motion in densely vegetated areas, thanks to its high acquisition frequency (12 d). OT stacking reveals a useful complement to InSAR, especially in mapping fast moving areas. In particular, we can highlight ground motion in the Hell-Bourg, Ilet à Vidot, Grand-Ilet, Camp Pierrot, and Le Bélier landslides.

An Image Denoising Method for Arc-Scanning SAR for Airport Runway Foreign Object Debris Detection

Arc-scanning synthetic aperture radar (AS-SAR) is an emerging technical means for detecting foreign object debris (FOD). Most FOD are small and appear as weak targets with a low signal-to-noise ratio (SNR) in AS-SAR images. Therefore, image noise is a fundamental challenge in detecting FOD on airport runways that leads to many false alarms. A weak scattering denoising method is proposed to aim at the noise caused by speckle and rough surface scattering. To enhance FOD detection, a transformation parameter concept is offered and adopted, which has different characteristics for the target and background. This paper estimates the transformation parameter through logarithms, normalization, and morphological erosion and optimizes them with edge-preserving filtering. The results show that despeckling and runway scattering suppression can be simultaneously implemented, and that field experiments validate the performance of this method.

Monitoring Land Subsidence along the Subways in Shanghai on the Basis of Time-Series InSAR

In recent years, Shanghai has entered a stage of microscale land subsidence, but the uneven subsidence is still significant, with long-term impacts on the operational safety of subways and other infrastructures. On the basis of 154 high-resolution Terra Synthetic Aperture Radar-X (TerraSAR-X) images captured from 2013 to 2020 and the time-series persistent scatterer-interferometric SAR (PS-InSAR) method, the land subsidence along the subways in Shanghai was acquired, and the levelling data of 56 benchmarks were used to validate the measurements derived by PS-InSAR. The results indicated that the two data sets agreed well, with a correlation coefficient of 0.9 and maximum D-value of 4.0 mm derived from six pairs of comparative data sequences. The proportion of PS points showing deformation rates between −3.0 mm/a and 3.0 mm/a reached 99.4%. These results indicated that the land subsidence trend along the subway was relatively stable overall, while significant deformation was distributed mainly along the suburban subways, especially the lines that were newly open to traffic, such as Line 5 and the Pujiang line (PJ Line); along these lines, the proportions of PS points with deformation rates exceeding ±3 mm/a were 7.2% and 7.6%, respectively, and the proportions were much smaller in the other lines. The maximum cumulative deformation (MCD) along the subways was located between Jiangchuan Road Station and Xidu Station of Line 5 with a value of −66.4 mm, while the second and third MCDs were −48.2 mm along Line 16 and −44.5 mm along PJ Line, respectively. Engineering constructions, such as human-induced ground loads, foundation pit constructions, and road constructions, were the main factors affecting local land subsidence. The analysis results also showed that land subsidence was relatively significant during the period before the subways were open to traffic due to subway construction, while land subsidence clearly slowed after the subway lines were open to traffic. This deceleration in land subsidence was closely related to the rise in the groundwater level.

A fast and accurate RFID tag positioning method based on AoA hologram and hashtables

RFID-based item localization for large-scale warehousing and inventorying applications has been gradually developing over the years. In these settings, fast and accurate item localization with low deployment cost is vital for inventory visibility and warehouse efficiency. However, existing tag positioning methods based on a single antenna offer either fast inference with low accuracy or high accuracy with slow inference. In this paper, we propose a phase-based SAR tag positioning method that offers both merits. Firstly, the traditional holograms formed in existing SAR methods are completely replaced by a one-step version of the recently proposed hologram mask (Angle-of-Arrival hologram), to accelerate the tag positioning task. Secondly, a pair of hashtables is implemented to output directly hologram grids from phase measurements, reducing further the hologram construction time. Thirdly, a pre-processing cross-validation stage tests the measurements at each operating frequency to determine the one leading to the lowest positioning error. After this, the model is trained and tested solely on this frequency, limiting both the inference time and on-site collection time. Finally, we efficiently infer the height information of tags from a single antenna moving along a rectilinear horizontal trajectory. Our comparative experiments show that our model achieves similar positioning accuracy to the state-of-the-art accuracy methods while offering a much lower inference time, in both short-range and long-range settings.

Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring

ABSTRACT More than half a decade after the launch of the Sentinel-1A C-band SAR satellite, several near real-time forest disturbances detection systems based on backscattering time series analysis have been developed and made operational. Every system has its own particular approach to change detection. Here, we have compared the performance of the main SAR-based near real-time operational forest disturbance detection systems produced by research agencies (INPE, in Brazil, CESBIO, in France, JAXA, in Japan, and Wageningen University, in the Netherlands), and compared them to the state-of-the-art optical algorithm, University of Maryland’s GLAD-S2. We implemented an innovative validation protocol, specially conceived to encompass all the analysed systems, which measured every system’s accuracy and detection speed in four different areas of the Amazon basin. The results indicated that, when parametrized equally, all the Sentinel-1 SAR methods outperformed the reference optical method in terms of sample-count F1-Score, having comparable results among them. The GLAD-S2 optical method showed superior results in terms of user’s accuracy (UA), issuing no false detections, but had a lower producer accuracy (PA, 84.88%) when compared to the Sentinel-1 SAR-based systems (PA90%). Wageningen University’s system, RADD, proved to be relatively faster, especially in heavily clouded regions, where RADD warnings were issued 41 days before optical ones, and the one that better performs on small disturbed patches (0.25 ha) with a UA of 70.11%. Of all the high-resolution SAR methods, CESBIO’s had the best results regarding UA (99.0%). Finally, we tested the potential of three hypothetical combined optical-SAR systems. The results show that these combined systems would have excellent detection capabilities, exceeding largely the producer’s accuracy of all the tested methods at the cost of a slightly diminished user’s accuracy, and constitute a promising and feasible approach for the forthcoming forest monitoring systems.

Anti-Jamming Method for SAR Using Joint Waveform Modulation and Azimuth Mismatched Filtering

Anti-Jamming Method for SAR Using Joint Waveform Modulation and Azimuth Mismatched Filtering

An Effective Multimodel Fusion Method for SAR and Optical Remote Sensing Images

An Effective Multimodel Fusion Method for SAR and Optical Remote Sensing Images

Geometric constraints based 3D reconstruction method of tomographic SAR for buildings

Geometric constraints based 3D reconstruction method of tomographic SAR for buildings

The influence of Sentinel-1 SAR sub-swath on the recorded backscatter time-series over managed hemiboreal forests

Abstract The view angle range of Sentinel-1 SAR in the Interferometric Wide swath (IW) measurement mode is 29.1° – 46.0°. The dependence of backscatter on the arbitrary local incidence angle is usually corrected using a linear regression model where the incidence angle is a predictor variable. We analysed the whole time series of Sentinel-1 SAR VV-polarised backscatter over the flat 15×15 km test site in Laeva, Estonia (26° 26′ 43″ E; 58° 31′ 56″ N). Time series containing measurements from three different orbits were constructed for 3,159 stands from nighttime data and for 1,105 stands from daytime data. We can confirm that daytime backscatter is systematically greater than nighttime backscatter. We found a significant deviation from linearity in the backscatter dependence on local incidence angle. The empirical finding may be caused by the microwave scattering dependence on local incidence angle or by the influence of Sentinel-1 SAR sub-swath configuration in the Terrain Observation with Progressive Scans SAR (TOPSAR) method that is used for the measurements.