Billions of people worldwide rely on the oceans for food and livelihood. Healthy oceans and coasts are essential for economic growth and food production, as well as for the health and wellbeing of local populations. The Blue Economy supports economic growth, social inclusion and improvement of livelihoods, while also ensuring the continued health of coastal and marine ecosystems and the services they provide. This takes careful planning and management, based on a sound scientific understanding of the marine and coastal environments and the communities that depend on them. Decision-makers in developing countries are aware of the need for evidence-based management of coastal and marine resources, but local experts and institutions often lack the resources needed to undertake the monitoring and research required. Marine environments are particularly expensive and challenging to measure and monitor using in situ techniques alone. In many cases there are no viable alternatives to Earth observation for providing the data required.

The power of EO to provide a relatively low-cost means of monitoring marine and coastal environment has long been recognised by the global oceanographic community, as well as by marine scientists in developing countries. As a result, the last three decades have seen an increasing number of initiatives designed to grow the capacity of maritime countries and island states to access and apply satellite-derived data to marine environmental management and research. This presentation will summarise some of the experiences and lessons learnt from past and current capacity-building projects such as ESA-LearnEO!, UNESCO-Bilko, Europe-Africa Marine Earth Observation Network (EAMNet), the Commonwealth Marine Economies (CME) programme, UKSA C-RISe, GCRF SOLSTICE and EO4SD-Marine.

One of the most important lessons is the need to involve local experts, both in research to gain new insights into marine systems, and in the design and development of training resources to support future capacity development in marine and coastal applications of EO. Local experts in universities, research institutes and NGOs possess a unique knowledge and understanding of both local environments and the social and economic circumstances in which sustainable development initiatives have to be implemented. This makes it vital that their perspectives and expertise is included in efforts to help low-income countries meet their sustainable development goals.

An obstacle that must be overcome to achieve this, is the relative lack of resources, knowledge and skills that currently prevents marine scientists in developing countries from accessing and using EO data-products effectively – and thus reduces their ability to deliver effective training in marine EO to younger generations of environmental scientists. There are several reasons for this – including low Internet connectivity, a lack of sufficient local computing resources, and limited access to advice and support from colleagues with greater EO expertise.

The speed of access to the Internet and local availability of adequate computing resources have both improved in recent years. Some centres of excellence are now well connected, but the digital divide is still a serious obstacle for many organisations and individual scientists. This must be borne in mind by any initiative aiming to increase the capacity of low-income countries to use EO-derived information. For example, cloud-based solutions to the access, processing and analysis of satellite data solves many of the problems arising from increasing data volumes that far exceed capacity to download and store the data locally. However, unless cloud-based facilities take account of the low bandwidths and intermittent connectivity still experienced by many developing country scientists, their value for sustainable development will be limited. The server-based architecture that the developed world is moving towards can sometimes be a hindrance to data access, so it may be necessary to complement this with a client-based system that will allow users to prepare requests off-line and submit these from low-bandwidth locations or during periods when their networks are subject to less traffic – for example in the middle of the night.

Supporting local scientists who want to develop the knowledge and skills required to utilise EO-data in monitoring and research is essential for capacity development. International training courses need to build on the combined expertise of both international and local experts. Training materials for use in university courses and continuing professional development work better if they use local examples to demonstrate how EO-derived information can be used for decision support in locally relevant contexts. Such case studies and tutorials should be developed in collaboration with local (or at least regional) experts and tested on local target audiences before being released more widely. The best tutorials are often those based on existing collaborative research that involve both local marine scientists and experts from the global EO community.

Developing the skills and expertise of local scientists is not sufficient, if there are insufficient resources available for their continued employment and on-going research activities. Many challenges associated with delivering decision support for Integrated Coastal Zone Management and Blue Economy development can only met through international collaboration drawing on available international and local expertise. This will make it possible to combine cutting-edge technologies with low-cost solutions that can be applied to data collection from coastal environments in low-income countries. Such research collaborations need to be equitable – in the sense that all participants are adequately resourced and compensated for time spent on the collaborative research. Research collaborations should be open, not just to academic and government research organisations, but also to local and international NGOs, which are often in a position to access traditional knowledge and harness community efforts to implement sustainable practices and collect supporting information for use in the research.

At present there are a number of international and national programmes that aim to support the development of monitoring and research capacity for decision support to meet the Sustainable Development Goals. We hope that these initiatives will continue, so that they provide a sustained and stable environment for fully exploiting the wealth of available EO data to provide on-going scientific support for the sustainable development agenda.

