<p>Spatial flows of people, goods, and information between regions exemplify inter-regional interactions, reflecting both geographical context and spatial distance between origins and destinations. Yet, the spatial patterns underlying such flows remain underexplored. This article introduces two indices designed to measure global and regional spatial patterns from a flow perspective. These indices allow for the assessment of statistical significance in spatial autocorrelation and spatial association of flows. Furthermore, the asymmetry of global autocorrelation is examined through applications to four illustrative datasets. The proposed methods are validated using simulation experiments that establish the distribution of index values and confirm their robustness. Finally, a case study of the U.S. county-level migration flows demonstrates the practical utility of the approach, highlighting how flow-based perspectives on spatial patterns can offer valuable insights for policymakers and planners engaged in regional development.</p>