Urban nature-based solutions planning for biodiversity outcomes: human, ecological, and artificial intelligence perspectives

Abstract

Nature-based solutions (NBS) harness ecosystem services for urban enhancement, promoting biodiversity, habitat creation, and water management while improving human well-being. However, decision-making often favours specific NBS designs, leading to uneven benefits distribution. Whereas human-centric NBS design relies on convenience, financial sustainability, historical aspects, and amenity increase through NBS technical solutions, flora- and fauna-centric (or eco-centric) design targets spatial connectedness of blue-green spaces, increase in species richness, and habitat within urban centres. Both approaches can shape the urban biodiversity landscape, yet; they often clash around planning priorities. Recent advances in AI offer potential for AI-centric urban planning, though its role remains unclear. This study examines the interplay between biodiversity and NBS planning across human-, eco-, and AI-centric domains, aiming for balanced urban outcomes. We blended narrative, integrative, and systematic literature review and propose future steps for more balanced NBS development. The findings of this work suggest that AI presents an opportunity for a more balanced NBS design through its applications in climate change prediction, water management, and project visualisation. Incorporating AI into urban planning tools can expedite modelling process, improve stakeholder communication, and enhance project outcomes visualisation. By integrating human, eco, and AI-centric approaches, urban planners can foster resilience and sustainability in NBS implementation, ensuring equitable distribution of benefits across urban landscapes.