scholarly journals Bathymetric Survey of the St. Anthony Channel (Croatia) Using Multibeam Echosounders (MBES)—A New Methodological Semi-Automatic Approach of Point Cloud Post-Processing

2022 ◽  
Vol 10 (1) ◽  
pp. 101
Author(s):  
Ante Šiljeg ◽  
Ivan Marić ◽  
Fran Domazetović ◽  
Neven Cukrov ◽  
Marin Lovrić ◽  
...  

Multibeam echosounders (MBES) have become a valuable tool for underwater floor mapping. However, MBES data are often loaded with different measurement errors. This study presents a new user-friendly and methodological semi-automatic approach of point cloud post-processing error removal. The St. Anthony Channel (Croatia) was selected as the research area because it is regarded as one of the most demanding sea or river passages in the world and it is protected as a significant landscape by the Šibenik-Knin County. The two main objectives of this study, conducted within the Interreg Italy–Croatia PEPSEA project, were to: (a) propose a methodological framework that would enable the easier and user-friendly identification and removal of the errors in MBES data; (b) create a high-resolution integral model (MBES and UAV data) of the St. Anthony Channel for maritime safety and tourism promotion purposes. A hydrographic survey of the channel was carried out using WASSP S3 MBES while UAV photogrammetry was performed using Matrice 210 RTK V2. The proposed semi-automatic post-processing of the MBES acquired point cloud was completed in the Open Source CloudCompare software following five steps in which various point filtering methods were used. The reduction percentage in points after the denoising process was 14.11%. Our results provided: (a) a new user-friendly methodological framework for MBES point filtering; (b) a detailed bathymetric map of the St. Anthony Channel with a spatial resolution of 50 cm; and (c) the first integral (MBES and UAV) high-resolution model of the St. Anthony Channel. The generated models can primarily be used for maritime safety and tourism promotion purposes. In future research, ground-truthing methods (e.g., ROVs) will be used to validate the generated models.

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Yuhang Yang ◽  
Zhiqiao Dong ◽  
Yuquan Meng ◽  
Chenhui Shao

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.


Coatings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 204
Author(s):  
Yuhao Zhou ◽  
Bowen Ji ◽  
Minghao Wang ◽  
Kai Zhang ◽  
Shuaiqi Huangfu ◽  
...  

Remarkable progress has been made in the high resolution, biocompatibility, durability and stretchability for the implantable brain-computer interface (BCI) in the last decades. Due to the inevitable damage of brain tissue caused by traditional rigid devices, the thin film devices are developing rapidly and attracting considerable attention, with continuous progress in flexible materials and non-silicon micro/nano fabrication methods. Therefore, it is necessary to systematically summarize the recent development of implantable thin film devices for acquiring brain information. This brief review subdivides the flexible thin film devices into the following four categories: planar, open-mesh, probe, and micro-wire layouts. In addition, an overview of the fabrication approaches is also presented. Traditional lithography and state-of-the-art processing methods are discussed for the key issue of high-resolution. Special substrates and interconnects are also highlighted with varied materials and fabrication routines. In conclusion, a discussion of the remaining obstacles and directions for future research is provided.


2021 ◽  
Author(s):  
Katerina Spanoudaki ◽  
George Zodiatis ◽  
Nikos Kampanis ◽  
Maria Luisa Quarta ◽  
Marco Folegani ◽  
...  

<p>The coastal area of Crete is an area of increasing interest due to the recent hydrocarbon exploration and exploitation activities in the Eastern Mediterranean Sea and the increase of the maritime transport after the enlargement of the Suez Canal. National and local authorities, like ports and the coast guard, who are involved in maritime safety, such as oil spill prevention, the tourism industry and policy makers involved in coastal zone management, are key end users’ groups who can benefit from high spatial and temporal resolution forecasting products and information to support their maritime activities in the coastal sea area of the island. To support local end users and response agencies to strengthen their capacities in maritime safety and marine conservation, a high-resolution, operational forecasting system, has been developed for the coastal area of Crete. The COASTAL CRETE forecasting system implements advanced numerical hydrodynamic and sea state models, nested in CMEMS Med MFC products and produces, on a daily basis, 5-day hourly and 6-hourly averaged high-resolution forecasts of important marine parameters, such as sea currents, temperature, salinity and waves. The COASTAL CRETE high-resolution (~ 1km) hydrodynamic model is based on a modified POM parallel code implemented by CYCOFOS in the Eastern Mediterranean and the Levantine Basin, while for wave forecasts, the latest ECMWF CY46R1 parallel version including a number of new features, a state-of-the-art wave analysis and prediction model, with high accuracy in both shallow and deep waters has been implemented with a resolution of ~1.8 km. The COASTAL CRETE hydrodynamic model has been evaluated against the CMEMS Med MFC model and with satellite Sea Surface Temperature data with good statistical estimates. The COASTAL CRETE wave model is calibrated with in-situ data provided from the HCMR buoy network operating in the area. Both the CMEMS Med MFC products and COASTAL CRETE forecasts are made available through a customized instance of ADAM (Advanced geospatial Data Management platform) developed by MEEO S.r.l. (https://explorer-coastal-crete.adamplatform.eu/). This application provides automatic data exchange management capabilities between the CMEMS Med MFC and the COASTAL CRETE models, enabling data visualization, combination, processing and download through the implementation of the Digital Earth concept. Among the numerous functionalities of the platform, a depth slider allows to explore the COASTAL CRETE products through the depth dimension, and a sea current magnitude feature enables the visualization of the currents vectors by overlaying them to any available product/parameter, thus allowing comparisons and correlations. The downscaled high-resolution COASTAL CRETE forecasts will be used to deliver on demand information and services in the broader objectives of the maritime safety, particularly for oil spill and floating objects/marine litters predictions. Such a use case is presented for the port area of Heraklion, implementing nested fine grid hydrodynamic and oil spill models (MEDSLIK-II).</p><p>Acknowledgement: Copernicus Marine Environment Monitoring Service (CMEMS) DEMONSTRATION COASTAL-MED SEA. COASTAL-CRETE, Contract: 110-DEM5-L3.</p>


Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2454 ◽  
Author(s):  
Ting Chan ◽  
Derek Lichti ◽  
Adam Jahraus ◽  
Hooman Esfandiari ◽  
Herve Lahamy ◽  
...  

Measuring the volume of bird eggs is a very important task for the poultry industry and ornithological research due to the high revenue generated by the industry. In this paper, we describe a prototype of a new metrological system comprising a 3D range camera, Microsoft Kinect (Version 2) and a point cloud post-processing algorithm for the estimation of the egg volume. The system calculates the egg volume directly from the egg shape parameters estimated from the least-squares method in which the point clouds of eggs captured by the Kinect are fitted to novel geometric models of an egg in a 3D space. Using the models, the shape parameters of an egg are estimated along with the egg’s position and orientation simultaneously under the least-squares criterion. Four sets of experiments were performed to verify the functionality and the performance of the system, while volumes estimated from the conventional water displacement method and the point cloud captured by a survey-grade laser scanner serve as references. The results suggest that the method is straightforward, feasible and reliable with an average egg volume estimation accuracy 93.3% when compared to the reference volumes. As a prototype, the software part of the system was implemented in a post-processing mode. However, as the proposed processing techniques is computationally efficient, the prototype can be readily transformed into a real-time egg volume system.


2017 ◽  
Vol 142 ◽  
pp. 1805-1810 ◽  
Author(s):  
Tom Lloyd Garwood ◽  
Ben Richard Hughes ◽  
Dominic O’Connor ◽  
John K Calautit ◽  
Michael R Oates ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6427
Author(s):  
Haoyu Niu ◽  
Derek Hollenbeck ◽  
Tiebiao Zhao ◽  
Dong Wang ◽  
YangQuan Chen

Estimating evapotranspiration (ET) has been one of the most critical research areas in agriculture because of water scarcity, the growing population, and climate change. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, researchers use water balance, soil moisture, weighing lysimeters, or an energy balance approach, such as Bowen ratio or eddy covariance towers to estimate ET. However, these ET methods are point-specific or area-weighted measurements and cannot be extended to a large scale. With the advent of satellite technology, remote sensing images became able to provide spatially distributed measurements. However, the spatial resolution of multispectral satellite images is in the range of meters, tens of meters, or hundreds of meters, which is often not enough for crops with clumped canopy structures, such as trees and vines. Unmanned aerial vehicles (UAVs) can mitigate these spatial and temporal limitations. Lightweight cameras and sensors can be mounted on the UAVs and take high-resolution images. Unlike satellite imagery, the spatial resolution of the UAV images can be at the centimeter-level. UAVs can also fly on-demand, which provides high temporal imagery. In this study, the authors examined different UAV-based approaches of ET estimation at first. Models and algorithms, such as mapping evapotranspiration at high resolution with internalized calibration (METRIC), the two-source energy balance (TSEB) model, and machine learning (ML) are analyzed and discussed herein. Second, challenges and opportunities for UAVs in ET estimation are also discussed, such as uncooled thermal camera calibration, UAV image collection, and image processing. Then, the authors share views on ET estimation with UAVs for future research and draw conclusive remarks.


Author(s):  
Muhammad Arsalan Khan ◽  
Wim Ectors ◽  
Tom Bellemans ◽  
Davy Janssens ◽  
Geert Wets

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are one of the most dynamic and multidimensional emerging technologies of the modern era. This technology has recently found multiple potential applications within the transportation field, ranging from traffic surveillance applications to traffic network analysis. To conduct a UAV-based traffic study, extremely diligent planning and execution are required followed by an optimal data analysis and interpretation procedure. In this study, however, the main focus was on the processing and analysis of UAV-acquired traffic footage. A detailed methodological framework for automated UAV video processing is proposed to extract the trajectories of multiple vehicles at a particular road segment. Such trajectories can be used either to extract various traffic parameters or to analyze traffic safety situations. The proposed framework, which provides comprehensive guidelines for an efficient processing and analysis of a UAV-based traffic study, comprises five components: preprocessing, stabilization, georegistration, vehicle detection and tracking, and trajectory management. Until recently, most traffic-focused UAV studies have employed either manual or semiautomatic processing techniques. In contrast, this paper presents an in-depth description of the proposed automated framework followed by a description of a field experiment conducted in the city of Sint-Truiden, Belgium. Future research will mainly focus on the extension of the applications of the proposed framework in the context of UAV-based traffic monitoring and analysis.


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