A global map to aid the identification and screening of critical habitat for marine industries

Marine industries face a number of risks that necessitate careful analysis prior to making decisions on the siting of operations and facilities. An important emerging regulatory framework on environmental sustainability for business operations is the International Finance Corporation’s Performance Standard 6 (IFC PS6). Within PS6, identification of biodiversity significance is articulated through the concept of “Critical Habitat”, a definition developed by the IFC and detailed through criteria aligned with those that support internationally accepted biodiversity designations. No publicly available tools have been developed in either the marine or terrestrial realm to assess the likelihood of sites or operations being located within PS6-defined Critical Habitat. This paper presents a starting point towards filling this gap in the form of a preliminary global map that classifies more than 13 million km² of marine and coastal areas of importance for biodiversity (protected areas, Key Biodiversity Areas [KBA], sea turtle nesting sites, cold- and warm-water corals, seamounts, seagrass beds, mangroves, saltmarshes, hydrothermal vents and cold seeps) based on their overlap with Critical Habitat criteria, as defined by IFC. In total, 5798×10³ km² (1.6%) of the analysis area (global ocean plus coastal land strip) were classed as Likely Critical Habitat, and 7526×10³ km² (2.1%) as Potential Critical Habitat; the remainder (96.3%) were Unclassified. The latter was primarily due to the paucity of biodiversity data in marine areas beyond national jurisdiction and/or in deep waters, and the comparatively fewer protected areas and KBAs in these regions. Globally, protected areas constituted 65.9% of the combined Likely and Potential Critical Habitat extent, and KBAs 29.3%, not accounting for the overlap between these two features. Relative Critical Habitat extent in Exclusive Economic Zones varied dramatically between countries. This work is likely to be of particular use for industries operating in the marine and coastal realms as an early screening aid prior to in situ Critical Habitat assessment; to financial institutions making investment decisions; and to those wishing to implement good practice policies relevant to biodiversity management. Supplementary material (available online) includes other global datasets considered, documentation and justification of biodiversity feature classification, detail of IFC PS6 criteria/scenarios, and coverage calculations.     

面向3DGIS场景的BIM模型转换与集成研究

通过深入分析BIM模型在3DGIS场景中集成的现状、问题和难点,针对图元信息转换优化、属性信息的提取整合、模型轻量化、共享调度、全生命周期的集成管理等内容,结合IFC、CityGML等标准,提出了一种BIM模型向3DGIS场景转换与集成的框架。以长江水利委员会大院管理信息系统为例,论述了在形成初步三维地形场景和建筑外观模型后,在该框架下将BIM建筑模型转换并集成到3DGIS场景中的过程,验证了该方法的实用性和可操作性。     

Extending a BIM-based data model to support 3D digital management of complex ownership spaces

Currently, 2D-based analogue building subdivision plans are used to represent the spatial extent of private, public and communal property ownership rights. These plans are recognized as posing a range of challenges in terms of communicating the spatial complexity of ownership spaces within multi-storey buildings. In response to these challenges, three-dimensional (3D) digital data environments are being investigated as a potential approach for managing complex, vertically stratified ownership arrangements. The argument presented in this article is that Building Information Modelling (BIM) can be adopted for 3D digital management of data related to complex ownership spaces. BIM provides a common and 3D digital data sharing space, underpinning a reliable basis for facilitating collaboration and decision-making over the lifecycle of buildings. However, ownership attributes and the spatial structure of ownership arrangements inside buildings are yet to be accommodated within the BIM data environment. In this article, we present a range of required data elements for managing complex ownership spaces, which have been elicited by investigating current practices pertaining to subdivision of ownership spaces within multi-storey buildings in Melbourne, Australia. An open data model in the BIM domain is extended with these data elements and a prototype model for a real multi-storey building is implemented to demonstrate the viability of the extended data model for 3D digital management and visualization of data related to complex ownership arrangements.     

房地一体化不动产三维数据模型研究

房地不动产具备天然的立体特性,在三维空间中对其进行准确刻画是当前城市地上地下综合开发的关键问题,国内外学者已经提出了各类房地不动产数据模型,旨在解决房地不动产的管理与权利空间的三维表达问题。分析国内外学者的研究成果发现,国外学者提出的房地不动产数据模型多以地籍为核心展开,不能完全适用于我国的房地不动产管理;而国内学者虽兼顾了地籍和房产,但忽略了建筑实体、建筑空间与产权空间的关系,无法将房地不动产信息与建筑物信息模型（Building Information Modeling,BIM）整合,不利于房地不动产的精细化管理。针对以上问题,本文提出了基于IFC（Industry Foundation Classes）标准扩展的房地一体化三维不动产数据模型,并通过实例验证了该模型在我国房地不动产管理上是可行的。研究结果表明,本文提出的模型正确表达了各类建筑对象和产权对象,既可以支持业务相关的关联关系的查询,也支持GIS常见拓扑关系的查询和表达,该模型除了能表达符合我国体制的房地不动产对象外,还关联了BIM模型中的建筑构件、建筑空间, 为城市建设与运维管理提供技术模型支持。     

