Spatial Sampling Interval Research Articles

Assessing the accuracy of global digital elevation models for hydrological analysis: the cases of Syria and Russia

Digital elevation models provide valuable information about the surface topography. The resolution and accuracy of the data used to create the models are critical for the results of hydrological analysis. Available global digital elevation models obtain high potential in terms of data sources; however, their performance requires meticulous evaluation for different terrain characteristics and applications. Aim. To determine the accuracy and resolution of data provided by current and old global models, namely SRTM 1, SRTM GL1, V3 ASTER, GMTED2010, PALSAR ALOS, and GTOPO 30, using the example of two terrains. The study considers the areas in Syria (Syrian coast) and Russia (Chernoyarsky and Akhtubinsky districts in the Astrakhan region) represented by different elevation models. A matching degree between model and real elevations measured by GPS was determined to carry out the hydrological analysis of the land surface. For this purpose, three statistical measures, including range, standard deviation and correlation were defined by means of BaseCamp, ARCGIS PRO & SAGA_GIS software. Data resolution indicates the degree of detail represented in the DEM dataset, which is established by the spatial sampling interval or the size of the grid cell used to represent the land surface. Data accuracy refers to the matching degree between the elevation values derived from the DEM and the actual data obtained on the surface. Results. In terms of correlation coefficient and standard deviation, the GMTED 2010 and ASTER V3 model for the Syrian region and the ALOS PALSAR and SRTM GL 1 model for the Russian region prove to be the most effective for hydrological analysis in the absence of accurate local models.

Null Phase Assumption-Based Technique for Constructing the Target Model of Seismic Irregularity on High-Speed Railways

High-speed railways are “lifeline projects” that shoulder the heavy responsibility of transporting relief supplies and medical forces for the first time after earthquakes. To ensure the train’s safety after earthquakes, it is of great urgency to ascertain a post-earthquake speed threshold. To that end, a target model for seismic irregularity emerges as a key parameter. In this paper, a null phase assumption-based technique for the mutual conversion between evolutionary power spectral density and non-stationary signal was proposed. Taking a high-speed railway track-bridge system as the research object, the target model of seismic irregularities was constructed based on the proposed technique. The rationality of the target model of seismic irregularities was verified, and the construction parameter settings were discussed. Moreover, a simplified frequency-domain fitting method for the target model of seismic irregularities was proposed based on the spectral decomposition theory. According to the research findings, the null phase assumption-based technique is capable of performing interconversion between seismic irregularity and its evolutionary power spectral density with satisfactory accuracy. It is recommended to set the minimum number of seismic irregularities, spatial sampling interval, hop size, and length of window function as 50, 0.25[Formula: see text]m, 1, and 40 to 100, respectively.

Single‐Shot Wavefront Sensing with Nonlocal Thin Film Optical Filters

AbstractConventional wavefront sensors suffer from the fundamental limitation of the space‐bandwidth product and have a trade‐off between their spatial sampling interval and dynamic range. Here, nonlocal thin film optical filters with optimized angle‐ and polarization‐dependent responses are leveraged to circumvent the fundamental limitation, and a robust single‐shot wavefront sensing system with a small spatial sampling interval of 6.9 µm and a large angular dynamic range of 15° is realized. The system only requires inserting two multilayer dielectric filters, fabricated using a mature thin film deposition technique, into a conventional 4‐f imaging apparatus. The polarization‐sensitive nonlocal filters are used to map the 2D phase gradients of the incident light field to the intensity variation of the x‐ and y‐polarized light, respectively, thus enabling single‐shot 2D wavefront reconstruction from images taken by a polarization camera. Such a system may be used for a variety of applications, including high‐resolution image aberration correction, surface metrology, and quantitative phase imaging.

