Livable Transit Corridors: Methods, Metrics, and Strategies (2016)

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23 Introduction This section provides an overview of the recommended methods used to assess livability in transit corridors. Assessment (Step 2 in Figure 1) involves the following three substeps: • Step 2.1: Select Livability Metrics. • Step 2.2: Identify and Select Study Corridor(s). • Step 2.3: Apply Metrics to Corridor(s). Discussion of recommended approaches for MPOs and their partners undertaking each of these steps is provided below. Step 2.1: Select Livability Metrics Select the metrics for analysis based on data availability, the technical experience of available analysts, the level of detail needed to identify and select strategies, and the interests of the corridor stakeholders. This Handbook provides one metric to represent each people and place characteristic associ­ ated with each Transit Corridor Livability Principle (see Table 2). These metrics are NOT intended to represent the complete variety of factors that one might associate with livability. Rather, they are offered as indicators that suggest potentially useful avenues for further investigations. Appendix E presents these metrics and their data sources, which can be used to quickly and routinely assess livability in a transit corridor, and assesses the availability and quality of each data source. Step 2.2: Define and Select Study Corridor(s) Define the study corridor’s boundaries using the corridor definition criteria described in Step 1 and the following substeps. Step 2.2.1: Identify General Study Area Identify the general area within your region of interest based on stakeholder input and transit expansion planning documents. This often requires a political and collaborative decision between stakeholders rather than a technical or analytical one. Full participation and colla­ boration between regional stakeholders can help ensure that the most relevant study areas are identified. S E C T I O N 2 Assess the Corridor (Step 2)

24 Livable Transit Corridors: Methods, Metrics, and Strategies Step 2.2.2: Select Corridor Alignment, Length, Catchment, and Segments Identify the primary existing or planned transit line within the general study area. Criteria for defining the boundaries of a corridor should be taken from the definition of a transit corridor developed by stakeholders in Step 1 of this Handbook. Recommended Practice: Defining Corridor Boundaries The analyst should represent the boundaries of all study corridors in a geographic information system (GIS) program (for example, see Figure 8). This will make the data collection, processing, and metrics calculation steps easier. Step 2.3: Apply Metrics to Corridor(s) Use the following process to complete the assessment step, using the metrics stakeholders selected in Step 2.1. Step 2.3.1: Collect Data Collect the data recommended in Appendix E for each metric selected for your study cor­ ridors by your technical advisory team. It is usually best to collect data in the most disaggre­ gated form available. In other words, given the choice between gathering U.S. Census data at the census tract or census block group levels, choose the block group level, which is smaller. The GIS files recommended above that analysts develop for identifying their study corridor boundaries are ideally suited for selecting the data inside those study corridors from larger data files. Validating the Metrics: Corridor Non-auto Internal Trip Capture To validate the metrics used in this Handbook, the research team used the metric scores for 31 transit corridors in the United States to predict a proxy indicator of quality of life (QOL) using an ordinary least squares (OLS) linear regression model. The proxy QOL indicator selected was the non-auto internal trip capture rate for each transit corridor in the sample. This model tested the hypothesis that the more livability opportunities in a corridor, and the higher its metric scores, the more QOL it would provide, and the more transit, pedestrian, and bicycle trips that would both start and end inside the corridor’s boundaries. Model results (see Appendix G) confirmed this hypothesis, suggesting that transit corridors with the most livability opportunities also internally capture the highest proportion of the trips they generate. All independent variables— the livability metrics—were statistically significant and the model predicted more than 90 percent of the variation of the internal capture indicator scores. These findings suggest that the metrics are valid and useful measures of transit corridor livability.

Assess the Corridor (Step 2) 25 Step 2.3.2: Data Preparation Prepare the data collected for calculating your metrics. All the data for metrics calculation should be in a single database file. The most effective approach to data preparation is to process and store the data in a set of geo­referenced GIS files. Step 2.3.3: Metrics Calculation Using the metrics selected in Step 2.1 and the spatial data processing capabilities of the ana­ lysts’ GIS program, calculate the existing­conditions metrics for each study corridor and, if appropriate, each corridor segment. An overview of the data calculation methods for each metric is provided in Appendix E. Recommended Practice: Selecting and Calculating Metrics One easy way to measure the livability opportunity characteristics of a transit corridor is to use the Transit Corridor Livability Calculator included as a companion piece to this Handbook. The Calculator provides data for most metropolitan­area census block groups in the United States that can be used to measure the corridor­level people and place characteristics for user­ defined transit corridors in the United States. Table 6 shows the data included in the Calculator for each metric. Figure 8. Example of a study corridor’s boundaries mapped in GIS.

26 Livable Transit Corridors: Methods, Metrics, and Strategies Metric Data Source(s) Included in Calculator? Transit employment accessibility (weighted employment within 45- minute commute) EPA’s Smart Locations Database (SLD) 2010 D5br: Jobs within 45-minute transit commute, distance decay (walk network travel time) weighted Yes Transit service coverage (aggregate frequency of transit service per sq. mile) SLD D4d: Aggregate frequency of transit service (D4d) per square mile Yes Housing unaffordability (percent of income spent for housing) HUD’s Housing Affordability Index Dataset (HAI) hh_type1_: housing cost as a percent of income for the regional typical household (HH), defined as: avg. HH Size for region, median income for region, average number of commuters per HH for region Yes Income diversity (variance from regional median household income) National Historical Geographic Information System (NHGIS), 2010 Census ID B19013: Coefficient of variance of block group median household income compared to either the metro area or the state median; closer to zero means less diversity, closer to one means more Yes Jobs density (employees/acre) SLD D1c: Gross employment density employees (jobs)/acre on unprotected land, 2010 Yes Retail jobs density (retail employees/acre) SLD D1c_Ret10: Gross retail employment density employees (jobs)/acre on unprotected land Yes Transit balance of ridership flows Transit agency route/line data Inbound (to CBD) daily boardings/inbound daily alightings No Health care opportunities (health care employees/acre) SLD D1c8_Hlth10: Gross health care (8-tier) employment density employees (jobs)/acre on unprotected land Yes Population density (population/acre) SLD D1b: Gross population density (people/acre) on unprotected land Yes Access to culture and arts (corridor entertainment employees/acre) SLD D1c_Ent10: Gross entertainment employment density employees (jobs)/acre on unprotected land Yes Pedestrian environment (intersection density) SLD D3bmm4: Intersection density in terms of intersections having four or more legs per square mile Yes Pedestrian collisions per 100,000 pedestrians Transportation Injury Mapping System (TIMS) 2010 Pedestrian collisions per 100,000 pedestrians Yes California Only Table 6. Transit corridor livability metrics, data sources, and their availability in the Calculator tool. The recommended way to calculate the average metric scores for the corridor of interest is by entering a list of census block group ID numbers into the Calculator for all metrics with data available (see Appendix H). For all corridors and associated metrics where Calculator data are not available or are insufficient, obtain data from comparable data sources and use a standard GIS software package to calculate metric values as needed.