Land Development + AI

Urbanization has led to the destruction of many green areas in cities, creating a challenge for policymakers to balance development with preserving green infrastructure. This study proposes integrating a low-carbon design approach and artificial intelligence (AI) into smart urban development. The study uses carbon sequestration in trees as a measurable factor to optimize land partitioning. The model uses genetic algorithms and input variables such as size, access, facilities, and carbon to generate greener solutions. Results show that the AI-based low-carbon design approach successfully expedites the parcelization process while preserving green infrastructure. This study highlights the importance of incorporating AI and carbon sequestration in urban planning.