The advent of satellites and other sensor technologies has led to an exponential increase in available environmental data. This data ranges from satellite imagery to meteorological and atmospheric measurements. However, analysing this data in real time and on a large scale is a complex challenge that exceeds traditional computing infrastructures.
Cloud computing offers a solution here by providing a scalable and flexible infrastructure that enables large amounts of data to be processed and analysed quickly. By utilising cloud platforms, researchers and environmentalists can access powerful computing resources without the need for expensive hardware investments, costly maintenance or downloading large amounts of data. This allows the development of applications in deep learning and artificial intelligence (AI) through GPU utilisation in the cloud. The aim is to develop EO-based prototypes and operational services.
In an increasingly digitalised world, the use of cloud computing is increasingly becoming a fundamental competence for companies and individuals. The ‘CloudComputing4EO’ project aims to promote this competence. Another aim of this project is to develop high-quality and easily accessible learning resources that enable people to expand their knowledge and skills in the field of cloud computing. At the same time, the teaching materials created can be used in university teaching and capacity building.