Before starting at LMN, I lived in China for over three years, where I became fascinated by the classical gardens of Suzhou. These gardens, unique to southern China, are populated by small pavilions and halls, sculpted rock outcroppings, shallow pools, and planted areas, all contained within a perimeter wall and arranged in an aesthetically pleasing manner. While a pleasing arrangement of rocks may be enough to satisfy bored tourists, architects and designers find the gardens endlessly fascinating for the way they orchestrate experience, frame space, and create illusory depth in their limited boundaries.
Suzhou’s gardens are characterized by ambiguity of interior and exterior space, collisions of disparate forms and materials, and above all the intricate layering of space to create subtle perceptual shifts that serve to destabilize the viewer’s sense of space and scale, inspiring a kind of sublime wonder, a worthy goal for designers in any era or cultural context.
How are these effects achieved? Is Chinese garden design a lost art, or subject to codes buried in ancient design manuals? Can we leverage our computational tools to quantify what makes these gardens so beguiling? Could spatial analysis of these gardens hold any lessons for designers today?
[single point isovist diagram – windows as obstacles]
[single point isovist diagram – windows as void]
As a starting point, we can analyze a floor plan based on “spatial intelligibility” – a metric that indicates the relative visual accessibility or enclosure of a space. Intelligibility is best understood as an aggregation of vectors, a summation of the length of direct sightlines in all directions. From any point in the space, we draw projecting rays outward until they hit obstacles, measure the distance from the origin point to the intersection point, and add the values. (For this example, we’ve used Grasshopper‘s Isovist component.)
[isovist grid with radial projecting lines]
[sample points with color map gradient – low density of samples]
Extending this logic to a grid, we can find this intelligibility value for every grid point and create a gradient map that visualizes the relative visual legibility of the space. In this simple example, we can see clearly that the ‘compressed’ space to the left has lower intelligibility values than the ‘open’ space to the right.
While this type of analysis, based only on physical barriers, could be useful (for retail planning, for instance, or urban design), we have so far assumed only solid obstacles. What would happen if we considered barriers that allowed visual, but not physical connections between adjacent spaces?
[sample points with color map gradient – high density of samples, windows as obstacles]
[sample points with color map gradient – high density of samples, windows as voids]
In Chinese gardens, there is a disjunction between physical accessibility and visual accessibility: windows often open to adjacent spaces that may be accessible only through convoluted, indirect routes. Screen walls divide space but still allow views through. While it may not be the most efficient layout, this complication is the root of many of the gardens’ pleasures, and is worth studying further.
For this analysis, we’ve picked the Garden of the Master of Nets, one of Suzhou’s most celebrated gardens. A moderately sized garden, it contains several areas of interest: a relatively enclosed section with halls and courtyards along a linear axis, a large open area around a shallow pool, and several intriguing areas where covered walkways collide with small pavilions and rockeries. By analyzing the plan for both physical and visual intelligibility, we can begin to quantify and visualize the unique qualities of each space.
Here, we’ve mapped physical intelligibility; how accessible is each point on the grid? Note the values around the pond: though visitors can see across, we’re treating the pond edge as a boundary.
Here, we’ve mapped visual intelligibility, and so we’ve removed the obstacle objects wherever a window or screen wall allows views through to spaces beyond. Note the pond edge again, some of the longest sightlines are to be had around the pool.
Finally, by calculating the difference between the physical and visual intelligibility values, we can create a map of the spaces where the disjunction between the two is greatest, and we can surmise that these are the areas where the surprising perceptual effects of the garden are most evident. The pond edge is worth noting again, as the views are open, but movement is restrained. More surprising, areas that are dense with rockeries and covered walkways are highlighted as well. These areas are physically divided but visually permeable thanks to the corridors’ open edges and prevalence of screen walls and windows.
Visual connectivity without physical access could be frustrating, but here is is an operative method of the design, and a technique that could be adapted for future building projects if such an effect is desirable. Designers today often deal with situations where circulation paths are kept separate for security, or sanitary, or social reasons. In such cases, visual connectivity may be encouraged as a way to enliven a users’ experience of the space. In retail design, intelligibility maps can be used to anticipate shopfront visibility, and thus sales. Extended to a sectional analysis, or a three-dimensional matrix, similar techniques could be used to analyze the overall legibility of a stadium or auditorium. In urban planning, these metrics could be used to anticipate traffic loads, or to speculate on usage patterns of public spaces. In all cases, intelligibility ties computational power to qualitative effects, and is worth further study as a metric that help designers bridge the gap between the digital and the physical.