The proposed project (hereafter: EO-VAS project) will RESHAPE Earth Observation Value Chain by BREAKING “DOWNSTREAM” component and significantly SIMPLIFYING development and delivery of Earth Observation Adding Value Services (hereafter: EO VAS). Project foundation is built around SINERGISE’s award-winning (2016 Copernicus Masters Award) Sentinel Hub Operational Prototype (world-first engine for archiving, processing and distribution of Sentinel data) and GEOVILLE’s extensive set of processing algorithms (applied in over 100 existent EO VAS). Main project delivery, EO-Toolset has an ambition to become: - First virtual market place for EO VAS, introducing completely NEW BUSSINESS MODEL in the area of EO services = model, benefiting all participants in EO value chain - from data providers, through service providers to end-users. - EO VAS innovation hub: fostering development of EO services, becoming a virtual meeting place for the exchange of new ideas and encouraging EO VAS experimenting - Virtual business incubator for emerging earth-observation oriented start-ups, that lack the means to commercialise their EO services by themselves. - Pre-processing engine for other EO domain services, helping them to reduce pre-processing costs and to turn their attention into domain expertise and higher quality of their products. EO-VAS will focus on the agriculture and non-life insurance as high revenue entry markets, with the entire optical EO space industry application domain field as revenue market. Conservative investment ROI turning point is 2022 with project’s 15-year’s Net present value of almost € 11,2 MIO, Internal rate of return of 46%. Importantly, due to the setup of EO-VAS enabling customer processing capacities, an significant economic benefit is expected to the entire EO application market, with an estimated leverage effect of 30, putting the effective value of EO-VAS at € 336 MIO.

The proposed project: “Copernicus for environmental law enforcement support” (hereafter: EnviroLENS) aims to widely open the doors towards regular usage of EO technologies in legal sector. The goal of EnviroLENS is to deliver specific environmental governance and enforcement services that will enable immediate and EFFECTIVE environmental MONITORING and ENFORCEMENT → providing legal precedents thus, establishing a confidence base amongst user community → providing a motivation for policy/contract designers to construct statutory/legal solutions that clearly foresee the usage of EO data/services → boosting the employment of EO services in legal sector. EnviroLENS delivers three types of innovations: 1. TECHNOLOGICAL INNOVATIONS Earth observation technology + Semantic data mining technology will be used to merge two seemingly unrelated domains (EO and legal domain) into a joint environmental enforcement eco-system. 2. CONCEPTUAL INNOVATIONS; EnviroLENS is delivering a cross-domain solution = not constrained by usage domain nor constrained by the type of EO service. The uniqueness of the EnviroLENS arises from its front-office capabilities; EnviroLENS can embrace any EO service and transform it by enriching it with new (LEGAL) added value. 3. COMMERCIAL INNOVATIONS are based on EnviroLENS open value chain strategy, the main idea being that anybody can contribute and receive commercial benefit out of his contribution. The project is dedicated into the promotion of EO data as admissible court evidence, not just to change the ruling procedures, but to provide tenets for policy makers and lawyers to seriously consider usage of EO data as regular means of environmental control (making it part of regulations: laws and contracts). EnviroLENS will create completely new market niche addressing LEGAL domain in areas of: Contractual management and Environmental governance. Project exibits high market potential with 30.000.000 EUR NPV and 35% IRR.

