Geography Reference
In-Depth Information
2.1.3.4
Networks Structuring an Environment
We are now ready to reunite the three alternative lines of our thought experiment.
Whatever network the walker chooses, the result is a structure of nodes (say, street
intersections) and edges between nodes (say, street segments between intersections).
Such a structure is a graph [ 4 , 9 , 15 , 22 ] . This graph, since it was drawn by the
walker on the ground, is also planar (each intersection of edges is a node) and
embedded (each node is at a particular location on the plane).
Each network structures the environment independent from prior landmark
experiences. It has distinguished locations, the intersections, that are easy to
perceive with the body senses as locations of choice. They are memorable, and
hence landmarks by themselves. Since the walker could draw only a network of
limited extent the individual intersections are countable and finite. Instead of polar
coordinates within the polar reference system locations can now be described using
this discrete network, e.g., “at the corner of”. Distances can now be measured
in numbers of intersections. Directions are discrete as well. In the radial and
the rectangular network only right angles exist, and even in the free-form street
networks intersections offer a very limited number of possible directions to take.
In graph theory, this property is characterized by the degree of nodes: The degree
of a node is the number of its incident edges. Radial and grid network have only
nodes of degree 4, except the pole in the radial network and the outer boundary
of the networks. Free-form street networks can also have nodes of degree 1 (dead-
ends), degree 3 (e.g., T-intersections) and degrees higher than 4 (more complex
intersections). However, due to physical space constraints this number cannot be
arbitrarily large. From a cognitive perspective the limited number of directions
is again a relief. The walker does no longer need to control constantly direction
and to integrate steps. Instead, the walker only counts the passed intersections
and memorizes discrete turn choices. These typically low counts are not stretching
numerical cognition and short term memory [ 6 , 13 ] .
Networks may appear relatively plain, but then there are also individual differ-
ences coming out of node degrees or node (or edge) centrality. For example, the
pole in a radial network has a node degree standing out in the otherwise regular
structure, and it is also the node of highest betweenness centrality in the network—
betweenness centrality of a node in a graph is a measure of how many shortest
paths a node is in [ 8 ] . The latter means that statistically it will be experienced more
often by walkers than other nodes. These reasons add to the pole's experiential
features. The pole is a stronger landmark than the other intersections, and due to
its uniqueness in this respect it is a global landmark. One function of a global
landmark is supporting global orientation and wayfinding. For example, even if a
walker somewhere in the radial network feels temporarily disoriented, some simple
heuristics will lead her back to the pole. She will follow the next meridian, i.e.,
the straight streets towards the sun, and will reach the pole. In other network forms
local variations may produce more subtle differences between nodes, but centers or
bottlenecks will stand out as well. A regular node, however, is a local landmark.
It helps locating events and referencing to these events as local anchor points.
 
 
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