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Transportation Planning and Sustainability Guidebook

Chapter 4: Data Collection & Availability for Sustainability Assessment

Section I. Introduction

Sustainability planning, assessment, and monitoring relies on data from a variety of sources to provide a complete picture of the environmental, economic, and social impacts as well as the basic functionality of transportation projects or agencies themselves. In the United States and internationally, data quality and availability have proven to be significant barriers to comprehensive transportation sustainability assessment (31,58,59). A research team in the UK developed an indicator-led approach to appraising sustainability in transportation. The appraisal method examines relationships among transportation, economy, environment, and society to cover all of the objectives in the UK sustainable development strategy and the European Commission's accepted definition of sustainable transportation. The goal was to operationalize already accepted definitions by selecting appropriate indicators. The research team intended to select indicators that were already in use or that relied on an existing data source in order to help with tracking progress from an established baseline. However, they found that several proposed indicators lacked data sources; in particular, the key social sustainability indicators like out-of-pocket transportation costs, quality and security of local environment for walking and cycling, equity of access to transport network from affordable housing (58).

For certain purposes, like developing performance measures or indicators for project delivery or system conditions, transportation agencies may face a data overload -- there may be too much data to choose from and the agency may struggle with what is the most important or most meaningful data to track. However, when it comes to sustainability assessment (particularly economic and social equity/quality of life impacts) agencies face a lack of sufficient data or may have questions about which measures are meaningful indicators of progress. In responding to survey questions about performance measures, DOTs demonstrated that they collect numerous environmental indicators (some of which are required by law) but fewer economic and social indicators. One DOT in particular expressed difficulty in finding a direct measure for social sustainability. Arizona, Delaware and California DOTs have been working to find appropriate performance measures. They reported difficulty in narrowing the list of measures to a manageable number and selecting the most meaningful ones. Further, data collection is costly and requires significant use of resources, and transportation agencies may find it difficult to prioritize additional data collection over other more urgent needs.

For sustainability, developing indicators may require creative use of available data. For example, several variables can be combined into a quality of life index. When considered alone, the data may indicate a certain state but when considered jointly the data may suggest trade-offs that occur. The UK's and other experiences (29, 59, 60) suggest that disaggregating traditional transportation statistics by transportation mode, geography or socioeconomic group could be a method for analyzing social equity. Such an analysis would require census data (demographics, geopolitical boundaries) and available transportation statistics.

Organizing indicators into a sustainability framework - like New Zealand, Texas or Missouri - can help narrow down a list of indicators or identify additional data that needs to be collected. Indicators ought to be linked to specific agency goals and the overall agency vision. By linking indicators to specific agency goals, objectives, and targets, it becomes necessary to sort through all of the available data and only choose indicators that provide a meaningful measure. Rather than collecting and tracking every possible piece of data, only the most important are selected (which can be financially beneficial given limited resources). With a streamlined list of indicators, the transportation agency can then track performance and more easily pinpoint why targets are not met. The agency can also assess trade-offs among different indicators that may result from policies. This must be done with the understanding that performance measures need not be static but must accurately reflect what the agency is trying to accomplish, as what gets measured gets managed. By considering the key indicators for assessing sustainability, gaps in data availability can be identified to guide future data collection or interagency data sharing.

Considerable benefits can be achieved by improving the coordination of existing transportation statistics gathering activities. Data cost effectiveness could be improved significantly. Data quality and usefulness could also be improved by focusing on: comprehensiveness, consistency, frequency, accuracy, transparency, and availability (61). In the meantime, transportation agencies can strive to identify meaningful measures based on available data sources. Following New Zealand and the UK's lead, agencies can also identify measures that they would like to have and potential sources for the data.

Section II: Available Data Sources

A significant challenge for sustainability analysis, evident in DOT interviews and the literature, is finding the right data at the appropriate geographic scale, level of aggregation, or timeframe. In the United States there are several publicly available and commonly used data sources for transportation and socioeconomic data. Table 4-1 summarizes some of these datasets. Environmental data sources, that are used more widely because of NEPA, are not included here.

For purposes of long-range planning, these data sources are produced at an appropriate time interval. However, for sustainability performance monitoring and lower-level planning activities, this data may not be sufficient. For example, there is no single integrated multi-modal database at the federal level. Many MPOs or state DOTs supplement public data sources with regional travel surveys, local land use information (primarily from comprehensive planning or zoning regulations), and data collected in-house (traffic counts, safety statistics, etc.). Additional data may also be available from other relevant state agencies, like economic development and public health departments or environmental agencies.

