Quantifying Urban Diversity: Multiple Spatial Measures of Physical, Social, and Economic Characteristics - Computational Approaches for Urban Environments - page 173

Tabl e 7. 6 Results of scenario test for bottom 10 % of block groups

Dwelling
density

Mixed use
(exclusive) Street length Building year

Mean change in raw UL C0.983 C0.580 C0.795 C0.507

Median change in raw UL C 0.980 C 0.539 C 0.777 C 0.447

Minimum change in raw UL C 0.969 C 0.408 C 0.714 C 0.382

given the worst value; thus, the bottom 10 % fall into this category. When these
block groups are given the best value, they all show a change of plus 1 in the UL
index. Given the uniform nature of this response for the mixed-use parameter, these
94 block groups were not examined, and the bottom 10 % was chosen selected
from the block groups for which a valid distance had been calculated (i.e., they
contained both residential and commercial points). Table 7.6 presents the results of
this scenario testing.
For all parameters, when the bottom 10 % of block groups are targeted in such a
manner that they become equal to the highest performing block group, an investment
in dwelling density produces the greatest effect on the UL index. This is followed by
the building year parameter, the street length parameter, and, finally, the mixed-use
parameter. However, as noted earlier, given the high number of block groups that
contained no mix of uses, this parameter would hold the greatest influence if those
block groups were targeted. This suggests that while adding a mix of uses to areas
that currently have none can have a dramatic effect (an increase of 1 in the UL
index), adding a greater mix to areas that already contain some mixing does not
result in a similar improvement. Given the results of this testing, it suggests that
while all of the parameters have a significant influence on the UL ,itmaymake
sense for city planners to target density and (only for areas where no mixing is
present) the mixed-use parameters. To a lesser extent, a focus on maintaining a
diverse mix of building ages may also be beneficial. This parameter can be difficult
to influence since buildings cannot be artificially aged, leaving the options of new
construction and preservation of older structures. It is important to note that these
conclusions may only be applied to the case study city, Washington, D.C., and
not necessarily to other cities. A wider study that includes the same methodology
applied to other cities would be needed to draw wider conclusions. This testing
highlights the importance of utilizing the UL index in conjunction with the four
subindex calculations. A skilled planner may locate areas in need of improvement
using the UL index and then consult the sub-indices to evaluate which parameter
will have the greatest impact on that location.
Ideally, city planners (perhaps to Jacobs' chagrin) and policy-makers can utilize
the individual parameters, along with the UL index to focus revitalization efforts
on specific locations within a city. For example, if a particular section of a city
is expected to undergo massive redevelopment, and it has also been identified as
having excessively long street lengths, the city may choose to make the inclusion
of shorter street lengths a prerequisite for any redevelopment or rezoning efforts.