<p>Traditional landscape maintenance methods lack the support of intelligent monitoring and control technologies, making it difficult to dynamically perceive plant growth conditions, facility operations, and environmental changes. As a result, issues such as disorganized pedestrian flow, vegetation degradation, and weakened landscape functionality often arise, leading to suboptimal outcomes in both design and maintenance effectiveness. Therefore, this study builds a landscape intelligent management system based on Internet of Things (IoT) technology and Geographic Information System (GIS) technology, aiming to intelligently monitor landscape design and maintenance, while reducing maintenance difficulty and costs. According to experiments, the highest values of patch area, patch type percentage, patch number, patch density and other indicators in the study area are all regional green spaces, while the highest edge feature index of landscape patches is protective green spaces, which is 1.41. After optimizing the regional landscape design, the vegetation coverage rate of the area increased from 24.5 to 26.8%, with an increase of 2.3%. The proposed method achieved a prediction accuracy of 99.5% in modeling the spatial conversion rates among different vegetation cover types (e.g., grassland, shrubland, and woodland) within the study area. In summary, the intelligent landscape management system can effectively design landscape patterns and provide intelligent monitoring methods for landscape maintenance. The deficiency of the research is that the human factors affecting the landscape environment are not considered enough, and further research on this part can be strengthened.</p>