Maximum Detection Depth Research Articles

Improvement of Fatigue Characteristics of Friction Stir Welded A6061-T6 Applying Shot Peening

Recently, researchers have developed the method as a harmless the crack by the surface modification. For the purpose of contributing to reliability improvement of the A6061-T6 structure by harmless method, the following research was carried out: The tensile residual stress of friction stir welding was added by shot peening, resulting in a more significant compressive residual stress than that of the base metal. The effect of the surface crack aspect ratio on the maximum harmless crack depth (ahml) of A6061-T6 was evaluated for residual stress distribution. The detectable depth was evaluated in the relationship between ahml and the maximum detectable crack depth (aNDI) by non-destructive inspection (NDI).

Depth Mapping in Turbid and Deep Waters Using AVIRIS‐NG Imagery: A Study in Wax Lake Delta, Louisiana, USA

AbstractRemote sensing has been widely applied to investigate fluvial processes, but depth retrievals face significant constraints in deep and turbid conditions. This study evaluates the potential for depth retrievals under such challenging conditions using NASA's Airborne Visible/Infrared Imaging Spectrometer‐Next Generation (AVIRIS‐NG) imagery. We employ interpretable machine learning to construct a hyperspectral regressor for water depth and explore the spectral characteristics of deep and turbid waters in Wax Lake Delta (WLD), Louisiana, USA. The reflectance spectra of WLD show minor effects from depth differences due to turbidity. Nevertheless, a Random Forest with Recursive Feature Elimination (RF‐RFE) effectively generalizes high and low turbidity cases in a single model, achieving a of . Moreover, this model shows a maximum detectable depth of approximately 30 m, outperforming other methods. A spectral analysis using Shapley additive explanations (SHAP) points out the importance of learning various spectral bands and non‐linear relationships between depth and reflectance. Specifically, the short blue and Near‐InfraRed (NIR) bands, with high attenuation coefficients, play a crucial role. This finding highlights attenuation as the key process for deep‐depth retrievals. The depth maps of WLD produced by this model accurately capture the spatial distribution of deep river and shallow delta regions. However, the high dependency on short blue and NIR bands leads to discontinuous areas due to the noise sensitivity of these bands. This result highlights a drawback of remote sensing using empirical models. Future research will focus on correcting such discontinuities by integrating data from multiple remote sensing sources.

Satellite bathymetry estimation in the optically complex northern Baltic Sea

Satellite bathymetry estimation (SBE) is a cost-effective method for producing depth information for shallow marine and aquatic areas. However, most SBE methods have been developed and are refined in clear water conditions and their feasibility in optically complex waters is poorly understood. This hinders the use of SBE in optically complex waters.To test the feasibility of SBE in optically complex waters, we used multi-temporal Sentinel-2 (S-2) imagery and in-situ measured depth information from dive computers to fit bathymetric models for 14 study areas in the northern Baltic Sea. We compared different methods of using multi-temporal S2-scenes, atmospheric correction, and statistical modeling, as well as different band combinations to define the optimal model for each study area. We tested the dependence of the depth estimation on 13 environmental variables with potential influence on the accuracy of the SBE.The optimal bathymetric models differed among the study sites, with the differences manifested in different requirements for atmospheric correction, band combination, statistical model, and the use of multiple S2-scenes. The coefficients of determination (R2) of the optimal models varied between 0.42 and 0.79, with mean (X) R2 equaling to 0.65. The coefficients of determination were positively related to the proportion of sea within the 5 km search kernel and to the exposure of the study site. At the predicted depth of 2 m, the differences between observed and predicted depths varied between 0.11 and 0.60 m (X = 0.35 m). At the predicted depth of 1 m, the differences varied between 0.04 and 0.34 m (X = 0.21 m).SBE provides accurate depth estimates in optically complex waters, even when in-situ calibration data are limited. However, the maximum detectable depth obtained with SBE in optically complex waters is significantly lower than in clear water conditions. The SBE process can be fine-tuned to the specific characteristics of an area, improving its performance in optically complex conditions. In particular, the identification of the optimal band combination is critical for successful SBE. The depth estimates produced in this study can be used in a variety of applications that require accurate information on the seafloor bathymetry.

