基于开放数据模式的植物信息模型应用与扩展

Applications and Extensions of Plant Information Models using Open Data Schema

摘要

【目的】建筑信息模型（Building Information Modeling, BIM）技术发展的核心是信息的互通共享，但现有BIM数据模式主要面向建筑工程，难以表征中国风景园林建设中植物要素的专业特征与工程需求。本研究将以风景园林核心要素——植物为研究对象，针对当前风景园林信息模型中植物信息组织缺失、语义表达不统一的问题，提出植物信息模型数据模式构建与标准化表达方法。【方法】通过调研分析对植物单体进行数字化定义，建立由2个大类、7个子类以及核心属性字段所构成的植物信息模型标准化数据清单，并在Revit软件中进行标准数据集内置应用；在此基础上制定植物属性数据映射规则，依托数据整理、扩展配置与文件导出，实现植物参数向数据模式结构化转换。【结果】在前湾公园景观工程的应用中，该方法实现了原生模型到工业基础类（Industry Foundation Classes, IFC）的植物属性扩展与导出，标准化植物数据清单可直接驱动建模与自动校核，生成的植物参数满足物种清单、养护要点和碳汇测算等基础数据需求。【结论】研究成果有助于提升植物信息模型的数字化表达，增强园林生态资产的标准化属性，为各阶段园林工程生态数字化管理提供技术支撑。

Abstract

[Objective] The core objective of Building Information Modeling (BIM) development is interoperable information sharing. However, existing BIM data schemas are mainly oriented toward building assets and are not sufficiently adapted to the professional characteristics and engineering requirements of landscape architecture, especially in the representation of plant elements in China’s landscape engineering. To remedy the absence of a domain-ready data schema in the landscape field, this study takes plants-the core ecological elements of landscape systems-as its object, and develops an application framework from two tightly coupled dimensions: 1) the construction and platform internalization of a standardized plant dataset, and 2) the practical use of the Industry Foundation Classes (IFC) to achieve cross-platform, semantics-preserving exchange of plant objects in landscape engineering. Beyond addressing a modeling gap, the objective is to articulate clear, computable semantics for living vegetation that capture species identity, spatial morphology, ecological habit, and lifecycle management needs in ways existing building-focused schemas do not. The study aims to clarify the scope and granularity of plant information required for design coordination and long-term stewardship, reduce ambiguity in terminology and units across stakeholders, and establish a consistent basis for ecological asset representation within broader urban digital ecosystems toward digital twins and city information models. [Methods] Plant instances were first digitally defined through literature review, project investigation, and analysis of landscape engineering workflows. A standardized plant data checklist was established, consisting of 2 categories, 7 subcategories, and 25 core attribute fields. These fields cover identification, geometric dimensions, ecological habits, ecological functions, procurement information, construction information, and operation and maintenance information. The dataset was embedded into the Revit software platform so that field identifiers, value types and units, and value-domain constraints could be enforced at the point of modeling, enabling direct authoring and downstream validation. On this basis, a user-defined attribute mapping method was adopted to carry plant semantics in IFC without altering existing entity boundaries. The procedure comprised four steps: attribute curation, mapping-rule authoring, configuration-based export, and post-export verification. In practice, Revit parameters were aligned one-to-one with IFC properties and quantities via an external configuration file that records, for each field, the target IFC property name and value type (with units) together with its source parameter. This design ensures structural conversion of plant parameters into IFC while maintaining semantic fidelity across tools. Consistency checks were conducted before and after export to verify presence, type, unit correctness, value-domain validity, and equivalence between authoring and exchange layers. [Results] The proposed method was applied to the Qianwan Park Phase I landscape project in Minhang District, Shanghai, with a project area of approximately 100,000 m ². The application enabled the extension and export of plant attributes from the native Revit model to IFC, while retaining the selected plant semantic information. With the standardized dataset internalized, the platform directly drove modeling and subsequent checking, and the exported IFC files provided structured storage of the 25 key plant attributes for representative plant species. In the viewer-based inspection workflow, attribute panels for representative species displayed identification information such as Chinese name, botanical name, family, and genus; geometric information such as height, crown spread, diameter at breast height (DBH), rootball depth, and rootball diameter; ecological information such as climate adaptability, soil requirements, and light requirements; and management information such as procurement items, planting date, and maintenance notes. Cross-species spot checks found no missing items, misplacements, or unit inconsistencies, as evidenced by semantic equivalence among the family parameter panels, the IFC property sets, and the viewer displays. Beyond technical fidelity, the normalized fields enabled immediate downstream use: species lists could be compiled programmatically; maintenance guidance could be filtered and scheduled from O&M attributes; and carbon-related estimates could use the geometric and ecological parameters as inputs with minimal manual preprocessing. The end-to-end validation artifacts further supported auditability and reproducible deliveries across design−construction−operations handoffs. [Conclusion] The findings enhance the digital expression of plant objects and strengthen the standardized, computable attributes of landscape ecological assets, thereby providing technical support for ecological, data-driven management of landscape projects. Concretely, the study demonstrates that a dictionary-led standardized dataset (2 classes, 7 subcategories, 25 fields) can be internalized in mainstream BIM authoring to unify semantics at source; and that a configuration-based IFC application method-maintaining current schema entities while conveying rich semantics through property/quantity groupings-can deliver cross-platform, traceable and verifiable plant information without modifying the IFC entity landscape. In a real-world park project with 35 tree species, the approach produced structured datasets that remained semantically equivalent across authoring, exchange, and viewing environments, and proved directly useful for species registers, construction communication, O&M planning, and carbon-awareness workflows. Strategically, this positions plants as first-class ecological assets within Landscape Information Modeling (LIM), enabling lossless information exchange across the lifecycle and facilitating integration with digital twins and city information modeling ecosystems. Future work will extend the dictionary and mapping pattern to additional landscape elements-terrain, pavements, water bodies, small structures, and site furnishings-under a unified, compatible data architecture; establish case repositories and sharing platforms to consolidate best practices; and explore generative algorithms to reduce manual authoring while better representing plant growth dynamics and seasonal change.

关键词

风景园林信息模型 / 植物信息模型 / 工业基础类 / 数据字典 / 属性集扩展

Key words

Landscape Information Modeling / Plant Information Modeling / Industry Foundation Classes / data dictionary / property set extension

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基金资助

上海建工集团股份有限公司课题“碳汇背景下的城市绿地生态数字资产构建关键技术研究”(24JCSF-25)

国家自然科学基金青年科学基金项目“基于BIM底层数据模式和语义网的建筑智能评估方法研究：以绿色机场为例”(52308031)

中央高校基本科研业务费专项资金(22120250202)