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JCSIS

Quantum Algorithms in Geo-Information Systems for Sustainable Climate Change Mitigation Solutions

Nizar M. SoufianHakan KhanLima Hongou
Volume 4

Abstract

The integration of quantum algorithms into geo-information systems (GIS) is emerging as a transformative approach to address the complexities of climate change mitigation. Quantum computing offers enhanced computational capabilities that can significantly improve the accuracy and efficiency of climate models by solving complex differential equations and optimizing largescale environmental data processing. For instance, quantum-enhanced machine learning models have demonstrated superior performance in predicting climate-related outcomes, enabling more precise simulations of atmospheric and oceanic processes. Additionally, quantum algorithms facilitate the optimization of renewable energy systems and carbon capture technologies by efficiently analyzing vast datasets to identify optimal configurations and strategies. The application of quantum computing in GIS also supports the development of high-resolution climate models, which are crucial for understanding localized climate impacts and informing targeted mitigation efforts. These advancements underscore the potential of quantum algorithms to revolutionize climate science by providing more accurate predictions and effective solutions for sustainable development.

Keywords

Quantum Computing, Geo-Information Systems, Climate Change Mitigation, Quantum Algorithms, Climate Modeling, Sustainable Development

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