PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Modeling Micro-Movement Variability in Mobility Studies
Dirk Hecker, Christine Körner, Hendrik Stange, Daniel Schulz and Michael May
In: Advancing Geoinformation Science for a Changing World Lecture Notes in Geoinformation and Cartography , 1 . (2011) Springer , Berlin Heidelberg , pp. 121-140. ISBN 978-3-642-19789-5


During the past years the interest in the exploitation of mobility infor-mation has increased significantly. Along with these interests, new de-mands on mobility data sets have been posed. One particular demand is the evaluation of movement data on a high level of spatial detail. The high dimensionality of geographic space, however, makes this requirement hard to fulfill. Even large mobility studies cannot guarantee to comprise all movement variation on a high level of detail. In this paper we present an approach to increase the variability of movement data on microscopic scale in order to achieve a better representation of population movement. Our approach consists of two steps. First, we perform a spatial aggregation of trajectory data in order to counteract sparseness and to preserve movement on macroscopic scale. Second, we disaggregate the data in geographic space based on traffic distribution knowledge using repeated simulation. Our approach is applied in a real-world business application for the Ger-man outdoor advertising industry to measure the performance of poster sites.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:9056
Deposited By:Christine Körner
Deposited On:21 February 2012