Fish Stock Assessment

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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 

UN37: Projection of risk to portfolio assets into future

Description

Ensuring the safety and efficiency of supply chains remains a top concern for ongoing monitoring and surveillance of transportation infrastructure, including highways and railways. This assures structural stability and operating safety, as well as preventing corrosion and degradation, which can lead to costly recovery, failures, and collapses. With a high temporal frequency at the network level, on-site survey activities might be demanding, costly and difficult to implement. To tackle these limitations, SAR techniques, such as the persistent scatterers interferometry methods can be used to monitor transportation assets and surrounding environment. This technique offers the advantage of covering vast areas, spanning thousands of square kilometres within a single footprint, while accurately detecting even minor changes in highways or railways infrastructure by measuring vertical and horizontal displacement of the ground.

Spatial Coverage Target

Highway and Railway Networks

Data Throughput

Rapid tasking 

Data availability

• High
• High

• Low
• Low

PRODUCT SPECIFICATIONS

Main processing steps

Shape file of the highway or railway networks should be acquired. Time series SAR data covers the extension of the network can be obtained from different sources such as Copernicus Sentinel-1 or commercial providers such as TerraSAR-X with the selection based on factors like spatial and temporal resolutions required for the application.  When dealing with known vulnerable locations that can be covered by a few images, VHR SAR imagery is suggested. However, for monitoring large areas, the use of Sentinel-1 data is recommended due to its free availability, larger swath width, and lower spatial resolution compared to commercial SAR imagery. Additionally, after detecting failures using Sentinel-1, utilizing VHR SAR imagery is advised to ensure higher accuracies. Then, SAR data should be pre-processed to correct for various artifacts and errors. This step includes calibration, atmospheric corrections, and removing noise caused by factors like topography and vegetation. By comparing the phase components of at least two SAR images captured in different times by using different PSI techniques (based on the application and area of interest) such as PS-InSAR and SBAS, it is possible to calculate ground deformations which had occurred between sensing periods.

Input data sources

Optical: N.A

Radar: Sentinel-1, VHR images from different sources like ICEYE, Capella space, and TerraSAR-X

Supporting data: N.A

Accessibility

Sentinel-1: freely and publicly available from ESA.

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

Spatial resolution

Sentinel1: 20m

SAR VHR: < 3m

Frequency (Temporal resolution)

Sentinel1: 6 days

SAR VHR: Daily

Latency

≤ 1 day

Geographical scale coverage

Globally

Delivery/ output format

Data type: Raster

File format: GeoTIFF

Accuracies

Thematic accuracy: 1 to 5 mm

Spatial accuracy: 1.5-2 pixels of input data

Constraints and limitations

• Monitoring large highway or railway networks is challenging and using Sentinel-1 can miss some risk events.
• SAR signals have limited penetration through certain materials, which can obstruct the measurements of ground movement beneath these surfaces

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

Skills: Ample

Knowledge: Ample

P36: Monitoring highway and railway networks

Download the product sheet gap analysis 

Maturity score

Mean: 2.5

STD: 0.66

Constraints and limitations

·  SAR signals have limited penetration through certain materials, which can obstruct the measurements of ground movement beneath these surfaces.

Relevant user needs

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

R&D gaps

·   Not cost-effective as need very detailed height data and an understanding of subsidence risks

Potential improvements drivers

·  Develop automated algorithms and systems for the detection of any subsidence. These algorithms can process large datasets quickly and provide real-time or near-real-time alerts to users when subsidence is detected, enabling prompt responses.

·  Provide tools and services for long-term trend analysis, enabling users to assess subsidence patterns over extended periods.

Utilisation level review

Utilisation score

Mean: 1.80

STD: 0.75

No utilisation

·  Users’ lack of EO knowledge and skills to utilize the EO product.

·  Unawareness of the existence of this EO product.

Low utilisation

Medium utilisation

·  Higher cost of using the best available commercial EO product.

High utilisation

Critical gaps related to relevant user needs

Guideline gap

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