Big data has brought about opportunities for landscape architecture, changing the design thinking of layout optimization simulation, expanding the platform for public participation in layout optimization simulation design, reflecting social and humanistic care, and promoting the integration of discipline cooperation and data. At the same time, it also brings about challenges. The proposal of data theory, the acquisition and analysis of data, and the protection of privacy are all issues that we need to face and solve. First, build a layout optimization simulation program under the background of big data. Follow the procedures of conventional layout optimization simulation, add big data analysis technology to the preliminary analysis, layout optimization simulation design, and later evaluation management, introduce new data processing methods, and build a theoretical framework of landscape optimization simulation methods that integrate new and traditional data. Second, studying the evolution of the landscape image layout of the three-dimensional pastoral complex is different: the overall landscape image layout of the three-dimensional pastoral complex shows a trend of fragmentation and heterogeneity. Among them, the arable land is gradually fragmented, the wetland and water area are simplified in form, the woodland and grassland patches are gradually distributed, the fragmentation is reduced by 76.19%, and the connectivity index is gradually increased. From a spatial perspective, the edge area outside the Fourth Ring Road becomes the most obvious area of fragmentation tendency. Finally, by introducing big data into the landscape layout optimization simulation, a layout optimization simulation method based on big data is constructed and used in the layout optimization simulation of the landscape image layout of the three-dimensional pastoral complex to guide the participatory layout optimization simulation.

中文翻译：

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大数据分析下的3D牧区景观图像布局优化提取仿真

大数据为景观设计带来了机遇，改变了布局优化模拟的设计思路，扩大了公众参与布局优化模拟设计的平台，体现了社会和人文关怀，并促进了学科合作与数据的整合。同时，它也带来了挑战。数据理论的提出，数据的获取和分析以及隐私保护都是我们需要面对和解决的问题。首先，在大数据背景下构建布局优化仿真程序。遵循常规布局优化仿真的步骤，在初步分析，布局优化仿真设计和后期评估管理中添加大数据分析技术，介绍新的数据处理方法，并建立整合新旧数据的景观优化模拟方法的理论框架。其次，研究三维牧区景观图像布局的演变是不同的：三维牧区景观图像的整体布局呈现碎片化和异质化的趋势。其中，耕地逐渐破碎化，湿地和水域形式简化，林地和草地斑块逐渐分布，破碎化减少76.19％，连通指数逐渐提高。从空间角度看，四环路以外的边缘区域成为最明显的破碎趋势区域。最后，通过将大数据引入景观布局优化模拟中，