satellite derived bathymetry (sdb): new methodology...
TRANSCRIPT
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SATELLITE DERIVED
BATHYMETRY (SDB):
NEW METHODOLOGY
TO HELP ADDRESS
THE NEARSHORE
BATHYMETRY DATA
GAP FOR ALASKA
Don Ventura
Fugro Pelagos, Inc.ASMC GeoJam 2017,
Anchorage, AK
February 2017
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Introduction
Photos: http://www.shedexpedition.com/wp-content/uploads/2014/04/Virginia-Beach-sky-view.jpg; http://gpmoorephoto.com/blog/wp-content/uploads/2012/11/Icy-Bay-Mount-Saint-Elias-Alaska-
Photo.jpg;
• Emphasis on nearshore surveys and the coastal
hinterland has increased over the past few years.
• Generated by concerns over various issues,
including:
• sea level rise due to climate change
• directly-attributable man-made issues such as
land subsidence through extraction of valuable
mineral and water resources;
• growth of, and reliance on, a seaborne Blue
Economy delivering goods as efficiently as
possible;
• concerns over erosion or damage to nearshore
ecosystems necessitating additional focus on
habitat mapping and environmental surveys in
general
• an increasing percentage of the world’s human
population residing in close proximity to the
coast which places extra emphasis monitoring
of this margin
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Introduction
At the same time….
• Economic pressures bring the need for cost-
effective methods of garnering geospatial
data in the nearshore
• Mapping of the land-sea interface requires
the adoption of a broader approach to
hydrographic surveying techniques and
technologies
• This presentation will discuss a solution to
this issue through the pragmatic use of
satellite derived bathymetry techniques in a
real-world scenario from Alaska.
The Importance of Hydrography
why is hydrography important?
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A dilemma….
• Much of the growth in resource exploitation within close proximity to the coast happens in
poorly developed countries with little infrastructure or in remote, resource-rich regions such as
Alaska
• We as an industry are an expensive data collection option for many of these countries and
regions
• Their lack of adequate charting becomes more acute as the global economy matures,
marginalizing them even more
• We need a different approach to lower the first rung on the geospatial data acquisition ladder
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Nearshore Mapping
• Where possible, the most cost effective approaches to mapping nearshore, high-impact
coastlines – notwithstanding absolute accuracy standards - are:
• Remote sensing from wide-area satellite imagery ($)
• Satellite Derived Bathymetry – SDB
• Multispectral Imagery
• Satellite Altimetry
• Airborne active sensor techniques ($$)
• High-resolution RGB Photography
• Hyperspectral Imagery
• Topographic Lidar
• Topo-Bathymetric Lidar
• Bathymetric Lidar
• Traditional acoustic hydrographic survey techniques ($$$)
• MBES, SBES, SSS etc.
• All of the above are affected in different ways by metocean conditions in the nearshore
environment: water clarity, seabed colour and rugosity, platform dynamics and
operational parameter windows etc.
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Remote Sensing Techniques (Geospatial)
Low Altitude
Corridor LiDAR
(Helicopter)
High Altitude
Photogrammetry
Low High
Low
HIg
h
Accuracy
Altitude Medium Altitude
LiDAR
Airborne
Bathymetric
LiDAR
Satellite
Imagery
Mobile /
Terrestrial Laser
ScanningSonar
Bathymetric Survey
High Altitude
SAR (Radar)
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Satellite Derived Bathymetry (SDB) and Imagery
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Approaches to use optical satellite imagery
Indicative / empirical methods:
Relate brightness and log-ratios to water depth
Photogrammetric / stereo approach:
Find matching points on seafloor
Physics based multispectral approach:
Resolve light-transfer and retrieve optical properties
Source: DigitalGlobe WorldView-2, acquisition date: 2011-10-30
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Physics-Based Approach: Overview
Image courtesy of the Centre for Spatial Environmental Research, University of Queensland
Schema of the light signal
measured by optical satellitesPhysical realization of the
system
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Raw Satellite Imagery: Heron Island WV2
Includes copyrighted material of DigitalGlobe. WorldView-2, acquisition date: 2011-10-30
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Atmospheric Effects Removed
Includes copyrighted material of DigitalGlobe. WorldView-2, acquisition date: 2011-10-30
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Water Column Removed
Includes copyrighted material of DigitalGlobe. WorldView-2, acquisition date: 2011-10-30
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Atmospheric Effects Removed (Pre-Correction)
Includes copyrighted material of DigitalGlobe. WorldView-2, acquisition date: 2011-10-30
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Atmospheric Effects Removed (Post Correction)
Includes copyrighted material of DigitalGlobe. WorldView-2, acquisition date: 2011-10-30
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Atmospheric scattering from adjacent land areas
Requirements for identification, correction of adjacency effect
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SDB Process Example: Antigua – ‘Raw Image’
Correction applied:
Atmosphere andadjacency
Water surface effects
Water column
Provides general information, but typically not well suited for aquatic and benthic analysis
Antigua
Northeast Antigua
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SDB Process Example: Antigua – SubSurface Reflectance
Correction applied:
Atmosphere andadjacency
Water surface effects
Water column
Antigua
Provides more detailed information on geomorphologic zoning, spatial and spectral patterns of the seafloor and benthic habitats.
