Digital twin technology, originating from the aviation industry, has exhibited promising performance in intelligent manufacturing, healthcare, and smart city development. This technology aims to establish digital twin models encompassing physical entity characteristics, maintenance, and operational data. High-quality digital twin models of parks can function as the intermediary connecting park entities and data information, thus bearing substantial implications for the intelligent management of parks. The digital twinning work in the park faces significant challenges due to the diverse environmental elements, complex management requirements, and high difficulty in 3D modeling, data storage, and rendering performance. Consequently, there has been a persistent systematic problem of ineffective and imprecise matching between information data, 3D models, and park entities. This paper presents a novel approach to the digital twinning process of parks by dividing it into four stages: demand analysis, technology selection, model building, and data binding. ,Moreover, it further extracts key influencing factors that are closely related to the actual needs of intelligent park management at each stage. The fundamental requirements of critical elements are addressed by implementing technical measures such as information weight grading screening, integration of various modelling technologies, compression of model grid topology, model parameter-driven updates, and formulation of data binding standards. This enables the establishment of an informative and precise technological framework for constructing digital twin models in park areas. Ultimately it aids in the advancement of intelligent management in parks.