The open-access EO data provided by the Sentinel missions is stimulating the development of scientific software for a broader scientific community and for interdisciplinary use. Our methods and toolboxes have to follow up to allow for the handling more and more diverse open data.
We here present the open-source seismological software project pyrocko (pyrocko.org) for earthquake source analysis that integrates space-geodetic observations of surface displacements, e. g. through InSAR and/or pixel offset measurements, and seismic waveforms. With the combination of these independent data we achieve to better constrain the characteristics of earthquake sources and thereby better inform earthquake hazard assessments.

Since the beginning of use of civil space-borne InSAR data in 1992 with ERS-1, we use them to measure and analyse the static surface displacement caused by large earthquakes worldwide from space. Also pixel offsets measured with space-borne SAR amplitude images and/or optical data can provide valuable surface displacement measurements. So, the Sentinel-1 and Sentinel-2 data contribute reliably a very rich database for earthquake source research. Inverting the surface displacement data informs us about earthquake source characteristics at depth, like fault dimension, fault offset and magnitude, and the mechanism with a very high spatial accuracy. These earthquake characteristics, combined with observed ground shaking form the basis for earthquake hazard assessments.
However, the observational backbone of such earthquake source analyses is still the network formed by globally installed seismic stations, recording seismic waves. Decades ago already the seismological community started to openly share a bulk part of national station recordings. This barrier-free access enabled seismologists to work globally and study phenomena with strongly reduced limits between the location of the earthquake and the location of their own stations. Also an operational use of seismic waveforms for real-time or near real-time earthquake source analysis is realized since a long time by e. g. the USGS (United States Geological Service), the Global Centroid Moment Tensor project and the German Geofon service hosted at GFZ (German Research Centre for Geosciences).
The use of InSAR data for earthquake source analysis, however, is not quite there yet. There is no operational earthquake source inversion and no deep integration of SAR/InSAR data with seismological observations. To advance from here through development of integrative modelling methods is the aim of our research. This research is realized together with software development. We present earthquake source analysis examples of data combinations that demonstrate the success of our developments. Particularly, we show harmonized model set ups for the different data, improvement of model robustness, and increased computational performance of the modelling. These results further indicate their large potential for a future use in operational earthquake data analysis.

Our python-based modular software toolbox pyrocko (pyrocko.org) incorporates state-of-the-art methods and solutions used in both disciplines, the InSAR-based earthquake research and waveform-based earthquake seismology. We provide a rare modern implementation and publication of existing methods, which have been mostly internally distributed so far. On top of this, we establish the first forward modelling routine that implements at the very basis both, static surface displacements (e. g. InSAR data) and seismological waveforms, for non-linear optimization and Bayesian inference of earthquake source parameters.

Our codes are published under the GNU General public License, Version 3. They are managed and accessible via github.com. This helps our users to follow our developments and to interact with us. We provide detailed software documentations and examples on our project webpage pyrocko.org. Our project is supported by German universities and GFZ and and we are also grateful for significant funding by the German Research Foundation DFG through an Emmy-Noether-Grant with the project name “Bridging Geodesy and Seismology”.

Co-ReSyF is a 3-year project (2016-2018) funded by the European Union, within the European Union’s Horizon 2020 research and innovation programme under grant agreement No 687289 that will end in December this year (2018). The consortium consists of eight partners, based in five different countries. It comprises a varied spectrum of entities ranging from academic institutions and national laboratories, to private companies and SMEs. Within the consortium we gather the technical expertise not only to develop the Co-ReSyF system, but also to actively test it with specific research applications. The team is managed by DEIMOS Engenharia S.A. (Portugal), and is composed of University College Cork (Ireland), Terradue Srl. (Italy), ACRI-HE (France), National Oceanography Centre (UK), ARGANS Ldt. (UK), LNEC (Portugal) and Instituto Hidrográfico (Portugal). This abstract will focus on presenting the main results and achievements of the project during this last three years.

During these three years the project developed a Virtual Research Environment (VRE) powered by cloud infrastructure to support the development and uptake of research applications using Earth Observation (EO) data for Coastal Water Research and the education of new generations of coastal researchers in the use of EO data. Co-ReSyF VRE functionalities aimend at overcoming issues faced by inexperienced and new EO researchers, whilst also targeting EO experts and downstream users, with main focus on enabling EO data access and processing for coastal and marine applications.

