Several characteristics differentiate Space Analytics from other built environment professionals like architects, urban designers, appraisers, engineers and planners in doing failure analysis and accident reconstruction.

  1. An innovative, reliable and award-winning spatial modeling methodology;
  2. High level research and publication;
  3. Multi-disciplinary knowledge,;
  4. Root cause analysis.

These characteristics offer wide perspectives on problems and avoid surprises.

This approach captures the latent aspects of built environments that we often miss or ignore. Three variables, the body, the brain and the built, function as an imperfect system. The building's floors, doors, walls et cetera are there for the eyes to see. The legs move the body and the brain through the built environment. The eyes and other senses send information to the brain's hippocampal region which tells the body where it is, where it was and where it can go. Walking legs send impulses that generate brain cells.

How the brain responds to spatial patterns depends on their legibility and complexity. Sometimes complexity is interesting. More complexity might be worth exploring. But a lot of complexity can be frustrating. Any complexity relating to fire exits is dangerous. Different kinds of buildings and places require different levels of complexity.

Our methodology combines elements of neuroscience with geometry. Using spatial intervals based on neuron firings when we walk, it measures complexity by decomposing the spatial configuration of movement surfaces into convex shape and linear shape intervals to form functional distance networks based on real or symbolic barriers, borders and direction changes. These can then be linked to vertical patterns such as façades. This methodology is available for licensing to selected organizations.

These two simple layouts could be parts of an office or a street system. They show two kinds of intervals, convex based on borders and lineal intervals based on seeing and moving forward. Linking the intervals makes networks that can be visually compared and analyzed with simple mathematics. see publication

Examples

Two specialty malls, each about 300,000 SF leasable area.

The drawings show the ground floors and convex shape intervals of two specialty malls each just over 300,000 SF. The networks show the sequence of convex shape intervals from the main entrance. The mall on the right was so complex that less than 30 percent leased out. It closed in less than two years to become the Happy Church. see publication