Nautical chart data uncertainty visualization as the means for integrating bathymetric, meteorological, and oceanographic information in support of coastal navigation

Abstract

Most navigational charts are an amalgamation of geospatial information of varying quality collected using different techniques at different times. Data collected with high resolution multi-beam echo sounders or lidar systems may co-exist on the chart with data collected with lead-line as far back as the 18th century. Data quality on charts is currently provided as a series of Category Zone of Confidence (CATZOC) values. For every part of the chart, CATZOC values provide information about the horizontal and vertical uncertainty of bathymetric information, as well as the seabed coverage and feature detection. CATZOC is portrayed in ECDIS as an additional layer with glyphs using a rating system of stars: six to two stars for the best to lowest quality data and “U” for unassessed data. With the provided information mariners may interpret the seabed morphology, identify shoals that pose a threat for the plotted voyage, and select routes that maintain under-keel clearance, however it is not always well understood and utilized by mariners. The aim of this research work is the development of new visualization and integration methods of data quality on charts to support decision making on board. In this two-fold work we begin with investigating new visualization methods for the bathymetric data uncertainty on charts and we subsequently utilize the results of the visualization work for the integration of marine navigation related information in support of decision making and safe navigation of ships.

Full text

N C D U V
NAUTICAL CHART DATA UNCERTAINTY VISUALIZATION
C.Kastrisios1, C. Ware1, B. Calder1,
NAUTICAL CHART DATA UNCERTAINTY VISUALIZATION
C.Kastrisios1, C. Ware1, B. Calder1,
T. Butkiewicz1, L. Alexander1, O. Hauser2
NAUTICAL CHART DATA UNCERTAINTY VISUALIZATION
T. Butkiewicz1, L. Alexander1, O. Hauser2
NAUTICAL CHART DATA UNCERTAINTY VISUALIZATION
ASTHE MEANS FOR INTEGRATING BATHYMETRIC, METEOROLOGICAL, AND OCEANOGRAPHIC
T. Butkiewicz , L. Alexander , O. Hauser
ASTHE MEANS FOR INTEGRATING BATHYMETRIC, METEOROLOGICAL, AND OCEANOGRAPHIC
I I S O C N
1University of New Hampshire, Center for Coastal and Ocean Mapping/UNH-NOAA Joint Hydrographic Center, Durham, NH, USA.
2
National Oceanic and Atmospheric Administration, National Ocean Service, Office of Coast Survey, Hydrographic Survey
Division, Pacific Hydrographic Branch, Seattle, WA, USA.
INFORMATION INSUPPORT OFCOASTAL NAVIGATION
National Oceanic and Atmospheric Administration, National Ocean Service, Office of Coast Survey, Hydrographic Survey
Division, Pacific Hydrographic Branch, Seattle, WA, USA.
INFORMATION INSUPPORT OFCOASTAL NAVIGATION
INTRODUCTION RESEARCH WORK PRELIMINARY RESULTS
INTRODUCTION RESEARCH WORK PRELIMINARY RESULTS
V
Navigational charts are generated from geospatial
information sources of varying quality, collected at different VISUALIZATION
Hue Lightness
V
ISUALIZATION
information sources of varying quality, collected at different
times, using various techniques. Requirements:
VISUALIZATION
Hue Lightness
V
Textures consisting of lines using the following strategies:
times, using various techniques.
Starting in the 18th century, depth information was collected
Requirements:
Unambiguously visualize the different uncertainty levels.
Textures consisting of lines using the following strategies:
Emphasize uncertainty while reducing visual clutter in low-uncertainty areas by varying:
•Line Density: Increasing the density of lines to indicate higher uncertainty values
Starting in the 18th century, depth information was collected
using hand deployed lead-lines. Improved techniques in the
20th century included single-beam echo-sounders. Most
Unambiguously visualize the different uncertainty levels.
Minimize the occlusion of navigational information.
•Line Density: Increasing the density of lines to indicate higher uncertainty values
•Opacity/Transparency: Decreasing the opacity of lines in areas with high-quality data
20th century included single-beam echo-sounders. Most
recently, high resolution depth information is collected using
Minimize the occlusion of navigational information.
Increase visual weight with the increase of data uncertainty.
•Opacity/Transparency: Decreasing the opacity of lines in areas with high-quality data
Disambiguate uncertainty levels through the use of:
recently, high resolution depth information is collected using
multi-beam echo sounders and airborne lidar systems. The
challenge for chart users is how to assess the quality of the
Maintain compatibility and effectiveness in all ECDIS modes.
Disambiguate uncertainty levels through the use of:
•Different texture orientations for “assessed” and “unassessed” levels.
challenge for chart users is how to assess the quality of the
depth information portrayed on the chart. Methods:
•Use of solid or dashed lines for uncertainty quantification.
depth information portrayed on the chart.
Data quality on charts is mainly encoded in the meta-object
Methods:
Investigate visual variables in terms of their suitability: Size Shape
Data quality on charts is mainly encoded in the meta-object
Quality of Data (M_QUAL) with one of the Category Zone
of Confidence (CATZOC) values. For every part of the chart,
Investigate visual variables in terms of their suitability:
Color / Hue
Size Shape
of Confidence (CATZOC) values. For every part of the chart,
CATZOC values provide information about the horizontal
Color / Hue
•Most primary and secondary colors are already reserved for other uses in the ENC/ECDIS or are not suitable for all ECDIS modes.
CATZOC values provide information about the horizontal
and vertical uncertainty of bathymetric information, as well
as the seabed coverage and feature detection.
Color lightness and saturation
