SPATRA aims at increasing the use of satellite data in land transport by developing two demonstrators in new downstream applications for monitoring and management of rail and road transport. SPATRA will use satellite with assisted in-situ data to develop two innovative applications for smart transport and logistics, to solve problems of principal modes of land transport, road and rail: road traffic congestions and negative impact of extreme temperatures on railway infrastructure. • SPATRA will provide benefits of satellite-based logistics and road traffic flow monitoring extended beyond improved efficiency by reducing congestion and improving the flow of goods and people. • A novel space-based service predicting the risk of rail buckling based on downstream application for estimation of the rail temperature will be developed that can support rail management plan to prevent track buckling induced train derailments.

SMART2 project will build on the results achieved in project SMART by advancement, innovation and implementation of SMART2 on-board long-range all-weather obstacle detection (OD) and track intrusion detection (TID) system. 2 new systems will be also researched, innovate and developed: advanced SMART2 trackside (TS) /airborne OD&TID systems. All 3 systems will be integrated into a holistic OD&TDI system via interfaces to central Decision Support System (DSS). A holistic approach to autonomous obstacle detection for railways would enable increased detection area including areas behind a curve, slope, tunnels and other elements blocking the train’s view on the rail tracks, in addition to a long-range straight rail-tracks OD. SMART2 platform will be flexible and open for interfacing additional OD&TDI modules based on future technologies. SMART2 project aims at developing a working prototype of the foreseen holistic OD&TDI that will be evaluated in different real-world railway use-case scenarios (TRL 6/7). The SMART2 will review and assess the relevant requirements, including existing ones (in regulation or related to current technologies), as well as those relating to emerging technologies (as being defined in past and ongoing R&D projects). Based on this analysis, a new set of lower complexity requirements will be proposed for a harmonised approach concerning all systems involved in the implementation of ATO GoA 3/4, in general, and, particularly for the OD&TID System.

Addressing critical challenges such as population displacement due to conflicts, exacerbated by factors like climate change, extreme weather events, food shortages, and poverty, remains paramount. The implementation of THEIA, integrating data fusion, processing, and analysis, particularly leveraging Geospatial Artificial Intelligence (GeoAI) and Machine Learning, is poised to enhance the efficacy of existing services significantly. Through the amalgamation of multi-temporal data and diverse datasets, THEIA empowers better decision-making and adapts to evolving policy and user needs. This technological advancement, bolstered by GeoAI, augments detection capabilities and ensures timely access to crucial information, bridging the gap between capabilities and stringent security demands. By integrating non-space data and end-user intelligence, THEIA’s supply chains add value not only at the operational level but also at regional and local levels, facilitating improved coordination. Furthermore, THEIA catalyzes fostering EU-independent capabilities and technologies, thereby bolstering the European space ecosystem's consolidation and ensuring the sustainable coexistence of legacy and New-Space solutions. Its services cater to a wide array of end-users, including EU entities such as SatCen and Frontex, Member State Ministries of Defence, Intelligence Agencies, Police Forces, NATO, and potentially Extra-EU National and Supranational Entities such as the United Nations.

OCEANIDS aims at building user-driven applications and tools, which act as an enabling technological layer for regional authorities & stakeholders in order to achieve a more resilient and inclusive systemic pathway to a Blue Economy in coastal regions. Brining spatial and non-spatial data & services under a single-access window platform for Climate-Informed Maritime Spatial Planning (CI-MSP), the project will allow a more integrated seascape management of coastal regions. The project delivers a Decision Support tool (the OCEANIDS Decision Support Platform - O-DSP), with an over-arching target to collect, harmonise and curate existing climate data services, making data accessible, reusable and interoperable for the development of local adaptation strategies. OCEANIDS facilitates access to knowledge, data & digital services critical for better understanding and managing climate risks, enhancing adaptive capacities and sup-porting transformative innovations. In addition, OCEANIDS sees inclusivity as an enabling, and required, factor towards a Blue Economy. The project has a strong focus on behavioural change, both on individual as well as on a systemic level, en-abling participating regions and communities to better understand and use potential social tipping points and systemic leverage points to accelerate transformative changes towards climate resilience. To achieve this, it promotes inclusive and deliberative governance through meaningful engagement and dialogue between citizens and stakeholders. This will be achieved using case-specific tools (i.e. ephemeral social networks) leveraging local citizens assemblies for bot-tom up deliberation, cultivating a culture of civic engagement, thus empowering individuals to take action in their own communities. Finally, the project will contribute to mobilising sustainable finance and resources towards adaptation at scale and closing climate protection gap.

Clear targets have been defined by the EU for a more competitive and sustainable agriculture (Green Deal). This requires data-driven decision making for farmers, governments and other policy makers, yet there is a severe reference-data gap when observations are needed at the local level. An underexploited source of data is generated by sensors used in agriculture, as they capture crucial information on the crops and the surrounding agri-environmental conditions. Tapping into this source and upscaling them the integration with other data (e.g. satellite) could result in enhanced capacities for regional agri-environmental monitoring. This would require a paradigm shift on how the monitoring systems work, and on the issues of data ownership and governance. The vision of ScaleAgData is thus to gain insight in (i) how these data streams should be governed to the benefit of all stakeholders, especially the farmers, and (ii) how these data can be integrated in the regional agri-environmental monitoring datasets. Through this upscaling, this wealth of information can be shared with a larger farmer community, thus shrinking the technological inequality in the sector. Specific attention will be paid to innovations in sensor technology, edge computing, data analytics, and novel EO-based products. These innovations will be co-designed and showcased in 6 Research and Innovation Labs, each with their specific thematic focus and spread across Europe. This will enable the assessment of the proposed innovations and data governance frameworks, and demonstrating added values of the improved monitoring capabilities for a range of users, including small-scale and agro-ecological farmers, the financial sector, and policy makers. With these outcomes, ScaleAgData aims at contributing to the overall competitiveness and sustainability performance of the European agricultural sector, and to the work of the HE candidate partnership “Agriculture of Data” and the Soil Mission.