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Technology Projects

This page gives an overview on all the studies and projects - currently ongoing - managed by the Research and Service Support and Ground Segment Technology Section (EOP-GSR), implemented as part of the ESA Technology and Research Programs. Such projects have been run through an inter-organisation cooperation framework, and in some cases have contributed to the release of some of the environments currently operated by RSS.
Information on past projects can be found in Projects Archive.


The main objective of the project is to develop and demonstrate the technologies for implementing and deploying an infrastructure to foster the joint usability of different and heterogeneous atmospheric datasets. This is a highly relevant aspect in Atmospheric Sciences, where a large variety of data in terms of sensing method, time, geometry, resolution, format and dimensionality (1D simple profile, 2D maps, 3D data volumes, 4D time series, etc.) usually prevents the combined use of various datasets, in particular e.g. for data fusion, trends analysis or data assimilation . Usability is the key aspects: EO products can be separately searched, downloaded, etc. but their joint use is not straightforward.


The objective of the Automation of Monitoring and Control of PDGS and Facilities (AMOC) project is to re-define the technologies and the M&C approach for Earth Explorer (EE) Missions (and potentially also other operational missions). In AMOC, the Agency is therefore seeking - first and foremost - a new concept, followed by a prototyping effort, of monitoring and control tools and systems.
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The Big Data from Space - Reference Architecture Framework (BIDS-RAF) project aims at the analysis, identification and benchmarking of technologies and interfaces for setting-up a prototype architectural framework (platform) to provide an environment for development, deployment and execution of EO Big Data processing chains in an interoperable way, independently from the computing infrastructure. Such a platform shall permit to ease the creation, automation and execution of processing chains in order to support the generation of new users’ applications and services build on the valuable information content hidden within Big Data.
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Over the recent years there has been a lot of effort to adopt blockchain technology in various domains. There has been a lot of confusion regarding the various types of blockchains as well as what are their benefits to the business, information security and what problems do they solve.
The Blockchain for Space Application (BC4SA) project will focus on the use cases that could be supported by the KSI Blockchain in the EO domain. The KSI Blockchain is a mature product provided by Guardtime for independent verification of data integrity and time. It has been in production since 2007 and is used by a number of organizations worldwide.
Besides finding the use cases and business cases, the goal is to document the user and technical requirements for implementing these use cases using KSI Blockchain. While KSI Blockchain is a generic technology that allows verifying any piece of data, integrating with it for a specific purpose requires a number of technical details to be thought through so that the end to end solution is secure but also user friendly and sustainable for further enhancements and from a maintenance cost perspective.


Current ESA and Copernicus Earth Observation (EO) missions are steadily increasing in volume, variety and complexity, interconnection, integration and delivery rate of data. This poses challenges to the way data are treated, from data collection, storage, management, dissemination and access to their analysis, exploitation, processing, integration and delivery to final consumers. In this context, the main objectives of the Co-registration of Data Streams (CORDS) project are to develop the technologies and to prototype a framework for integrating geo-referenced data from different domains and data sources, including data streams, in a fashion that they can be used in a single frontend.
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Landslides are deadly natural disasters than kill an estimated 4,600 people a year. Moreover, landslides cause billions of euros of damage to infrastructure every year worldwide. Railway and road networks are particularly at risk from landslides, and disruption of this crucial infrastructure from landslides leads to significant economic loss. There is no large scale, high accuracy landslide monitoring system currently available.
The objective of the Developing Critical Infrastructure Resilience (DCIR) is to de-risk the operational methodology for determining likelihood of slope failure from rainfall events by using satellite remotely sensed derived data. This rainfall driven landslide model approach to slope failure can be used for management and predictive maintenance of assets.


In recent years, a number of new use cases for the use of satellite imagery in the finance/industry have emerged. They can be small scale where a single investment analyst acquires a small number of images from a single region to understand the context on the ground.
The aim of the Deep Learning for Limited satellite images Training set (DELLT) project is to build an artificial intelligence platform to address the key constraint of having a vast amount of training data to build deep learning algorithms.


The continuously increasing amount of satellite data and their use is a demanding task for the scientific community and for any other user. To design and implement modules to move data exploitation activities (access, visualization, processing, etc.) close to the Payload Data Ground Segment (PDGS) is the scope of the Extended Data Visualization (EDAV) framework.


