Portfolio

The objectives of this feasibility study are to assess the technical feasibility and commercial viability of an integrated solution and associated services which support the optimization of freight transport through ports (e.g. routing and scheduling), based on a better understanding of users and stakeholders needs and transport conditions, and better information exchange. 

Rezatec and the Eden Project will explore how geospatial data analytics could benefit individual growers or forest owners with small areas under management, by providing commercially valuable and actionable decision support tools accessed via a self-service, digital platform. In addition, these analytics could be provided as an operational service to other creative visual installations at museums and institutions around the world.

Vialone leverages Big Earth Observation Data to support European organic rice farming and trade. Copernicus data and tailored in-situ sensors keep rice paddy fields constantly monitored from both space and ground. Vialone unlocks best practices of organic paddy management and supplies early information on growth trends. Thanks to Vialone, the so-called mature consumer will be able to make healthy and informed choices based on reliable traceability information on top-tier organic rice. 

Precise Apiculture Supported by Space Technologies (acronym: PASST) is a mobile application that enables the implementation of precise apiaries management based on the latest satellite technologies and geolocation in connection with close cooperation with agricultural producers.

RailSAT intends to enhance the current practices of monitoring railway track geometry and the surrounding environment by using Earth observation satellite data, in particular Interferometric Synthetic Aperture Radar (InSAR), and satellite navigation. 

VtDaws is a service developed on a SaaS model. VtDaws includes in its features the access to EO data (especially Sentinel and Copernicus Services data), a change/anomalies detection engine based on machine learning techniques, a warning service transforming data into information to the users and community sourcing features to add in-situ data and share information on smartphones or tablets.

SnowSense aims at the qualitative, spatial and temporal improvement of available snow information (snow covered area, snow parameters). It integrates space and ground-based assets to achieve this target. The project has won the 2013 ESA IAP IntegSpace Award.

The ARCT^TM stakeholder mapping tool offers visualization of “Project Health” in the cross-roads between society, environment, business and policy. The unique de-risking tool combines climate change risks with other factors and makes them relevant, simple and visual for owner and decision makers of any infrastructure project.

ARCT has also found a fun and engaging way to score and report on the UN Sustainability Goal Climate Action goal #13. www.arct.tools.

Alba Orbital is working to develop satellite applications which utilize each aircraft’s unique ‘Automatic Dependent Surveillance-Broadcast’ (ADS-B) signature. ADS-B signals contain data on flight path, and flight weather conditions, and can be used to enhance global weather forecasts, verify aircraft carbon emissions, and aid in Mayday scenarios, especially when fused with other satellite and ground based data-sets. 

Our mission is to help organizations manage their natural resources more efficiently and sustainably. To achieve this goal, we augment satellite imagery with Artificial Intelligence and environmental expert knowledge to deliver actionable business insight to our customers.

Planet B is too far away – let’s take care of Planet A.

Greenhouse owners are in a very competitive market, in which unexpected costs due to damage and decay of the greenhouse assets can cause severe problems. This feasibility study aims to provide insights into how an early warning service using space data can help greenhouse owners to prevent or mitigate non-insurable risks threatening their business.

A number of countries are making preparations to turn the rapidly warming Arctic into a busy global shipping route.

The objective of the ARC-REACH project is to validate the need and feasibility to setup a cost-effective low-power long-range dynamic radio network, tailored for tracking of cargo and maritime activity, complemented with remote sensing of the environment.

Smallholders are underserved by credit providers as lenders are unable to assess their risk. Sensonomic’s system uses predictive and prescriptive simulations to assess system effects of credit deployment and open the market. With its dynamic data consumption, and iterative and reactive simulations, the service provides a continually updated prediction of how robust the credit providers portfolio is.

Proposed system serves as a platform for Airside area management based on ICAO and EUROCONTROL legislative as a support for satellite navigation.

AIME Aeronautical Information Management Environment software platform enables to create and share digital aeronautical data including the temporal warning messages (Digital NOTAM) in AIXM 5.1 format.

The aim of this project is to investigate the feasibility of developing the next generation of CBRN information management system through the provision of a web-based service model which enables a wide user community to have access to the type of advanced CBRN IM technology already available to the military in the UK, the USA and NATO.

CERASAT aims to provide reliable, real-time and global rainfall measurement services. It extracts the rainfall information from the signalling data generated in satellite communication (SatCom) networks by employing advanced machine learning and signal processing techniques. CERASAT can complement existing rainfall measurement solutions e.g. rain gauges and weather radars.

HiVaCroM uses a time series of Sentinel-1 SAR observations as the basis for generating field-level canopy cover measurements for high value potato crops on a national scale. The canopy cover measurements are required frequently, throughout the growing season, as input to yield models and to inform crop performance metrics. The yield model and crop performance metrics provided important information that growers and supply chain can use to manage crop-related risk during the growing season.