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��Using EO and advanced analytics to assess public transport infrastructure resilience to improve safety and efficiency

Fran Martín Rivas

USER CONSULTATION PLATFORM 2025

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Who we are

Founded in 2020 | 15+ years of experience in Earth Observation (EO) and Artificial Intelligence (AI)

Trusted by the public and private sectors | €1M+ in revenue

Strong track record with ESA | Leading multiple European projects

Our mission is to unlock the value of satellite and geospatial data through Artificial Intelligence, generating insights and analysis that are accessible, useful, and easy for users to understand.

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Context: Public Transport under climate stress

Why EO matters now

Public transport is increasingly exposed to climate-driven disruptions:
Extreme events such as heatwaves, floods, landslides, storms, and fires are increasing in frequency.
Impacts: service interruptions, infrastructure stress, safety risks.
Operators increasingly need:

Early warning system
Situational awareness
Forecast-driven planning
Environmental compliance

EO provides the missing environmental layer behind delays, vulnerabilities and operational risks.

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EO Value for Public Transport

What Earth Observation brings

Reveals invisible risks, such as subsidence under a tram line, allowing preventative maintenance.
Enables proactive, forecast-driven planning through climate and environmental analytics; for example, 3-day ozone forecast alerts can trigger ventilation adjustments in metro stations during pollution peaks.
Scales to entire public transport networks, offering network-wide vulnerability mapping rather than isolated asset monitoring.
Supports regulatory compliance, for instance when Sentinel-5P confirms measurable NO₂ reductions after implementing a Low Emission Zone, validating adherence to EU air-quality action plans.
Strengthens operational decision-making by feeding EO-derived risk and health indicators directly into routing, planning and communication systems.

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Case Study 1: Air Quality & Climate Indicators for PTOs (JULIA)

The JULIA project aims to accelerate the adoption of EU Space services in the public transport sector.

Within this system, EarthPulse provides the environmental intelligence layer, turning Copernicus air-quality and climate data into simple, actionable indicators that operators can use in real time.

What we deliver?

Real-time and forecasted air quality so operators know when pollution peaks are coming.
Weather and climate indicators — rainfall, temperature — combined with forecasts to show how conditions will affect operations.

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Case Study 1: Air Quality & Climate Indicators for PTOs (JULIA)

How Public Transport Operators can use it?

Adjust ventilation and health measures in stations on high-pollution or extreme-heat days.
Adapt routes or service frequency when weather is likely to cause delays or safety issues.
Anticipate changes in demand during heatwaves or heavy rain.

Which is the impact?

More reliable services under extreme weather.
Reduced passenger exposure to pollution peaks.
Stronger sustainability and policy decisions backed by real, objective data.

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Case Study 2: Climate-Resilient routing for DRTs (Rural Drive)

RURALDRIVE transforms rural mobility by combining AI, satellite-based environmental data, and energy-efficient transport solutions. The project delivers a next-generation DRT platform with climate-resilient routing, optimized EV fleet management, and an AI assistant.

In that vision, EarthPulse provides the environmental intelligence that feeds the routing engine.

What we’ll deliver?

A Safety Layer combining wildfire and flood risk with forecast updates, highlighting where environmental hazards may affect road segments.

A Healthy Layer based on vegetation condition and air quality, identifying cleaner and more comfortable route alternatives.

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Case Study 2: Climate-Resilient routing for DRTs (Rural Drive)

How it will be used?

For strategic routing, selecting default routes that avoid hazard-prone areas and prioritise healthier corridors.

For dynamic routing, adapting paths in real time when wildfire, flood or air-quality conditions suddenly change.

To support operational decision-making.

What will be the impact?

Safer journeys by avoiding segments exposed to climate hazards.

Healthier route alternatives for passengers.

More reliable rural mobility.

Greater resilience for DRT systems operating in areas with limited alternatives and higher exposure to climate risks.

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Operational & Technical requirements

Data characteristics

Variable spatial resolution, depending on the use case. City level AQ monitoring only require km resolution, but safety-critical events increasingly require sub-10 m insights.
Flexible temporal frequency. Strategic planning can work with daily or multi-day updates, but operational monitoring benefits from hourly conditions.
Reliability & accuracy: environmental layers must provide clear confidence levels and minimal noise.
Forecast depth: short-term (hours–days) is key for operations; long-term (weeks–months) supports planning and resilience strategies.

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Service characteristics

Low latency.
High availability APIs
Scalability: able to support networks that rangefrom small rural routes to large national systems.
Interoperability: seamless integration with a widerange of systems.
Interpretability: operators need simple, operationalindicators (“safe/unsafe”, “low/medium/high risk”)rather than raw EO layers.
Reproducibility: services must adjust to differentgeographic contexts and different operator needs.

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Gaps & Opportunities

Where EO performs well today

Global coverage & consistency.
Environmental intelligence at scale.
Reliable historical baselines.

Where improvements would further enhance services

Higher spatial resolution.
Higher temporal frequency.
Simplified integration and
data access.
Stronger localised forecasts.

New ESA EO missions are key for success!

Where EO performs well today

Global coverage & consistency: ideal for network-wide monitoring across cities and rural areas.
Environmental intelligence at scale: robust for air quality, heat, vegetation, moisture and hazard indicators.
Reliable historical baselines: excellent for understanding long-term climate and environmental trends.
Forecast integration: strong for mid-term planning (1–3 days), useful for AQ alerts and weather-driven operations.

Higher spatial resolution: moving from 10–30 m to 1–5 m would enable true road-segment-level routing and vulnerability maps.
Higher temporal frequency: sub-daily updates needed for dynamic operations (floods, landslides, air pollution spikes).
Lower latency: faster processing pipelines to support real-time alerts and DRT dynamic rerouting.
Stronger localised forecasts: downscaled AQ & climate forecasts to improve operational reliability.
Simplified integration: more ready-to-use EO products (e.g., “safe/unsafe”, “healthy/unhealthy”) instead of raw layers.

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To wrap up

Earth Observation turns the Earth’s hidden risks into knowledge we can act on. Together with GNSS, it unlocks a new era of smarter, safer and climate-resilient public transport.

From low air quality to landslides and wildfire risk, satellites are providing operators with a level of insight and awareness never seen before.

...We’re only at the beginning! With higher resolution, faster updates and more accurate forecasts, the next generation of mobility will not just react to environmental extreme events… it will anticipate them, plan on them, and mitigate them.

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Many thanks!

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Get in touch with us

www.euspa.europa.eu

Linking space to user needs

EUSPA

@space4eu

EUSPA

EU4Space

USER CONSULTATION PLATFORM 2025