Satellite radar remote sensing data provide high-value information for emergency response in relation to different types of natural or man-made disasters, thanks to their all-weather and day-night imaging capability. Furthermore, in this context the system observation response time is a key aspect. The overall delay of the process, starting from the acquisition planning and command uplink up to the datatake transmission to ground and product generation for the final users, is determined by several factors which rely on the design of both space and ground segments.
Two different solutions can dramatically shorten the global response time of an Earth Observation system: the deployment of a constellation of sensors at space segment level and the installation on the ground of a distributed network of local stations for image reception and processing.
The launch of the Spanish spacecraft PAZ on 22nd of February of 2018 allows to HISDESAT as owner and operator of PAZ satellite, create in conjunction with AIRBUS a radar satellite constellation with TerraSAR-X and TanDEM-X, shortening revisit time and enhancing the end-to-end acquisition capability.
On the other side, the data ageing time (time elapsed from the image sensing up to the delivery of the processed product to the user) can be significantly reduced at ground segment level through the adoption of a distributed concept, by suitably selecting the geographical positions of the receiving ground stations and by powering them with an integrated state-of-the-art data processing terminal.
This is the idea behind the multi-mission Direct Access Terminal (DAT) project: to provide the fastest access to remote sensing data ever made for a specific area of interest, determined by the X-band antenna visibility cone.
A prototype of Direct Access Terminal is currently available and installed at Indra Sistemas premises; it was designed, developed and tested in the framework of an ESA GSTP 6.2 project, with the cooperation of HISDESAT, in charge of PAZ satellite operations and services commercialization. The newly developed multi-mission DAT is able to receive PAZ, TerraSAR X or TanDEM X X-band telemetry data from a local antenna, to decipher them and to directly generate radar image products for the terminal users. Connected with the Mission Ground Segments and the Service Segments to receive auxiliary data and to manage the image processing requests, it also includes a local archive for on-demand additional processing and it is able to receive telemetry data from other external remote stations.
The design drivers, main system features and the most relevant results in terms of computing performance will be shown for the already developed prototype. Special focus will be given on the expected time performance that could be achieved with the operational units, as related requirements with this respect are becoming more and more challenging. For maritime surveillance applications the current maximum data ageing allowed is in the order of ten minutes for the overall near-real-time data processing chain, from raw telemetry downlink up to the product delivered to the final users. In order to reach the goal, all possible delays have been carefully minimized taking care of each processing step in the chain. Shared storage, parallel processing, multi-threading, high throughput network and real time extraction of instrument source packets are just ones of the aspects taken into account for the design of the multi-mission DAT.
It is noteworthy that the DAT could be expanded in both vertical and horizontal dimensions, adding higher-level processors for specific missions and integrating the management of new remote sensing missions, either radar or optical, to further improve the potential of the solution.
The inclusion into the M-DAT of the added-value processing chain in order to directly generate higher-level products (vessel detection, oil-spill detection, change mapping, etc..), and the integration of the additional services of acquisition feasibility analyses and users management centre are already on the evolution roadmap for the M-DAT system, with the aim to convert it in a more ambitious and complete Multi-mission Centre for Earth Observation Services: M-CEOS.
The M-DAT could be also equipped with a Long Term Archive in order to extend its own on-demand image processing capability and to perform analyses over historical data. Referring to other possible extensions, an M-CEOS could also receive from the central Service Segment additional auxiliary data such as the AIS signals received by one of the secondary payloads of PAZ satellite. This additional interface could feed a newly developed Anomaly Detection processor that combines AIS technology with SAR imaging processing, that allows surveillance of areas of special interest during a defined time interval, in order to provide information about the presence of ships, interception of a vessel in a defined nearby area, ships adrift at sea or showing anomalous speeds, groupings of vessels, ships entering and exiting ports, and so on. The higher level processors are going to be fully integrated into the M-DAT processing chain to keep high computing performance all over the chain, in order to provide a fast end to end service to the final users. The bidirectional communication between the local user centre of the M-CEOS and the central Service Segment would be performed in background, only at the time of submitting the final production requests confirmed by the M-CEOS users to be acquired by the constellation satellites.
Regarding the Earth Observation data exploitation, M-CEOS also offers the possibility to generate higher level products starting from already generated L1B (or L0) products through the M-DAT catalogue. Thanks to the Long Term Archive envisaged in the M-CEOS, it will also be possible to request specific services exploiting at the same time historical and recent acquisitions, for example coherence maps, change detection services and time series analyses over defined areas.
Taking into account the modularity concept of the GCore kernel, additional functions could be included or not into the extended M-DAT, providing the possibility to build fully customized data access solutions tailored to the specific Customer needs.

