Artificial Intelligence in Landscape Architecture: A Survey
Yue Xing, Wensheng Gan, Qidi Chen
TL;DR
This survey addresses how AI can transform landscape architecture by enabling data-driven design, planning, and management. It maps core AI technologies—such as ML, DL, CV, NLP, RL, and digital twin concepts—to LA tasks, and surveys concrete case studies including urban renewal in Dengfeng, rural digital twins, and heritage digitization efforts. It highlights AI-enabled design generation, ecosystem simulation, and maintenance optimization, while also detailing challenges around data quality, privacy, and the need for human-in-the-loop decision making. The findings argue that AI holds strong potential to improve sustainability, efficiency, and public participation in LA, but realizing this potential requires interdisciplinary collaboration, governance frameworks, and talent development.
Abstract
The development history of landscape architecture (LA) reflects the human pursuit of environmental beautification and ecological balance. With the advancement of artificial intelligence (AI) technologies that simulate and extend human intelligence, immense opportunities have been provided for LA, offering scientific and technological support throughout the entire workflow. In this article, we comprehensively review the applications of AI technology in the field of LA. First, we introduce the many potential benefits that AI brings to the design, planning, and management aspects of LA. Secondly, we discuss how AI can assist the LA field in solving its current development problems, including urbanization, environmental degradation and ecological decline, irrational planning, insufficient management and maintenance, and lack of public participation. Furthermore, we summarize the key technologies and practical cases of applying AI in the LA domain, from design assistance to intelligent management, all of which provide innovative solutions for the planning, design, and maintenance of LA. Finally, we look ahead to the problems and opportunities in LA, emphasizing the need to combine human expertise and judgment for rational decision-making. This article provides both theoretical and practical guidance for LA designers, researchers, and technology developers. The successful integration of AI technology into LA holds great promise for enhancing the field's capabilities and achieving more sustainable, efficient, and user-friendly outcomes.