Modeling spatial autocorrelation in spatial interactiondata: empirical evidence from 2002 Germanyjourney-to-work flows

摘要

Since before the inception of work by Okabe, the intermingling ofspatial autocorrelation (i.e., local distance and configuration) and distance decay(i.e., global distance) effects has been suspected in spatial interaction data. Thisconvolution was first treated conceptually because technology and methodology didnot exist at the time to easily or fully address spatial autocorrelation effects withinspatial interaction model specifications. Today, however, sufficient computer powercoupled with eigenfunction-based spatial filtering offers a means for accommo-dating spatial autocorrelation effects within a spatial interaction model for modest-sized problems. In keeping with Okabe' s more recent efforts to disseminationspatial analysis tools, this paper summarizes how to implement the methodologyutilized to analyze a particular empirical flows dataset.