@article {7321, title = {Effective Automated Procedures for Hydrographic Data Review}, volume = {2(3)}, year = {2022}, month = {August 25}, pages = { 338-354}, publisher = {MDPI}, address = {Basel, Switzerland}, abstract = {

Reviewing hydrographic data for nautical charting is still a predominately manual process, performed by experienced analysts and based on directives developed over the years by the hydrographic office of interest. With the primary intent to increase the effectiveness of the review process, a set of automated procedures has been developed over the past few years, translating a significant portion of the NOAA Office of Coast Survey\’s specifications for hydrographic data review into code (i.e., the HydrOffice applications called QC Tools and CA Tools). When applied to a large number of hydrographic surveys, it has been confirmed that such procedures improve both the quality and timeliness of the review process. Increased confidence in the reviewed data, especially by personnel in training, has also been observed. As such, the combined effect of applying these procedures is a novel holistic approach to hydrographic data review. Given the similarities of review procedures among hydrographic offices, the described approach has generated interest in the ocean mapping community.

}, keywords = {automated procedures, data review, hydrographic survey, nautical charts}, doi = { https://doi.org/10.3390/geomatics2030019}, url = {https://www.mdpi.com/2673-7418/2/3/19/htm}, author = {Giuseppe Masetti and Tyanne Faulkes and Matthew J. Wilson and Julia Wallace} } @article {7375, title = {Introducing Programming to Ocean Mapping Students}, volume = {28}, year = {2022}, month = {November 11}, pages = {108-120}, publisher = {International Hydrographic Office (IHO)}, address = {Monaco}, abstract = {

The next generation of ocean mappers need to master programming skills to meet increasingly higher expectations for timely ping-to-public data workflows. As such, the e-learning Python for Ocean Mapping (ePOM) project was established at the Center for Coastal and Ocean Mapping/NOAA-UNH Joint Hydrographic Center (University of New Hampshire). The project aims to support new ocean mapping students and professionals in reaching a minimum level of programming skills. These skills are then expanded with further powerful capabilities by leveraging the open-source Python scientific stack and the NOAA (National Oceanic \& Atmospheric Administration) Office of Coast Survey\’s Pydro distribution. To the best of our knowledge, the ePOM project represents the first attempt at creating a set of comprehensive open-source courses providing students with the required initial coding skills for a career in the ocean mapping field.

}, keywords = {education, ocean data science, ocean mapping, programming, scientific computing}, doi = {https://doi.org/10.58440/ihr-28-a13}, url = {https://ihr.iho.int/articles/introducing-programming-to-ocean-mapping-students/}, author = {Giuseppe Masetti and Semme J Dijkstra and Rochelle Wigley and Tyanne Faulkes} } @proceedings {6519, title = {Hydrographic Survey Validation and Chart Adequacy Assessment Using Automated Solutions}, year = {2019}, month = {March 18-21}, address = {Biloxi, MS, USA}, abstract = {

The rising trend in automation is constantly pushing the hydrographic field toward the exploration and the adoption of more effective approaches for each step of the ping-to-public workflow. However, the large amount of data collected by modern acquisition systems - especially when paired with the force multiplier factor provided by autonomous vessels - conflict with the increasing timeliness expected by today\’s final users. Such a situation represents a processing challenge for the largely human-centered solutions that are currently available, and the adoption of automated and semi-automated data quality procedures seems the only scalable and long-term solution to the problem. At the same time, there is an inherent value in propagating the application of such procedures upstream in the survey workflow. In fact, capturing potential issues close (in time and space) to their occurrence has the advantages of reducing the efforts required for their solution and limiting their extent. As such, modern surveys should rely more and more on robust data quality procedures that are applied in near real-time.

With the challenge to automate and standardize a large portion of the quality controls used to analyze hydrographic data, NOAA\’s Office of Coast Survey and the UNH Center for Coastal and Ocean Mapping have jointly developed (and made publicly available) a pair of software solutions - QC Tools for quality control and CA Tools for chart adequacy - that collect algorithmic implementations for a number of these tasks. Their aim is to verify whether the acquired data satisfy the adopted agency standards (and, in a more general sense, fit for the intended purpose). These standards usually focus on data quality aspects like data density, coverage, and uncertainty evaluation which are largely automated by the developed tools discussed in this paper, leaving to the experienced hydrographer the duty to review the results and supervise the validation process. After an overview of the tools (and the relevant recent improvements driven by field feedback), this work focuses on a new chart adequacy algorithm as well as an experimental approach for bathymetric anomaly detection and classification. A number of examples that use the publicly available solutions in real-world scenarios are also illustrated.

