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Spatial correlations of ground-motion intensity measures (IMs) are essential for seismic analysis of spatially distributed systems. In this paper, geostatistical analysis is conducted to calculate the spatial correlations for cumulative absolute velocity (CAV), Arias intensity (Ia), and spectral accelerations (SA) using a total number of more than 1500 earthquake records from nine recent earthquakes occurred in Taiwan, California, and Japan. The results indicate that the spatial correlations for these IMs are closely related to the regional site conditions, and they can be predicted based on the spatial correlations of shear-wave velocity in the top 30 m (V S30). In general, an IM recorded from a relatively homogeneous regional site condition tends to have a larger spatial correlation range than that from a heterogeneous site condition. Due to their intrinsic similarity to represent the integration of acceleration time histories, CAV and Ia have similar spatial correlation coefficients. Besides, the range of spatial correlation of SA generally increases as the spectral period increases. Simple predictive equations are proposed in this study to quantify the spatial correlations of CAV, Ia, and SA based on regional site conditions. Methods for data correction are also proposed to eliminate artificial correlations due to biased distance scaling and V S30 estimation in the database. Finally, Monte Carlo method is used to generate spatially distributed IMs. The results demonstrate that the annual frequency of exceedance curves for spatially distributed IMs differ significantly if different ranges of spatial correlations are used.