Quantifying Urban Diversity: Multiple Spatial Measures of Physical, Social, and Economic Characteristics - Computational Approaches for Urban Environments - page 155

Tabl e 7. 2 Truncated list of
commercial uses for
mixed-use calculation

Use Code Description

001 Residential-single family (commercial use)

031 Hotel-small

032 Hotel-large

::: :::

043 Store-department

044 Store-shopping center/mall

045 Store-restaurant

046 Store-barber/beauty shop

::: :::

048 Commercial-retail-condo

049 Commercial-retail-misc

051 Commercial-office-small

::: :::

067 Commercial-restaurant

068 Commercial-restaurant-fast Food

::: :::

465 Vehicle service station-market

values closer to 0 have a shorter distance between residential and commercial mean
centers than values closer to 1. As with the first method, block groups that either
do not contain commercial points or do not contain residential points are assigned a
value of 1, indicating that they are the least mixed use. For both of these methods,
“commercial” includes uses described as “retail.” See Table 7.2 for a truncated list
of the uses included as “commercial” in these calculations.
The idea behind both of these methods is that the calculations reflect the level
of intermixing of residential and commercial uses. The closer the shortest distance
between a residential location and a commercial location within the same block
group, the more intermixed these uses are; the closer the mean centers of these two
use types, the more mixed these uses are. For both methods, the Euclidean distance
is used for the calculations, as opposed to the Manhattan or network distance. This
is done purposefully to separate the measure of mixed-use as much as possible from
the actual structure of the street network, which has its own measure in the form
of street lengths. This will help to identify areas that may have an adequate street
network, but a poor mix of uses, or vice versa. Both methods are evaluated since they
may provide slightly different results, though one, the mean center calculation, is far
less computationally intensive than the other, making it more repeatable for other
cities. As with the block length parameter, lower values (closer to 0) are preferred to
higher values (closer to 1), since lower values are indicative of a more fine-grained
mix of uses.
It should be noted that in the interest of easing the computational complexity of
these calculations, they have both been limited to commercial and residential points
within the same block group. This creates the possibility, particularly for the mean
shortest distance method, that some residential points may be assigned a distance