Automating the Marine Chart Production Processes

Furuya, Hitoshi

doi:10.3138/6716-9222-4534-3440

“…The identification of nautical chart discrepancies in comparison to newly collected hydrographic survey datasets has received only limited attention in the scientific literature despite its importance for the safety of navigation and relevance in the evaluation of the adequacy of the current charts, as well as for coastal change analysis and coastal zone management [21][22][23][24][25]. In addition, many of the techniques developed for geospatial data analysis on land cannot be directly applied to the nautical cartography realm, mainly because of the peculiar safety of navigation requirement [12,[26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Masetti

¹

,

Faulkes

²

,

Kastrisios

³

2018

IJGI

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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.

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“…The identification of nautical chart discrepancies in comparison to newly collected hydrographic survey datasets has received only limited attention in the scientific literature despite its importance for the safety of navigation and relevance in the evaluation of the adequacy of the current charts, as well as for coastal change analysis and coastal zone management [21][22][23][24][25]. In addition, many of the techniques developed for geospatial data analysis on land cannot be straightly applied to the nautical cartography realm, mainly because of the peculiar safety of navigation requirement [12,[26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Masetti¹,

Faulkes²,

Kastrisios³

2018

Preprint

View full text Add to dashboard Cite

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.

show abstract

“…The topic of the identification of nautical chart discrepancies in comparison to newly collected hydrographic survey datasets has received only limited attention in the scientific literature despite its importance to the safety of navigation and relevance in the evaluation of the adequacy of the current charts, as well as for coastal change analysis and coastal zone management [21][22][23][24]. In addition, many of the techniques developed for geospatial data analysis on land cannot be straightly applied to the nautical cartography realm mainly because of the peculiar safety of navigation requirement [12,[25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Masetti¹,

Faulkes²,

Kastrisios³

2018

Preprint

0

View full text Add to dashboard Cite

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.

show abstract

Automating the Marine Chart Production Processes

Cited by 3 publications

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Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

Automated Identification of Discrepancies between Nautical Charts and Survey Soundings

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