## 2 Geo Big Data Analysis Platforms  
The latest generations of EO satellites are acquiring increasingly significant volumes of data with a full global coverage, higher spatial resolution and impressive temporal resolution. A new era of EO based on the Big Data paradigm is coming, where innovative tools able to support remote sensing investigations will be increasingly necessary in order to exploit all the potentially available geospatial information contained therein, to effectively contribute to study phenomena at the global scale and to monitor them in (near) real time [32; 33]. Indeed, it is no longer technically feasible or financially affordable to transfer the data and use traditional local processing methods to address this data scaling challenge. The size of the data and complexities in preparation, handling, storage and analysis are the key aspects that should be taken into account [27]. This is the reason why, in the last few years, both satellite EO technology and innovative computing infrastructures have advanced significantly. Such solutions, developed by national space agencies, open source communities and private companies have a great potential to streamline data distribution and processing capabilities, while simultaneously lowering the technical barriers for users to exploit the EO Big Data and to develop innovative services. In this context, ESA started the EO Exploitation Platforms initiative in 2014, a set of research and development activities that in the first phase (up to 2017) aimed to create an ecosystem of interconnected Thematic Exploitation Platforms (TEPs) on European footing, addressing the most important topics on remote sensing (i.e., coastal, forestry, hydrology, geohazards, polar, urban themes and food security). Briefly, TEPs are a collaborative, virtual work environment providing access to EO data and tools, processors and IT resources required using one coherent interface [34]. In 2017, the European Commission in collaboration with ESA and EUMETSAT launched an initiative within the Copernicus program to develop data and information access services that facilitate access to EO Big Data. Earth Servers 1 and 2 are instead two EO Big Data cubes founded by the Horizon 2020 framework [35; 36]. Their service interface is rigorously based on the Open Geospatial Consortium \"Big Geo Data\" standards, web coverage service and web coverage processing service [37]. Considering the high potential of EO Big Data also in commercial applications, Amazon included the full archive of Copernicus Sentinel-2 data in the Amazon Web Service platform through a collaboration with the start-up Sinergise [38; 39]. They developed the Sentinel-Hub, a service-oriented satellite imagery infrastructure that takes care of all the complexity of handling of the satellite imagery archive and makes it available for end-users via easy-to-integrate web services [40]. Since 2015, the innovative GEE processing platform dramatically transformed and pushed one step ahead the EO satellite data user community. GEE consists of a multi-petabyte analysis-ready data catalog with a high-performance, intrinsically parallel computation service. It is accessed and controlled through an Internet-accessible application programming interface and an associated web-based interactive development environment that enables rapid prototyping and visualization of results [28]. Following the user demands, GEE has created a technological solution that removes the burden of data preparation, yields rapid results and maintains an active and engaged global community of contributors. Extensive research and development activity has been performed using GEE, and new applications and services can be deployed to deliver great impact to important environmental, economic and social challenges, including at the local, regional and global scales [41; 42; 43]. Such applications highlight the value of exploiting the EO data, pointing out that the main challenge is in providing the proper connection between data, applications and users.