Tools for Visual and Spatial Analysis of CAD Models

The paper describes a suite of spatial analysis programs to support architectural design. Building these computational tools not only supports the task of spatial analysis for designers but it also helps us think about the spatial perception. We argue that building design software is an important vehicle for understanding architecture, using our efforts to build various visual and spatial analysis tools as examples. 1. Tool building as a way to understand design concepts The past twenty-five years have seen the development and refinement of tools for simulating, analyzing, and predicting the performance of building designs with respect to lighting, energy, acoustic, and structural behavior. Surprisingly, little work has been done on modeling the spatial characteristics of designs, although they strongly influence users' experience of buildings, and determining the spatial structure of a building is the central focus of architectural design. Tools for analyzing spatial characteristics have for the most part been neglected in CAAD research. Plenty of work has been done outside the arena of CAAD on spatial and visual analysis of built environments. Architectural researchers have looked at the relation between physical features of the built environment and experiential qualities that users perceive. For example, Benedikt (Benedikt 1979), Thiel (Thiel 1961; Thiel 1981), Appleyard, Lynch, & Myer (Appleyard and others 1964) among others have proposed frameworks, theories, and specific analyses of perceptual space that can—and we argue ought—be made computable. Computations of these analyses would be immediately usable both to CAAD users directly as well as to intelligent CAAD programs of the type described by Koile (Koile 1997). We suggest however that implementing such analyses in a 2 ELLEN YI-LUEN DO AND MARK D. GROSS computer program is often nontrivial and raises issues may have been glossed over in the original, non-computational, formulation. In this paper we aim to do two things. First, we describe a class of tools for spatial analysis of building designs based on Benedikt's isovist research and other models of the perception of architectural space. Second, we point out that the detailed implementation strategy chosen to build a tool for analysis can have a tremendous effect on the outcome, not only making the tool more or less efficient, but actually affecting the framing of architectural concepts. Thus we see the building of CAAD tools not only as a means to perform useful calculations, but also as a way to think about underlying and central concepts of space, place, and architecture. In the following sections we discuss computational tools for spatial analysis in architecture. In particular, we consider how different implementation approaches influence the results of the computation, and more fundamentally, how the tools lead us to think differently about underlying architectural concepts. We focus here on models of the perception of spaces and places as exemplified by Benedikt's work on isovist (Benedikt 1979). Accordingly, section two reviews briefly the underlying work of Benedikt and others on spatial and visual analysis. Section three discusses our experience implementing visual and spatial analysis tools for CAD models. We briefly describe the algorithms, and presentations of these tools. Finally, in section four, we compare the strengths and weaknesses of these different methods and propose an agenda for future work. 2. Concepts of visual and spatial analysis Good designers manipulate the placement and spatial relations of walls, screens, and partially defined boundaries to provide feelings of containment and privacy, opportunities for survey and outlook, and the sense of flow and direction in a building. A well designed building is an appropriate and varied arrangement of spaces whose spatial characteristics match intended uses and offer a range of physical definitions of habitable space. Analyses of the spatial and visual character are often done for the design of museums, office work group layouts, prisons, and religious and ceremonial buildings. The level of analysis ranges from informal inspection to a more careful checking of sight lines and boundaries. Often, though, architects do not perform spatial analysis, but simply work on the basis of their own experience when designing the spatial characteristics of a building. Rooted in the principles of human perception (e.g., Ittelson's Visual Space Perception (Ittelson 1960)) this relationship between form and perception, environment and behavior is widely discussed throughout the discipline of architecture. Porter's How Architects Visualize (Porter 1979)) offers a good overview of the perceptual issues. Ashihara's Aesthetic Townscape used 'degree of enclosure' to describe and discuss the composition of townscapes, observing for example, that people pause and linger in the 'inside corners' of spaces (Asihara 1983). Lynch discussed 