Overview
The Local Index of Transit Availability was developed by the Local
Government Commission (LGC) through a grant from The Energy Foundation.
Principal research for the project was conducted by Timothy Rood,
AIA.
The Local Index of Transit Availability (LITA) is a system for
rating transit service intensity, or transit availability, in various
parts of a metropolitan area. LITA scores are intended to be useful
to transit service planners as well as local land use planners and
policymakers, allowing them to see where transit service is most
intense and aiding them in developing appropriate land use plans
and policies for areas with high, medium and low transit availability.
In areas where ordinances require minimum roadway levels of service
for new development, which often has the effect of pushing new development
to peripheral areas poorly served by transit, LITA scores can provide
an additional point of reference for land use and siting decisions.
 Faced
with the negative externalities of automobile-dependent low-density
development — such as increasing commute lengths, traffic congestion,
air quality problems and loss of open space — many communities
are turning to strategies such as transit-oriented development ,
or TOD. Transit-oriented development proposes to allocate the land
closest to transit stations to compact, walkable mixed-use development,
with clear and memorable street patterns, buildings configured to
enclose streets and public spaces, and generous provisions for pedestrians
and bicyclists. Whether new development or infill, such environments,
it is hoped, will require fewer and shorter automobile trips from
their inhabitants, who may shift some trips to nonmotorized modes
or transit.
Given their incremental nature in a largely built-out, automobile-dominated
metropolitan area, TOD strategies can only be effective in changing
travel patterns if they are widespread and coordinated with transit
investments. Planning a single new urban village or pedestrian pocket
in an outlying suburban area with poor transit service is unlikely
to show significant effects on traffic or air quality. At the same
time, many inner-city and older suburban areas are struggling to
attract new development as catalysts for revitalization. These existing
communities are often better served by transit and other urban services
than are outlying areas, but urban redevelopment is discouraged
by many factors, including higher land costs, clearance and environmental
mitigation costs, tax policies, lending practices and perceptions
of safety. If found to have critical elements of transit-oriented
development, inner-city and older suburban areas might be ideal
candidates for policy incentives to encourage compact, mixed-use
infill development.
 Communities
wishing to try transit-oriented development as a step toward easing
their traffic congestion, air quality and quality of life issues
might well ask where to start. TOD strategies must make more sense
in some places than in others, but local planners and policymakers
often have little information to work with in trying to make transit-oriented
land use decisions. The purpose of the LITA project was to develop
methods of accounting for transit service that could inform land
ñ use and transportation decisions, which are often made
under assumptions of near-universal automobile travel without regard
to accessibility by alternative modes. The LITA system is one of
two transit rating systems developed as part of the project, the
other being a considerably more data-intensive Regional Index of
Transit Accessibility, or RITA, developed from a regional transportation
model. Recommendations for RITA are available from the research
team.
For transit-oriented development to be effective in reducing auto
travel, two additional factors besides transit availability should
also be considered: land use intensity, to concentrate trip origins
and destinations around transit-accessible points, and walkability,
to enable people to make local trips comfortably on foot and to
access transit without a car. The project team has identified appropriate
methods for assessing these two additional factors, which were included
in the Riverside case study. Land use intensity is easy to quantify
and can in fact be measured using a subset of the data collected
for the LITA capacity component. Walkability is difficult to quantify
definitively, but several indicators of walkability, such as street
interconnectedness, are quite simple to measure.
LITA Components and Methodology
LITA combines three aspects of transit service
intensity — capacity, frequency, and route coverage —
to rate small areas within a metropolitan area, such as census tracts
or Traffic Analysis Zones.
The frequency component is calculated as transit vehicles per 24-hour
day, using a weekly average that includes weekend service.
For the capacity component, the first method to be tested was seat-miles
divided by combined resident and employed population. The second
approach was seat-miles divided by the peak load factor for the
transit lines serving each area.
For the route coverage component, the first method tested was route-miles
per square mile; the second was transit stops per square mile, recognizing
that transit is only accessible at its designated access points.
After being standardized, or expressed in terms of their mean and
standard deviation, the scores for all three LITA components are
averaged to give an overall LITA score.
Choosing units of analysis
LITA relates the amount of transit service in an area to that area's
population (resident and employed) and to its land area (preferably
the developed land area). LITA scores could be calculated for any
unit of land area for which population and land area data are available,
but the units should be fairly small in order to capture as much
variation as possible.
 Census
tracts or traffic analysis zones (TAZs) are often the smallest units
of land area for which population data are readily available, and
either unit is appropriate for LITA analysis. (LITA test scores
were calculated for census tracts in Riverside County and for TAZs
in Metro-Dade County, Florida.) It should be noted, however, that
some TAZs and census tracts in outlying areas can be quite large,
making those results difficult to interpret if the transit service
level is uneven throughout the area. Also, tracts and TAZs will
not necessarily coincide with the neighborhoods, districts or zones
for which plans and policies are being developed. If population
and employment data are available for even smaller units, such as
census block groups, LITA scores can be calculated for these smaller
units to approximate these planning areas more closely. The ideal
unit of land area for analyzing transit availability would be the
immediate catchment area of each transit stop or station, but this
approach is impractical since these areas can be very small and
would also overlap.
Large-scale regional transit facilities require detailed land use
planning of the surrounding area in order for TOD strategies to
be effective in reducing the need for automobile travel. Policies
for special areas such as rail stations should be defined for the
actual station area, preferably based on network walking distance,
rather than for the tracts or other units used to calculate the
LITA rating. LITA is an informational tool, and LITA scores will
always need to be evaluated in light of actual conditions on the
ground. The more fine-grained and comprehensive the LITA analysis,
the more interpretable and useful its results are likely to be.
Because transportation patterns are regional, LITA scores would
ideally be calculated for every subunit in an entire metropolitan
area. This may not always be possible, or a particular area may
be of more immediate interest. Since LITA scores are expressed in
terms of their statistical distribution, it is important that LITA
scores be generated for a random sample of subareas that are served
by transit throughou ôt a metropolitan area, county, transit
service area or other large geographic unit. LITA scores for a particular
area of interest can then be standardized based on this regional
distribution of scores.
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