Sat. data used:
Moderate res. (15m grid)
Northeast Antigua
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SDB Process Example: Antigua – Seafloor Reflectance
Correction applied:
Atmosphere andadjacency
Water surface effects
Water column
Antigua
Sat. data used:
Moderate res. (15m grid)
Northeast Antigua
Provides very detailed information on geomorphologic zoning, spatial and spectral patterns of the seafloor and benthic habitats. It represent a clear view to the surface being corrected for water column effects and a perfect baseline for benthic habitat mapping.
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SDB Process Example: Antigua – Satellite Derived Bathymetry
Correction applied:
Atmosphere andadjacency
Water surface effects
Water column
Sat. data used:
Moderate res. (15m grid)
Provides bathymetric information in a dense grid. Data are mapped using EOMAP’s physics based inversion algorithms, which has been applied in more than 40 areas worldwide.
Antigua
Northeast Antigua
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Can we trust the cheapest option?
We can, if we apply an integrated approach….
• SDB can provide very effective cost-effective and initial coverage of a suitable, clear-
water nearshore area
• We can take the initial results and do at least three things:
• Use the data to provide reconnaissance information for follow-on, more easily
quantifiable survey techniques (put an otherwise poorly charted area in focus)
• Conduct more discrete, higher-resolution surveys of the most critical areas for
development or coastal defence/monitoring
• Use the active sensor data to refine the original SDB results to create a better-
defined, integrated product which can start to attain accuracies acceptable to a
wider stakeholder group
• We can also start to recognize the benefits of well-developed algorithms of satellite
imagery to extract even more habitat info from the coastal zone.
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Seafloor Reflectance over Bathymetric Data
Includes copyrighted material of DigitalGlobe. WorldView-2, acquisition date: 2011-10-30
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Assessing the Utility of SDB
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Application: Coastal Zone Management
Worldbank-ESA Integrated Coastal Zone Management: SBD for Palk Bay, India
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Application: Nautical Charting
EOMAPs SDB product competed against three other methods from other service providers
and was used in the BA2066 chart, the first UKHO chart which includes SDB data.
See also the UKHO session at the shallow water conference 2015:http://www.shallowsurvey2015.org/presentations/SS2015_Session05_Talk1_UKHO.pdf
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Client: Qatar Shell GTL limited
Challenge: Fast bathymetry survey to support seismic programs 740 sqkm offshore area
to be mapped within 2 weeks.
Solution and benefits:
o EOMAP physics based processing using Worldview-2 satellite data, generating a
large area bathymetry map with excellent agreement to a multi-beam data set, which
was limited to a single, localized area
Significant cost savings > $1M
Project schedule efficiently supported
HSE risks mitigated
Recognized as key technology to aid
the planning and preparation
of seismic surveys
Applications: Shell Qatar Seismic Survey Support
740 sqkm Qatar shallow water bathymetry survey, 2010.doi:10.2523/17346-MS https://www.onepetro.org/conference-paper/IPTC-17346-MS‘Supporting Qatar Shell with the execution of onshore and offshore seismic programs’ , IPTC conference 2014
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Application: Legal Evidence
South China Sea: Den Haag court case
Using Very High resolution Satellite Images for Den Haag court case
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Application: Seafloor Baseline and Monitoring
Clients: Environmental Agency Abu Dhabi EAD, CONABIO Mexico, Australia Ningaloo, ..
Challenge: Regulatory requirement to update the coastal habitat mapLarge and remote submerged area to be covered in high-resolution.
Solution and benefits:
o Harmonized data processing on seafloor properties using multiple satellites
o Robust and consistent measures and maps through EOMAP technologies
Fast delivery, no HSE risks, largely independent on in situ measures
Cost effective, outstanding resolution
“The mapping ..of the project has met our expectations, and we have already begun to use the delivered data in our day-to-day operations”Anil Kumar, Director, Environment Information Management, EAD
EAD database: http://enviroportal.ead.ae/mapviewer37 000 sqkm, layers produced by EOMAP 2013/2014
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Application: Alaska
Arctic Domain Awareness Center
Proposal To Address The Shortfall In Nearshore Bathymetry
Addressing the Arctic Domain Awareness Center (ADAC)’s
Request for Proposal – Sept 2016
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Which issues were we trying to address?
• We focussed mainly on Question 3 of the RFP under category: “Mitigating Arctic
Environmental Hazards”, specifically:
• “How can we improve awareness and understanding of nearshore bathymetry
across the Arctic (in particular, the North American Arctic)?”
• In doing so, another question posed in the RFP was also partially addressed:
• “How can “on-demand” “local/localized” domain awareness be achieved (via user
defined parameters) and what kind of technologies can best support localized
domain awareness in austere Arctic environments?”
