A Cloud-based platform for geo-analytics production from big satellite data: Rheticus?

摘要

The ESA's Copernicus Program gave birth to a new era of Big Data for Earth Observation (EO) by Remote Sensing. Furthermore, the ease development and launch of small satellites boosts the availability of satellite imagery. As a consequence of the increasing volume and variety of remote sensing data, EO community faces new challenges in handling datasets. It is not feasible to let operators carrying out the collection, management, processing and analysis of such a huge amount of data through out-dated approaches. Moreover, information have to be provided through smarter and more dynamic ways than ever before. The paper presents a cloud-based platform developed by Planetek Italia, called Rheticus? from the name of the unique pupil of Nicolaus Copernicus. Rheticus? is able to process high volumes of EO data (e.g. satellite imagery, weather data, open data sources, and so forth) to provide several continuous Earth monitoring services, ranging from the detection and monitoring of geo-hazards and infrastructure instability, to marine water quality monitoring, from supporting aquaculture activities, to wildfire detection as well as land cover monitoring. Rheticus?' web interfaces providing business intelligence tools, for the extraction of knowledge derived from continuously processed satellite imagery, simplify the use of this information for non-expert users. Whether it's land monitoring or infrastructure, perimeter of the fires or monitoring the quality of coastal marine waters, Rheticus? works as a big hub that processes the data automatically to deliver geoinformation services ready-to-use in users' final applications. Automatic data analysis allows creating geo-analytics and dynamic indicators, and providing actionable knowledge to decision makers. This way engineering and utilities companies, public and private organizations can now easily integrate geospatial free and open information in their business processes, without having to worry about technical data analysis