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In the urban transportation field, planners and engineers have explored the relationship between urban destinations and travel behavior for more than half a century. However, we still have only a preliminary understanding about how the spatial arrangement of different types of urban activity destinations influence human travel, and how urban development policies influence travel patterns. Recent developments in urban sensing and cell phone technologies have enabled spatially-detailed and massive GIS-based datasets on land use, points of interest (POIs), cell phone and GPS-based tracking, etc. These new datasets provide rich possibilities for better understanding and modeling of urban activity patterns and travel behavior. In this study, we utilize such spatially-detailed data—POI data and large-scale travel tracker data—to explore the link between urban activity destinations and human travel patterns. First, we employ the timely and large-scale urban activity-based travel survey for the Chicago Metropolitan Area, implemented from January 2007 to February 2008 (Chicago Metropolitan Agency for Planning 2008). We derive travel patterns for both commute and non-commute activities in the Chicago Metropolitan Area for individuals and groups of individuals with various socioeconomic characteristics. The Chicago activity-based travel survey includes 10,552 households (23,452 individuals) who participated in either a one-day or two-day survey, providing detailed travel information for each household member for a particular assigned travel day(s). Second, we combine a spatially-detailed business establishment dataset (the InfoUSA 2008 …