Newsletter no. 6

Telespazio UK WP2 contribution to Nature Demo

How structural health of critical infrastructures can be measured to quantify their exposure from natural hazards exacerbated by climate change to contribute to risk calculations?

As climate disruptions become more frequent and intense, the resilience of Europe’s infrastructure is crucial as it supports economic flows, human well-being, and social stability throughout the continent. However, this challenge provides a historic opportunity to revolutionise infrastructure by integrating it with nature. The Nature-Based Solutions for Demonstrating Climate-Resilient Critical Infrastructure (NATURE-DEMO) project creates, validates, and spreads nature-based solutions (NbS) for protecting infrastructure against climate threats. It covers critical sectors (e.g. transport and energy) and engages an alliance of infrastructure owners, scientists from industry and academia, and public authorities.

One of the NATURE-DEMO objectives is to develop a digital decision support platform aimed at enhancing the implementation of Nature-based Solutions. Telespazio UK has worked on asset and regional structural health monitoring improvements that will support the decision-making by providing information derived from remote sensing techniques, specifically satellite and drone data.

Satellite imagery enables large-scale, continuous observation over extended areas, providing valuable insights into environmental conditions, infrastructure, and land use. Drones, on the other hand, offer flexible, high-resolution, and site-specific data collection, allowing for frequent inspections and rapid responses to emerging issues. Together, these technologies create a complementary approach: satellites deliver broad context, while drones provide detailed precision. The use of both source of data provides stakeholders with actionable insights that facilitate informed decision-making regarding climate adaptation measures.

Regarding satellite data, Telespazio UK work focuses on the use of Interferometry SAR and specifically in Persistent Scatters Interferometry (PSI). Telespazio UK that uses PSI data to generate Red-Amber-Green (RAG) alerts on assets of interest and these alerts can become more granular when future projections of infrastructure displacements using time series and climate models are added into the calculations.

The first tool, named Satellite Structural Health Monitoring, ingests high resolution PSI and a 3D Building Information Model to generate detailed RAG alerts. The second tool, named Linear Asset Structural Stability, ingests medium resolution PSI data from the European Ground Motion Service (EGMS) to generate RAG alerts over extended assets. Both tools have also the capability to generate alerts based on the forecasted behaviour of the asset thanks to a ML model implemented for the forecasting of displacement in time series from PSI data.

On the other hand, the company CATEC specialised in drone surveys contributes with the integration of Unmanned Aerial Systems (UAS) into environmental monitoring processes significantly enhances the evaluation and management of Nature-based Solutions (NbS) aimed at protecting critical infrastructure. These platforms offer varying capabilities in terms of endurance, payload capacity, and sensor integration, enabling flexible deployment across demonstration sites. The onboard payloads such as multispectral cameras for vegetation indices, thermal sensors for heat mapping, LiDAR systems for topographic modelling, and high-resolution RGB cameras, together provide a valuable environmental assessment framework.

Satellite Structural Health Monitoring (S-SHM) Tool

The goal of the tool described and brought by TPZ UK as background IPR to generate a Red-Amber-Green (RAG) alerts over the different elements of a Building Information Model (BIM) or 3D representation of a critical infrastructure.

Different levels of alerts are raised in correspondence with the datasets of motion observed near or on each BIM element. The Structural Health Monitoring (SHM) BIM based alerting system tool uses an algorithm developed by Telespazio UK named Satellite-SHM (S-SHM), which is mainly based on two sets of data:

• Dynamic site data, provides the motion observed on the infrastructure and its surroundings. This data is mainly from satellites, which justify the name of the algorithm:
  • • PSI data, which can provide observed past and ongoing motion using archive and new satellite acquisitions. In addition, thanks to the time series forecasting developed in this project, this data also provides information on the forecasted displacement. Optional In-situ sensors data, if available, which can provide information on past motion although its main functionality is the possibility to deliver data in real time (e.g. GNSS sensors)
• Static site data, provides information on the infrastructure as follows:
  • • BIM, including geometric and structural information
    • Motion thresholds for the different infrastructure elements stated at the design phase ideally. These thresholds can be included in the BIM.

These two datasets are combined and linked, and RAG alerts are raised for each BIM element, see schema beside.

Linear Asset Structural Stability (LASS) Tool

The goal of the Linear Asset Structural Stability (LASS) algorithm is to generate RAG alerts over linear assets exploiting all the information provided by a PSI database, which can be EGMS (European Ground Motion Service) or any other PSI source. Interpretation of the PSI results and their application to specific assets for structural stability monitoring is a key step in providing information in an easy-to-use format.