The expanding operational capability of global monitoring from space, combined with data from long-term EO archives, in-situ networks and models provides users with unprecedented insight into environmental data from space. It represents a unique opportunity for science, research and technology development, specific applications, but also poses a major challenge to achieve its full potential in terms of data exploitation. It raises new issues in terms of discovery, access, exploitation, mining, visualization and sharing of very large and diverse data repositories (the so-called Big Data), with profound implications on how users perform data-intensive Earth Science.
Given the context above, the objective of this activity is to review the emerging IT solutions, select and further evolve the necessary software components to significantly improve future data access and exploitation mechanisms in terms of performance and scalability, and to widen the applicability of the developed solutions (complete and interoperable EO resource metadata model, metadata exposed through JSON(-LD) encoding, etc.).

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The continuously increasing amount of long-term and of historic data in EO facilities in the form of online datasets and archives makes it necessary to address technologies for the long-term management of these data sets, including their consolidation, preservation, and continuation across multiple missions. The management of long EO data time series of continuing or historic missions, with more than 20 years of data available already today, requires technical solutions and technologies which differ considerably from the ones exploited by existing systems.
The objective of this activity is to investigate and develop solutions for access- and exploitation-optimised organisation of data repositories to overcome limitations of today’s storage-optimised implementations (e.g., zipped file based archive). To satisfy such new data access and exploitation scenarios (e.g., pixel-based discovery, access and on-the-fly processing), the archiving structures and data models will have to facilitate user-friendly bulk data retrieval, data processing, visualization, as well as displaying and downloading data layers served by standardized spatial data services.


The main objective of the Mission Planning and Analysis (MPA) project is to identify, benchmark and prototype the components for a constellation multi-mission planning and analysis tool. The tool shall build on existing capabilities and be capable to interface and integrate with international and national EO space assets, with particular focus on large constellations. The technology requirements for such a constellation mission planning system shall be driven by very different and heterogeneous scenarios and customers’ requirements, in order to offer a robust requirement framework for future exploitation of the tool.


The current Product Distribution Facility (PDF) developed as a subsystem of the PROBA-V User Segment and maintained and deployed at VITO, allows users to discover, download, order and subscribe to products from the SPOT-VEGETATION and PROBA-V collections, as well as derived bio-geophysical products. This project shall address the evolution of the current PDF for the SPOT-VEGETATION and PROBA-V data and derived vegetation products at VITO, in order to support next generation of EO data discovery and access services.
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This project aims at addressing the technology needs for a Quality Control Metadata Management Systems in support of the new generation of land monitoring services. This shall include survey about use cases, applicable specifications and alternatives to current operational practices in QC management.
The project shall also deliver an Open Source Software (OSS) system to be potentially deployed in the framework of an operational Land Monitoring Service for QC Metadata Management in synergy with the experiences and results of both the EEA project on Land Cover Continuous Monitoring (LCCM) and the Copernicus Land Monitoring Service (CLMS).


The objective of the Tool Augmentation by User Enhancements and Orchestration (TAO) project is to analyse, identify and benchmark technologies and interfaces for a light, consistent and harmonised software framework, which shall define and demonstrate the basis for next generation of EO toolboxes. Furthermore, these new advanced toolboxes shall support and ease the integration and orchestration of the already existing ones (like e.g. the Orfeo ToolBox anf the Sentinel Toolboxes), addressing in particular user-provided processing modules, as well as the integration of EO product manipulation, analysis and visualisation tools. The framework shall also permit to ease the automation and parallelisation of processing chains in order to address huge data volumes. 

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The objective of the Web based ASI Social SDI (WASDI) project is to implement a unique, simple and intuitive interface to foster the exploitation of the asset concerning EO data and satellite products, for satisfying requirements of users’ communities and, in particular, experts/researchers in the field of Earth Sciences, managers of services and public administrations (i.e. civil protection decision makers).The project aims at developing software tools that will be available for Italian National Collaborative Ground Segment.
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Contributors to this page: ycoene
Michele Iapaolo


Page last modified on Tuesday 14 of April 2020 13:40:49 CEST by ycoene.