Meta-analysis was used to investigate the relationship between visuo-spatial ability and performance in remote environments. In order to be included, each study needed to examine the relationship between the use of an ego-centric perspective and various dimensions of performance (i.e., identification, localization, navigation, and mission completion time). The moderator analysis investigated relationships involving: (a) visuo-spatial construct with an emphasis on Carroll’s (1993) visualization (VZ) factor; (b) performance outcome (i.e., identification, localization, navigation, and mission completion time); (c) autonomy to support mission performance; (d) task type (i.e., navigation vs. reconnaissance); and (e) experimental testbed (i.e., physical vs. virtual environments). The process of searching and screening for published and unpublished analyses identified 81 works of interest that were found to represent 50 unique datasets. 518 effects were extracted from these datasets for analyses. Analyses of aggregated effects (Hunter & Schmidt, 2004) found that visuo-spatial abilities were significantly associated with each construct, such that effect sizes ranged from weak (r = .235) to moderately strong (r = .371). For meta-regression (Borenstein, Hedges, Figgins, & Rothstein, 2009; Kalaian & Raudenbush, 1996; Tabachnick & Fidell, 2007), moderation by visuo-spatial construct (i.e., focusing on visualization) was consistently supported for all outcomes. For at least one of the outcomes, support was found for moderation by test, the reliability coefficient of a test, autonomy (i.e. to support identification, localization, and navigation), testbed (i.e., physical vs. virtual environment), intended domain of application, and gender. These findings illustrate that majority of what researchers refer to as “spatial ability” actually uses measures that load onto Carroll’s (1993) visualization (VZ) factor. The associations between this predictor and all performance outcomes were significant, but the significant iv variation across moderators highlight important issues for the design of unmanned systems and the external validity of findings across domains. For example, higher levels of autonomy for supporting navigation decreased the association between visualization (VZ) and performance. In contrast, higher levels of autonomy for supporting identification and localization increased the association between visualization (VZ) and performance. Furthermore, moderation by testbed, intended domain of application, and gender challenged the degree to which findings can be expected to generalize across domains and sets of participants.