Urban phenology: Toward a real-time census of the city using Wi-Fi data

Constantine E. Kontokosta, Nicholas Johnson

Research output: Contribution to journalArticle

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 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 population dynamics at high spatial and temporal resolutions would have significant implications for city operations and policy, strategic long-term planning processes, emergency response and management, and public health. This paper develops a real-time census of the city using Wi-Fi data to explore urban phenology as a function of localized population dynamics. Using Wi-Fi probe and 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 America Community Survey, the Longitudinal Employer-Household Dynamics survey, and New York City administrative records – we present a model to create real-time population estimates classified by residents, workers, and visitors/tourists in a given neighborhood and localized to a block or geolocation proximate to a Wi-Fi access point. The results indicate that the approach has merit: we estimate intra-day, hourly worker and resident population counts within 5% of survey validation data. Our building-level test case demonstrates similar accuracy, estimating worker population to within 1% of the reported building occupancy.

Original languageEnglish (US)
Pages (from-to)144-153
Number of pages10
JournalComputers, Environment and Urban Systems
Volume64
DOIs
StatePublished - Jul 1 2017

Fingerprint

phenology
census
population development
worker
population dynamics
resident population
local population
city
time
social media
planning process
instrumentation
public health
tourist
employer
probe
environmental conditions
resident
management
modeling

Keywords

  • Census
  • Community
  • Human dynamics
  • Population
  • Urban studies
  • Wi-Fi

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Ecological Modeling
  • Environmental Science(all)
  • Urban Studies

Cite this

Urban phenology : Toward a real-time census of the city using Wi-Fi data. / Kontokosta, Constantine E.; Johnson, Nicholas.

In: Computers, Environment and Urban Systems, Vol. 64, 01.07.2017, p. 144-153.

Research output: Contribution to journalArticle

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