Measuring Spatial Autocorrelation of Vectors

This article introduces measures to quantify spatial autocorrelation for vectors. In contrast to scalar variables, spatial autocorrelation for vectors involves an assessment of both direction and magnitude in space. Extending conventional approaches, measures of global and local spatial associations for vectors are proposed, and the associated statistical properties and significance testing are discussed. The new measures are applied to study the spatial association of taxi movements in the city of Shanghai. Complications due to the edge effect are also examined.Natural Science Foundation of China [41271386, 41428102]; Open Foundation of Shenzhen Key Laboratory of Urban Planning and Decision Making [UPDMHITSZ2014A01]; State Key Laboratory of Resources and Environmental Information SystemSSCIARTICLEliuyu@urban.pku.edu.cn3300-3194