Logo image
Quantifying Distance Overestimation From Global Positioning System in Urban Spaces
Journal article   Open access   Peer reviewed

Quantifying Distance Overestimation From Global Positioning System in Urban Spaces

Stephen J Mooney, Daniel M Sheehan, Garazi Zulaika, Andrew G Rundle, Kevin McGill, Melika R Behrooz and Gina Schellenbaum Lovasi
American journal of public health (1971), v 106(4), pp 651-653
Apr 2016
PMID: 26890178
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4815998View
Accepted (AM)Open Access (License Unspecified) Open

Abstract

Dimensional Measurement Accuracy Environment Geographic Information Systems - instrumentation Humans New York City Travel Urban Population Walking
To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City. 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. 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). 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.

Metrics

16 Record Views
21 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Public, Environmental & Occupational Health
Logo image