An Ocean of Possibilities: Applications and Challenges of Marine Geomorphometry

Abstract

An increase in the use of geomorphometry in the marine environment has occurred in the last decade. This has been fueled by a dramatic increase in digital bathymetric data, which have become widely available as digital terrain models (DTM) at a variety of spatial resolutions. Despite many similarities, the nature of the input DTM is slightly different than terrestrial DTM. This gives rise to different sources of uncertainties in bathymetric data from various sources that will have particular implications for geomorphometric analysis. With this contribution, we aim to raise awareness of applications and challenges of marine geomorphometry.

Full text

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An Ocean of Possibilities: Applications and
Challenges of Marine Geomorphometry
Vincent Lecours
Department of Geography
Memorial University of Newfoundland
St. John’s, Canada
vlecours@mun.ca
Margaret F. J. Dolan
Geological Survey of Norway
Trondheim, Norway
Vanessa L. Lucieer
Institute for Marine and Antarctic Studies
University of Tasmania
Hobart, Australia
Aaron Micallef
Department of Physics
University of Malta
Msida, Malta
Abstract— An increase in the use of geomorphometry in the
marine environment has occurred in the last decade. This has
been fueled by a dramatic increase in digital bathymetric data,
which have become widely available as digital terrain models
(DTM) at a variety of spatial resolutions. Despite many
similarities, the nature of the input DTM is slightly different than
terrestrial DTM. This gives rise to different sources of
uncertainties in bathymetric data from various sources that will
have particular implications for geomorphometric analysis. With
this contribution, we aim to raise awareness of applications and
challenges of marine geomorphometry.
I. INTRODUCTION
Exploration and characterization of the ocean floor
continuously presents new possibilities and challenges. Thanks
to recent and ongoing improvements in acoustic remote
sensing technology, seabed relief can now be measured
rapidly, extensively and at fine spatial scales [1]. Among these
technologies, multibeam echosounder systems (MBES)
provide some of the most detailed and accurate data currently
available [2]. Most of the MBES data are collected during
navigational charting efforts, with a particular focus on
shallower coastal waters where the seabed relief can pose a
hazard to navigation. Due to potential safety concerns,
standards regarding data quality and uncertainty are high for
these shallow datasets. Datasets from deeper waters, however,
still lag behind in terms of quality and quantity. Owing to the
technological challenges and high costs associated with
bathymetric mapping of large and deeper parts of the seabed, it
is estimated that only 5-10% of the oceans are mapped with a
resolution comparable to that on land [3].
The adoption of terrestrial geomorphometric techniques to
investigate marine environments increased in the past decade
[e.g 4]. The primary digital terrain model (DTM) data source
for marine geomorphometry has been bathymetry (depth) grids
generated from MBES data. These DTMs are analyzed to
characterize geomorphological features of the seabed, which
can at times be sources of biological information (e.g. coral
reefs). Bathymetric data have proven their potential to help the
scientific community and government agencies advance their
understanding of seabed ecosystems and geomorphological
processes [5].
The terrestrial geomorphometric literature provides a rich
source of potential analytical techniques for marine studies [6].
It is important, however, to acknowledge that different data
collection and processing techniques used to create underwater
DTM makes the nature of the input DTM different. In addition,
it is more difficult to capture terrain variability underwater
since changes in topography are more subdued in comparison
to terrestrial landscapes. Issues encountered in terrestrial
geomorphometry, such as underlying data uncertainty and the
choice of the analysis algorithm and scale (resolution and
neighborhood size), are also relevant underwater, but they
manifest themselves differently due to the differences in the
input data.
In this contribution, we review some of the most common
applications and challenges encountered in marine
geomorphometry and explore potential future directions.
Lecours et al.