Assessment of global detection capability of oceanographic lidar

The profiling of marine bio-optical properties by oceanographic lidar is of great significance to the monitoring of the marine environment and the study of the global carbon cycle. In this study, the global detection capability of oceanographic lidar is analyzed with different specifications. To evaluate the detection performance, a simulator on multi-platform is developed. Based on the quasi-single elastic scattering approximation lidar equation and the bio-optical models, the simulator can generate different kinds of outputs, such as lidar signal profiles, signal-to-noise ratio profiles, maximum detectable depth distributions. The optical properties profiles of the global ocean could be derived from the global chlorophyll-a concentration profile data set, which is used as the input to the simulator. The simulation results are compared with the measurements from airborne lidar in the South China Sea, which verifies the reliability of the simulator. The global detection capability of spaceborne lidar with different power aperture products is simulated, and the influence of laser wavelength is analyzed. The results show that, for the simulated spaceborne lidar with typical specifications at 486 nm, there are probabilities ranging from 0.66 to 0.85 that the upper boundary of the thermocline can be detected on a global scale. In the cleanest open ocean, the lidar has a good capability to penetrate the upper boundary of the thermocline, while it cannot penetrate the subsurface chlorophyll maximum layers, in which the global penetration ratio is 0.93 under the simulation specifications at 486 nm. Finally, the influence of repetition frequency is analyzed, and the results show that reducing the pulse repetition frequency at the same average power can effectively reduce the background light of cumulative profiles and improve the signal-to-noise ratio.

Direct and quantitative assessments of near-infrared light attenuation and spectroscopic detection depth in biological tissues using surface-enhanced Raman scattering

Optical imaging and spectroscopic modalities are of broad interest for in-vivo molecular imaging, fluorescence guided cancer surgery, minimally invasive diagnostic procedures, and wearable devices. However, considerable debate still exists as to how deeply visible and near-infrared (NIR) light could penetrate normal and diseased tissues under clinically relevant conditions. Here we report the use of surface-enhanced Raman scattering (SERS) nanotags embedded in ex-vivo animal tissues for direct and quantitative measurements of light attenuation and spectroscopic detection depth at both the NIR-I and NIR-II spectral windows. SERS nanotags are well suited for this purpose because of their sharp spectral features that can be accurately differentiated from fluorescence and background emission. For the first time, the spectroscopic detection depth is quantitatively defined and measured as the maximal thickness of tissues through which the embedded SERS nanotags are still detected at a signal-to-noise ratio (SNR) of three (99.7% confidence level). Based on data from six types of fresh ex-vivo tissues (brain, kidney, liver, muscle, fat, and skin), we find that the maximum detection depth values range from 1—3 mm in the NIR-I window, to 3—6 mm in the NIR-II window. The depth values are largely determined by two factors – the intrinsic optical properties of the tissue, and the overall SNRs of the system without the tissue (system SNR, a result of nanotag brightness, instrument efficiency, and data acquisition parameters). In particular, there is an approximately linear-logarithmic relationship between the system SNR and maximum detection depth. Thus, the detection of hidden or occult lesions can be improved by three strategies – reducing tissue attenuation, minimizing background noise, and maximizing the system’s performance as judged by SNR.Graphical

Point-cloud acquisition in CFRP composites using ultrasonic location estimation with the phase-shift reference pulse

Wrinkles in carbon fiber reinforced plastics (CFRP) degrade the mechanical performance. The numerical study on wrinkles requires internal structural point cloud for the meso-structure reconstruction. This paper explores the ultrasonic location estimation with the phase-shift reference pulse for the point-cloud acquisition. The point-cloud acquisition using pulse-echo signals is a time-delay estimation which is a multi-reflection and multi-delay problem. We theoretically simplify the multi-reflection problem as a single-reflection problem and propose a normalized-cross-correlation-peaks (NCCPeaks) method for the multi-delay problem. The proposed method can eliminate some amplitude decrease and balance the smearing and frequency-dependent effects. Simulation shows that the proposed method has the maximum detectable depth without missing inter-ply estimations and a stronger noise resistance than the instantaneous phase method. An experiment is implemented on the 32-ply CFRP sample with an induced wrinkle. The estimation results of the instantaneous phase and NCCPeaks methods are almost the same at the first thirteenth layers. After the thirteenth layer, the NCCPeaks method has a stabler estimation and lower false estimation index than the instantaneous phase method.

