基于机器学习的空间模式分析与景观设计优化研究
Research on Spatial Pattern Analysis and Landscape Design Optimization Based on Machine Learning

随着城市化进程的推进，景观设计面临着更为复杂的挑战，特别是在空间布局优化、功能区划和用户体验方面。机器学习技术作为一种强大的数据分析工具，在景观设计领域有着极大的应用潜力。本研究探讨了机器学习在空间模式分析中的应用，旨在为景观设计提供优化决策支持。研究发现，通过分析大量空间数据，机器学习能够发现潜在的空间分布规律、用户行为模式及其相互影响关系，从而帮助设计师在空间布局、功能区划和环境适应性方面进行优化。尽管如此，机器学习在景观设计中的应用也面临数据采集、模型复杂性和可解释性等挑战，不过未来随着技术的进步，其应用前景将更加广阔。
With the advancement of urbanization, landscape design faces more complex challenges, especially in terms of spatial layout optimization, functional zoning and user experience. As a powerful data analysis tool, machine learning technology has great application potential in the field of landscape design. This study explores the application of machine learning in spatial pattern analysis, aiming to provide optimization decision support for landscape design. The study found that by analyzing a large amount of spatial data, machine learning can discover potential spatial distribution patterns, user behavior patterns and their mutual influence, thereby helping designers to optimize spatial layout, functional zoning and environmental adaptability. Despite this, the application of machine learning in landscape design also faces challenges such as data collection, model complexity and interpretability. However, with the advancement of technology in the future, its application prospects will be broader.