In: Geomorphometry for Geosciences, Jasiewicz J., Zwoliński Zb., Mitasova H., Hengl T. (eds), 2015. Adam Mickiewicz University in Poznań
- Institute of Geoecology and Geoinformation, International Society for Geomorphometry, Poznań

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II. APPLICATIONS
A. Geohazards, Hydrodynamic and Geomorphological
Mapping
In dynamic environments such as the ocean, monitoring
and detecting change is often crucial. The action of
hydrodynamics on the seabed can cause changes in bathymetry
that can become hazards for navigation in coastal waters.
Hydrographic conditions, on the other hand, are directly related
to the morphology of the seabed at all scales [7]. For instance,
banks are known to have far-reaching effects on currents and
circulation patterns, which in turn can modify bedforms [7].
Local geomorphometric attributes have been used to
develop seabed hydrodynamic models. For instance, aspect can
be used as proxy for local and regional currents and gives
information on the exposure of the seabed at a particular
location. Curvature is thought to influence local
hydrodynamics. The ruggedness of the seabed affects
sedimentation and hydrological patterns near the seabed by the
drag or bottom friction that influences the currents. These
terrain attributes can also assist geomorphic and physiographic
classifications of the seabed, as demonstrated by [8]. Regional
geomorphometry can be used to study the legacy of glaciations
in the geomorphology of continental shelves. The retreat of
under sea ice margins leaves different geomorphic evidences
than terrestrial-based ice margins, which can be found on the
seabed [9] and identified using geomorphometric
classifications. For instance, submarine glacial landforms,
captured by multibeam bathymetric data in areas of hypothetic
ice-streams, provide evidence on the style of deglaciation, the
extent of ice-margins, the calving rates, and the sea level at
specific periods in time [10].
Mapping subaqueous geomorphological features is also
crucial in identifying potential underwater geohazards.
Adaptation of terrestrial geomorphometric techniques, such as
morphometric attributes and their statistical analyses, feature-
based quantitative representation, and automated topographic
classification, has been shown to be effective in improving
current understanding of the morphology and physical
processes that characterize submarine mass movements in
passive glaciated margins [e.g. 11, 12].
B. Habitat Mapping
Seabed habitat mapping is probably the field that has
benefitted the most from techniques of geomorphometry to
date. Habitat mapping involves characterizing a habitat in
terms of its physical, chemical and biological attributes [13].
Many of these attributes are known to be linked to terrain
morphology, thus highlighting the potential of terrain
derivatives to describe marine habitats. The abundance and
distribution of marine species can be strongly influenced by
many biotic and abiotic factors, but topography and
geomorphology are among the most important drivers of their
distribution at many scales [14]. Slope, aspect, curvatures and
measures of seabed roughness have all been used in habitat
mapping studies [15]. MBES data have become essential in
studying marine habitats due to their remoteness and the
difficulties in sampling them. Consequently, geomorphometric
analysis performed on bathymetric data is also increasingly
used to find surrogates (i.e. proxies) of species distribution [14,
15]. Seabed complexity and heterogeneity can allow us to
numerically quantify the spatial arrangement and structure of
habitats. Since the complexity of the seabed has been linked to
the distribution of species at different scales, terrain attributes
can be used as surrogates of species distribution [15]. The
quantitative nature of terrain attributes also facilitates the
analysis of relationships between environmental and biological
factors and provides a mean to compare between geographic
regions and also the same region over multiple time steps.
C. Human Dimension
It is estimated that more than 40% of all the Earth’s ocean
floor has already been altered by anthropogenic activities [16].
The physical disturbances of the seabed increase its roughness
and produce changes in hydrodynamic patterns and sediment
distribution that can then affect bedforms and species
distribution [5]. Mapping and analyzing seabed
geomorphology using geomorphometry allows monitoring
changes in the shape of the seabed and identifying these
variations in roughness, thus facilitating the assessment of
anthropogenic impacts on some areas and potential new
hazards for navigation [5].
Geomorphometric techniques can also be used in search
and rescue operations. The difficulties in locating the recently
vanished Malaysia Airlines aircraft (flight MH370) highlighted
the lack of knowledge of seabed features in the search area
[17]. The forecasting of the path of floating debris was limited
by the lack of knowledge of seabed roughness and topography
from which it is possible to estimate surface current directions
and ocean mixing rates, both essential to these predictions [18].