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This first Φ-Week Bootcamp, organised by Design & Data GmbH and hosted by the European Space Agency (ESA) as part of the Φ-week brought together a mix of earth observation (EO) researchers, data scientists and innovators, non-space corporates, tech leaders, aspiring entrepreneurs, students and young professionals for an intensive 3-day event.

Participants used creative methods based on design thinking to create new concepts regarding innovative EO-based applications addressing real problems of the food and energy sectors. Throughout the Bootcamp a variety of resources were made available to enable these ideas to be made into fully workable solutions. The teams also worked with expert mentors who supported them in developing viable business models. On the final day an expert jury decided which innovative ideas, products and business models were the most promising. The best ideas received feedback to further develop into a more mature start-up plan.

We will present the key highlights of the Bootcamp and demonstrate how creative methods such as design thinking can enable greater cross-sector idea generation, leading to more innovative applications of EO data.

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EO4cultivar is a four year project funded by the UK Space Agency to develop EO-based solutions for agriculture in South America. By developing the ability to easily disseminate and incorporate Earth Observation (EO) data for use in decision making in agricultural supply chains, EO4cultivar will have real impacts on supporting crop production and managing risk in agricultural supply chains in Peru and Colombia.
In this paper we will outline how EO4cultivar is working with commercial and government stakeholders in Peru and Colombia to deliver information frequently and rapidly within the growing season via trusted channels. We will demonstrate how radar and optical data from ESA's Sentinel satellites are being used to provide up to date information on crop status (e.g. health, growth stage or vigour) throughout the growing season. These data are being provided to commercial growers and farmer advisory organisations via secure data services that provide 'analysis ready' maps, images and analytics that they can use in the office or on portable devices. These services allow stakeholders to monitor crop performance and target management at the individual field or farm scale, as well as deliver crop identification to support biosecurity, resource planning and market intelligence needs at the regional scale.
The project has the overall aims of delivering a sustainable economic benefit through improving the competitiveness of agriculture, whale also delivering societal and environmental benefit, through improved agricultural practices and promoting ways to encourage sustainable use of natural resources. There is a specific focus on the needs of smallholders, to improve opportunities and outcomes for smallholders growing crops that are within the scope of the project and for which there are export supply chains. We will explore the challenges that this presents for developing commercially and socially sustainable services, and the approach that the project is talking through collaboration with stakeholders across the supply to enable these aims to be met.

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Geospatial information (GI) is contributing in monitoring the world’s greatest issues: health risks, resource and land management, disasters, biodiversity, air quality, etc. The increasing number of satellites launched since the 1970s, with a significant supply of satellite imagery presents countless examples of how satellite image users’ can support specific analyses, decisions and associated actions in bringing major benefits to society and the human kinds: number of lives saved, improvements in environmental quality, enhanced regulatory efficiency, etc. Since these benefits are linked to huge investments for the development of this technology, it needs somehow to be reasonably justified for policy makers’. The growing trend towards free access to satellite images raises the question of valuation with a particular acuity. The valuation of GI is still in its infancy due to the difficulties it presents in quantifying exactly its value and examine its benefits. With the absence of a market price, quantifying the value of the satellite images and their usefulness, is as effortful as challenging in the way it can describe the consequences of economic benefits of uses, or losses in case of substitution or acquisition of other sources of information.

The objective of this paper is to present an economic valuation of very high-resolution (VHR) satellite images (Rapid-Eye, Pléiades, SPOT 5, SPOT 6-7) as perceived by the direct users, using a statistical method. We will focus on the images provided since 2011 by the spatial data infrastructure (SDI) GEOSUD/ Theia, based in Montpellier, France (http://ids.equipex-geosud.fr/ http://www.theia-land.fr/en). While the current access and use of the VHR satellites images is free through the platform, quantifying the value of these data presents a significant undertaking for the community of satellite images users and a support tool for other applications in related fields. A survey among the totality of registered users (510 French public bodies and research laboratories, 700 users account) on the platform found a mean value of 1696 euro for a 60x60 sq.km SPOT 6-7 VHR image. For the 13000 images available on the platform, the total user benefits is 22.048 M euros. In addition, 74% of GEOSUD subscribers are ready to pay 750 euro per image above a threshold of 8 images acquired for free. The results show, that users in general have more tendency to pay for a fixed yearly amount to adhere to a VHR pooling mechanism system, than to be quoted per image. However, if an amount of 500 euros was fixed as membership fee, GEOSUD will probably lose 63% of the current number of subscribers.

