For many earthquake engineering applications, site response is estimated through empirical correlations with the time-averaged shear-wave velocity to 30 m depth (V S30 ). These applications therefore depend on the availability of either sitespecific V S30 measurements or V S30 maps at local, regional, and global scales. Because V S30 measurements are sparse, a proxy frequently is needed to estimate V S30 at unsampled locations. We present a new V S30 map for California, which accounts for observational constraints from multiple sources and spatial scales, such as geology, topography, and site-specific V S30 measurements. We apply the geostatistical approach of regression kriging (RK) to combine these constraints for predicting V S30 . For the V S30 trend, we start with geology-based V S30 values and identify two distinct trends between topographic gradient and the residuals from the geology V S30 model. One trend applies to deep and fine Quaternary alluvium, whereas the second trend is slightly stronger and applies to Pleistocene sedimentary units. The RK framework ensures that the resulting map of California is locally refined to reflect the rapidly expanding database of V S30 measurements throughout California. We compare the accuracy of the new mapping method to a previously developed map of V S30 for California. We also illustrate the sensitivity of ground motions to the new V S30 map by comparing real and scenario ShakeMaps with V S30 values from our new map to those for existing V S30 maps.