III. CHALLENGES
A. Spatial Scale
As in terrestrial geomorphometry, spatial scale is an
important issue to consider in marine applications. Most of the
phenomena studied are likely to be observed at different scales,
and the scale of analysis should always match the scale of the
phenomena being observed [19]. For instance, many terrain
attributes used in habitat mapping were found to be useful
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surrogate for species distribution at a local scale while others
were more important at broader scales [14].
The spatial resolution and extent of MBES data is
dependent upon the footprint and frequency of the system. As
the distance between the seabed and the sensor increases, the
footprint gets bigger and the spatial resolution decreases. This
makes submarine DTMs more likely to include datasets of
different resolutions, meaning that geomorphometric
techniques, which are sensitive to data resolution, need to be
very robust in marine applications. The integration of different
datasets at different scales over large areas is very challenging
[13].
B. Technological Challenges
The dynamic nature of the oceans makes collection of
bathymetric data dependent upon a lot of different factors that
are likely to induce errors or artifacts in the final DTM.
Artifacts are common in bathymetric data and can strongly
affect the derivation of terrain attributes. Common errors in
depth measurements include errors in the acoustic
measurement itself, movements of the supporting platform, and
inaccuracies in sound velocity corrections [1]. Motion-induced
errors are among the most important source of errors and will
vary depending on the platform used (e.g. ship or underwater
vehicle). Positional accuracy is also an important challenge,
especially for the use of underwater vehicles such as remotely
operated vehicles (ROV) or autonomous underwater vehicles
(AUV). Unlike in satellite and airborne remote sensing,
underwater equipment and technologies cannot use the Global
Positioning System (GPS) to accurately georeference depth
measurements and location. All data are therefore positioned
relatively to surface GPS using acoustic telemetry systems: the
deeper the survey, the worse the positional accuracy gets [20].
When positional accuracy is lower than the spatial resolution
of the DTM, artifacts can be introduced and a mismatch
between the locations from different datasets can occur, which
is a critical issue in change detection where dataset registration
is very important. These challenges are greater in the deep sea
than in coastal environments.
IV. FUTURE OF MARINE GEOMORPHOMETRY
A. Towards a Complete Coverage
Applications of geomorphometry in the marine
environment are likely to increase as more bathymetric data
become available in different types of seabed environment.
MBES allow for systematic collection of data, but when the
water becomes too shallow for surveying systems, it creates a
gap in the continuous data. The combination of bathymetric
LiDAR data with acoustic surveys will ultimately call for
seamless analysis from terrestrial to marine environment. Such
continuous dataset is likely to improve the study of large
landforms that overlap between land and the ocean and the
identification of geohazards in shallower waters, but will also
increase the challenge of integrating different datasets together.
On the other hand, the collection of higher resolution
bathymetric data in the deep sea will become easier and more
frequent with the increasing use of underwater vehicles. This
will help gain additional knowledge on the structure and
geomorphology of deeper environments. There is still much to
learn about the complexity of the seabed at different depths and
environmental settings. As stated in [5]: “It is generally
assumed that seabed structure becomes less complex as one
moves from the continental shelf to greater depths, but is it, or
does this simply reflect our lack of knowledge?”
B. Advances in Technologies and Techniques
The ability to produce a continuous acoustic image of the
surface of the seabed using multibeam acoustics has
revolutionized our ability to understand marine
morphodynamics and the composition and distribution of
sediments, which has in turn significantly improved our
knowledge of seabed processes. Technology and equipment to
survey the seabed is improving in quality, accuracy and cost-
efficiency, which will allow an increase in data availability and
quality. Algorithms that consider the specific characteristics of
underwater surveying, such as the CUBE (Combined
Uncertainty and Bathymetric Estimator) [21], are being
developed to improve bathymetric data processing and are
likely to become more accessible through processing software.