Dual-ratio approach for detection of point fluorophores in biological tissue.

Diffuse in vivo flow cytometry (DiFC) is an emerging fluorescence sensing method to non-invasively detect labeled circulating cells in vivo. However, due to signal-to-noise ratio (SNR) constraints largely attributed to background tissue autofluorescence (AF), DiFC's measurement depth is limited. The dual ratio (DR)/dual slope is an optical measurement method that aims to suppress noise and enhance SNR to deep tissue regions. We aim to investigate the combination of DR and near-infrared (NIR) DiFC to improve circulating cells' maximum detectable depth and SNR. Phantom experiments were used to estimate the key parameters in a diffuse fluorescence excitation and emission model. This model and parameters were implemented in Monte Carlo to simulate DR DiFC while varying noise and AF parameters to identify the advantages and limitations of the proposed technique. Two key factors must be true to give DR DiFC an advantage over traditional DiFC: first, the fraction of noise that DR methods cannot cancel cannot be above the order of 10% for acceptable SNR. Second, DR DiFC has an advantage, in terms of SNR, if the distribution of tissue AF contributors is surface-weighted. DR cancelable noise may be designed (e.g., through the use of source multiplexing), and indications point to the AF contributors' distribution being truly surface-weighted in vivo. Successful and worthwhile implementation of DR DiFC depends on these considerations, but results point to DR DiFC having possible advantages over traditional DiFC.

Study of a Compton backscattering wall defects detection device using the Monte Carlo method

Abstract In view of the shortcomings of traditional wall defect detection methods, such as small detection range, poor accuracy, non-portable device, and so on, a wall defects detection device based on Compton backscattering technology is designed by Monte Carlo method, which is mainly used to detect the size and location information of defects in concrete walls. It mainly consists of two parts, the source container and the detection system: first, through the simulation and analysis of the parameters such as the receiving angle of the backscattered particles and the rear collimating material of the detector, the influence of the fluorescent X-ray peak of the detector collimating material on the backscattered particle counts is eliminated and the detected error is reduced; second, the ring array detector design, compared with single array detector and surface array detector, can facilitate real-time detection of defect orientation, expanding the single scan range and improving the detection efficiency. After simulation and comparative analysis, the relevant optimal parameters are obtained: the object is detected using a Cs-137 γ-ray source with an activity of 6 mCi, and a ring detector consisting of four 0.5-inch cube-shaped CsI scintillator detectors is placed at 150° to receive the backscattered photons. The simulation analysis using the Monte Carlo FLUKA program showed that the maximum depth of wall defect detection is 8 cm, the maximum error fluctuation range of defect depth and thickness is ±1 cm, the overall device weight is <20 kg, and the measurement time is <5 min.

Confronting turbidity, the major challenge for satellite-derived coastal bathymetry

Monitoring the complex seafloor morphology that drives the functioning of shallow coastal ecosystems is vital for assessing marine activities. Satellite-derived bathymetry (SDB) can provide a crucial dataset for creating the bathymetry maps needed to understand hazards and impacts produced by climate change in vulnerable coastal zones. SDB is effective in clear water, but still has limitations in application to areas with some turbidity. Here, using the twin satellites Sentinel-2A/B, we integrate water quality information from the satellite with a multi-temporal compositing method to demonstrate a potential for comprehensively operational bathymetric mapping over a range of environments. The automated compositing method diminishes the turbidity impact in addition to inferring the maximum detectable depth and removing optically deep-water areas. Examining a wide range of conditions along the Caribbean and eastern coast of the U.S. shows detailed bathymetry as deep as 30 m at 10 m spatial resolution with median errors <1 m when compared to high-resolution lidar surveys. These results demonstrate that the model adopted can provide useful bathymetry in areas that do not have consistently clear water and can be extended across multiple geographic regions and optical conditions at local, regional, and national scales.

