6533b85efe1ef96bd12c0943

RESEARCH PRODUCT

A pre-processing and network analysis of GPS tracking data

Stefano De CantisAntonino AbbruzzoMauro Ferrante

subject

Focus (computing)Computer sciencebusiness.industry05 social sciencesGeography Planning and DevelopmentReal-time computing0211 other engineering and technologies021107 urban & regional planning02 engineering and technologyUnit (housing)ComputerSystemsOrganization_MISCELLANEOUS0502 economics and businessEarth and Planetary Sciences (miscellaneous)Global Positioning Systemcluster-based method global positioning systems network analysis spatio-temporal dataTracking dataSettore SECS-S/05 - Statistica Sociale050207 economicsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticabusinessGeneral Economics Econometrics and FinanceNetwork analysis

description

Global Positioning System (GPS) devices afford the opportunity to collect accurate data on unit movements from temporal and spatial perspectives. With a special focus on GPS technology in travel surveys, this paper proposes: (1) two algorithms for the pre-processing of GPS data in order to deal with outlier identification and missing data imputation; (2) a clustering approach to recover the main points of interest from GPS trajectories; and (3) a weighted-directed network, which incorporates the most relevant characteristics of the GPS trajectories at an aggregate level. A simulation study shows the goodness-of-fit of the imputation data algorithm and the robustness of the clustering algorithm. The proposed algorithms are then applied to three cases studies relating to the mobility of cruise passengers in urban contexts.

yearjournalcountryeditionlanguage
2020-07-03Spatial Economic Analysis
https://doi.org/10.1080/17421772.2020.1769170