Enhancing the Efficiency of Ping-to-Chart Process with Automated Tools
In the realm of hydrographic data processing, manual data entry and review can be a tedious, error-prone, and time-consuming task. However, many of these requirements are mechanical and conducive to automation. This is where Quality Control (QC) Tools come into play.
QC Tools are software applications or systems designed to automatically check, validate, and ensure the accuracy and reliability of hydrographic survey data and related nautical information. These tools contribute significantly to automating the workflow in hydrographic data handling and nautical documentation update.
Data Quality Assessment
QC Tools evaluate hydrographic data quality by checking parameters such as survey date, positional accuracy, depth accuracy, and seafloor coverage. These checks are essential for determining the reliability of the data used in nautical charts and electronic navigational charts (ENCs).
Classification into Zones of Confidence (ZOC)
These tools automatically categorize hydrographic survey data into quality categories (e.g., A1, A2, B, C, D, U) that indicate the confidence level of the data. This facilitates standardized quality ratings across hydrographic products.
Integration with Nautical Documentation
QC Tools automate the updating of nautical documentation by linking quality-assessed hydrographic data with chart production systems. This ensures that charts and related publications reflect the most accurate and current survey information.
Data Synthesis and Standardization
QC Tools support the creation of standardized hydrographic and marine data sets, which underpin modern maritime navigation solutions. This enables the seamless update and distribution of nautical documentation.
Public Access and Decision Support
Through automated quality control and standardization, these tools also enable greater public access to validated observational hydrographic data, supporting data synthesis efforts and informed maritime decision-making.
In summary, QC Tools streamline the processing of hydrographic data by ensuring data quality through automated assessments and classifications, which then feed directly into the automated updating of nautical charts and documentation. This enhances the accuracy, reliability, and timeliness of maritime navigation products.
Automation of these tasks increases accuracy and reproducibility by reducing subjectivity and human errors. The ability to provide algorithmic interpretation of specific requirements for hydrographic processing and cartographic generalization is an important step towards a fully automated workflow.
The QC Tools interface has functions to import data, detect anomalous grid data, ensure requirements for grid sounding density and uncertainty have been achieved, scan selected designated soundings, implement an agreement check, and export seabed area characteristics. The NOAA Office of Coast Survey has been used as a pilot study to guide the implementation of these tools.
The ocean mapping community uses open-source formats like the Open Navigation Surface Bathymetry Attributed Grid (BAG) format and the International Hydrographic Organization (IHO) S-57 format for gridded bathymetric data and vector features. The QC Tools package, described here, implements ideas for automation in hydrographic processing.
The QC Tools package uses the HydrOffice project, which makes available and easily accessible several libraries likely to be useful in the construction of ocean mapping tools. The package addresses common challenges in hydrographic processing, such as identifying anomalous grid depth data (fliers), ensuring no grid data gaps or "holidays" exist, validating feature objects, and comparing sounding selections.
Automated routines can aid reviewers by flagging anomalies they may have missed, especially those of lesser magnitude, which are more difficult to detect manually. Automated routines can also ensure that data meets statistical metrics defined by hydrographic offices. The tasks are suitable for automation because many requirements are objective and quantitative.
Faster overall ping-to-chart times are also a benefit of automation. Throughout the charting process, it is often necessary to compare sounding selections. The QC Tools package, described here, implements ideas for automation in hydrographic processing.
The QC Tools package is written in Python and uses a modularized environment, allowing for easy customization. This makes it a versatile tool for the hydrographic community, facilitating the development of more efficient and accurate hydrographic data processing workflows.
- QC Tools assess the quality of hydrographic data by evaluating parameters such as survey date, positional accuracy, depth accuracy, and seafloor coverage.
- These tools automatically categorize hydrographic survey data into quality categories, facilitating standardized quality ratings across hydrographic products.
- Integration of QC Tools with nautical documentation automates the updating of charts, ensuring they reflect the most accurate and current survey information.
- QC Tools support the creation of standardized hydrographic and marine data sets, essential for modern maritime navigation solutions.
- Greater public access to validated hydrographic data, made possible by QC Tools, supports data synthesis efforts and informed maritime decision-making.
- The QC Tools package, written in Python and using a modularized environment, is a versatile tool for the hydrographic community, facilitating the development of more efficient and accurate hydrographic data processing workflows.
- Automation of tasks, such as data quality assessment, automates the workflow in hydrographic data handling and nautical documentation update, contributing significantly to renewable-energy projects, climate-change studies, environmental-science research, and the industry associated with business, housing-market, and real-estate, data-and-cloud-computing, and technology sectors.
