The importance of sound velocity determination for bathymetric survey

Bathymetric surveys are carried out whenever there is a need to know the exact morphological trend of the seabed. For a correct operation of the echo sounder, which uses the principle of acoustic waves to scan the bottom and determine the depth, it is important to accurately determine the sound velocity in water, as it varies according to specific parameters (Density, Temperature, and Pressure). In this work, we want to analyse the role of sound velocity determination in bathymetric survey and its impact on the accuracy of depth measurement. The experiments are conducted on data set provided by “Istituto Idrografico della Marina Militare Italiana” (IIM), the official Hydrographic Office for Italy, and acquired in the Ligurian sea. In our case, the formulas of Chen & Millero (UNESCO), Medwin, and Mackenzie were applied. The introduction of errors on chemical-physical parameters of the water column (Temperature, Pressure, Salinity, Depth) simulating inaccurate measurements, produces considerable impacts on sound velocity determination and subsequently a decrease of the depth value accuracy. The results remark the need to use precise probes and accurate procedures to obtain reliable depth data.

New Stereo Vision Algorithm Composition Using Weighted Adaptive Histogram Equalization and Gamma Correction

This work presents the composition of a new algorithm for a stereo vision system to acquire accurate depth measurement from stereo correspondence. Stereo correspondence produced by matching is commonly affected by image noise such as illumination variation, blurry boundaries, and radiometric differences. The proposed algorithm introduces a pre-processing step based on the combination of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Adaptive Gamma Correction Weighted Distribution (AGCWD) with a guided filter (GF). The cost value of the pre-processing step is determined in the matching cost step using the census transform (CT), which is followed by aggregation using the fixed-window and GF technique. A winner-takes-all (WTA) approach is employed to select the minimum disparity map value and final refinement using left-right consistency checking (LR) along with a weighted median filter (WMF) to remove outliers. The algorithm improved the accuracy 31.65% for all pixel errors and 23.35% for pixel errors in nonoccluded regions compared to several established algorithms on a Middlebury dataset.

Snowpack Distribution Using Topographical, Climatological and Winter Season Index Inputs

A majority of the annual precipitation in many mountains falls as snow, and obtaining accurate estimates of the amount of water stored within the snowpack is important for water supply forecasting. Mountain topography can produce complex patterns of snow distribution, accumulation, and ablation, yet the interaction of topography and meteorological patterns tends to generate similar inter-annual snow depth distribution patterns. Here, we question whether snow depth patterns at or near peak accumulation are repeatable for a 10-year time frame and whether years with limited snow depth measurement can still be used to accurately represent snow depth and mean snow depth. We used snow depth measurements from the West Glacier Lake watershed, Wyoming, U.S.A., to investigate the distribution of snow depth. West Glacier Lake is a small (0.61 km2) windswept (mean of 8 m/s) watershed that ranges between 3277 m and 3493 m. Three interpolation methods were compared: (1) a binary regression tree, (2) multiple linear regression, and (3) generalized additive models. Generalized additive models using topographic parameters with measured snow depth presented the best estimates of the snow depth distribution and the basin mean amounts. The snow depth patterns near peak accumulation were found to be consistent inter-annually with an average annual correlation coefficient (r2) of 0.83, and scalable based on a winter season accumulation index (r2 = 0.75) based on the correlation between mean snow depth measurements to Brooklyn Lake snow telemetry (SNOTEL) snow depth data.

Hydraulic model experiment of energy dissipation on the horizontal and USBR II stilling basin

Flow conditions on overflow systems can result in construction failure, mainly due to the high flow energy. Stilling basin at downstream of the spillway is useful for reducing flow energy. It can reduce the destructive force of water flow. Controlling the hydraulic jump is an important part that includes the jump’s energy, length, and height. The physical hydraulic model was carried out with several series, by making a series of bottom lowering of horizontal and USBR II stilling basin. The experimental study is expected to represent flow behavior in the overflow system regarding flow conditions and energy dissipation. Based on the analytical calculation of flow velocity, the amount of flow energy that occurs at each control point is calculated. The control points are the starting point of the spillway, the chute way toe, and flow depth after the hydraulic jump. The energy loss can be calculated for each control point, while the efficiency of energy dissipation on stilling basin is calculated at the downstream flow depth after the hydraulic jump. Velocity calculated by dividing discharge per unit width by water depth which is based on the flow depth measurement data in the hydraulic model.

Vari-Focal Light Field Camera for Extended Depth of Field

The light field camera provides a robust way to capture both spatial and angular information within a single shot. One of its important applications is in 3D depth sensing, which can extract depth information from the acquired scene. However, conventional light field cameras suffer from shallow depth of field (DoF). Here, a vari-focal light field camera (VF-LFC) with an extended DoF is newly proposed for mid-range 3D depth sensing applications. As a main lens of the system, a vari-focal lens with four different focal lengths is adopted to extend the DoF up to ~15 m. The focal length of the micro-lens array (MLA) is optimized by considering the DoF both in the image plane and in the object plane for each focal length. By dividing measurement regions with each focal length, depth estimation with high reliability is available within the entire DoF. The proposed VF-LFC is evaluated by the disparity data extracted from images with different distances. Moreover, the depth measurement in an outdoor environment demonstrates that our VF-LFC could be applied in various fields such as delivery robots, autonomous vehicles, and remote sensing drones.

In-Situ Depth Measurement of Laser Micromachining

Precision laser micromachining plays an important role in the biomedical, electronics, and material processing industries. During laser drilling, precision depth detection with micrometer-level resolution is required, particularly with blind-hole or heterogeneous structures. We present an optical detection system utilizing an optical confocal structure, experimentally confirmed to achieve a >95% accuracy for micron-diameter holes that are tens-of-microns deep. This system can be easily integrated into commercial laser micromachining processes, and can be employed in laser drilling and three-dimensional active-feedback laser printing.

Acousto-optic filtration in low-coherence spectral-domain interferometry

The basic principles of measurements in spectral-domain low coherence interferometry (optical coherence tomography, optical coherence microscopy) based on acousto-optic filtration are discussed. Relations for extracting information about sample’s spatial structure from a series of spectral interference images acquired with spectral tuning are given. The implementation of measurements in spectral domain using acousto-optic filtration is considered. The effect of the acousto-optic filter characteristics on depth measurement range and depth resolution is estimated. The results of modelling of the interference signal and experimental data obtained in the scheme with acousto-optic filtration of interfering beams at the output of Michelson interferometer are presented.

Thingsboard-based prototype design for measuring depth and pH of kulong waters

Kulong is a post-tin mining area that is not reclaimed, resulting in the formation of a basin that is gradually filled with water through natural processes. In carrying out an inventory of kulong water to find out the potential and benefits of its water, a method is needed to measure the depth and pH value of kulong water in a practical way and can be monitored in real-time. Depth measurement usually uses an echosounder and to check the pH value using a manual pH meter. However, this method is somewhat less effective because it requires a relatively long process and the resulting data must be recorded manually. In this study, a thingsboard-based prototype design was designed to measure the depth and pH of the Kulong waters. measurement data is processed using a hotspot or WIFI internet connection. The measured value data will be processed and uploaded to the Thingsboard server, which is an online-based Internet of Things (IoT) platform. So that data can be displayed in real-time through the website and can be accessed via a laptop or smartphone.