Spatially explicit modeling plays a vital role in land use/cover change and urbanization research as well as resources management;however,current models lack proper validation and fail to incorporate uncertainty into the formulation of model predictions.Consequently,policy makers and the general public may develop opinions based on potentially misleading research,which fails to allow for truly informed decisions.Here we use an uncertainty strategy of spatially explicit modeling combined with the series statistic of Kappa index for location and quantity to estimate the uncertainty of future predications and to determine model accuracy.We take the Beijing metropolitan area as an example to demonstrate the uncertainty in extrapolations of predictive land use change and urban sprawl with spatially explicit modeling at multiple resolutions.The sensitivity of scale effects is also discussed.The results show that an improvement in specification of location is more helpful in increasing accuracy as compared to an improvement in the specification of quantity at fine spatial resolutions.However,the spatial scale has great effects on modeling accuracy and correct due to chance tends to increase as resolution becomes coarser.The results allow us to understand the uncertainty when using spatially explicit models for land-use change or urbanization estimates. Spatially explicit modeling plays a vital role in land use / cover change and urbanization research as well as resources management; however, current models lack proper validation and fail to incorporate uncertainty into the formulation of model predictions. Policy, policy makers and the general public may able opinions based on potentially misleading research, which fails to allow for truly informed decisions. Here we use an uncertainty strategy of spatially explicit modeling combined with the series statistic of Kappa index for location and quantity to estimate the uncertainty of future predications and determine formula accuracy.We take the Beijing metropolitan area as an example to demonstrate the uncertainty in extrapolations of predictive land use change and urban sprawl with spatially explicit modeling at multiple resolutions. The sensitivity of scale effects is also discussed.The results show that an improvement in specification of location is more helpful in increasing accura cy as compared to an improvement in the specification of quantity at fine spatial resolutions.However, the spatial scale has great effects on modeling accuracy and correct due to chance tends to increase as resolution became coarser.The results allow us to understand the uncertainty when using spatially explicit models for land-use change or urbanization estimates.