Optimization Simulation of Landscape Spatial Pattern Gradient Based on Second Class Survey Data Analysis

Traditional landscape spatial pattern research often lacks comprehensive dynamic analysis capabilities and optimization design support, which limits its effectiveness in practical applications. To solve this problem, this article uses second-class survey data, combined with key factors such as landscape type, shape, and edge ratio, and uses computer technology to simulate and optimize the landscape spatial pattern. This method not only enhances the dynamic analysis capability of landscape space, but also provides effective optimization solutions for different types of landscapes. By conducting in-depth analysis of the second-class survey data in the research area, we can gain a more accurate understanding of the current status and evolutionary trends of landscape space. The research results show that after applying this method, the diversity index of landscape spatial pattern can reach 9.5, indicating that the optimized landscape has higher diversity and ecological value. This optimization method based on secondclass survey data analysis can effectively improve the overall quality and user experience of landscape space. And it provides scientific basis and innovative strategies for future landscape planning and design.