Appraisal of microvascular erythrocyte velocity as well as aggregation are critical features of hemorheological assessment. Examination of erythrocyte velocity-aggregate characteristics is critical in assessing disorders associated with coagulopathy. Microvascular erythrocyte velocity can be assessed using various methodologic approaches; however, the shared assessment of erythrocyte velocity and aggregation has not been well described. The purpose of this study therefore is to examine three independent erythrocyte assessment strategies with and without experimentally induced aggregation in order to elucidate appropriate analytic strategy for combined velocity/aggregation assessment applicable to in-vivo capillaroscopy. We employed a hierarchical microfluidic model combined with Bland-Altman analysis to examine agreement between three methodologies to assess erythrocyte velocity appropriate for interpretation of cinematography of in-vivo microvascular hemorheology. We utilized optical and manual techniques as well as a technique which we term transversal temporal cross-correlation (TTC) to observe and measure both erythrocyte velocity and aggregation. In general, optical, manual and TTC agree in estimation of velocity at relatively low flow rate, however with an increase in infusion rate the optical flow method yielded the velocity estimates that were lower than the TTC and manual velocity estimates. We suggest that this difference was due to the fact that slower moving particles close to the channel wall were better illuminated than faster particles deeper in the channel which affected the optical flow analysis. Combined velocity/aggregation appraisal using TTC provides an efficient approach for estimating erythrocyte aggregation appropriate for in-vivo applications. We demonstrated that the optical flow and TTC analyses can be used to estimate erythrocyte velocity and aggregation both in ex-vivo microfluidics laboratory experiments as well as in-vivo recordings. The simplicity of TTC method may be advantageous for developing velocity estimate methods to be used in the clinic. The trade-off is that TTC estimation cannot capture features of the flow based on optical flow analysis of individually tracked particles.