In this paper, we illustrate how far spatial accuracy of a land-use map governs land-use changes monitoring frequency on a urban sprawl monitoring case study. From a specific Monte Carlo approach propagating uncertainties, conf4idence curves for minimal monitoring frequency to detect significant changes in urban sprawl indicators were built. Results showed that frequency decreased when uspscaling indicators but it also showed very low monitoring frequency for indicators at the lower level. INTRODUCTION When setting up land-use monitoring systems, spatial uncertainties and their impact on the detection of indicator changes are usually ignored. To capture a significant change in land-use indicators is thus strongly related to its spatial resolution, the velocities of the process it represents and the accuracy of the used indicators. As a consequence, the required monitoring land-use change frequency, corresponding to the mimimum time step to ensure a significant change in indicators, also depends on these three factors: indicator spatial resolution, change process velocity and spatial indicator accuracy.