PerceptiveSentinel project will deliver PerceptiveSentinel platform - an INTERMEDIATE EO service that will through seamless access to highly pre-processed DATA provide: - MODELLING and PUBLISHING capabilities for - DESIGN, EXPOSURE and EXPLOITATION of EO-processing chains for - FORECASTING, MONITORING and HISTORICAL ANALYSIS in different domain fields, based on - MULTI-TEMPORAL and MULTI-SPECTRAL EO-Data and Non-EO Data MODELLING. PerceptiveSentinel platform will combine BIG-DATA SOURCES, (2) both spatial and non-spatial, (2) whether remote sensed, observed in-situ or derived (3) whether public, private or proprietary—onto a single system. The data will be transformed into action by applying STREAMING MACHINE LEARNING to UNLOCK its value. Platform’s capabilities will significantly shorten development cycles, enabling rapid development of EO services, opening new opportunities for large-scale exploitation of data and provide the means for new EO “downstream players” to smoothly enter the market without the investment into their own storage and processing capabilities. Commercialisation approach will be based on (1) FREE and OPEN access to services and data, (2) OPEN-VALUE-CHAIN approach, (3) LOW COST of services and on (4) DELIVERING VALUE TO END USERS. It is our intention that PerceptiveSentinel platform becomes FIRST value and benefit sharing EO platform in the world. We intent to expose an alternative business model building on COOPERATIVE VALUE CREATION and capture, including all aspects of EO value chain from data providing, product/service development, publishing and consuming. We believe in synergetic effects of cooperation, using PerceptiveSentinel platform to establish alliances with external partners, taking an open approach to participation and building joint commercial success on the delivery of new added value.

Global Earth Monitor project (GEM) is addressing the challenge of continuous monitoring of large areas in a sustainable cost effective way. The goal of the project is to establish a new disruptive Earth Observation (EO) DATA-EXPLOITATION MODEL which will dramatically enhance the exploitation of Copernicus data. For the first time a continuous monitoring of the planet on the global/regional scale will be enabled for a sustainable price. Disruptive innovations are planned in the technology and in the methodology domain, where a proprietary concept of Adjustable Data Cubes (a combination of static and dynamic data cubes) will be developed and integrated with EO-oriented open source Machine Learning (ML) framework EO-LEARN. During the project EO-LEARN will be upgraded to consume ML technologies from widely accepted ML frameworks and to adapt/evolve them to specifics of EO-data interpretation. Modern ML technologies and approaches (GAN, RNN, LSTM, Attention & Bayesian Deep Learning, Curriculum Learning, Incremental learning, Meta-learning, Hybrid modelling) will be combined to construct GLOBAL, SCALE-INDEPENDENT interpretation models with the special focus on CAUSALITY and CHANGE DETECTION. Technological and Methodological innovations will be combined into a unique CONTINUOUS MONITORING PROCESS. The process, based on seamless combination of data interpreted with sub-resolution, native resolution and super-resolution methods, will deliver optimal combination of Processing/Storage costs – enabling continuous monitoring of large areas for just a FRACTION OF CURRENT COSTS. The concept of continuous monitoring will be validated through the development of five specific use-cases and through their employment in a 10-month demonstration - operational continuous monitoring of 10 MIO square km area.

BirdWatch will support the restoration of spatial heterogeneity on farmland, a necessary component in the lasting recovery of our ecosystems. Farmland is a major source of our food and farmland biodiversity is vital for our subsistence, at least when it is in a healthy condition. BirdWatch will make this monitoring of farmland habitat suitability, a product of both rigorous species distribution modelling and EO data-based geospatial features of the individual farmland parcels, freely accessible to various stakeholders and the interested public. The bird species’ requirements regarding their habitat are the guiding factor of the habitat suitability assessment. With the knowledge on farmland bird habitat requirements and the capability to monitor farmland in terms of habitat suitability opens up the possibility to optimise the structural makeup of farmland and associated greening measures. Combined with the requirements of local stakeholders, including their budgetary and operational constraints, BirdWatch becomes a tool for the optimisation of greening measures both ins terms of farmland bird species requirements and stakeholder constraints. With more effective greening measures at optimised cost, farmers will be supported to increasingly reach ecological and economical sustainability. This will alleviate the burden of costs and economic pressure, thus incentivising landowners to take action towards the improvement of their lands. Additionally, economic instruments such as the CAP or the EAFRD which distribute financial aid to sustainable and organic farming activities will be provided with evidence-based support in monitoring compliance with national and EU biodiversity regulations and the definition of new, increasingly effective policies. With an evidence-based view on biodiversity and the effectiveness of greening measures, BirdWatch encourages the improvement in the communication and mutual understanding between scientists, farmers and administrative bodies.