The approach chosen aims at clarifying the contributions that these information make to the economic activity and particularly to the direct users of the satellite images. The contribution to the literature is in applying an existing economic method within the framework of a spatial data infrastructure (SDI) in order to value non-market data and their benefits. Besides, the direct users constitute a first link between the SDI and the wider community of users of image-based products and services. Hence, by estimating the value that these users draw directly from the VHR satellite images, this research fills part of the gap that exists between the users’ needs for justification materials and the investors’ exigencies on the availability of this technology on the market. The results obtained could be used to stimulate the public awareness about future decision making related to the Earth observation field and more particularly the satellites images. In addition, similar valuation for other SDIs’ products and services could help the decision makers and orient them in designing mechanisms in order to capture more investments and justify the costs of their future interventions.

As the supply of satellite images is expected to see very high growths in coming years, with new comers of large number of ‘small and low-cost’ satellites, the maintenance of existing systems and the development of new innovative systems is becoming more strategic. For this, the valuation approaches should evolve to be more extensive, comprehensive, user-oriented, and more closely tied to explicit targets. Hence, with the absence of standardized practices for measuring the contribution to society of geo-spatial information, this study comes to set a corner stone for future valuation works in which the benefits and impacts of the Earth observations can be investigated and assigned appropriately to their information resources.

Some references of the team
Jabbour, C., Rey-Valette, H., Maurel, P., Salles, JM., 2018. Spatial Data Infrastructure Management: A two-sided market approach for strategic reflections. International Journal of Information Management, accepted, to be published.
Rey-Valette H, Maurel. P., Miellet, Ph., SY, M., Pigache, L., 2017. Mesurer les impacts des infrastructures de données géographiques (IDG) et des observatoires pour assurer leur pérennité. Application à l’IDG SIG-LR. Revue Internationale de Géomatique, n° 3/2017, pp 375-397.

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Earth-i has been delivering to the state of Queensland, Australia, for 2016 and 2017 a very high resolution base image map of their entire state of approx. 2 million km2, with the 2018 coverage having been completed. The entire area is covered with VHR satellite data from the DMC3/TripleSat constellation operated by 21AT. The data is delivered both as individual tiles and as a colour-balanced full-scale mosaic at 80cm pixel size. Other countries around the globe or individual states within them are considering similar projects with an annual very high-resolution coverage. With such large area coverages, the price per km2 falls substantially, hence making it affordable for the customer and yet still be attractive for the supplier.
A number of country wide / regional EO applications benefit from the NASA/USGS LandSat and ESA/EU Sentinel programme, which have well and truly pushed the medium resolution satellite data into the ‘Big Data’ space and service providers are fast coming up with the tools to harvest such ‘free’ data volumes. The Australian government has created their data ‘Cube’ incorporating all the historic ’free’ datasets in a homogenised grid ready for use in a variety of applications, which has seen an enormous uptake. However, for applications such as infrastructure monitoring, localised environmental impact assessment, detailed road mapping, urban sprawl or smart cities, one needs to have very high resolution base data. Otherwise structures of interest will not be mapped, or changes tracked sufficiently enough. VHR image coverage at least once or twice a year is necessary to verify and quantify significant spatial changes. Having recognised these requirements, the Queensland government has provided a very high resolution base map to all its departments on an annual basis. With a spatial accuracy of 6m (CE90) or better, this highly-detailed base map allows the various institutions to plan in accordance to the same data set, ensuring GIS information from multiple sources are accurately represented. In addition, such a VHR base map complements the aerial photo coverage they currently provide over cityscape areas.
This very high spatial resolution annual base image map will not only be used by the regulator, but also as part of the Queensland Globe, and the RGB composite mosaic is free to use for all interested parties. Hence, every engaged citizen, but also the corporate world, agriculture, mining, shale gas or coal companies can verify that their geospatial information provision will be fit for purpose in accordance with the governmental base map.
It is already clear to a lot of politicians and managers that such monitoring and mapping technology is not a ‘nice to have’, but an essential part of any responsible government’s / company’s information tool box. One wants to be and should be, at any time, in a position to make the most informed decisions with an up-to-date geospatial repository, to which the very high resolution earth observation data should contribute an integral part.