The Effect of Suspended Particulate Matter on the Supraglacial Lake Depth Retrieval from Optical Data

Supraglacial lakes (SGL) are a specific phenomenon of glaciers. They are important for ice dynamics, surface mass balance, and surface hydrology, especially during ongoing climate changes. The important characteristics of lakes are their water storage and drainage. Satellite-based remote sensing is commonly used not only to monitor the area but also to estimate the depth and volume of lakes, which is the basis for long-term spatiotemporal analysis of these phenomena. Lake depth retrieval from optical data using a physical model requires several basic assumptions such as, for instance, the water has little or no dissolved or suspended matter. Several authors using these assumptions state that they are also potential weaknesses, which remain unquantified in the literature. The objective of this study is to quantify the effect of maximum detectable lake depth for water with non-zero suspended particulate matter (SPM). We collected in-situ concurrent measurements of hyperspectral and lake depth observations to a depth of 8 m. Additionally, we collected water samples to measure the concentration of SPM. The results of empirical and physically based models proved that a good relationship still exists between the water spectra of SGL and the lake depth in the presence of 48 mg/L of SPM. The root mean squared error for the models ranged from 0.163 m (Partial Least Squares Regression—PLSR model) to 0.243 m (physically based model), which is consistent with the published literature. However, the SPM limited the maximum detectable depth to approximately 3 m. This maximum detectable depth was also confirmed by the theoretical concept of Philpot (1989). The maximum detectable depth decreases exponentially with an increase in the water attenuation coefficient g, which directly depends on the water properties.

Signal and measurement considerations for human translation of diffuse in vivo flow cytometry.

.Significance: “Diffuse in vivo flow cytometry” (DiFC) is an emerging technology for fluorescence detection of rare circulating cells directly in large deep-seated blood vessels in mice. Because DiFC uses highly scattered light, in principle, it could be translated to human use. However, an open question is whether fluorescent signals from single cells would be detectable in human-scale anatomies.Aim: Suitable blood vessels in a human wrist or forearm are at a depth of to 4 mm. The aim of this work was to study the impact of DiFC instrument geometry and wavelength on the detected DiFC signal and on the maximum depth of detection of a moving cell.Approach: We used Monte Carlo simulations to compute fluorescence Jacobian (sensitivity) matrices for a range of source and detector separations (SDS) and tissue optical properties over the visible and near infrared spectrum. We performed experimental measurements with three available versions of DiFC (488, 640, and 780 nm), fluorescent microspheres, and tissue mimicking optical flow phantoms. We used both computational and experimental data to estimate the maximum depth of detection at each combination of settings.Results: For the DiFC detection problem, our analysis showed that for deep-seated blood vessels, the maximum sensitivity was obtained with NIR light (780 nm) and 3-mm SDS.Conclusions: These results suggest that—in combination with a suitable molecularly targeted fluorescent probes—circulating cells and nanosensors could, in principle, be detectable in circulation in humans.

