Classification of spatio-temporal trajectories from Volunteer Geographic Information through fuzzy rules

Abstract

Volunteer Geographic Information (VGI) is one of the key enablers of the mobility mining discipline. This work introduces a novel data-driven methodology to create a classifier of spatio-temporal trajectories based on VGI. Although other solutions have been proposed, they usually do not fully consider the low resolution and uncertainty of VGI due to its inherent human nature. The proposed approach introduces a classifier based on fuzzy rules that are able to deal with this kind of data. The solution is applied in a use case for real-time detection of tourists and local citizens’ flows and it is compared with a well-established trajectory classifier exhibiting quite promising results.