Paper Info
Title
Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows
Abstract
Since before the inception of work by Okabe, the intermingling of spatial autocorrelation (i.e., local distance and configuration) and distance decay (i.e., global distance) effects has been suspected in spatial interaction data. This convolution was first treated conceptually because technology and methodology did not exist at the time to easily or fully address spatial autocorrelation effects within spatial interaction model specifications. Today, however, sufficient computer power coupled with eigenfunction-based spatial filtering offers a means for accommodating spatial autocorrelation effects within a spatial interaction model for modest-sized problems. In keeping with Okabe’s more recent efforts to dissemination spatial analysis tools, this paper summarizes how to implement the methodology utilized to analyze a particular empirical flows dataset.
Year
DOI
Venue
2009
10.1007/s10109-009-0082-z
Journal of Geographical Systems
Keywords
Field
DocType
distance decaygravity modelspatial autocorrelation � spatial filterspatial interaction,distance decay,empirical evidence,gravity model,spatial filter,spatial autocorrelation,spatial analysis,spatial filtering
Spatial analysis,Distance decay,Convolution,Filter (signal processing),Gravity model of trade,Statistics,Journey to work,Geography,Autocorrelation,Spatial filter
Journal
Volume
Issue
ISSN
11
2
1435-5949
Citations 
PageRank 
References 
6
1.46
2
Authors
1
Name
Order
Citations
PageRank
Daniel A. Griffith19123.76