'imageability' (Lynch 1960), and changes of views in sequence when moving in an environment (Lynch 1972), and the use of 'viewshed' -terrain maps for analyzing visual effects from a major viewpoint TOOLS FOR VISUAL AND SPATIAL ANALYSIS OF CAD MODELS 3 (Lynch 1976). Appleyard, Lynch, and Myer discussed spatial and visual perceptions associated with movement along a highway (Appleyard and others 1964). Various theoretical and empirical research efforts have been made to account for the relation between physical form and human perception of spaces, which we review below briefly. These include Benedikt's work on isovists (Benedikt 1984; Davis and Benedikt 1979) and the work of Hillier and Hanson (Hillier and Hanson 1984) on space syntax and Peponis on various space partitioning schemes (Peponis and others in press). However these efforts to understand the relation between built form and perceived space have not been widely applied, in part because they involve tedious calculations from floorplans. These calculations can be easily made using computers, adding spatial analysis tools to the growing collection of tools for analyzing building performance. Benedikt proposed that a space, or an environment, is perceived as a collection of visible surfaces not occluded by physical boundaries such as walls and partitions (Benedikt 1979). He defined an 'isovist' at a given point in the floorplan as the space visible from that point, looking around in 360 degrees. Quantifying the isovist areas, perimeters, and solid boundaries can be used to compare the quality of different spaces. He further described making physical (say, clear plexiglass) models of isovists along a defined path and stacking these models to visualize a moving user's changing perception of a built environment. In his papers (Benedikt 1979; Davis and Benedikt 1979) he described computational implementations that were done at the University of Texas at Austin in the 1970's. In The Social Logic of Space , Hillier and Hanson presented 'space syntax' as a way to describe and analyze the character of spaces and predict human behavior patterns and cultural activities in these spaces (Hillier and Hanson 1984). In space syntax the connectivity between spaces—the integration value—captures the depths of topological values. Hillier and Hanson analyzed two dimensional planar views to draw and quantify connectivity and integration values. First, a convex space is indicated by drawing maximal 'space bubbles' between wall partitions. Then an 'axial line' is drawn to connect convex spaces. The number of intersections for each axial line in relation to overall area produces an 'integration value'. Empirical observations found that the frequency of activities coincides with integration values of an axial map, that is, in real life more highly integrated places tend to have more activities. Researchers at University College, London have developed the Axman program to support axial map calculation. Users import a picture of the floor plan or bubble diagrams as an underlay and then draw axial lines on top of the plan. The Axman program finds intersections among all axial lines, calculates the integration values for each line, and displays axial lines in different (rainbow) colors: Red lines indicate the most integrated paths and blue or violet lines indicate the least integrated ones. Peponis, WIneman, and others. (Peponis and others in press) recently proposed various spatial analyses to study the shape and spatial configuration of building plan. These analyses are based on the identification of the boundaries of spaces in a floorplan with certain properties, in particular with respect to a viewpoint moving through the floorplan. They recognized that a wall end or a corner can be an important index of spatial qualities because the 'endpoints' appear and disappear or remain invisible as the viewer moves. Their endpoint partition', for example, identifies convex areas that are 4 ELLEN YI-LUEN DO AND MARK D. GROSS “informationally stable” with respect to shape, i.e. all their points are visually connected to the same edges of the plan. They are supervising a computer implementation of spatial partition analysis in the Microstation environment (Peponis and Wineman 1997). 3. Implementation methods of spatial analysis tools We describe our work on automated spatial analysis of CAD models, which includes two main styles of analysis. The first, a discrete approach, involves calculations of perceived space, by computing the projections and extensions of physical boundaries, and the computation of viewsheds and visual fields. The second, a continuous approach, involves the calculation of spatial gradients or fields. We describe several programs, built on a variety of platforms, including PL/I, Topdown Pascal on Macintosh, Tk/Tcl on Sun, AutoLISP with AutoCAD, and Macintosh Common Lisp, that perform these computations on floor plans and sections entered by a designer. 3.1. 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