Monitoring Changes in Port Activity Patterns

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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 

UN9: Understanding stock levels and monitoring supply chains.

Description

The EO data enables the financial management sector to regularly track changes in port activity patterns including cargo volumes, vessel traffic, and infrastructure development. By analysing these changes, financial managers can make informed investment decisions, assess the financial health of companies engaged in port operations, and identify emerging market trends. 

Spatial Coverage Target

Ports

Data Throughput

Rapid tasking 

Data availability

• High
• High

• Low
• Low

PRODUCT SPECIFICATIONS

Main processing steps

Monitoring changes in port activities over time is applicable by using VHR images with suitable temporal frequency. Then we can perform change detection analysis on the acquired satellite images to identify and quantify changes in the port's infrastructure, cargo volume, vessel traffic, and other relevant parameters. This analysis involves comparing two or more images taken at different times and highlighting the differences between them.  The change detection analysis becomes more informative when we possess labelled data of the port.  In addition to conventional change detection techniques, automated change detection methods using machine learning algorithms can be advantageous in this context.

Input data sources

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

Radar: N.A

Satellite-based products: N.A

Supporting data:  AIS

Accessibility

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

Spatial resolution

Optical VHR: ≤ 0.5 m

Frequency (Temporal resolution)

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

• Cloud presence near large water bodies
• Limited available labelled data of port activities.
• Temporal resolution and Cloud presence of the satellite data can limit the frequency of monitoring and timely detection of rapid changes in port activities.
• Discerning fine-scale details of port activities.
• Access to high-quality EO data, especially from commercial satellite providers, can be costly.
• Limited nighttime observations

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

Skills: Essential

Knowledge: Essential

P13: Monitoring Changes in Port Activity Patterns

Download the product sheet gap analysis 

Maturity score

Mean: 2.4

STD: 0.66

Constraints and limitations

·  Cloud presence near large water bodies

·  No observation at night

·  Cost of VHR satellite imagery

Relevant user needs

UN37: Projection of risk to portfolio assets into the future.

R&D gaps

·  Limited available labelled data of port activities.

·  Temporal resolution and cloud presence of the satellite data can limit the frequency of monitoring and timely detection of rapid changes in port activities.

·  Discerning fine-scale details of port activities.

·  Limited nighttime observations

Potential improvements drivers

·  More frequent VHR optical satellite imagery.

·  More investigation of the use of VHR Synthetic Aperture Radar (SAR) imagery.

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

·  Provide more labelled data on port activities.

·  VHR nighttime light observation.

Utilisation level review

Utilisation score

Mean: 2.33

STD: 0.94

No utilisation

Low utilisation

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