An evaluation of ontology matching techniques on geospatial ontologies

Standardization is one of the pillars of interoperability. In this context, efforts promoted by the Open Geospatial Consortium, such as CityGML (Technical University, Berlin), a standard for exchanging three-dimensional models or urban city objects, are welcomed. However, information from other domains of interest (e.g. energy efficiency or building information modeling) is needed for tasks such as land planning, large-scale flooding analysis, or demand/supply energy simulations. CityGML allows extension in order to integrate information from other domains, but the development process is expensive because there is no way to perform it automatically. The discovery of correspondences between CityGML concepts and other domains concepts poses a significant challenge.

Ontology matching is the research field emerged from the Semantic Web to address automatic ontology integration. Using the ontology underlying CityGML and the ontologies which model other domains of interest, ontology matching would be able to find the correspondences that would permit the integration in a more automatic manner than it is done now.

In this paper, we evaluate if ontology matching techniques allow performing an automatic integration of geospatial information modeled from different viewpoints. In order to achieve this, an evaluation methodology was designed, and it was applied to the discovery of relationships between CityGML and ontologies coming from the building information modeling and Geospatial Semantic Web domains. The methodology and the results of the evaluation are presented. The best results have been achieved using string-based techniques, while matching systems give the worst precision and recall. Only in a few cases the values are over 50%, which shows the limitations when these techniques are applied to ontologies with a partial overlap.     

地震后重建过程中的建筑最低成本分析

震后重建工作中,传统建筑最低成本的分析方法无法平衡成本与建筑需求性关系,造成最低成本下建筑的抗震能力较低。设计震后建筑最低成本分析方法,分析震后建筑成本需求关系,提供建筑成本与需求关系的基本数据;优化IFC建筑标准,定义最低成本指标;对分析因素进行综合设置,平衡价值链上需求关系;分析需求与建筑成本关系,完成震后建筑最低成本分析方法的构建,实现最低成本分析。实验数据表明,设计的建筑最低成本分析方法既能满足需求关系,又能实现建筑成本的最低化分析。     

Integration of cadastral survey data into building information models

Cadastral surveying plays an important role in defining legal boundaries of land and property. The current practice for recording cadastral survey data mainly relies on 2D digital or analog documents. This practice is efficient for simple land parcels but can be challenged in complex building developments. To address the issues stemmed from 2D methods of representing cadastral survey data, 3D spatial information models can be considered as a viable solution for managing cadastral survey data. Building Information Modeling (BIM) enables colsslaborative 3D management of the design, construction, and operation of buildings. There have been extensive studies conducted to investigate the connectivity between BIM and 3D cadaster. Most of these studies focus on managing legal information, such as ownership boundaries and attributes, in BIM-based environments. However, there is limited investigation on how survey- ing measurements can be mapped into BIM. In this study, the proposed method for integrating the cadastral survey data into the BIM environment includes identifying cadastral survey requirements, using BIM entities relevant to cadastral survey data, enrichment of a BIM proto- type, and evaluation of the prototype. The major contribution of this study is to demonstrate the storage of cadastral survey data such as survey marks and traverse lines in the BIM environment. Therefore, this research contributes to the further enrichment of BIM with incorporating data elements related to cadastral surveying practices. It is confirmed that current BIM-based tools provide restricted capabilities for explicit management and visualiza- tion of cadastral survey data. This limitation can be addressed in the future enhancements of BIM in terms of supporting important elements for cadastral survey data.     

BIM模型到多细节层次GIS模型转换方法

BIM精细化三维模型中的数据是三维GIS重要的数据来源,然而两者数据模型在几何和语义上差异是阻碍BIM与GIS集成应用的重要问题。IFC与City GML分别为BIM和三维GIS领域最通用的标准数据模型,当前的数据转换工具虽然可有效地将IFC数据转为City GML数据,但还是难以顾及到City GML所有的LOD层级,存在信息丢失和几何不准确的问题。本文通过分析IFC数据模型与City GML模型中所有的建筑构件类型以及其关联的语义信息,分别建立IFC数据模型到City GML各层级的映射模型,描述了一种从BIM模型到多层次细节GIS模型的完整转换方法。并通过具体的实验数据进行了验证,保证数据转换方法的正确性以及稳健性。