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For over 30 years ESA’s Earthnet Programme has played a significant role as part of ESA’s mandatory activities, providing the framework for integrating non-ESA missions, i.e. Third Party Missions (TPM), into the overall ESA Earth Observation (EO) strategy. Complementary to ESA-owned EO missions, the programme allows European users access to a large portfolio of TPM and is particularly important for promoting the international use of EO data.

In line with the Earthnet Programme objectives, ESA aims to foster cooperation and collaboration with not only other national space agencies, but also commercial mission providers. In recent years the availability of low cost small satellites and the innovation of constellations have resulted in an increasing number of commercial companies who have established business models to provide information services fed by their own satellite systems. These New Space players are now playing an important role in the EO international strategy. Some of these new missions are potential candidates for Earthnet TPMs and ESA have therefore set up a project to assess the quality and the suitability of these missions and also to establish dialogues with the various mission providers in order to improve the overall coherence of the EO system; this project is known as the Earthnet Data Assessment Pilot (EDAP).

The EDAP consortium, headed by Telespazio VEGA UK is aimed at the provision of various clusters of expertise to perform an early data quality assessment of existing or future EO missions from national or commercial providers, which may potentially become TPMs within ESA’s Earthnet Programme. Complementary to this support is a focus on the generation of methodologies and guidelines for training and capacity building with each mission provider in regards to performing efficient data quality assessments in preparation for future missions.

This poster presents how the EDAP activities are organised and executed, and will also provide details of the various missions included within each of the instrument-specific domains covering Optical Sensors, Synthetic Aperture Radar (SAR) and Atmospheric missions. Important multi-mission aspects will also be presented for studies that will require inputs from several missions, possibly spanning multiple instrument domains; such studies contribute to interoperability across existing and future missions and help foster synergies between these missions.

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Keywords – Sentinels, Copernicus, ESA Kick-Start Activities, large-scale risk assessment, building assessment, urban areas.

Abstract - Vulnerability and exposure data currently used by insurance and re-insurance companies tend to fall far short of the ideal resolution and accuracy for feeding the models that are used to determine fair insurance fees. The ideal “exposure information on urban areas” would include characterizing each building in terms of risk-related features, such as number of stories, occupancy, year built, area, construction type, number and size of windows, and countless other features. Insurance companies are hungry for such data, that would allow them increase their competitiveness, in a framework where large-scale statistics are still the go-to solution, while at the same time retaining a balanced level of financial risk. This situation triggered our academic spin-off company, Ticinum Aerospace (TA) to submit a business case to a European Space Agency (ESA) call of type Kick-Start Activity (KSA). The proposal, built on the previous technical experience of the company [1], was accepted and a preliminary study co-funded by the Business Applications sector of the European Space Agency was started. The KSA analysed and positively assessed the marketability and financial viability of a new service, named CountFloors [2] covering this information gap. During the project, a case study was performed on a large fraction of the province of Groningen, The Netherlands, as requested by a local customer. The study involved multi-temporal Sentinel-2 data and thousands of street-level images of around 150,000 buildings in the city of Groningen and the surrounding countryside. The satellite and ground images were input into an Artificial Intelligence (AI)-based system, which analysed the data and mapped a set of vulnerability and exposure proxies on every single building in the area of interest. A preliminary assessment of results revealed accuracy levels around 93%. The full paper will report more details about the service and the procedure implemented, and will report how a KSA study turned into a real service for a real customer earlier than expected.

References
[1] Iannelli, G.C. and Dell’Acqua, F., 2017. Extensive exposure mapping in urban areas through deep analysis of street-level pictures for floor count determination. Urban Science, 1(2), p.16.
[2] ESA Business Applications Department, description of the CountFloors KSA project. Online. Available at: https://business.esa.int/projects/countfloors

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Data collected by the European Earth Observation programme, Copernicus, is made available through a number of Data and Information Access Services (DIAS). An increasing number of commercial service providers create front-office services on top of the DIAS: cloud offerings with give the European research community a rich set of tools.
However, research institutions and end user researchers struggle to incorporate these commercial digital services into their activities in a structured manner. Service discovery and procurement are difficult and take up an inordinate amount of time. Service providers find it difficult to reach and meet the needs of the research community in areas such as legal, financial and technical compliance. EO services are often provided by small companies that struggle to scale and market their services widely, making it difficult for researchers and institutions to be aware of them, let alone to procure and access them.

