Geography Reference
In-Depth Information
people pass by each other in transit, and therefore only locations of stops are
considered for analysis. Other studies may include instantaneous interactions during
passing.
The Geohash system provides a convenient spatial structure to determine proxim-
ity for its grouping efficiency. For a Level 9 Geohash, the default spatial proximity is
set at 2 m, and for Level 8 Geohash, 30 m. All stops for all individuals of interest are
included in the analysis. However, like all discrete grid systems, locations along the
boundary of adjacent grid boxes can be within the proximity threshold even though
these locations are not in the same grid box (i.e. the fault line issue). Therefore,
proximity examination needs to include locations in all Geohash boxes adjacent to
the box of interest.
2
Figure
20.15
provides an example of the adjacent Geohash
boxes needed for analysis of nearby points. The spatial proximity needs to be
adjusted to about 5 m for Level 9 and 45 m for Level 8 Geohashes.
Once the Geohash Level is determined, all stops falling in the same Geohash
box as well as in adjacent Geohash boxes are grouped. The analysis then proceeds
one group at a time to determine stops within temporal proximity. Both spatial
proximity and temporal proximity should be defined based on application domains.
Individuals can sit next to each other in a basketball game or run far apart in a
marathon race. One can drop a package at a friend's house, and another person
might pick up the package an hour later. There are four types of space-time
constraints on communication (Janelle
1995
). Spatially, communications can take
place among individuals who are in presence or telepresence, and temporally, it
can be synchronous or asynchronous. The four types of space-time constraints on
communication can also guide for the conceptualization of interactions.
Once the proper thresholds for spatial proximity and temporal proximity are
determined, Euclidean distance (or travel distance) and time differences can be
calculated among locations in a group to determine stops that are within the
desired spatial proximity and temporal proximity. Individuals within the spatial
and temporal proximity can then be identified and connected for a social network
of potential interactions. In a case study of 50 individuals in a suburban town
(Moore, Oklahoma, USA), we define the space-time proximity as within one level
8 Geohash grid (
45 m) and 30 min. Eleven of the 50 individuals are within
space-time proximity of synchronous presence over 553 days of the study period
(3/4/2009-9/8/2010). The width of an edge corresponds to the relative frequency
of the potential to meet. The connection between person ID 16 and person ID
30 is an example of a strong connection with a relatively high frequency for
potential meetings in places where both individuals visited at about the same time
(Fig.
20.16
). Individuals with IDs not listed in the social network have no records of
presence within the defined space-time proximity to other individuals in the study.
2
The issue can be solved with the fault line algorithm. Its source code is available at
http://code.
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