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Spatial Data Integration for Low-Income Worker Accessibility Assessment: A Case Study of the Chicago Metropolitan Area

The transformation of numerous and often disparate data sources into knowledge that supports critical decisions in a timely manner is essential in today's fast-growing market and digital government. Data integration is being increasingly recognized in the transportation sector as a valuable asset-forming activity aiding decision-making. This paper will describe a spatial data integration application for a specific policy area: lowincome worker accessibility in urban areas. This policy context is that entry-level job growth, which is appropriate for the skill level of welfare clients and low-income individuals, is mostly occurring far away from inner city neighborhoods or isolated pockets in the suburbs, where bulk of low-income and economically deprived families live. Many job-rich areas do not have affordable housing, including affordable rental housing, or there are implicit barriers to fair housing. Transit connections between job rich areas and where the bulk of the low-income and welfare recipients live (inner city neighborhood and isolated pockets in the suburbs) are limited and in some cases, non-existent. Vehicle ownership rates among such individuals are also very low. Most individuals in this category also do not have driver's licenses. Many entry-level jobs start at off-peak times. Job locations that are accessible during normal business hours are inaccessible during off-peak hours, since most transit services served peak hour transit markets. There are three strategies of overcoming the spatial mismatch between jobs and home locations: (1) bring jobs closer to low-income neighborhoods (2) bring affordable housing solutions near employment generating areas and (3) provide transportation connections between jobs and housing. For effective and holistic solutions to the low-income worker accessibility solution, a database integrating information supporting all three strategies above is fundamental, in order to identify sub-markets that are likely to benefit most from a particular strategy. To facilitate the planning and development of effective cross-sectoral strategies, a Geographic Information System that ties together data from the transportation, affordable housing and economic development sectors is currently under development. This paper will describe the architecture of this GIS and the data components of the system. A survey of urban geospatial data managers in relevant sectors in the Chicago area will drive the data requirements of the integrated system. Further, data quality issues of the integrated geospatial data will be described, focusing on coverage/scope, consistency, completeness, accuracy, timeliness and accessibility. Since this GIS is an integration of existing geospatial data, the scope of conflation tools and the impact of spatial aggregations in the disparate input databases will be documented. Since data specialists from the different sectors "speak different languages", the development of effective metadata is Proceedings of the 2003 Mid-Continent Transportation Research Symposium, Ames, Iowa, August 2003. © 2003 by Iowa State University. The contents of this paper reflect the views of the author(s), who are responsible for the facts and accuracy of the information presented herein.