The Open Clouds for Research Environments (OCRE) consortium aims to change this: to bridge this gap between the supply and demand sides and enable and facilitate researchers to use these Earth Observation services in a safe and easy manner, in order to make it part of their day-to-day scientific activity.
OCRE combines the expertise of CERN, GÉANT, RHEA and Trust-IT with the contribution of SixSq, as technology provider, together with EARSC and Evenflow as support to outreach activities. In response to EC call INFRAEOSC-01-2018, ‘Access to Commercial Services through the EOSC-hub’, the OCRE consortium will put in place a service delivery and adoption vehicle for this usage.
This presentation will introduce the benefits of the Open Clouds for Research Environment for providers and for researchers. It will also address how OCRE aggregates community demand and requirements and applies these into a pan-European call-for-competition, for commercial service providers to respond to. This tender which will be launched in Q3 of 2019, will result in procurement-compliant framework agreements with suitable suppliers. In the presentation OCRE will talk about how providers can respond to this opportunity.
In addition the presentation will touch upon how researchers, affiliated/not affiliated to institutions will be able to consume the services through ready-to-use contracts, without the need to run their own tender and how OCRE will stimulate usage through an adoption fund.

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Satellites have fundamentally changed how we perceive and understand the world we live in. Yet, exploitation of Earth Observation (EO) data is in its infancy, with the main limitation being the lack of appropriate digital resources such as storage and computing capacity.

The Copernicus program currently generates 4-5Tb of data per day and is only one of many satellite constellations sending back EO data. However the produced data requires huge storage in order to allow users to benefit from datasets. Cloud computing afforded the required storage capacity and on a scalable level to add or remove storage nodes according to the demand.

Simultaneously, the recent advancements in data processing techniques such as Deep Learning (DL) paved the way to have an integral solutions for EO big data understanding.
By bringing together a unique combination of high performance computing, ultra fast data storage and advanced data analytics, our ability to derive useful insights will be revolutionised.

In this abstract, we present an end-to-end platform which addresses the tight coupling of High Performance Computing (HPC) facilities, massive Earth Observation Data (EOD) and deep learning algorithms. The platform allows users to use pre-processed data in addition to run their own processing tasks utilising from a cloud-based centralised data store for various open datasets.

The architecture relies on open-source tools starting from the data ingestion step until the developed endpoint services. The data ingestion process includes Sentinel-1,2,3,5 and Landsat-8 products once became available on Sentinels Scientific Data Hub and USGS data stores. Once the data were ingested to our cloud-based storage, a set of preprocessing tasks are executed to allow users to run algorithms without spending long time on pre-processing steps. Moreover, the user has the ability to automate a data processing pipeline that runs periodically once the ingestion step is completed.

The platform is equipped with geospatial tools which allows designing and customising multi-purpose analysis services as simple as NDVI or more complicated such as object detection, classification and segmentation. In addition, pre-trained classification CNN models are deployed and ready to be utilised by users.

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The market for Earth Observation (EO) based services is changing dramatically. Driven by advances in Information Technology and the rapid increase in the availability of satellite data coming from public infrastructures like Copernicus and new commercial satellite constellations, the shift to online services seems evident. This is further encouraged by government policies for open data and new data coming from diverse sensors such as mobile and in-situ. Experts consulted during the EARSC Industry Survey suggest that the online services market will grow from less than 5% to be greater than 25% in 5 years’ time.
The shift to online services is a real challenge in a traditionally B2B or B2G market but is, especially for an SME, a real opportunity to develop a new offer, to expand its commercial reach with new or foreign customers. EARSC supported its members to set up the eoMALL web-platform (http://www.eomall.eu) to enter this new market and to develop.

eoMALL is a web platform dedicated to the promotion of European EO added value services. It aims at becoming the reference platform for any EO customer to be aware of EO based services which can be purchased online. eoMALL helps any user to identify EO based services suitable and provides links to selling points which could be either a private marketplace, a broker website or a DIAS. Any services promoted on the eoMALL fulfil a common template making ease the comparison of services. Thus, the eoMALL customer is able to identify which service, or set of services, fits with its expectation. eoMALL is a transparent platform generating qualitative leads to the service provider and, or, platform owner. Designed by and for companies, the eoMALL platform delivers analytics to companies involved in the web-platform to understand what the characteristics of this new user are (location, sectors, topics of interest, wording to search for services). eoMALL is an enabler to link a customer and a provider, is a tool to contribute to the development of the knowledge of companies involved.

Officially launched in January 2018, eoMALL already supports European companies to develop and to expand in different markets such as Communications, Energy, Environment, Forestry, Maritime, Real Estate Management, Retail & Geo-Marketing and Security.

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