2D seismic design on frontier basins using potential field data, a case study in the south of the eastern arm of the East African Rift System

AbstractThe 2D seismic design for a frontier basin was conducted from potential field data and available geological information using a case of a Block within the East African Rift System. The Block forms part of a southern extension of the eastern branch of the East African Rift System. The most significant structural features of the Block within this part of the rift were mapped using Airborne Gravity Gradiometry data along A, B and C sub‐basin boundaries. The Block covers a total area of more than 10,107 km2 in the central north of Tanzania. The 2D seismic lines were planned to intersect the major structures within the Block, in which a total of 1074 line kilometres from 18 seismic lines were proposed. The spatial sampling interval of 12.5 m with a minimum of two samples per wavelength was deemed adequate for a frontier basin, as would record dips well above 15° limit from the minimum target of 2000 m. The relevant source spacing may be suitable if tested, and the required energy has been recorded. These parameters, though may need refining depending on the field, are proposed for a good resolution imaging and wide bandwidth recording of complex geology for a frontier basin. The seismic design provided the basis for the economic evaluation of the possible survey to be undertaken for a frontier basin. The suggested parameters allow for the flexibility of inclusion or improvement in any subsequent study related to the seismic acquisition in a Block with similar characteristics.

Post-acquisition upsampling method for scanning x-ray microscopy.

A method of post-acquisition upsampling for scanning x-ray microscopy is developed in this study to improve the spatial resolution beyond the Nyquist frequency as determined by the intervals of a raster scan grid. The proposed method is applicable only when the probe beam size is not negligibly small compared with the pixels that constitute a raster micrograph-the Voronoi cells of a scan grid. The unconvoluted spatial variation in a photoresponse is estimated by solving a stochastic inverse problem at a higher resolution than that at which the data are acquired. This is followed by a rise in the spatial cutoff frequency due to a reduction in the noise floor. The practicability of the proposed method was verified by applying it to raster micrographs of x-ray absorption in Nd-Fe-B sintered magnets. The improvement thus achieved in spatial resolution was numerically demonstrated via spectral analysis by using the discrete Fourier transform. The authors also argue for a reasonable decimation scheme for the spatial sampling interval in relation to an ill-posed inverse problem and aliasing. The computer-assisted enhancement in the viability of scanning x-ray magnetic circular dichroism microscopy was illustrated by visualizing magnetic field-induced changes in domain patterns of the Nd2Fe14B main-phase.

A real-time phase processing system for phase sensitive optical time domain reflectometer.

In order to improve the real-time performance of a phase-sensitive optical-time-domain reflectometer (Φ-OTDR), a fully digital phase processing system is demonstrated. Using digital down-conversion and field programmable gate array (FPGA) hardware calculation, the phase of the Rayleigh scattering light can be demodulated in real-time. Benefiting from the pipeline calculation in the FPGA, the real-time performance of this system is not affected by the interrogation rate and fiber sensing distance. Experiments show that this real-time detection system has the same vibration detection performance as an offline data process and has good stability. The dynamic strain sensing with a sensing distance of 50 km, an interrogation rate of 1kHz, and a spatial sampling interval of 1m is experimentally demonstrated. The obtained results indicate that the fully digital signal processing system can ensure the real-time detection of Φ-OTDR under the condition of long distance and high resolution.

A Transmissive Imaging Spectrometer for Ground-Based Oxygen A-Band Radiance Observation

The oxygen A-band (759–770 nm) is a commonly used band for atmospheric observations. The signal in this band has wide dynamic range and can be used to invert several atmospheric parameters, such as air pressure and atmospheric optical depth, at different altitudes. High-resolution oxygen A-band radiance imaging spectrometer (HARIS) is an imaging spectrometer that operates in the oxygen A-band, which is designed for the observation of the direct solar radiance that passes through the atmosphere. HARIS is a transmissive imaging spectrometer that uses a compact transmissive optical system combined with reflective grating spectroscopy, while an area scan CMOS detector is used as the photosensitive element for the observations. HARIS response is associated with the observed target through a calibration process, which uses a monochromator with a supercontinuum laser for the spectral calibration, an integrating sphere with a spectrophotometer for the radiometric calibration and a meridian for the geometric calibration is employed to correct for distortions. The calibration results show that HARIS has an average spectral resolution of 0.33 nm and a field-of-view of 3.085 × 0.03° with an average spatial sampling interval of 0.0138°. Finally, the performance of HARIS is verified through field tests, in which the solar radiance data with an average signal-to-noise ratio of 438.93 is obtained.