The core of the platform is given by three components that provide combined data access, processing, visualisation and capabilities:
• Geoportal: the main user access point where he can discover different EO coastal datasets and package them, run the existing applications using those data packages and visualise or download the application run results. This interface is aimed at the novice users with functionalities that allow them to run the existing applications without a in-depth knowledge of the algorithm behind those applications (e.g. pre-defined parameter values, customised thematic data searches).
• Workflow Manager: aimed at the intermediate level users providing access to a suite of EO image processing tools and coastal application components that can be chained into customisable processing workflows to generate different EO based outputs. The main purpose of this component is to allow users to compose their own workflows based on already pre-existing tools or bring their own tools to enrich the Co-ReSyF toolkit.
• Cloud Integration Service: directed at expert users where they can build, test and deploy their applications in dedicated cloud infrastructures and make them available through standardised interfaces (e.g. Web Processing Service)

Those components are complemented by a set of user support systems that helps guiding the researcher through the wide array of datasets, applications and processing chains, available to him in the platform to achieve his research goals.
• Knowledge Base: Wiki like website where all technical and scientific information regarding the tools and applications integrated in the Co-ReSyF platform.
• User Forum: Online forum organized by categories where the platform users, developers and experts can discuss all issues related to the integrated functionalities

Already integrated in the platform are 5 core Research Applications, developed under the project, and also a set of tools that the researchers can use to build their own applications in a user friendly manner. Additionally other potential tools or applications can be added by the research community for sharing with other researchers that may find it useful. The set of core applications to be developed during the project lifetime are:
• Bathymetry Determination from SAR Images
• Determination of bathymetry, benthic classification and water quality from optical sensors
• Vessel detection
• Oil spill detection
• Time-series processing for hyper-temporal optical data analysis
• Ocean coastal altimetry

The development of the platform during these three years was done in close connection with a wide community of coastal and oceanic researchers, who were offered the opportunity to experience, test and guide the development of the platform, whilst using it as a tool for their own research. Co-ReSyF also linked with global stakeholders in various areas, such as climate, coastal and EO research to provide further guidance in the development of the platform, create synergies and assured a higher outreach of the work being developed: Future Earth Coasts (FEC), EurOcean, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Group on Earth Observations (GEO) Blue Planet, World Meteorological Organisation (WMO) World Climate Research Programme (WCRP), and the NOAA Center for Satellite Applications and Research (STAR).

In the next years the consortium aims to position this VRE as an educational tool for coastal researchers, partnering with key academic institutions to establish Co-ReSyF as part of their curriculum. Furthermore, it will integrate additional innovative coastal research applications and expand its user and developer community to provide long term sustainability to the platform.

Today, particularly so in the face of climate change and the need to meet global food and water security requirements, there is an urgent need for a better understanding of land surface interactions (LSIs). Developing methodologies to understand LSIs at different spatial scales and their response to climate change is also essential to assessing the dynamics and distribution of key biophysical parameters and to ensure long term security of the Earth's terrestrial ecosystems. The recent rapid developments in Earth Observation (EO) technology (new satellites launched, drones) demonstrate the real need and the true potential of this technology in this direction.
In this context, ENviSION-EO Marie Skłodowska Curie EU-funded action proposes the implementation of cutting-edge modelling interventions to a Land Biosphere Model (LSM) towards developing a 2D LSM tool that will allow deriving for the first time spatio-temporal estimates of key parameters characterising LSIs. Furthermore, the action aims to unravel the potential of an EO-based modelling technique, so-called "triangle", in deriving estimates of key parameters characterising LSIs from EO data acquired from ESA's (Sentinel-3) and unmanned aerial vehicles (UAVs). Another aspect of ENviSION-EO lies in elucidating the potential of the latter technique in developing a technique for downscaling existing global operational products of SSM provided today at a meso-scale-resolution using Sentinels-3 data.
ENviSION-EO proposes to undertake ground-breaking research that will lead to the development of innovative modelling methodologies, LBM open source tools and EO-derived products. It is anticipated that these will greatly increase our capability to model LSIs at multiple, previously unattained, observation scales, and provide important information for both new research and practical applications. Our project results will also support efforts ongoing globally towards the operational development of related products using technologically advanced EO instruments launched recently or scheduled to be launched in the coming years.
In this presentation we introduce ENviSION-EO project and its research aims and objectives for its 2 years duration. Subsequently, initial results of the research carried out so far are presented, in particular, relevant to the development of a 2D land biosphere model, its synergistic use with different EO and from its validation at different European ecosystems.

