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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Spatial and Temporal Characterization of Activity in Public Space, 2019-2020.

Christa Brelsford1, Jessica Moehl2, Eric Weber2

  • 1Geospatial Science and Human Security Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA. brelsfordcm@ornl.gov.

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This study analyzed short (<4 hours) versus long (>4 hours) visits to public places in the US from 2019-2020. The ratio of short-to-long visits can estimate non-worker public space usage and reveal activity pattern changes.

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Area of Science:

  • Geospatial analysis
  • Urban studies
  • Public health

Background:

  • Understanding public space usage is crucial for urban planning and public health.
  • Differentiating between obligatory (work) and non-obligatory (leisure, shopping) activities in public spaces is challenging.
  • Existing data often lacks granular detail on visit duration and purpose.

Purpose of the Study:

  • To characterize the spatial and temporal variation in the ratio of short-to-long duration visits to public places in the US.
  • To develop a metric (short-to-long visit ratio) for estimating non-worker use of public space.
  • To provide insights into public space activity patterns, particularly during the COVID-19 pandemic.

Main Methods:

  • Utilized anonymized and aggregated foot traffic data from SafeGraph, a geospatial data provider.
  • Estimated the number and duration of short (<4 hours) and long (>4 hours) visits at the US census block group level.
  • Calculated a ratio of short-to-long visits to represent non-worker activities.

Main Results:

  • Data characterizes weekly spatial and temporal variations in short-to-long visit ratios across the US from January 2019 to December 2020.
  • Long visits (>4 hours) serve as a reliable proxy for workers, validated against economic data.
  • Short visits (<4 hours) are indicative of non-obligatory activities such as leisure, shopping, and civic engagement.

Conclusions:

  • The short-to-long visit ratio offers a novel approach to estimate non-worker engagement with public spaces.
  • These findings provide valuable data for understanding shifts in public space utilization during the COVID-19 pandemic.
  • The study contributes to a broader understanding of human activity patterns in urban environments.