Big Data Processing and Visualization of Offshore Current Based on Python
Authors: 
Yachao Zhang, Xiaojie Zhang, Wei Sha, Xianghuang Li, Yingxin Wei, Yanfen Deng, Jianhua LiuAuthors Info & Claims
Pages 115 - 121
Abstract
The use of acoustic doppler current profilers (ADCP) for measuring current is becoming increasingly widespread. ADCP can rapidly collect a voluminous amount of detailed flow velocities with high temporal and spatial resolutions. This paper presents an ADCP postprocessing and visualization framework, which allows the big data processing, analysis, and visualization of offshore current measurements. The software is written with the open-source multiplatform programming language Python. It has the following features, including measurement outlier detection and removal, measurement data interpolation, velocity extrapolation in the unmeasured areas near the water surface and the bottom, computation of depth-averaged velocities and eigenvalue, and generation of the professional report and figure. It can provide efficient information for those who are engaged in ocean dynamic surveys and help to make supervision and decision in many ocean-related fields, such as ocean engineering construction, ecology, biology, disaster science, and so on.
CCS CONCEPTS•Computing methodologies•Modeling and simulation•Model development and analysis•Modeling methodologies
References
[1]
Schofield O, Glenn SM, Moline MA, Oliver M, Irwin A, Chao Y, Arrott M. 2013. Ocean Observatories and Information: building a global ocean observing network. Springer, New York, 319–336. https://doi.org/10.1007/978-1-4614-5684-1_14
[2]
Huang, D., Zhao, D., Wei, L., Wang, Z., & Du, Y. 2015. Modeling and analysis in marine big data: Advances and challenges. Mathematical Problems in Engineering, 384742.1-384742.13. https://doi.org/10.1155/2015/384742
[3]
Datasets of National Oceanographic Data Center. From http://www.nodc.noaa.gov/access/allproducts.html
[4]
Kim, D., & Muste, M. 2012. Multi-dimensional representation of river hydrodynamics using ADCP data processing software. Environmental Modelling & Software, 38, 158-166. https://doi.org/10.1016/j.envsoft.2012.05.011
[5]
Yang, Z., Xie, W., Huang, L., & Wei, Z. 2018. Marine data security based on blockchain technology. In IOP conference series: Materials science and engineering. Vol. 322, No. 5, 052028. https://doi.org/10.1088/1757-899x/322/5/052028
[6]
Oberg, K.; Mueller, D. 2007. Validation of streamflow measurements made with acoustic Doppler current profilers. J. Hydraul. Eng. 133, 1421–1432. https://doi.org/10.1061/(asce)0733-9429(2007)133:12(1421)
[7]
Yorke, T.H.; Oberg, K.A. 2002. Measuring river velocity and discharge with acoustic Doppler profilers. Flow Meas. Instrum. 13, 191–195. https://doi.org/10.1016/s0955-5986(02)00051-1
[8]
Parsons, D. R., Jackson, P. R., Czuba, J. A., Engel, F. L., Rhoads, B. L., Oberg, K. A., ... & Riley, J. D. 2013. Velocity Mapping Toolbox (VMT): A processing and visualization suite for moving‐vessel ADCP measurements. Earth Surface Processes and Landforms, 38(11), 1244-1260. https://doi.org/10.1002/esp.3367
[9]
Flener, C., Wang, Y., Laamanen, L., Kasvi, E., Vesakoski, J. M., & Alho, P. 2015. Empirical modeling of spatial 3d flow characteristics using a remote-controlled ADCP system: monitoring a spring flood. Water, 7(1), 217-247. https://doi.org/10.3390/w7010217
[10]
Morlock SE. 1996. Evaluation of Acoustic Doppler Current Profiler Measurements of River Discharge. U.S. Geological Survey, Water-Resources Investigations Report, 95-4218, 1-37. https://doi.org/10.3133/wri954218
[11]
Dorfmann, C., Steidl, J., & Zenz, G. 2013. ADCPtool: an open source ADCP postprocessing framework. In Proceedings of the 35th IAHR World Congress, Chengdu, China.
