Research, ToolsComputation, Landscape

Reinventing Planting Design

A Generative AI Approach

TYPE: Research
YEAR: 2023
Collaborators: Nandi Yang (SWA)
Funding: Supported by Patrick T. Curran Fellowship
In the field of landscape architecture, the integration of ecological principles with aesthetic design is a critical yet complex task. This research introduces an innovative AI-driven tool designed to revolutionize planting design by embedding ecological intelligence into the design process. This paper presents the methodology, including data synthesis, AI model training with generative adversarial networks (GANs), and integration into a practical design interface. The model is trained on multifaceted input data such as topography, soil, and climate data. The results indicate the AI model's effectiveness in generating planting layouts that balance ecological accuracy with aesthetic appeal. Significantly, this research extends the professional practice of landscape architecture.

Full article can be found:

Methodology Framework

Rhino/Grasshopper Interface. We prototyped our Interface called ECO GEN using HumanUI in Grasshopper

Form finding, generative design integration

Iterative Design Process and Final Plating Layout Design Visualization