Relationship between the spatial sampling intervals of high-density acquisition techniques and vertical resolution

Relationship between the spatial sampling intervals of high-density acquisition techniques and vertical resolution

A Novel Crack Quantification Method for Ultra-High-Definition Magnetic Flux Leakage Detection in Pipeline Inspection

Cracks that may cause pipeline cracking and leakage become the main risk of in-service pipelines after conventional metal loss defects have been detected. Therefore, it is imperative to develop ultra-high-definition magnetic flux leakage (MFL) detection for cracks. Due to the larger spatial sampling interval of conventional MFL inspections than the crack defect width, sparse sampling will result in problems such as missed detection of crack defects or insufficient signal sampling of crack defect MFL signals. To address the problem, this paper presents a detection topology in which the magnetic field signal is integrated first and then sampled, and it can effectively sample the leakage magnetic field of cracks. Furthermore, a magnetic field spatial integration (MFSI) method is proposed based on the magnetic dipole model, which develops an analytical solution for the depth quantification of crack defects. Using the multi-MFL spatial integral values under different lift offs, iterative equations are constructed, and the numerical solution for the width quantification of crack defects is provided. The finite element simulation and physical experiment are constructed. And, the results show that the proposed MFSI method can realize the quantification of crack size. When the crack defect aspect ratio is greater than 4, the quantization error of the crack depth and width does not exceed 0.7 mm and 0.1 mm, respectively. The robustness of the MFSI method for crack quantification is also discussed and verified. Moreover, based on theoretical analysis and simulation data, this paper concludes that the distribution of cracks MFL signal is width-insensitive, which would cause that classic MFL opening profile recognition methods for metal loss defects are no longer applicable to crack defects. Therefore, the proposed MFSI method is useful and meaningful for crack defect quantification in ultra-high-definition MFL detection.

A Motion Planning Method for Automated Vehicles in Dynamic Traffic Scenarios

We propose a motion planning method for automated vehicles (AVs) to complete driving tasks in dynamic traffic scenes. The proposed method aims to generate motion trajectories for an AV after obtaining the surrounding dynamic information and making a preliminary driving decision. The method generates a reference line by interpolating the original waypoints and generates optional trajectories with costs in a prediction interval containing three dimensions (lateral distance, time, and velocity) in the Frenet frame, and filters the optimal trajectory by a series of threshold checks. When calculating the feasibility of optional trajectories, the cost of all optional trajectories after removing obstacle interference shows obvious axisymmetric regularity concerning the reference line. Based on this regularity, we apply the constrained Simulated Annealing Algorithm (SAA) to improve the process of searching for the optimal trajectories. Experiments in three different simulated driving scenarios (speed maintaining, lane changing, and car following) show that the proposed method can efficiently generate safe and comfortable motion trajectories for AVs in dynamic environments. Compared with the method of traversing sampling points in discrete space, the improved motion planning method saves 70.23% of the computation time, and overcomes the limitation of the spatial sampling interval.

