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Quantifying distance overestimation from global positioning system in urban spaces

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  • Mooney, S.J.
  • Sheehan, D.M.
  • Zulaika, G.
  • Rundle, A.G.
  • McGill, K.
  • Behrooz, M.R.
  • Lovasi, G.S.

Abstract

Objectives. To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City. Methods. We performed structured walks along urban streets carrying Globalsat DG-100 GPS Data Logger devices in highest and lowest quartiles of building height and tree canopy cover. We used ArcGIS version 10.1 to select walks and compute the straight-line distance (Geographic Information System-measured) and sum of distances between consecutive GPS waypoints (GPS-measured) for each walk. Results. GPS distance overestimates were associated with building height (median overestimate = 97% for high vs 14% for low building height) and to a lesser extent tree canopy (43% for high vs 28% for low tree canopy). Conclusions. Algorithms using distances between successive GPS points to infer speed or travel mode may misclassify trips differentially by context. Researchers studying urban spaces may prefer alternative mode identification techniques.

Suggested Citation

  • Mooney, S.J. & Sheehan, D.M. & Zulaika, G. & Rundle, A.G. & McGill, K. & Behrooz, M.R. & Lovasi, G.S., 2016. "Quantifying distance overestimation from global positioning system in urban spaces," American Journal of Public Health, American Public Health Association, vol. 106(4), pages 651-653.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2015.303036_3
    DOI: 10.2105/AJPH.2015.303036
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    Cited by:

    1. Mooney, Stephen J. & Hosford, Kate & Howe, Bill & Yan, An & Winters, Meghan & Bassok, Alon & Hirsch, Jana A., 2019. "Freedom from the station: Spatial equity in access to dockless bike share," Journal of Transport Geography, Elsevier, vol. 74(C), pages 91-96.
    2. Jason Y. Scully & Anne Vernez Moudon & Philip M. Hurvitz & Anju Aggarwal & Adam Drewnowski, 2019. "A Time-Based Objective Measure of Exposure to the Food Environment," IJERPH, MDPI, vol. 16(7), pages 1-14, April.
    3. Yang, Wei & Hu, Jie & Liu, Yong & Guo, Wenbo, 2023. "Examining the influence of neighborhood and street-level built environment on fitness jogging in Chengdu, China: A massive GPS trajectory data analysis," Journal of Transport Geography, Elsevier, vol. 108(C).

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