Computational Intelligence for Urban Carbon Neutrality: From Sensing to Decision-Making

Dear Colleagues,

Urban carbon neutrality is a core goal of global sustainable development, relying on accurate carbon sink monitoring, real-time data acquisition and intelligent decision-making. Technologies such as remote sensing, the Internet of Things and the Internet provide multi-source, high-resolution data support for urban carbon cycle research, while artificial intelligence algorithms realize efficient processing and deep mining of these complex data. A comprehensive integration of these technologies is critical to quantifying urban carbon sinks, optimizing low-carbon management strategies, and promoting the transition to green urban development. However, this task faces challenges such as heterogeneous data fusion, multi-scale process coupling, and dynamic decision-making under complex urban scenarios.

This Special Issue is dedicated to showcasing recent advances in computational intelligence applications for urban carbon neutrality, spanning from carbon sink sensing to low-carbon decision-making. Submissions may present original research, methodological innovations, state-of-the-art reviews, or future outlook perspectives.

Specific methods and application fields include, but are not limited to, the following:

• Remote sensing inversion and monitoring of urban carbon sinks.
• IoT-based urban carbon emission and sink data acquisition.
• AI-driven multi-source data fusion and carbon cycle modeling.
• Internet-supported collaborative decision-making for urban low-carbon governance.
• Intelligent optimization of urban green infrastructure and carbon sequestration schemes.

Dr. Yang Yi
Prof. Dr. Mingchang Shi
Guest Editors

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