With the continuous development of remote sensing technology and the widespread application of high-resolution remote sensing images, digital landscape design based on high-resolution remote sensing image interpretation is gradually becoming a new design concept and method. This study is based on high-resolution remote sensing images to classify gardens, and combined with ground survey data, statistical analysis software is used to invert the landscape elements of gardens. The experimental results showed that the R2 value was relatively large, while the MRE and RMSE values were small, indicating that the analysis results were close to the true values and the fitting effect was relatively ideal. The overall image segmentation was excellent, with an average diameter at breast height of 8.0-17.0cm, mixing degree of 0.4-0.6, vertical diversity of 0.5-0.8, and a clear forest hierarchy when the average density was between 800-1100 plants/hm2. This indicates that the quality of landscape architecture designed at this landscape scale changes significantly and the effect is good. Digital landscape design based on high-resolution remote sensing image interpretation can not only improve design efficiency and accuracy, but also provide strong support for the sustainable development of urban planning and landscape design.