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Addressing location uncertainties in GPS‐based activity monitoring: A methodological framework
Author(s) -
Wan Neng,
Lin Kan Ge,
Wilson Gaines
Publication year - 2017
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/tgis.12231
Subject(s) - global positioning system , computer science , context (archaeology) , data mining , variety (cybernetics) , location data , data science , scale (ratio) , geography , real time computing , artificial intelligence , cartography , telecommunications , archaeology
Abstract Location uncertainty has been a major barrier in information mining from location data. Although the development of electronic and telecommunication equipment has led to an increased amount and refined resolution of data about individuals’ spatio‐temporal trajectories, the potential of such data, especially in the context of environmental health studies, has not been fully realized due to the lack of methodology that addresses location uncertainties. This article describes a methodological framework for deriving information about people's continuous activities from individual‐collected Global Positioning System (GPS) data, which is vital for a variety of environmental health studies. This framework is composed of two major methods that address critical issues at different stages of GPS data processing: (1) a fuzzy classification method for distinguishing activity patterns; and (2) a scale‐adaptive method for refining activity locations and outdoor/indoor environments. Evaluation of this framework based on smartphone‐collected GPS data indicates that it is robust to location errors and is able to generate useful information about individuals’ life trajectories.