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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Related Experiment Video

Updated: Sep 17, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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A visitor-enriched census in the U.S. cities using large-scale mobile positioning data.

Meicheng Xiong1, Di Zhu2,3, David Van Riper4

  • 1Department of Geography, Environment and Society, University of Minnesota, Twin Cities, Minneapolis, USA.

Scientific Data
|July 2, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a "visitor census" using mobile data to enrich traditional census information. It incorporates human movement patterns to provide a more dynamic understanding of socio-demographics.

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Area of Science:

  • Socio-demographics
  • Human Mobility
  • Data Science

Background:

  • Traditional census data offers valuable socio-demographic insights but often treats units as static.
  • Existing data products overlook the interactions and mobilities of individuals within census units.

Purpose of the Study:

  • To introduce a novel
  • visitor census
  • dataset by integrating human visitations from mobile positioning data.
  • To enrich traditional census data with dynamic socio-demographic information based on observed mobilities.
  • To bridge the gap between aggregated census data and individual-level analysis using digital traces.

Main Methods:

  • Identification and validation of potential home locations for 3.58 million anonymous mobile phone users across seven U.S. metropolitan areas in July 2021.
  • Enrichment of visited place socio-demographic profiles using home detection results from mobile positioning data.
  • Development of an adaptive data generation framework for integrating diverse socio-demographic features at multiple scales.

Main Results:

  • A semantically enriched
  • visitor census
  • dataset incorporating human visitations and spatial interactions.
  • Demonstration of enriching place-based socio-demographic profiles with mobility data.
  • Validation of a framework for integrating conventional census and mobile phone data.

Conclusions:

  • The
  • visitor census
  • enhances traditional resident-based census knowledge by incorporating mobilities and spatial interactions from digital traces.
  • This approach bridges the gap between aggregated and individual analysis.
  • The framework supports future integration of diverse socio-demographic features at varying spatial and temporal scales.