Satellite-Derived Bathymetry for Port and Coastal Monitoring

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Product Category

• Land use
• Land cover
• Natural Disaster
• Climate Change
• Coast Management 

• Marine
• Earth's Surface Motion

Financial Domains

• Investment management 
• Risk Analysis 
• Insurance management 
• Green finance

User requirements 

UN12: Analysis of potential risks in specific regions

Description

Shallow water zones are dynamic, so it is important to be monitored regularly. Satellite-derived bathymetry (SDB) is preferable due to the low cost and near real-time monitoring. Therefore, SDB can help assess the vulnerability of critical infrastructure like shipping lanes, ports, and canals to potential blockages or accidents. By having accurate and up-to-date information on water depths, authorities and stakeholders can identify areas that may be at risk of blockages or accidents and take preventive measures to avoid costly disruptions. For example, the blockage of the Suez Canal stands out as one of the most significant and compelling demonstrations of the importance of SDB in this context. In addition, such information can be used to adjust insurance plans and make informed decisions about the most cost-effective and safe shipping routes.

Spatial Coverage Target

Ports, canals, and coastal areas (with max depth 20m) 

Data Throughput

Rapid tasking 

Data availability

• High
• High

• Low
• Low

PRODUCT SPECIFICATIONS

Main processing steps

Shallow water zones are dynamic, so it is important to be monitored regularly. Satellite-derived bathymetry (SDB) is preferable due to the low cost and near real-time monitoring. Therefore, SDB can help assess the vulnerability of critical infrastructure like shipping lanes, ports, and canals to potential blockages or accidents. By having accurate and up-to-date information on water depths, authorities and stakeholders can identify areas that may be at risk of blockages or accidents and take preventive measures to avoid costly disruptions. For example, the blockage of the Suez Canal stands out as one of the most significant and compelling demonstrations of the importance of SDB in this context. In addition, such information can be used to adjust insurance plans and make informed decisions about the most cost-effective and safe shipping routes.

Input data sources

Optical: Sentinel-2, VHR based on the availability like Pleiades 1A/1B & NEO, WorldView2&3, and SPOT6/7

Radar: N.A

Supporting data:  Ground truth water depth data like LIDAR, single or multi beam Echo-Sounder data.

Accessibility

Sentinel-1&2:  freely and publicly available from ESA.

Optical VHR imagery: commercially available on demand from EO service providers.

Spatial resolution

Sentinel-2: 10 m

Optical VHR: ≤ 1 m

Frequency (Temporal resolution)

Sentinel-2: 6 days

Optical VHR: Sub-daily to Daily

Latency

< 1 Day

Geographical scale coverage

Globally

Delivery/ output format

Data type: Raster

File format: GeoTIFF

Accuracies

Thematic accuracy: 80-90%

Spatial accuracy: 1.5-2 pixels of input data

Constraints and limitations

• The lack of local in-situ data like LIDAR or Echo-Sounder data
• Cloud presence
• Limited to estimate water depth up to max 20m

User's level of knowledge and skills to extract information and perform further analysis on the EO products.

Skills: Ample

Knowledge: Essential

Similar Products

Name of the Product: Planet Biomass Proxy (link)

Spatial resolution: 2 m,10 m,15 m, and 30 m

Frequency (Temporal resolution): Daily

Latency: Few weeks

Geographical scale coverage: Globally

Delivery / output format: ASCII XYZQ files (Point clouds), GeoTIFF (Raster), KMZ overlays for Google Earth, PDF maps and contour lines (Shape files)

Accuracies: 80-90%

Accessibility: Commercially available from EOMAP

P30: Satellite-derived bathymetry for port and coastal monitoring

Download the product sheet gap analysis 

Maturity score

Mean: 2.2

STD: 0.40

Constraints and limitations

·   Cloud presence

·   Proximity with effluents can make the task more complex.

·   Limited to estimate water depth up to max 20 m

Relevant user needs

UN12: Analysis of potential risks in specific regions.

R&D gaps

·   Lack of local in-situ data like LIDAR or Echo-Sounder data

·   The optical-based products depend on the turbidity and the specificities of the location, meaning that worldwide coverage is difficult.

Potential improvements drivers

·  Fusion, with in-situ sensors, long time series of data to model the specificities of the location, combination with other satellite sensors, hyperspectral, SAR, but they need to be acquired at exactly the same time!

Utilisation level review

Utilisation score

Mean: 2.50

STD: 0.87

No utilisation

Low utilisation

·  Higher cost of using the commercial EO product.

·  Unawareness of the existence of commercial EO products with better specifications.

Medium utilisation

High utilisation

·  High importance and relatively accurate versus comparable methods of gathering this type of information.

Critical gaps related to relevant user needs

Utilisation gap

UN12: Analysis of potential risks in specific regions