Data for evaluating system performance is collected regularly by transportation agencies and includes pavement condition, travel times, crash rates, etc. Measuring system performance is a necessary piece of sustainable transportation assessment, but not sufficient on its own. If a transportation system improves its operations at the expense of the environment, economy, and/or society, it may not be sustainable. When taken together, these four areas represent the sustainability of the transportation system and/or agency.

Various DOTs have been collecting data on the environment for several years as a result of the 1969 NEPA and several subsequent laws regulating air quality, water quality, noise, historic preservation, etc. Today agencies are able to evaluate the impacts of projects on the environment, both natural and built, by tracking noise pollution, construction run-off, wetland replacement, material recycling, and other data collected in-house. Agencies also gather data on operational impacts, both internal (like DOT fleet fuel consumption, energy use, paper recycling) and external (like air quality and highway plantings). Now, with emphasis on climate change and energy independence, transportation agencies are beginning to measure greenhouse gas emissions and fuel consumption. While a considerable amount of environmental data is collected by the transportation agency, additional data is obtained from federal and state resource agencies or local governments.

When it comes to sustainability indicators for the economy or social equity/quality of life, agencies tend to lack sufficient data sources. Aside from estimates of project costs and benefits, a majority of economic data is obtained from outside agencies like the US Census Bureau, state or local economic development agencies, and private data collection companies. Developing social indicators can require creative use of available data. For example, several variables can be combined into a quality of life index; when considered alone the data may indicate one state but when considered jointly the data may suggest trade-offs that occur. The UK experience (29) suggests that disaggregating traditional transportation statistics by geography or socioeconomic group could be an effective method for analyzing social equity. Experience in the United States in applying Health Impact Assessment (HIA) to transportation projects also supports disaggregation of available data as a means for assessing social impacts (60). Such an analysis requires census data (demographics, geopolitical boundaries) and available transportation and health-related statistics. GIS could also aid in such an analysis.

Data sources for GIS are becoming increasingly necessary for early environmental screenings and for assessment of economic, social, and land use impacts. GIS analysis is recommended as an effective way to examine local impacts during a strategic sustainability assessment and is also a valuable visualization and analytical tool for spatial analysis and scenario planning. In interviews with state DOTs, several mentioned using GIS to help identify environmental impacts (Delaware, Tennessee, Florida) and others expressed a desire to do so but cited the availability of data files as a primary barrier. In order to fully utilize GIS analysis, statewide data sources for transportation infrastructure, land use, and environmental features would be necessary. There are numerous GIS data clearinghouses available online, but not all data sources are free, and some may not provide the detail necessary to conduct corridor or project analyses. Additionally, there may be data gaps in states or counties that do not generate their own GIS files. For specific transportation projects, GIS data can be generated by attaching spatial data to existing data sources like transit station locations or employment centers (essentially mapping either manually or with GPS equipment). Creating GIS datasets is often costly and labor-intensive.

The GeoCommunity Data Catalog and Geospatial One Stop (geodata.gov) are two examples of clearinghouses that offer statewide and county-level data. There are also specific GIS data sources with particular relevance to transportation planning. Examples include:

• US Census Bureau's TIGER/Line files include features like roads, railroads, rivers, lakes, and legal and statistical boundaries;
• Bureau of Transportation Statistic's National Transportation Atlas Database (2008) which provides numerous data files that can be downloaded by US DOT region;
• US Geologic Survey data files;
• Environmental data from EPA; and
• US Department of Agriculture Forest Service Geodata Clearinghouse.

Additional GIS resources are provided on the FHWA website.

The data sources presented above are the most commonly used sets for transportation planning because of the frequency of collection, appropriateness of scale, and convenient format. Additional data sources are available but may not be as useful for transportation planning purposes due to limited scale, less frequent collection, and cost of use (see Table 4-2).

Section III: Applications of Data Sources

This section demonstrates applications of different data sources in various sustainable transportation planning practices and assessment methods identified in the survey and literature. Table 4-3 summarizes various practices, data requirements, sources, and limitations. A similar analysis is provided as part of each case study in Chapter 5. In addition to the publicly available data sources in Tables 4-1 and 4-2, some of the practices require data from private sources, which may not be free or easy to obtain. Also, GIS-based practices depend upon the availability of a comprehensive database, and so may not be easily applied by all state DOTs. Development of GIS databases for the purpose of sustainability assessment requires cooperation among multiple agencies and can be labor-intensive and costly.