[12]
Muste M., Yu K. and Spasojevic M. 2004. Practical aspects of ADCP data use for quantification of mean river flow characteristics; Part I: moving-vessel measurements. Flow Measurement and Instrumentation, 15(1), 1-16. https://doi.org/10.1016/j.flowmeasinst.2003.09.001
[13]
Oliphant T. 2006. Guide to NumPy. From http://www.numpy.org
[14]
McKinney, W. 2011. Pandas: a foundational Python library for data analysis and statistics. Python for high performance and scientific computing, 14(9), 1-9.
[15]
Jones E., Oliphant T., Peterson P. 2001. SciPy: Open source scientific tools for Python. From http://www.scipy.org
[16]
Barrett P, Hunter J, Miller J T, 2005. Matplotlib–A Portable Python Plotting Package. Astronomical data analysis software and systems XIV, ASP Conference Series, 2005, 347, 91-95.
[17]
RD Instruments. 1996. Acoustic Doppler Current Profiler - Principles of Operation. Second edition for broadband ADCPs, San Diego, CA.
[18]
Kim D, Muste M. 2012. Multi-dimensional representation of river hydrodynamics using ADCP data processing software. Environmental Modelling & Software, 38: 158-166. https://doi.org/10.1016/j.envsoft.2012.05.011
[19]
SonTek. 2000. Doppler Velocity Log for ROV/AUV Applications. SonTek, San Diego, CA.
[20]
Gunawan B., Neary V.S., McNutt J. 2011. ORNL ADV Post-Processing Guide and MATLAB Algorithms for MHK Site Flow and Turbulence Analysis. Oak Ridge National Laboratory, ORNL/TML-2011/338. https://doi.org/10.2172/1034377
[21]
Cheng N.S. 2007. Power-law index for velocity profiles in open channel flows. Advances in Water Resources, 30, 1775-1784. https://doi.org/10.1016/j.advwatres.2007.02.001
[22]
Fan Dong-hua. 2014. Research on computing vertically-averaged current velocity and direction. Journal of Waterway and Harbor, 35(4): 463-468.
[23]
Chen, Y. W., Yap, K. H., & Lee, J. Y. 2013. Tianditu: China's first official online mapping service. Media, Culture & Society, 35(2), 234-249.
[24]
XU Zhi-yang, MEI Jin-juan, HE Jie. 2010. A quantitative method for judging rise and fall of tide in estuary. Journal of China hydrology, (3), 65-67.
[25]
Pawlowiczr, Beardsleyb, Lentzs. 2002. Classical tide harmonic analysis including estimates in MATLAB using T-TIDE. Computers and Geosciences, (28), 929-937. https://doi.org/10.1016/s0098-3004(02)00013-4.
[26]
Zhang Y, Sha W, Zhang X, 2023. Analysis of Current at a Continuous Observation Station in the Shallow Water of the Northern Outer Shelf of the East China Sea. Journal of Physics: Conference Series. IOP Publishing, 2023, 2486(1): 012043. https://doi.org/10.1088/1742-6596/2486/1/012043
Recommendations
Big Data Analysis with Interactive Visualization using R packages
BigDataScience '14: Proceedings of the 2014 International Conference on Big Data Science and ComputingCompared to the traditional data storing, processing, analyzing and visualization which have been performed, Big data requires evolutionary technologies of massive data processing on distributed and parallel systems, such as Hadoop system. Big data ...
Educational data mining with Python and Apache spark: a hands-on tutorial
LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & KnowledgeEnormous amount of educational data has been accumulated through Massive Open Online Courses (MOOCs), as well as commercial and non-commercial learning platforms. This is in addition to the educational data released by US government since 2012 to ...
Mid-water current aided localization for autonomous underwater vehicles
Survey-class autonomous underwater vehicles (AUVs) typically rely on Doppler Velocity Logs (DVL) for precision localization near the seafloor. In cases where the seafloor depth is greater than the DVL bottom-lock range, localizing between the surface and ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
September 2023
441 pages
ISBN:9798400707667
DOI:10.1145/3627377
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 December 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- Youth Science Foundation, East China Sea Bureau, Ministry of Natural Resources
Conference
ICBDT 2023
ICBDT 2023: 2023 6th International Conference on Big Data Technologies
September 22 - 24, 2023
Qingdao, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 30Total Downloads
- Downloads (Last 12 months)21
- Downloads (Last 6 weeks)1
Reflects downloads up to 13 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format