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Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA

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  • Nathaniel H Merrill
  • Sarina F Atkinson
  • Kate K Mulvaney
  • Marisa J Mazzotta
  • Justin Bousquin

Abstract

We introduce and validate the use of commercially available human mobility datasets based on cell phone locations to estimate visitation to natural areas. By combining this data with on-the-ground observations of visitation to water recreation areas in New England, we fit a model to estimate daily visitation for four months to more than 500 sites. The results show the potential for this new big data source of human mobility to overcome limitations in traditional methods of estimating visitation and to provide consistent information at policy-relevant scales. However, the data providers’ opaque and rapidly developing methods for processing locational information required a calibration and validation against data collected by traditional means to confidently reproduce the desired estimates of visitation. We found that with this calibration, the high-resolution information in both space and time provided by cell phone location-derived data creates opportunities for developing next-generation models of human interactions with the natural environment.

Suggested Citation

  • Nathaniel H Merrill & Sarina F Atkinson & Kate K Mulvaney & Marisa J Mazzotta & Justin Bousquin, 2020. "Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-19, April.
    • Handle: RePEc:plo:pone00:0231863
    DOI: 10.1371/journal.pone.0231863
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    1. Van Berkel, Derek B. & Tabrizian, Payam & Dorning, Monica A. & Smart, Lindsey & Newcomb, Doug & Mehaffey, Megan & Neale, Anne & Meentemeyer, Ross K., 2018. "Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR," Ecosystem Services, Elsevier, vol. 31(PC), pages 326-335.
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