Paper Info
Title
Estimating Incoming Cross-border Trips Through Land Use data Resources - A Case of Karachi City.
Abstract
A multitude of studies have been motivated on the association between land use, urban settings and transport infrastructure to assist policy makers in sustainable planning. Alike, incorporation of cross-border trips have been an integral part of transportation demand models through external surveys. The present study seeks to explore the Incoming Cross Border Traffic (ICBT) into a study area based on the characteristics of a study area that attracts cross-border trips from outside region. This paper presents an analysis of cross-border trips in Karachi Metropolis, largest city of Pakistan, through Household Individual Survey (HIS-2010) and land use data from alternative resources. Results reveal that land use particulars, socioeconomic characteristics and travel attributes of individuals significantly influences cross-border trips and this effect varies spatially. Work, shopping and Education trips are discussed through separate models in this paper with a number of practical insights to policy makers for sustainable development of city. This study contribute in elucidating travel behaviour through land use parameters and also persuade professionals to integrate estimation of cross-border trips by socioeconomic parameters, in transport forecasting models.
Year
DOI
Venue
2016
10.1016/j.procs.2016.04.125
Procedia Computer Science
Keywords
Field
DocType
Cross-border trips,study area,land use parameters,travel demand models,Open source data,Geographically Weighted Regression (GWR)
Travel behavior,Multitude,Computer science,Data resources,Environmental planning,Artificial intelligence,Sustainable development,TRIPS architecture,Transport infrastructure,Machine learning,Socioeconomic status,Land use
Conference
Volume
ISSN
Citations 
83
1877-0509
0
PageRank 
References 
Authors
0.34
1
7
Name
Order
Citations
PageRank
Syed Fazal Abbas Baqueri111.11
Won Do Lee201.01
Luk Knapen38622.42
Tom Bellemans47323.16
Davy Janssens523838.08
Ansar-Ul-Haque Yasar611842.31
Geert Wets776667.59