Communications - Scientific letters of the University of Zilina X:X | DOI: 10.26552/com.C.2026.013

Cloud-Based Modular System for Acquisition and Visualization of OCO-2 Remotely Sensed CO2 Data

Maroš Valášek ORCID...1, *, Roman Budjač ORCID...2, Martin Hanzely ORCID...3, Neven Vrček ORCID...3
1 Department of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Zilina, Zilina, Slovakia
2 Research Centre, University of Zilina, Zilina, Slovakia
3 Travelco s.r.o., Oscadnica, Slovakia
4 Department of Information Systems Development, University Zagreb, Varazdin, Croatia

In this paper is presented a cloud-based framework for automated acquisition and visualization of Orbiting Carbon Observatory-2 (OCO-2) satellite CO₂ data. The system employs an ETL pipeline with OPeNDAP protocol for selective data retrieval, reducing network overhead while processing L2 Standard and L2 Lite FP products. Built on Amazon Web Services (AWS) infrastructure, using Python (Pandas, Dash, Plotly) and Docker orchestration, the modular architecture implements dependency injection for runtime flexibility. The deployed system achieves daily automated ingestion with 2.25 km × 1.29 km spatial resolution, enabling the real-time monitoring through interactive web visualization. The system is designed as a foundation for future analytical research, providing ready integration points for machine learning models to perform advanced CO₂ pattern recognition and predictive analysis.

Keywords: CO₂, data acquisition, remote sensing, machine learning
Grants and funding:

This work was supported by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under Project 09I03-03-V04-00562.

Conflicts of interest:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: November 14, 2025; Accepted: December 5, 2025; Prepublished online: January 16, 2026 

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