Research on View Analysis and Spatial Optimisation of Landscape Design under XGBoost Model

In the process of urbanization, the landscape design of urban public space helps to improve the living quality and happiness of citizens. This paper takes the geographic data of Province G as the research object and preprocesses its landscape data. The agglomeration evolution characteristics of the regional landscape are studied by using the average nearest neighbor index, and the distribution pattern characteristics of the regional landscape are analyzed by the landscape pattern index, and the pattern characteristics of the regional landscape are also analyzed from the landscape level and the type level, respectively. The XGBoost algorithm was used to model the urban landscape design features, and the specific features affecting the urban landscape design were analyzed by combining with the SHAP model decoding method. It was found that the ANN index value of regional landscapes decreased by 16.05% between 2000 and 2022, and the AI index of urban landscapes decreased from 63.512 to 62.424.When the level of urbanization development was around 20%, the LPI index of woodland types was in the range of [0.5,1.5]. When the CONTAG index is between [0.2,0.8], the SHAP value of the urban landscape pattern index stabilizes between -0.2 and 0.2, and there is a significant decrease in the SHAP value after exceeding 0.8. Urban landscape design needs to be based on the level of urbanization development to meet the landscape needs of citizens through diverse landscape space combinations.