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This research aims to design micro-scale nature-based solutions for revitalizing abandoned land by utilizing AI-based predictive models.

May 28, 2026Open Access

Designing micro-scale Nature-Based Solutions using AI-based predictive models

Key Points

This research aims to design micro-scale nature-based solutions for revitalizing abandoned land by utilizing AI-based predictive models.
Developed a blue-green belt and green infrastructure network for abandoned land in Bucharest.
Integrated proposals into the Master Plan for urban revitalization.
Used AI and geospatial tools for efficient resource management and sustainability evaluations.
Successfully designed micro-scale nature-based solutions that enhance ecological restoration and social-economic benefits in Bucharest.
Establishing a robust plan for expanding green infrastructure networks contributed to urban revitalization.

Abstract

Nature-based solutions (NBS) are methods supported by natural processes addressing environmental, social and economic challenges, and offering multiple ecosystem services. Despite their importance, the literature lacks studies showing how to design NBS at different spatial scales. Our study fills in the gap, designing micro-scale NBS for revitalizing abandoned land in Bucharest. The methodology included creating a blue-green belt and potential green infrastructure network, integrated in the proposed Master Plan, and plans for expanding the network. AI and geospatial tools proved essential to ensure the efficiency and sustainability of proposals, opening avenues for developing efficient resource management methods and regeneration scenarios.

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