Spatio‐temporal sampled‐data control for delay reaction‐diffusion systems

AbstractThis article considers the exponential stabilization and performance for delay reaction‐diffusion systems (DRDSs), with spatial sampled‐data controller (SSDC) and spatio‐temporal sampled‐data controller (STSDC). Firstly, an SSDC is designed to stabilize the DRDSs. Using Lyapunov functional and Wirtinger's inequality technique, we obtain sufficient conditions to ensure the exponential stability of DRDSs. When there exist external disturbances, performance is considered and criteria are provided for the disturbed DRDSs, under the designed SSDC. Then, an STSDC is adopted for DRDSs. Time discrete item brings new difficulties for the analysis of the desired properties. To overcome these difficulties, a novel Lyapunov functional is constructed and Halaney's inequality is used. Moreover, the descriptor method is adopted. Under these techniques, delay‐dependent conditions are obtained to guarantee the exponential stability. The performance is also considered for the disturbed DRDSs under the designed STSDC. A Razumikhin‐type method is introduced together with the Lyapunov‐like functional. Sufficient conditions are presented to achieve performance for DRDSs with STSDC. Our theoretical results show that the spatial sampling interval does affect the desired properties, the shorter the spatial sampling interval, the easier to achieve the desired properties. Moreover, the time delay also influences the exponential stability of DRDSs, and smaller time delay is beneficial to the achievement of the stability. Finally, examples are given to illustrate the validity of results.

Distributed Event-Triggered Output Synchronization of Complex-Valued Memristive Reaction-Diffusion Complex Networks with Spatial Sampled-Data

This study addresses the problem of output quasisynchronization for coupled complex-valued memristive reaction-diffusion complex networks via the distributed event-triggered control scheme. First, by using the separate method, set value mapping, and intermediate value theorem, the complex-valued memristive reaction-diffusion complex networks can be transferred into two semi-uncertain real-valued reaction-diffusion complex networks. Second, a distributed output piecewise event-triggered control (OPETC) scheme with spatial sampled-data is first proposed including a spatial sampling event-triggered generator and spatiotemporal sampling state feedback controller. Furthermore, this scheme can effectively save the measurement resources and lower the update rate of controllers in spatial and time domain. Third, the synchronization analysis is considered by utilizing an appropriate Lyapunov function, the Halanay inequality, and the improved Wirtinger inequality. Subsequently, several output event-triggered quasisynchronization criteria are derived. The relations among event trigger conditions, spatial sampling interval, convergence rate, and control gain are given by rigorous mathematical derivation. Finally, multiple simulations are compared to substantiate the validation of the OPETC scheme.

Miniature all-optical flexible forward-viewing photoacoustic endoscopy probe for surgical guidance.

A miniature flexible photoacoustic endoscopy probe that provides high-resolution 3D images of vascular structures in the forward-viewing configuration is described. A planar Fabry–Perot ultrasound sensor with a bandwidth of 53 MHz located at the tip of the probe is interrogated via a flexible fiber bundle and a miniature optical relay system to realize an all-optical probe measuring 7.4 mm in outer diameter at the tip. This approach to photoacoustic endoscopy offers advantages over previous piezoelectric based distal-end scanning probes. These include a forward-viewing configuration in widefield photoacoustic tomography mode, finer spatial sampling (87 µm spatial sampling interval), and wider detection bandwidth (53 MHz) than has been achievable with conventional ultrasound detection technology and an all-optical passive imaging head for safe endoscopic use.

On Angular Sampling Intervals for Reconstructing Wideband Channel Spatial Profiles in Directional Scanning Measurements

Directional scanning measurement is the dominant strategy taken to measure channel spatial profiles for millimeter wave (mmWave) frequency bands. The focus of the paper is on wideband channel spatial profile reconstruction and angular sampling interval (ASI) selection for directional scanning measurement. We propose to employ the trigonometric interpolation technique to reconstruct the spatial channel profile and to use Nyquist sampling theorem and spherical wave mode theory to determine the ASI. Our analysis demonstrated that the half-power beam width (HPBW) of the antenna is a good approximation for the ASI setting to ensure accurate directional scanning measurements. The reconstructed power-angle-delay profile (PADP), composite power angular spectrum (PAS), delay and angle characteristics match well with those of the target in the measured data when the ASI is set to the antenna HPBW.

