Neighborhood audit methods (AKA Systematic Social Observation) are often used to create measures of neighborhood built and social environments. But even with the enhanced efficiency of virtual neighborhood audit methods using CANVAS-Street View, it is generally not possible to collect data from every block in a City. Thus, spatial interpretation methods, such as kriging, are often used to estimate neighborhood conditions at locations not visited by the audit team. Ordinary kriging uses the data collected at visited locations (blocks or intersections), and the spatial correlation between the data elements, to estimate conditions at all other locations in a neighborhood or City. In recently published work we investigated whether Universal Kriging could be used to create improved estimates of neighborhood physical disorder across entire cities. Universal kriging builds upon Ordinary Kriging by using additional external data, such as Census data, in the interpolation/estimation process. We find that using additional data on housing vacancy, along with the observed physical disorder metrics, in a Universal Kriging model could improve model fit and estimation of physical disorder across a city. In addition, Universal Kriging could create equivalently accurate estimates of physical disorder, but require the collection of disorder measures from fewer locations across a city.