SOLS: An Open-Source Spaceborne Oceanic Lidar Simulator

In recent years, oceanic lidar has seen a wide range of oceanic applications, such as optical profiling and detecting bathymetry. Furthermore, spaceborne lidars, CALIOP and ICESat-2, designed for atmospheric and ice science applications, have been used for ocean backscattering retrievals, but, until now, there has been no spaceborne lidar specifically designed for ocean detection. There is a demand for an effective lidar simulator to study the detection potential capability of spaceborne oceanic lidar. In this study, an open-source spaceborne oceanic lidar simulator named SOLS was developed, which is available freely. Moreover, the maximum detectable depth and corresponding optimal wavelength for spaceborne lidar were analyzed at a global scale by using SOLS. The factors controlling detection limits of a spaceborne ocean profiling lidar in different cases were discussed. Then, the maximum detectable depths with different relative measurement errors and the influence of solar background radiance were estimated. Subsequently, the effects of laser and detector parameters on maximum detectable depths were studied. The relationship between the lidar detectable depth and the ocean mixed layer depth was also discussed. Preliminary results show that the maximum detectable depth could reach deeper than 120 m in the oligotrophic sea at low latitudes. We found that 490 nm is the optimal wavelength for most of the open seawater. For coastal water, 532 nm is a more suitable choice considering both the technical maturity and geophysical parameters. If possible, a lidar equipped with 440 nm could achieve the greatest depth in oligotrophic seawater in subtropical gyres north and south of the equator. The upper mixed layer vertical structure in most of the global open ocean is within the lidar maximum detectable depth. These results show that SOLS can help the design of future spaceborne oceanic lidar systems a lot.

Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric LiDAR for Shallow Water Bathymetry and Object Detection.

Airborne LiDAR bathymetry (ALB) has proven to be an effective technology for shallow water mapping. To collect data with a high point density, a lightweight dual-wavelength LiDAR system mounted on unmanned aerial vehicles (UAVs) was developed. This study presents and evaluates the system using the field data acquired from a flight test in Dazhou Island, China. In the precision and accuracy assessment, the local fitted planes extracted from the water surface points and the multibeam echosounder data are used as a reference for water surface and bottom measurements, respectively. For the bathymetric performance comparison, the study area is also measured with an ALB system installed on the manned aerial platform. The object detection capability of the system is examined with placed small cubes. Results show that the fitting precision of the water surface is 0.1227 m, and the absolute accuracy of the water bottom is 0.1268 m, both of which reach a decimeter level. Compared to the manned ALB system, the UAV-borne system provides higher resolution data with an average point density of 42 points/m2 and maximum detectable depth of 1.7–1.9 Secchi depths. In the point cloud of the water bottom, the existence of a 1-m target cube and the rough shape of a 2-m target cube are clearly observed at a depth of 12 m. The system shows great potential for flexible shallow water mapping and underwater object detection with promising results.

Surface enhanced deep Raman detection of cancer tumour through 71 mm of heterogeneous tissue.

Detection of solid tumours through tissue- from depths relevant to humans- has been a significant challenge for biomedical Raman spectroscopy. The combined use of surface enhanced Raman scattering (SERS) imaging agents with deep Raman spectroscopy (DRS), i.e., surface enhanced deep Raman spectroscopy (SEDRS), offer prospects for overcoming such obstacles. In this study, we investigated the maximum detection depth through which the retrieval of SERS signal of a passively targeted biphenyl-4-thiol tagged gold nanoparticle (NP) imaging agent, injected subcutaneously into a mouse bearing breast cancer tumour, was possible. A compact 830 nm set-up with a hand-held probe and the flexibility of switching between offset, transmission and conventional Raman modalities was developed for this study. In vivo injection of the above SERS NP primary dose allowed surface tumour detection, whereas additional post mortem NP booster dose was required for detection of deeply seated tumours through heterogeneous animal tissue (comprising of proteins, fat, bone, organs, blood, and skin). The highest detection depth of 71 mm was probed using transmission, translating into a ~40% increase in detection depth compared to earlier reports. Such improvements in detection depth along with the inherent Raman chemical sensitivity brings SEDRS one step closer to future clinical cancer imaging technology.

