The Role and Effect of Deep Learning in Landscape Design Innovation

The application of Deep Learning (DL) in the field of landscape design has attracted increasing attention and become a key tool to promote innovation and enhance the effect. Through a case study, this paper discusses the role of DL in landscape design innovation and its effects. As a data-driven design engine, DL provides scientific support for planning, vegetation design, and spatial layout through intelligent analysis of a large number of geographical, ecological, and human data. Its innovation is reflected in the ability to automatically generate design schemes, simulate people flow, and improve design efficiency. DL provides a powerful visualization tool for designers, and through high-quality image generation, it improves the expression of design concepts and the communication effect with stakeholders. The effect demonstrated in the case study shows that DL has significant potential in improving the quality, creativity, and sustainability of landscape design. However, the challenges include data privacy, technical feasibility, and social acceptance, which need to be further solved in future research. Looking forward to the future, DL will become a more indispensable tool in landscape design, promoting interdisciplinary cooperation and the development of landscape design in a more intelligent, innovative, and sustainable direction.