Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Using crowdsourced fitness tracker data to model the relationship between slope and travel rates

    Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Michael J. Campbell; Philip E. Dennison; Bret W. Butler; Wesley G. Page
    Date: 2019
    Source: Applied Geography. 106: 93-107.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    DOI: https://doi.org/10.1016/j.apgeog.2019.03.008
    PDF: Download Publication  (2.0 MB)

    Description

    One of the critical factors affecting travel rates while hiking, jogging, or running along a trail is the slope of the underlying terrain. Models for predicting this effect have been used in a wide variety of scientific and applied contexts, including recreation planning, search and rescue, wildland firefighter safety, social network analysis, and recreating historical human movement patterns. Despite their wide use, these models are based on datasets with very small sample sizes that were collected without using instantaneous measures of travel rate and assume symmetrical effects about the slope of maximum travel rate. These models also typically resulted in a single mathematical function, ignoring the significant variability that can occur between a fast and a slow individual, or between walking and running travel rates. In this study we modeled travel rates using a database of GPS tracks from 29,928 individuals representing 421,247 individual hikes, jogs, and runs on trails in and around Salt Lake City, Utah for an entire year between July 1, 2016 and June 30, 2017. Three widely-used probability distribution functions (Laplace, Gauss, and Lorentz) were used to predict travel rates based on terrain slope along segments of trails with uniform slopes. To account for the variability in travel rates between fast and slow movement, a series of travel rate models were generated to predict travel rate percentiles, ranging from the 1st to the 99th, thus providing a flexible basis for predicting travel rates as a function of slope. The large number of samples allowed us to introduce a novel term that accounts for asymmetry in travel rates on uphill and downhill slopes.

    Publication Notes

    • You may send email to rmrspubrequest@fs.fed.us to request a hard copy of this publication.
    • (Please specify exactly which publication you are requesting and your mailing address.)
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Campbell, Michael J.; Dennison, Philip E.; Butler, Bret W.; Page, Wesley G. 2019. Using crowdsourced fitness tracker data to model the relationship between slope and travel rates. Applied Geography. 106: 93-107.

    Cited

    Google Scholar

    Keywords

    fitness tracker, GPS data, travel rate, hiking, running, slope, least cost path

    Related Search

    XML: View XML
Show More
Show Fewer
Jump to Top of Page
https://www.fs.usda.gov/treesearch/pubs/58950