River Bathymetry Retrieval From Landsat-9 Images Based on Neural Networks and Comparison to SuperDove and Sentinel-2

The Landsat mission has kept an eye on our planet, including water bodies, for 50 years. With the launch of Landsat-9 and its onboard Operational Land Imager 2 (OLI-2) in September 2021, more subtle variations in brightness (14-bit dynamic range) can be captured than previous sensors in the Landsat series (e.g., 12-bit Landsat-8). The enhanced radiometric resolution of OLI-2 appeals to the aquatic remote sensing community because the instrument might be capable of resolving smaller differences in water-leaving radiance. This study evaluates the potential to map river bathymetry from Landsat-9 imagery. We employ a neural network (NN)-based regression model for bathymetry retrieval and compare the results with optimal band ratio analysis (OBRA). The effect of Landsat-9 pan-sharpening on depth retrieval is also examined. In addition, we perform an intersensor comparison with Sentinel-2 and newly available 8-band SuperDoves from the PlanetScope constellation. Depth retrieval results from the Colorado and Potomac Rivers imply that Landsat-9 provided more accurate bathymetry across a range of depths up to 20 m, particularly when pan-sharpened. Downsampling the SuperDove data improved bathymetry retrieval due to enhanced signal-to-noise ratio, most notably in deep waters (maximum detectable depth increased from &#x223C;15 to &#x223C;20 m). Similarly, the enhanced spectral resolution of 8-band SuperDoves improved depth retrieval relative to 4-band Doves. The NN-based model outperformed OBRA by incorporating more spectral information.

Ocean mixed layer depth estimation using airborne Brillouin scattering lidar: simulation and model.

The potential of Brillouin scattering lidar for detecting the mixed layer depth (MLD) was studied. We simulated the Brillouin scattering lidar signal in various water environmental parameters and developed an MLD retrieval model for Brillouin scattering lidar data. We first analyzed the theoretical maximum detectable depth for Brillouin scattering lidar in low-latitude sea regions based on the multiple scattering lidar equations. Subsequently, a theoretical method for calculating the Brillouin scattering frequency shift and linewidth was derived based on the international thermodynamic equation of seawater-2010 and the coupled wave equations. Then we used the theoretical method and the temperature-salinity (T-S) profile of the global Argo data in low-latitude regions to simulate the vertical profile distribution of the Brillouin scattering frequency shift and linewidth. Furthermore, we used a maximum angle method to estimate the ocean MLD in low-latitude regions based on the vertical profile distribution of the Brillouin scattering frequency shift and density in seawater. They are well correlated, which indicates that the frequency-shift component of the Brillouin scattering lidar signal for estimating ocean MLD is feasible and reliable. It appears that airborne or spaceborne Brillouin scattering lidar technology provides great potential for high-efficiency, large-area, and long-term monitoring of the global ocean MLD and upper-ocean water bodies.

Electric and magnetic dipole antennas of a directional resistivity logging-while-drilling tool for “look-around” boundary detection

Directional resistivity logging-while-drilling tools play an important role in geosteering. In contrast to the widely used tool with magnetic dipole transmitters and receivers, tools are investigated with electric and magnetic dipoles as transmitters and/or receivers for “look-around” boundary detection. Measurement schemes are selected based on their look-around boundary detection abilities. Those measurement schemes are studied regarding the sensitivity and depths of boundary detection, the optimal transmitter-receiver distance and frequency, and the effects of a drill collar using the coefficient propagator method and the finite-difference method. Higher sensitivity to a boundary often implies a shallower depth of investigation. More specifically, the measurement schemes using an electric dipole transmitter and receiver are the least sensitive to the boundary; however, such schemes have the maximum depth of detection and the strongest signal strength. The schemes using electric and magnetic dipole transmitters and receivers have a moderate depth of detection and signal strength. The measurement schemes with a magnetic dipole transmitter and receiver have the highest sensitivity to the boundary and the weakest signal strength. The drill collar affects the response of all of the measurement schemes. However, this effect cannot be corrected with a simple coefficient for the schemes using an axial electric dipole transmitter, but it can be corrected for others. The optimal frequencies and optimal transmitter-receiver distances of those schemes have two types: the changing one that changes with the distance to boundaries and the fixed one that usually has the lowest frequency or the shortest transmitter-receiver distance. The characteristics of each measurement scheme will guide the tool designs and determine its role in the application and method of interpretation.

