Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows

被引:41
作者
Griffith, Daniel A. [1 ]
机构
[1] Univ Texas Dallas, Sch Econ Polit & Policy Sci, Richardson, TX 75080 USA
关键词
Distance decay; Gravity model; Spatial autocorrelation; Spatial filter; Spatial interaction; OPPORTUNITY;
D O I
10.1007/s10109-009-0082-z
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
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.
引用
收藏
页码:117 / 140
页数:24
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