Belo a schema of the LASS tool is shown. There are two sets of inputs: dynamic site data, which gives information on the displacement on the asset; and static site data, which provides the location of the asset to be analysed and also a set of thresholds to be used in the generationof the RAG alerts.

The LASS algorithm is divided into three modules: Datasets preparation, PSI time series deep analysis and evaluation, and linear asset RAG classification.

The first step of the dataset preparation is to ingest two vector datasets:

• • Linear asset dataset - this contains the location of the asset and specific asset information.
  • PSI Dataset - containing measurement point location, time series of displacement and annual velocity.

After data reading, the algorithm splits the linear asset into smaller segments with a defined length (e.g. 100m), although end sections of the assets may vary slightly. The segment length defines the granularity of the algorithm results and can be adapted to the area of study. In order to assess the stability of each segment, the PSI measurement points within a buffer (e.g. 10m buffer) of each segment are used.

The next step is to analyse in detail the information provided by all the measurement points linked to each linear asset segment. Each of these points contains a time series describing its motion during the period of analysis. In order to understand the stability of the linear asset, this time series needs to be analysed in detail.

The generation of alerts algorithm works in the same way than in S-SHM. It is focused on the analysis of:

• • Accumulated Displacement, and
  • Recent Mean Displacement

The three parameters above are computed and recorded for each measurement point and linked to the nearest linear infrastructure segment.

Once the displacement near each linear infrastructure segment is analysed, the segments are classified in Red-Amber-Green. For this classification, two different thresholds are considered for each parameter: the comfort and the safety thresholds. A segment is classified as Green when all the three parameters are below the comfort thresholds which indicates the linear asset is stable. A segment is classified as Amber when any of the parameters exceed the comfort thresholds and are below the safety one, which indicates a cause for concern. Finally, a segment is classified as Red when one of the parameters exceeds the safety thresholds, which indicates requirement of immediate inspection.

In summary, these satellite data based methods aim to assess the structural health of assets using S-SHM and infrastructures using LASS. They provide structural measurement data (surface movement) and contributes to the physical risk assessment of the structure at local level with high resolution and regional level with medium resolution. High resolution is provided by satellites such as CosmoSkymed imaging with radar at 3m pixel resolution and integrating the measurements in the BIM of the structure and Sentinel-1 at 10m pixel resolution for large coverage of linear infrastructures. In addition, both methods can be used not only to measure the structural health at one point in time but study the historical evolution of the structural behaviour opening the possibility to correlate damages and trends to specific climate or other dynamic events. This scalability allows to use both products to assess the structural health prior and post interventions at different scales according to the size of the infrastructure allowing periodic updates on the measurements.

The project will inform on the implementation of S-SHM and LASS models for two demonstration sites: Gschliefgraben landslide and Gradaščica River in SW of Ljubljana inclusing monitoring data updates after the implementation of NbS.

About Telespazio UK

With a pedigree in space technology stretching back nearly 50 years Telespazio UK (TPZ UK) is an experienced consulting, technology, engineering and space services development business. A subsidiary of Telespazio S.p.A in Rome (joint-venture between Leonardo and Thales), TPZ UK has built its first-class reputation by exploiting technology developments in Earth Observation and satellite navigation & communications, pioneering innovative services for customers across institutional, defence & security and commercial markets..

As a leader in satellite systems, applications and geo-information, TPZ UK ensures the clients receive the best advice, support and management. The domain experts specialise in earth observation, navigation, telecommunications, instrument, payload and ground segment systems, as well as software and downstream application development enabling commercial markets to benefit from space data derived solutions. TPZ UK develops Geospatial and EO applications to support the changing world, providing new insights and helping improve decision making with reliable data, for example, applications that can monitor critical infrastructure or extreme climatic events.

The NATURE-DEMO project continues to make excellent progress, and the consortium meeting held in Vienna in 17-19 November 2025 provided partners with an opportunity to review achievements, discuss current challenges, and define directions for the next phase of implementation.

During the discussions, partners reviewed the project’s progress over the first year and a half, covering research activities, the development of digital tools, planning activities at demonstration sites, and strengthening communication strategies. The importance of collaboration between teams and the role of an integrated approach in developing nature-based solutions was highlighted.

Participants also discussed collaboration with external experts and how their experience contributes to improving project outcomes, particularly in risk assessment, climate resilience, and integrating solutions into decision-making processes.

The Vienna meeting marked an important step in consolidating the project’s strategic directions and preparing activities for the coming months. The consortium will continue working on developing the digital platform, documenting demonstration sites, engaging stakeholders, and promoting nature-based solutions at the European level.