•Both interact with base information and may alter the perception of the underlying chart features.
as the seabed coverage and feature detection. •Both interact with base information and may alter the perception of the underlying chart features.
•The portrayed layer can obscure ENC “Base Display” information.
•The portrayed layer can obscure ENC “Base Display” information.
•The portrayed layer of data quality can become dominant in dusk and night modes.
CURRENT SITUATION
Size
•The identification of the different CATZOC levels becomes ambiguous whenever only a few of the levels are displayed.
CURRENT SITUATION
•The identification of the different CATZOC levels becomes ambiguous whenever only a few of the levels are displayed.
Shape
CURRENT SITUATION
VISUALIZATION Orientation Density
Shape
•Arbitrary shapes are not intuitive and require a legend.
VISUALIZATION
CATZOC is portrayed in ECDIS as an additional
Orientation Density
•Arbitrary shapes are not intuitive and require a legend.
Orientation,and density
CATZOC is portrayed in ECDIS as an additional
layer with symbols using a rating system of stars:
•They can create an ambiguous visualization of the different CATZOC levels.
layer with symbols using a rating system of stars:
six to two stars for the best to lowest quality data
and “U” for unassessed data. INTEGRATION
Possible solution:
and “U” for unassessed data. INTEGRATION
Highlight features (e.g., soundings, wrecks, rocks, and obstructions) that pose a threat to the vessel.
Possible solution:
Use a sequence of textures, created by combining two or more visual variables.
Highlight features (e.g., soundings, wrecks, rocks, and obstructions) that pose a threat to the vessel.
Example workflow:
Use a sequence of textures, created by combining two or more visual variables. Example workflow:
User selects one of the available visualization/integration extents.
Visual Variables
User selects one of the available visualization/integration extents.
User defines THU and TVU values for ZOC D.
I
Visual Variables
Features that intersect the integration extent are selected (i.e., charted location + circle for THU)
Depths are “reduced” based on their vertical uncertainty.
I
NTEGRATION
Depths are “reduced” based on their vertical uncertainty.
Features shoaler than the safety depth are highlighted with circles around their charted location and
Requirements:
Features shoaler than the safety depth are highlighted with circles around their charted location and
“reduced depth” is displayed within the circles.
Integrate the quantitative information encoded in the ENC.
Support mariners in voyage planning and execution.
Support mariners in voyage planning and execution.
Methods:
Methods:
Investigate the possible extents of the visualization/integration:
Overview: Covers the entire ECDIS screen. Useful in route planning.
Safety Zone: A zone of fixed width for each leg of the voyage. Useful in hazards appraisal (similar to the existing Cross-Track Limits (XTL) in ECDIS).
INTEGRATION
Safety Zone: A zone of fixed width for each leg of the voyage. Useful in hazards appraisal (similar to the existing Cross-Track Limits (XTL) in ECDIS).
Safe Course: A zone of width equal to the horizontal uncertainty of the underlying M_QUAL. Useful for hazards appraisal but mostly for the route monitoring.
INTEGRATION
During route planning, the mariner checks for The task can be accomplished with the support of
Safe Course: A zone of width equal to the horizontal uncertainty of the underlying M_QUAL. Useful for hazards appraisal but mostly for the route monitoring.
Watch Area: A circle or cone around the vessel’s position based on the vessel’s characteristics. Useful for route monitoring (similar to Anti-Grounding or Look-
During route planning, the mariner checks for
features along the intended route shoaler than the
safety depth.
The task can be accomplished with the support of
ECDIS and a user-defined zone on both sides of the
planned course.
Ahead settings in ECDIS).
safety depth. planned course.
Possible solution:
Possible solution:
Develop the four extent options as additional layers in ECDIS. Potential depth and position of a 10m charted feature for
Develop the four extent options as additional layers in ECDIS.
Use as a sequence of steps in route planning and monitoring.
Potential depth and position of a 10m charted feature for
different CATZOC situations
FUTURE WORK
FUTURE WORK
Visualization of hazards:
Visualization of hazards:
Investigate color (e.g., magenta, black), type of line (e.g., solid, dashed, or dotted), size of font and line,
Investigate color (e.g., magenta, black), type of line (e.g., solid, dashed, or dotted), size of font and line,
location of the displayed reduced depth (e.g., over the shoal, on the outline of the circle).
Horizontal and vertical uncertainty for ZOCs D:
Propose numerical values.
Propose numerical values.
Feedback:
PROBLEM STATEMENT
Feedback:
Seek opinions of professional mariners.
Portraying CATZOC with these star symbols creates visual clutter, which can obscure high-quality depth
PROBLEM STATEMENT Seek opinions of professional mariners.
IHO Engagement:
Portraying CATZOC with these star symbols creates visual clutter, which can obscure high-quality depth
information.
IHO Engagement:
Present final research results to the respective IHO bodies for further evaluation and implementation.
ACKNOWLEDGEMENTS
information.
Horizontal (THU) and vertical uncertainty (TVU) may not be adequately taken into account.
ACKNOWLEDGEMENTS
This work is supported by the National Oceanic and Atmospheric Administration (NOAA) Grant NA15NOS4000200
Objective: Develop a better method for portraying CATZOC in ECDIS. Overview Safety Zone Safe Course Watch Area
This work is supported by the National Oceanic and Atmospheric Administration (NOAA) Grant NA15NOS4000200
Objective: Develop a better method for portraying CATZOC in ECDIS. Overview Safety Zone Safe Course Watch Area
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