Data-Driven Tool Uses Amplitude-Based Statistics To Identify Seismic Fractures

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 191668, “Big Data Analytics for Seismic Fracture Identification Using Amplitude-Based Statistics,” by Egbadon Udegbe, SPE, Eugene Morgan, SPE, and Sanjay Srinivasan, SPE, Pennsylvania State University, prepared for the 2018 SPE Annual Technical Conference and Exhibition, Dallas, 24–26 September. The paper has not been peer reviewed. Data-analysis tools for extracting information about critical subsurface features such as fractures are still evolving. Traditional methods rely on time-consuming iterative work flows, which involve computing seismic attributes, denoising, and expert interpretation. Additionally, the increasingly widespread acquisition of time-lapse seismic surveys has led to heightened demand for reliable automated work flows to assist in deriving feature interpretation from seismic data. The authors present a novel data-driven tool for fast fracture identification in post-stack seismic data•sets. Introduction The paper develops an automated work flow for fast and robust fracture identification that directly uses seismic amplitude data as input. Adapted from real-time face-detection methods, the proposed algorithm computes spatiotemporal amplitude statistics using Haar-like bases to characterize the seismic amplitude properties that correspond to fracture occurrence in a unit window. In this approach, the amplitude data are decomposed into a lower-dimensional collection of simple-to-calculate mini-attributes, which contain gradient and curvature characteristics at varying locations and scales. These features serve as inputs to a cascade of boosted classification trees, which select and combine the most-discriminative features to develop a probabilistic binary classification model. This approach helps to eliminate the computationally intensive and subjective use of seismic attributes in existing approaches. Approach The proposed methodology uses a supervised learning approach. This involves specifying examples of seismic amplitude regions that either contain or do not contain fractures and subsequently presenting these examples to a binary classification scheme that develops a set of rules to distinguish between both fracture and nonfracture windows. Finally, using this trained classification model, any arbitrary amplitude section or volume can be scanned to determine the location of fractures on the basis of the rules defined within the specified window. Training-Window Selection. Careful consideration is required in defining the dimensions of the unit window. In 2D, this unit window is a rectangular region parallel to time and space axes. In 3D, the unit window refers to a cuboidal region with one time and two space axes. The dimensions of the window in the vertical (time) direction are influenced by the time-sampling interval and the source wavelet frequency. In the lateral directions, window dimensions are influenced by the spatial sampling interval, which is a result of the survey acquisition geometry. Overall, smaller unit windows lead to higher resolution in identifying fracture presence. This, however, is achieved at the expense of fewer amplitude features to characterize the window, as well as slower scan speeds, because more regions must be visited to make predictions. Once a seismic amplitude data set with known fracture locations and a unit window with specified dimensions has been established, multiple locations within the data set may be visited and amplitude samples extracted from both fractured and nonfractured regions.

Global Bathymetry and Topography at 15 Arc Sec: SRTM15+

An updated global bathymetry and topography grid is presented using a spatial sampling interval of 15 arc sec. The bathymetry is produced using a combination of shipboard soundings and depths predicted using satellite altimetry. New data consists of >33.6 million multibeam and singlebeam measurements collated by several institutions, namely, the National Geospatial‐Intelligence Agency, Japan Agency for Marine‐Earth Science and Technology, Geoscience Australia, Center for Coastal and Ocean Mapping, and Scripps Institution of Oceanography. New altimetry data consists of 48, 14, and 12 months of retracked range measurements from Cryosat‐2, SARAL/AltiKa, and Jason‐2, respectively. With respect to SRTM15_PLUS (Olson et al.,), the inclusion of these new data results in a ∼1.4‐km improvement in the minimum wavelength recovered for sea surface free‐air gravity anomalies, a small increase in the accuracy of altimetrically derived predicted depths, and a 1.24% increase, from 9.60% to 10.84%, in the total area of ocean floor that is constrained by shipboard soundings at 15‐arc sec resolution. Bathymetric grid cells constrained by satellite altimetry have estimated uncertainties of ±150 m in the deep oceans and ±180 m between coastlines and the continental rise. Onshore, topography data are sourced from previously published digital elevation models, predominately SRTM‐CGIAR V4.1 between 60°N and 60°S. ArcticDEM is used above 60°N, while Reference Elevation Model of Antarctica is used below 62°S. Auxiliary grids illustrating shipboard data coverage, marine free‐air gravity anomalies, and vertical gradient gradients are also provided in common data formats.