Pose Estimation of Excavator Manipulator Based on Monocular Vision Marker System.

Excavation is one of the broadest activities in the construction industry, often affected by safety and productivity. To address these problems, it is necessary for construction sites to automatically monitor the poses of excavator manipulators in real time. Based on computer vision (CV) technology, an approach, through a monocular camera and marker, was proposed to estimate the pose parameters (including orientation and position) of the excavator manipulator. To simulate the pose estimation process, a measurement system was established with a common camera and marker. Through comprehensive experiments and error analysis, this approach showed that the maximum detectable depth of the system is greater than 11 m, the orientation error is less than 8.5°, and the position error is less than 22 mm. A prototype of the system that proved the feasibility of the proposed method was tested. Furthermore, this study provides an alternative CV technology for monitoring construction machines.

The Global Magneto-ionic Medium Survey: A Faraday Depth Survey of the Northern Sky Covering 1280–1750 MHz

Abstract The Galactic interstellar medium hosts a significant magnetic field, which can be probed through the synchrotron emission produced from its interaction with relativistic electrons. Linearly polarized synchrotron emission is generated throughout the Galaxy and, at longer wavelengths, modified along nearly every path by Faraday rotation in the intervening magneto-ionic medium. Full characterization of the polarized emission requires wideband observations with many frequency channels. We have surveyed polarized radio emission from the Northern sky over the range 1280–1750 MHz, with channel width 236.8 kHz, using the John A. Galt Telescope (diameter 25.6 m) at the Dominion Radio Astrophysical Observatory, as part of the Global Magneto-Ionic Medium Survey. The survey covered 72% of the sky, decl. −30° to +87° at all R.A. The intensity scale was absolutely calibrated, based on the flux density and spectral index of Cygnus A. Polarization angle was calibrated using the extended polarized emission of the Fan Region. Data are presented as brightness temperatures with angular resolution 40′. Sensitivity in Stokes Q and U is 45 mK rms in a 1.18 MHz band. We have applied rotation measure synthesis to the data to obtain a Faraday depth cube of resolution 150 rad m−2 and sensitivity 3 mK rms of polarized intensity. Features in Faraday depth up to a width of 110 rad m−2 are represented. The maximum detectable Faraday depth is ±2 × 104 rad m−2. The survey data are available at the Canadian Astronomy Data Centre.

Assessment of magnetite as a magnetic tracer for sediments in the study of ephemeral gully erosion: Conditioning factors of magnetic susceptibility

AbstractIn gully erosion, the detached soil can be transported over long distances along the landscape. The eroded material can be redistributed and/or deposited on the soil surface along the landscape and then eventually be buried by newly eroded and deposited sediment. There can be significant variability of the soil conditions (e.g., texture and moisture content) over which the eroded material travels. The eroded material can be detected through the use of magnetic tracers attached to or mixed with the eroded soil. In this study we evaluated the degree to which the magnetic signal of the magnetite is conditioned by (i) burial depth of tracer, (ii) condition of soil covering the tracer and (iii) tracer concentration. In the laboratory containers were filled with a specific soil. In the filling process, a 0.5‐cm layer of a soil–magnetite mixture was interspersed in the soil profile at a certain depth. Experiments encompassed three different soil–tracer concentrations (1000:1, 200:1, 100:1), four burial depths of tracer (0 cm, 3 cm, 5 cm and 10 cm from soil surface), and two different soils. In each case, the magnetic susceptibility was measured with a susceptometer. Experiments were repeated with different soil moisture contents. If the tracer is located under the soil surface, a minimum soil–tracer concentration of 200:1 is required for its correct detection. The intensity of the magnetic signal decreases dramatically with the vertical distance of the tracer from the soil surface. The maximum detection depth for the tracer's magnetic signal is strongly dependent on the natural magnetic susceptibility of the soil, which masks the tracer's signal. Variation in soil moisture content does not significantly affect the magnetic signal. For extensive field studies, the soil–tracer volume to be handled would be very high and therefore, it is necessary to explore new tracer application techniques.