KEYWORDS: land surface interactions, Earth Observation modelling, SVAT modeling

To observe and understand in an integrated way the history and the functioning of the Earth system subject to global changes in order to predict its evolution is a fundamental stake in research as well as for numerous socio-economic and environmental issues in relation with sustainable development goals. The integrated knowledge of the Earth system (solid Earth, ocean, atmosphere, continental surfaces and ecosystems) relies on observation data acquired at different spatial and temporal scales by various vectors (satellites, ships, planes, balloons, in-situ networks ...) which constitute both heritage and long-term knowledge bases essential to research activities. Today, thanks to the increased number of Earth observation satellites, of geophysical ground observation networks and of dedicated campaigns, a huge amount of data is collected. In the 21st century, scientists and public actors must have an easy and interoperable access to the numerous data from all components of the Earth system, regardless of their nature, mode of collection or location, since understanding phenomena and processes related to the Earth system dynamics and its evolution requires taking into account all the different terrestrial components and their interfaces. In addition, multi- and interdisciplinary approaches offer innovative perspectives for processing and analyzing data services also for new research paradigms.

This requires innovative infrastructures to accelerate analysis, dissemination and intelligent use of data, indicators and models from national and international observing systems on the entire Earth System and their access by the scientific community, public policy actors and citizens.

This is what we propose to explore through the setting up of the Earth System Research Infrastructure in the framework of the French roadmap. This project federates for the time being four data and services poles dedicated to the four physical compartments of the Earth System : AERIS for the atmosphere, ODATIS for the oceans, THEIA for continental surfaces and ForM@Ter for the solid Earth. The research infrastructure intends to generate and disseminate data and derived products usable by all scientific communities as well as by public policy actors.

Many Earth Observation research projects end with excellent results but with no plan or prospect for those results to be exploited by business. One hears many examples where project teams are unable to continue their work beyond the end of an interesting project, and a gap ensues before new funds are found to allow further research work. In the meantime, people move on, skills and knowledge are lost, and end-users lose interest. Europe’s investment in the R&D then fails to generate any further societal or economic return to Europe, which is a loss and a waste.

For industry it is very frustrating to face heavy competition for R&D funding, whilst also having to justify the investment of company resources into the match-funding required for such R&D programmes. On the other hand, research groups from universities and institutes often find it easier to secure such R&D funding, but find it very frustrating when the results of their research fail to enable new products or services to be brought to market. There is a clear disconnect here.

EARSC is the European Association of Remote Sensing Companies, which represents and promotes the interests of the Earth Observation services industry in Europe. At EARSC, we are trying to set up a process to help businesses to bring the results of research to commercial realisation; “From Research to Business”.

This process will include expert support to researchers and innovators, from whatever their background, to access the most relevant support available for the stage of maturity which they have reached. We introduce the concept of an Exploitation Readiness Level (ERL) which reflects this level of maturity.

We seek to ensure access to expert advice on markets, on legal issues, on technical issues or on finance. Many sources of support for each of these exist and so we plan to link to as many as possible and to connect innovators to experts who are able to support them with the advice that they need. Are they missing a key technology? Could we help connect them with other businesses which may be able to help? Do they need a market assessment for the product or service they are working on? We have the expertise to undertake such assessments and the resources to engage with experts in these domains.

Depending on their situation, businesses may require project funding, they may need loans, or they may need equity finance. Again, EARSC can connect with many potential sources and we bring awareness of different funding agencies and programmes which may be suitable for the situation. The ERL will be the guide for the type and degree of resource which is required. This should be applied in a dynamic way, such that the support provided also develops and evolves alongside the evolution of the concept’s exploitation readiness level.

In short, EARSC seeks to make its expertise and that of its network available for those seeking to bring new research ideas to market. EARSC will start work on this important initiative in 2019. We hope for success in supporting many new businesses, or old business with new ideas, to connect with research and develop ideas into commercial success – “From Research to Business”.

Through this presentation we hope to reach out to the research and industry communities attending LPS2019 to publicise what we are doing and how we can help them. The presentation will cover the essential features of the initiative, and highlight the early successes achieved, and the challenges encountered.