Earth observation (EO) has become an operational source of big data. Fostered by the European Copernicus programme with its high-performance satellite fleet and open access policy, the user community has increased and widened considerably during the last years. For example, a recent study by PWC shows that the return of investment into Copernicus is about four euros to one, primarily from its downstream applications (ESA/PWC, 2019). This raises high expectations for valuable thematic products and intelligent knowledge retrieval. In the private sector, NewSpace companies launch(ed) hundreds of small satellites which have become a complementary source of EO data. In the last years IT giants like Google and Amazon entered the scene and brought their expertise of artificial intelligence (AI) to EO data – but often lacked profound EO domain knowledge. The general research goal of the host institutions is to exploit this new and exciting revolution in data-intensive – or even data-driven – science for EO by developing and tailoring novel data science and AI concepts for geo-relevant use cases and combining them with existing rich physical model-based EO expertise. In this context, the specific challenges of EO data must be taken into account, such as heterogeneous data sources, extreme scales, data complexity, shortage of training data and high quality requirements. Also the European Space Agency (ESA) responded to the current disruptive development in EO by founding the Φ-Lab, which intends to accelerate the adoption of AI techniques by EO and space researchers. This vibrant field of AI for EO (AI4EO) will be the home of the proposed innovation lab.
Germany is very well positioned in this blooming field of AI4EO. The number of publications on deep learning (a very recent approach adopted in AI) in EO by German institutions in the past five years ranks number three after China and the US. Among all institutions, the host institutes Technical University of Munich (TUM) and German Aerospace Center (DLR) rank the first among all non-Chinese institutions. Despite these successes, most of the efforts in the international community remain at the exploitation phase through purely application-oriented research. Fundamental science questions remain open. The proposed Future Lab AI4EO (hereinafter referred to as “The Lab”) will bring 20 renowned international organizations in 9 countries and 27 highly-ranked scientists together to research three fundamental, yet rarely addressed, challenges faced by EO-specific cutting-edge AI research, namely, Reasoning, Uncertainties, and Ethics. In addition, other innovative AI4EO topics will be addressed by our Beyond Fellow program, based on which ca. 70 highly talented PhD and PostDoc researchers will invited to visit our lab.
The research carried out in the Lab will not only advance cutting-edge EO science but also lay the foundations, in particular by addressing theoretical analysis, quantification of uncertainties, and ethics of AI, towards equitable AI4EO technology transfer. It will consolidate the pole position of Germany in AI4EO and establish Germany as the AI gravity center in the field of EO.