A generative AI decision-making tool for interactive greenspace design using a pollinator habitat indicator

Generative artificial intelligence (AI) is increasingly used in landscape architecture to accelerate design development and enhance stakeholder engagement. This study presents a new landscape concept design tool to support collaborative greenspace problem-solving by integrating rapid scenario generation with a Pollinator Habitat Indicator (PHI). We define this as the PHI-AI Landscape Design Tool. The model combines text-to-image generative workflows with a simplified pollinator-oriented reference that compares AI-generated scenarios based on broad landscape cover composition. The PHI-AI Landscape Design Tool generated varied concept layouts with planting and pathway configurations responsive to descriptive prompts and user-defined parameters. It generates layout variations that reflect visually coherent planting configurations, and circulation connections to existing infrastructure for user functionality. This enables the rapid production of multiple design alternatives that remain legible, adaptable, and flexible to human-controlled editing prompts for stakeholder engagement. This study offers a framework for integrating a simplified ecological reference into the planning phase of landscape design.