Scalable Data Processing Platform for Earth Observation Data Repositories

Main Article Content

Hrachya Astsatryan
Arthur Lalayan
Gregory Giuliani


Earth observation (EO) satellite data is essential to environmental monitoring. At a national and regional level, the open data cubes harness the power of satellite data by providing application programming interfaces and services to the end-users. The volume and the complexity of satellite observations are increasing, demanding novel approaches for data storing, managing, and processing. High-performance computing (HPC) and cloud platforms may improve Big EO data processing performance. However, it is necessary to consider several vital aspects for efficient and flexible EO data processing, such as the interoperability from cloud-HPC and EO data repositories, automatic provisioning and scaling of cloud-HPC resources, cost-effectiveness, support of new EO data formats and open-source packages, or linkage with data cube platforms. The article proposes a scalable EO data processing platform interoperable from cloud-HPC and EO data repositories. The platform enables linking any data repository supporting web coverage service or SpatioTemporal Asset Catalog Application Programming Interfaces (STAC-API), and any cloud or HPC resource supporting scheduling system API for providing access to the cluster backends.

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Author Biographies

Hrachya Astsatryan, Institute for Informatics and Automation Problems National Academy of Sciences of Armenia 1, Yerevan, Armenia

Dr. Astsatryan received his Ph.D. degree in Computer Science with an emphasis on optimal organization of distributed systems from the Institute for Informatics and Automation Problems (IIAP) and the M.S. degree in applied mathematics from Yerevan State University, Armenia.  In 2020, Dr. Astsatryan defended HDR (Habilitation a Diriger les Recherches) entitled "Service Tradeoff for HPC and Big Data Infrastructures" from the Institut National Polytechnique de Toulouse, France. His research interests lie in the broad areas of high-performance and scientific computing, high-performance data analytics, and large-scale energy aware distributed systems. Dr. Astsatryan published more than 80 articles in journals, conferences or workshops. His research has been sponsored by EC Framework Programmes, ISTC, INTAS, SNCF, and CRDF.

Arthur Lalayan, Institute for Informatics and Automation Problems National Academy of Sciences of Armenia 1, Yerevan, Armenia

Arthur Lalayan is currently Ph.D. student in computer science at the National Polytechnic University of Armenia (NPUA). He received his Bachelor’s degree and Master’s in informatics and computer science degree from NPUA in 2019 and 2021, respectively. His research interests include large scale data analytics and optimization.

Gregory Giuliani, Institute for Environmental Sciences, University of Geneva, Geneva, Chatelaine, Switzerland

Dr. Gregory GIULIANI is the Head of the Digital Earth Unit and Swiss Data Cube Project Leader at GRID-Geneva of the United Nations Environment Programme and a Senior Lecturer at the University of Geneva’s Institute for Environmental Sciences. He is a geologist and environmental scientist who specializes in Remote Sensing, Geographical Information Systems and Spatial Data Infrastructures. He also works at GRID-Geneva of the United Nations Environment Programme since 2001, where he was previously the focal point for Spatial Data Infrastructure and is currently the Head of the Digital Earth Unit. Dr. Giuliani's research focuses on Land Change Science and how Earth observations can be used to monitor and assess environmental changes and support sustainable development.