Context In metapopulations, colonisation is the result of dispersal from neighbouring occupied patches, typically juveniles dispersing from natal to breeding sites. When occupancy dynamics are dispersal driven, occupancy should refer to the presence of established, breeding populations. The detection of transient individuals at sites that are, by definition, unoccupied (i.e. false positive detections), may result in misleading conclusions about metapopulation dynamics. Until recently, the issue of false positives has been considered negligible and current efforts to account for such error have been restricted to the context of species misidentification. However, the detection of transient individuals visiting multiple sites while dispersing is a distinct source of false positives that can bias estimates of occupancy because visited sites do not contribute to metapopulation dynamics in the same way as do sites occupied by established, reproducing populations. Although transient-induced false positive error presents a challenge to occupancy studies aiming to account for all sources of detection error and estimate occupancy without bias, accounting for it has received little attention. Aims Using a novel application of an existing occupancy model, we sought to account for false positives that result from transient individuals being observed at truly unoccupied sites (i.e. where no establishment has occurred). Methods We applied a Bayesian multi-season occupancy model correcting for false negative and false positive errors, to 3 years of detection or non-detection data from a metapopulation of water voles, Arvicola amphibious, in which both types of patch-state misclassification are suspected. Key results We provide evidence that transient individuals can cause false positive detection errors. We then demonstrate the flexibility of the occupancy model to account for both false negative and false positive detection errors beyond the typical application to species misidentification. Accounting for both types of observation error reduces the bias in estimates of occupancy and avoids misleading conclusions about the status of (meta) populations by allowing for the distinction to be made between resident and transient occupancy. Conclusion In many species, transience may result in patch-state misclassification which needs to be accounted for so as to draw correct inference about metapopulation status. Making the distinction between occupancy by established populations and visitation by transients will influence how we interpret patch occupancy dynamics, with important implications for the management of wildlife. Implications The ability to estimate occupancy free of bias induced by false positive detections can help ensure that downward trends in occupancy are detected despite such declines being accompanied by increasing frequency of transients associated with, for example, reductions in mate availability or failure to establish. Our approach can be applied to any occupancy study in which false positive detections are suspected because of the behaviour of the focal species.