Urban Phenology: Toward a Real-Time Census of the City
Posted: 28 Jun 2016 Last revised: 29 Jun 2016
Date Written: January 1, 2016
Abstract
New streams of data are being generated by a range of in-situ instrumentation, mobile sensing, and social media that can be integrated and analyzed to better understand urban activity and mobility patterns. While several studies have focused on understanding activity patterns and flows of people throughout a city, these data can also be used to create a more spatially and temporally granular picture of local population, and to forecast localized population given some exogenous environmental or physical conditions. Effectively modeling neighborhood population dynamics would have significant implications for city operations and policy, for the engagement and empowerment of residents in neighborhood planning processes, and for the ability to address community quality-of-life concerns.
Our research seeks to develop a real-time census of the city within the context of describing an urban phenology that can serve as a baseline for understanding neighborhood activity patterns. Using WIFI connection data accounting for more than 20,000,000 data points for the year 2015 from New York City’s Lower Manhattan neighborhood - combined with correlative data from the U.S. Census ACS, the LEHD survey, and New York City administrative records - we present a model to create real-time population estimates of residents, workers, and visitors/tourists in a given neighborhood and localized to a block or geolocation. Our results indicate that the approach has merit: we estimate intra-day worker and resident population counts within 5% of survey data. Our building-level test case demonstrates similar accuracy, estimating worker population to within 1% of the reported occupancy.
Keywords: urban studies; human dynamics; population; community; census
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