Identifying Borders of Activity Spaces and Quantifying Border Effects on Intra-Urban Travel through Spatial Interaction Network

Abstract

Detecting borders of urban activity spaces is essential for understanding urban dynamic structures. The emerging big geo-data help to extract valuable knowledge about the relationship between urban structures and human activities at fine granularities. Despite the well-developed urban structure and transportation network design technology, barriers attenuating intra-urban travel still exist as borders of urban activity spaces. To understand the effects of activity space borders, this study first delineates the activity space borders and identifies the borders into three categories: natural, infrastructural, and administrative borders. Then, the border effect from three types of borders is evaluated through the spatial interaction model revealing their influence on intra-urban travel connections. On basis of the modeling results, we introduce an indicator, border thickness, to measure the distance increased caused by each border of activity space. This study provides a border effect perspective for investigating the urban activity spaces. We reveal the different border effects for natural, infrastructural, and administrative borders. Further, we locate the thick borders and discuss their relations with the urban structure.

Meihan Jin

Researcher
2021 - present
Postdoc
2018 - 2021

My research interests include Geographical Information Systems, spatial interaction and travel behavior.

Yu Liu

Professor
1997 - present

Professor of GIScience