Work

Cloud-Based Modular System for Acquisition and Visualization of OCO-2 Remotely Sensed Co2 Data

Year: 2026

Type: article

Abstract: 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.

Source: Communications - Scientific letters of the University of Zilina

DOI: 10.26552/com.c.2026.013

Authors: Maroš Valášek, Roman Budjač, Martin Hanzely, Neven Vrček

Institutions: University of Žilina, University of Zagreb

Language: English

Topic: Atmospheric and Environmental Gas Dynamics

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W7124427340