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Goals and Objectives
The Goal of this proposal is to deliver a cost-effective, modern and up-scaleable approach
to improving awareness and understanding of nearshore bathymetry focused on the Alaska
Arctic coast. The SDB feasibility study will address the following objectives:
Definition and accurate determination of Alaska Arctic coast’s environmental suitability to
extract bathymetry from satellite;
Definition of bathymetric data specifications and areas of interest by key stakeholders
relying on nearshore arctic bathymetry for management decisions;
Raising awareness of SDB and Satellite derived habitat characterization as an alternative
method for nearshore bathymetric data collection, its reliability and cost effectiveness as
compared with active sensor methods;
Processing of suitable–for-SDB data and development of SDB deliverables to requested
data spec, thereby reducing bathymetric data gap;
Assess usefulness and value of generated SDB results in improving understanding of
nearshore bathymetry.
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Extent of the AOI
The area of coverage obtainable with contemporary (operational) satellite technology is
shown in red below:
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Extent of the Available Lo-Cost Imagery
Approximately 148 scene footprints in blue result in approx. 450-1000 cloud and ice free
Landsat 8 scenes to be analysed
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Possible Satellite Derived Data Outputs
High Resolution Satellite Derived Bathymetry
o Bathymetry data (32bit floating GeoTIFF, ASCII XYZ file);o Metadata (XML);o Map (PDF);o On request: Fledermaus SD file, KMZ file, contour lines, etc.
High Resolution Seafloor Habitat Mapping
o Seafloor habitat classification (ESRI polygon shapefile), including relevant attributes;o Subsurface reflectance data (GeoTIFF);o Metadata (XML);o Map (PDF).
Land Cover Mapping
o Land use classification (ESRI polygon shapefile), including relevant attributes;o Subsurface reflectance data (GeoTIFF);o Metadata (XML);o Map (PDF).
Raw satellite Imagery Data for the aboveo Satellite image data: GeoTIFF and metadata.
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Tasks and Deliverables
1. Data feasible for SDB processing along the Alaska Arctic to include:
• Multi-temporal satellite image analysis of Landsat 8 and Sentinel 2a raw data;
• Identification and mapping of optically shallow water (approx. SDB area);
• Vector polygon shape of the approximate feasible SDB area (based on Landsat
and Sentinel);
• Vector polyline shape of the coastline (based on Landsat and Sentinel).
2. Stakeholder outreach
• Stakeholder specific SDB processing plan;
• Stakeholder outreach report;
• Unit cost analyses of SDB vs. other data acquisition methods for developed plans.
3. Processed SDB data deliverables - Optional
• Bathymetric grid, 15m and/or 10m spacing stored as ASCII XYZ and/or GeoTIFF
including metadata;
• Vector polygon shape of obstruction not identified in the bathymetric dataset.
4. SDB Results Survey and final report
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Project Impact/Benefit
• Risk reduction for on-site responders;
• Improved intelligence for possible ports of refuge and or grounding locations for
distressed vessels;
• Improved intelligence to support management decisions;
• A powerful bathymetric reconnaissance tool to better focus limited time and resources to
collect active sensor data;
• Increased confidence in a more complete and up-to-date coastal bathymetry dataset;
• Advancement of “on-demand” bathymetry concept that could result in a game-changing
approach to collect nearshore bathymetry in challenging environment.
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Project Impact/Benefit
The impact and benefit of a regional, holistic, nearshore bathymetric dataset with additional
information on seabed composition and habitat characterization for generally un-surveyed
or poorly surveyed swathes of the Alaskan coastline can assist the following agencies and
institutions with:
• marine rescue,
• navigation safety,
• resource management,
• coastal infrastructure management,
• climate adaptation and resilience,
• economic investment,
…and habitat protection responsibilities all stand to benefit from this baseline data.
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Programmatic Risks and Mitigation Plans
• This is a low-risk, high-reward opportunity.
• The ability to analyse 125,000 km of Alaska coastline to
improve understanding of nearshore bathymetry for the
proposed price is unprecedented.
• There is a risk that SDB results may not generate data
quality levels specified by the stakeholder.
• That in itself is also a valuable result that would further
improve the state of practice of using SDB as a viable
method to augment other tried and true, but more
expensive active sensor bathymetry acquisition methods.
• Negative results can be used to specify where further
data acquisition with active sensors is the right way to go.
• Known spring thaws and other environmental factors
affecting water clarity will be taken into account when
selecting satellite imagery.
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Summary
• Alternative solutions to the nearshore mapping of many areas are feasible
• They will not always attain navigational charting standards
• They don’t need to for non-charting agencies
• We need to have an open mind as to how we better serve a greater stakeholder group
• There are ways and means of improving initial results from SDB with iterative processes
utilizing ALB full waveform algorithms and a GT approach
• There are ways and means of improving final coverage and data density which agrees
within a reasonable tolerance for the benefit of many clients
• Key is to quantify what we have and apply appropriate risk to the data usage
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Thank You