Intermittent distributed control for a class of nonlinear reaction-diffusion systems with spatial point measurements

This paper addresses the intermittent distributed stabilization problems of a class of nonlinear reaction-diffusion systems, where the state measurements are available at a finite number of sampling spatial points. By developing piecewise switching-time-dependent Lyapunov function methods combined with the descriptor system approach, L2-norm and H1-norm stability criteria are established, respectively. For the case of Dirichlet boundary condition, it is shown that the H1-norm stability implies the pointwise-in-space stability. The obtained stability conditions establish a quantitative relationship among the upper bound of the spatial sampling intervals, control width, and rest width. In the framework of linear matrix inequalities, sufficient conditions for the existence of intermittent distributed static output-feedback controllers are derived. A comparison between the two stability criteria is given by means of a numerical example.

Application of spline interpolation to speckle shearography measurements for damage identification

This paper aims to explore a new technique for structural damage identification using cubic spline interpolation. The method is based on the interpolation of modal rotations measured with speckle shearography. In order to locate the damaged areas, we make use of the analytical derivative of the cubic spline function to compute the modal curvature, which is known to be very sensitive to damage. A comprehensive parametric study of the spatial sampling interval is carried out to find its influence on noise filtering. Furthermore, the identification quality dependency on the mode shape and respective noise is also examined. The results obtained with the proposed method show the consistency of the localizations. Additionally, the challenging tasks of identifying small and multiple damage are tackled, yielding a good performance.

Baseline-free adaptive damage localization of plate-type structures by using robust PCA and Gaussian smoothing

Abstract Damage localization in plate-type structures has been widely investigated by exploring the structural characteristic deflection shapes (CDS’s) or their spatial derivatives. Despite the substantial advances in this kind of methods, several key issues still need to be addressed to boost their efficiency for practical applications. This study considers three essential problems: susceptibility to measurement noise, absence of baseline-data on pristine structures, and selection of measurement sampling interval and that of the parameters to be used in the de-noising techniques for more accurate damage localization. To tackle these problems, a novel baseline-free adaptive damage localization approach is proposed, which combines the robust Principal Component Analysis (PCA) with Gaussian smoothing. A damage localization evaluator is defined to determine both the spatial sampling interval of the CDS’s and the scale parameter of Gaussian smoothing to warrant a better damage localization. Moreover, effects of the measurement noise and numerical errors due to the use of the finite difference scheme on the estimate of the CDS derivatives are quantified. Finally, the feasibility and the effectiveness of the proposed method are verified both numerically and experimentally by using a cantilever plate with a small damage zone. It is found that the second-order spatial derivative of the CDS’s is able to provide the best damage localization results among the first four order spatial derivatives of the CDS’s.

In-orbit verification of microwave humidity sounder spectral channels coregistration using the moon

In-orbit verification of the coregistration of channels in a scanning microwave or infrared radiometer can in principle be done during normal in-orbit operation, using the regular events of lunar intrusion in the instrument cold space calibration view. A technique of data analysis based on best fit of data across lunar intrusions has been used to check the mutual alignment of the spectral channels of the microwave humidity sounder (MHS) instrument. MHS is a cross-track scanning radiometer in the millimeter-wave range flying on EUMETSAT and NOAA polar satellites, used operationally for the retrieval of atmospheric parameters in numerical weather prediction and nowcasting. This technique does not require any special operation or maneuver and only relies on the analysis of data from the nominal scanning operation. The coalignment of sounding channels and window channels can be evaluated by this technique, which would not be possible using Earth landmarks, due to the absorption effect of the atmosphere. The analysis reported shows an achievable accuracy below 0.5 mrad against a beam width at 3 dB and spatial sampling interval of about 20 mrad. In-orbit results for the MHS instrument on Metop-B are also compared with the prelaunch instrument characterization, showing a good correlation.