Availability of GIS tools to effectively combine multiple
datasets and perform geomorphometric analyses is key in
making marine geomorphometry accessible to marine
scientists with a wide range of background and experience [22,
23]. Better practices to report data type, quality and scale
within metadata will need to be implemented in order to allow
the most informed analysis of these data [24]. New techniques
are also likely to make the jump from the terrestrial literature to
the marine literature. For instance, geographic object based
image analysis (Geobia) has been gaining some traction in the
seabed mapping community as the spatial resolution of
acoustic data improves [e.g. 25, 26].
V. CONCLUSION
As stated in [6], “One way to promote better practice in the
use of quantitative terrain analysis from bathymetric data is to
ensure that studies of geomorphometry become more
widespread in the marine literature, thereby making the issues
surrounding quantitative terrain analysis more accessible to
marine scientists from a variety of backgrounds.” Marine
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scientists need to be encouraged to apply geomorphometric
techniques underwater to make use of the full potential of their
expensive datasets.
With a few exceptions, most issues being investigated in
terrestrial geomorphometry, such as uncertainty and error
propagation, the choice of algorithms or the multiscale nature
of DTMs are rarely considered in marine geomorphometry
applications. Since the terrestrial geomorphometry community
is currently trying to tackle some of these issues, it will be
important for marine scientists to remain aware of
developments in this field, and to build up a marine
geomorphometry community to draw on experiences from
terrestrial techniques.
ACKNOWLEDGMENTS
VL is funded by the Natural Sciences and Engineering
Research Council of Canada. AM is funded by Marie Curie
Career Integration Grant PCIG13-GA-2013 618149 within the
7
th
European Community Framework Programme.
REFERENCES
[1] Lurton, X., 2010. An introduction to underwater acoustics: principles
and applications (second edition). Springer/Praxis Publishing, 704 p.
[2] Schimel, A.C.G., Healy, T.R., Johnson, D., and D. Immenga, 2010.
Quantitative experimental comparison of single-beam, sidescan, and
multibeam benthic habitat maps. ICES Journal or Marine Science 67,
1766-1779.
[3] Wright, D. and W. Heyman, 2008. Introduction to the special issue:
marine and coastal GIS for geomorphology, habitat mapping, and
marine reserves. Marine Geodesy 31, 223-230.
[4] Wilson, M.F.J., O’Connell, B., Brown, C., Guinan, J.C., and A.J.
Grehan, 2007. Multiscale terrain analysis of multibeam bathymetry
data for habitat mapping on the continental slope. Marine Geodesy 30,
3-35.
[5] Anderson, J.T., Holliday D.V., Kloser, R., Reid, D.G., and Y. Simard,
2008. Acoustic seabed classification: current practice and future
directions. ICES Journal of Marine Science 65, 1004-1011.
[6] Dolan, M.F.J, and V.L. Lucieer, 2014. Variation and uncertainty in
bathymetric slope calculations using geographic information systems.
Marine Geodesy 37, 187-219.
[7] White, M., Mohn, C., and M.J. Orren, 2007. Physical processes and
seamount productivity. In: T.J. Pitcher, T. Morato, and P.J.B. Hart, eds.
Seamounts: Ecology, Fisheries and Conservation, Oxford: Blackwell
Publishing, pp. 65-84.
[8] Harris, P., Macmillan-Lawler, M., Rupp, J., and E.K. Baker, 2014.
Geomorphology of the oceans. Marine Geology 352, 4-24.
[9] Syvistki, J.P.M., 1991. Towards an understanding of sediment
deposition on glaciated continental shelves. Continental Shelf Research
11, 897-937.
[10] Shaw, J., Piper, D.J.W., Fader, G.B.J., King, E.L., Todd, B.J., Bell, T.,
Batterson, M.J., and D.G.E. Liverman, 2006. A conceptual model of
the deglaciation of Atlantic Canada. Quaternary Science Reviews 25,
2059-2081.
