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Object-oriented GIS Data Modelling for Urban Design
2. Development of Data Modelling for Urban Design
The recent development of the model-based design in computer-aided building design has become the motivating example for the experiment of using a similar approach for urban design. Autodesk, Bentley and Graphisoft have developed “object-oriented” CAD packages capable of performing model-based design, which is also known as building information model, virtual building, or parametric building modeller. The motive of this paper is to utilize data modelling technology to support computerized urban design process.
Computerized urban design utilizes spatial modelling technologies such as CAD, and most recently 3D GIS. Most computerized urban design activities will need spatial database of some kind, where data are stored in certain format. The structure, format, and technology level of the spatial database will determine the capacity and capability of the software application used for urban design. Through data modelling, spatial database should be designed to accommodate urban design analysis and design decision-making process.
The idea of applying data modelling to physical design is not entirely new in the realm of design since the systematic design thinking in the 60s and 70s. Forty years ago, Alexander proposed a “set-subset” theory, where he suggested designers to construct analytical design process through problem classification in hierarchical logic. He initiated the use of constructive or schematic diagram of design variables as design tool, which implied a preliminary idea of design programming and data modelling. He argued that performance standards, which resembles urban design guidelines in their roles, can be set up for every misfit variable that exhibits continuous variation along a well defined scale (Alexander, 1964). In his theory, he experimented on redistribution or reclassification of the design variables, which is comparable to the object-oriented (OO) principles, where variables related with the same object are clustered together. Alexander’s problem solving principle of classification is actually the preliminary stage of current data modelling principle. It can be followed by the transformation of “misfit variables” by semantic and logical deduction into objects, subtypes, attributes, validation rules, connectivity rules and relationship rules, which are the basic components of OO data model.
Further researches following Alexander’s earlier work also supported the concept of data modelling for design process. Geoffrey Broadbent, Anthony Ward, Amos Rapoport, Luckman, Best, etc, have discussed the role of operation research (OR) methodology in design process, which has much compatibility with data modelling techniques.
The developments of computerized urban applications in the prior days were emphasized more on the analytical and predictive aspects of the applications. The development of Planning Support System (PSS) was a significant evidence of this trend (Klosterman 2001). A PSS usually contains several levels of predictive urban modelling or simulation, which requires a database modelling as the foundation. Several DSSs and PSSs were built on ArcView version 3.x GIS platform by customizing ArcView system and adding on its original functions. Relational spatial database was not existed in this version; therefore developers could not design spatial database through data modelling, and have to customize the functionality of relational spatial database through its customization language such as Avenue. In the later version of ArcView, ArcGIS 8.x has the capability to build spatial database designed through the data model of UML and XML and the customization platform ArcObjects with embedded VBA. Planners have benefited from the object-oriented ArcGIS Parcel Data Model recently (ESRI 2001), which was actually designed for cadastral purpose, with more emphasis on land ownership and distribution. Although containing urban objects, ArcGIS Parcel Data Model may not be suitable for accommodating urban design activities, since design process needs sufficient built-up physical data.