}, keywords = {automated solutions, ca tools, chart adequacy, hydroffice, hydrographic survey validation, qc tools}, doi = {10.13140/RG.2.2.28983.57761}, url = {https://www.researchgate.net/publication/331966330_Hydrographic_Survey_Validation_and_Chart_Adequacy_Assessment_Using_Automated_Solutions}, author = {Giuseppe Masetti and Tyanne Faulkes and Christos Kastrisios} } @article {6623, title = {Opening the Black Boxes in Ocean Mapping: Design and Implementation of the HydrOffice Framework}, year = {2019}, month = {July 11}, pages = {Freemantle, WA, Australia}, abstract = {

Modern ocean mapping relies heavily on complex algorithms that may strongly affect the reported outputs (e.g., gridded bathymetry, acoustic mosaics). When implemented in commercial software, these algorithms usually cannot be directly examined, and thus represent black boxes.

To ease the understanding of existing algorithms and the creation of better tools for ocean mapping, since 2016 the UNH Center for Coastal and Ocean Mapping and NOAA Office of Coast Survey have been developing an open research framework containing applications that cover all phases of the ping-to-public process. This effort, called HydrOffice, aims to facilitate data acquisition, to automate and enhance data processing, and to improve survey products. These themes are driving the creation of a growing collection of hydro-packages, each dealing with specific aspects of the ocean mapping workflow. The overall goal is to speed up the testing of new ideas and the Research-to-Operations (R2O) transition by minimizing the effort to develop and test new ideas.

HydrOffice has developed a number of applications that encode both existing specifications and long-term best practices, while enabling and extending recent discoveries and research-driven techniques. In return, many users have reported HydrOffice increases workflow efficiency, confirming the benefits of this approach.

}, keywords = {hydroffice, ocean mapping, open tools}, doi = {10.13140/RG.2.2.18516.55681}, url = {https://www.researchgate.net/publication/334611395_Opening_the_Black_Boxes_in_Ocean_Mapping_Design_and_Implementation_of_the_HydrOffice_Framework}, author = {Giuseppe Masetti and Tyanne Faulkes and Brian R Calder} } @proceedings {6622, title = {Pydro and HydrOffice}, year = {2019}, month = {June 18-20}, address = {Canberra, ACT, Australia}, keywords = {hydroffice, ocean mapping, open tools, pydro}, doi = {10.13140/RG.2.2.21557.42721}, url = {https://www.researchgate.net/publication/334605587_AusSeabed_Workshop_-_Pydro_and_HydrOffice}, author = {Giuseppe Masetti and Tyanne Faulkes} } @article {6403, title = {Automated Identification of Discrepancies Between Nautical Charts and Survey Soundings}, volume = {7}, year = {2018}, month = {September 28 }, pages = {392}, publisher = {MDPI Publishing}, address = {Basel, Switzerland}, abstract = {

Timely and accurate identification of change detection for areas depicted on nautical charts constitutes a key task for marine cartographic agencies in supporting maritime safety. Such a task is usually achieved through manual or semi-automated processes, based on best practices developed over the years requiring a substantial level of human commitment (i.e., to visually compare the chart with the new collected data or to analyze the result of intermediate products). This work describes an algorithm that aims to largely automate the change identification process as well as to reduce its subjective component. Through the selective derivation of a set of depth points from a nautical chart, a triangulated irregular network is created to apply a preliminary tilted-triangle test to all the input survey soundings. Given the complexity of a modern nautical chart, a set of feature-specific, point-in-polygon tests are then performed. As output, the algorithm provides danger-to-navigation candidates, chart discrepancies, and a subset of features that requires human evaluation. The algorithm has been successfully tested with real-world electronic navigational charts and survey datasets. In parallel to the research development, a prototype application implementing the algorithm was created and made publicly available.

}, keywords = {change detection, chart adequacy, Nautical cartography, ocean mapping, safety of navigation, triangulated irregular network}, doi = {https://doi.org/10.3390/ijgi7100392}, url = {https://www.mdpi.com/2220-9964/7/10/392}, author = {Giuseppe Masetti and Tyanne Faulkes and Christos Kastrisios} }