[11] Micallef, A., Berndt, C., Masson, D.G., and D.A.V. Stow, 2007. A
technique for the morphological characterization of submarine
landscapes as exemplified by debris flows of the Storegga Slide.
Journal of Geophysical Research 112, F02001.
[12] Micallef, A., Berndt, C., Masson, D.G., and D.A.V. Stow, 2008. Scale
invariant characteristics of the Storegga Slide and implications for
large-scale submarine mass movements. Marine Geology 247, 46-60.
[13] Brown, C.J., Smith, S.J., Lawton, P., and J.T. Anderson, 2011. Benthic
habitat mapping: A review of progress towards improved
understanding of the spatial ecology of the seabed using acoustic
techniques. Estuarine, Coastal and Shelf Science 92, 502-520.
[14] Harris, P.T., and E.K. Baker, eds., 2012. Seabed geomorphology as
benthic habitats: GeoHab atlas of seabed geomorphic features and
benthic habitats. Elsevier:Amsterdam, 900 p.
[15] McArthur, M.A., Brooke, B., Przeslawski, R., Ryan, D.A., Lucieer,
V.L., Nichol, S., McCallum, A.W., Mellin, C., Cresswell, I.D., and
L.C. Radke, 2010. On the use of abiotic surrogates to describe marine
benthic biodiversity. Estuarine, Coastal and Shelf Science 88, 21-32.
[16] Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F.,
D’Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R.,
Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig,
E.R., Spalding, M., Steneck, R., and R. Watson, 2008. A global map of
human impact on marine ecosystems. Science 319, 948-952.
[17] McNutt, M., 2014. The hunt for MH370. Science 344, 947.
[18] Smith, W.H.F., and K.M. Marks, 2014. Seafloor in the Malaysia
Airlines Flight MH370 Search Area. EOS Transactions of the
American Geophysical Union 95, 173-180.
[19] Hobbs, N.T., 2003. Challenges and opportunities in integrating
ecological knowledge across scales. Forest Ecology and Management
181, 223-238
[20] Rattray, A., Ierodiaconou, D., Monk, J., Laurenson, L.J.B., and P.
Kennedy, 2014. Quantification of spatial and thematic uncertainty in
the application of underwater video for benthic habitat mapping.
Marine Geodesy 37, 315-336.
[21] Calder, B.R., and L.A. Mayer, 2003. Automatic processing of high-
rate, high-density multibeam echosounder data. Geochemistry,
Geophysics, Geosystems 4, 1048-1070.
[22] Lundblad, E.R., Wright, D.J., Miller, J., Larkin, E.M., Rinehart, R.,
Naar, D.F., Donahue, B.T., Anderson, S.M., and T. Battista, 2006. A
benthic classification scheme for American Samoa. Marine Geodesy
29, 89-111.
[23] Erdey-Heydorn, M.D., 2008. An ArcGIS seabed characterization
toolbox developed for investigating benthic habitats. Marine Geodesy
31, 318-358.
[24] Greene, H.G., Bizzaro, J.J., Tilden, J.E., Lopez, H., and M.D. Erdey,
2005. The benefits and pitfalls of GIS in marine benthic habitat
mapping. In: D.J. Wright, and A.J. Scholz, eds. Place matters:
geospatial tools for marine science, conservation, and management in
the Pacific Northwest. Corvallis, OR: Oregon State University Press.
[25] Diesing, M., Green, S.L., Stephens, D., Lark, R.M., Stewart H.A., and
D. Dove, 2014. Mapping seabed sediments: comparison of manual,
geostatistical, object-based image analysis and machine learning
approaches. Continental Shelf Research 84, 107-119.
[26] Lucieer, V.L. and G. Lamarche, 2011. Unsupervised fuzzy
classification and object-based image analysis of multibeam data to
map deep water substrates, Cook Strait, New Zealand. Continental
Shelf Research 31. 1236-1247.
Lecours et al.