Multi-temoporal and spatially explicit population data are vital in many fields, such as demography, urban planning, disaster prevention, economics, and environmental modeling. The population data used in these studies are, however, typically aggregated at census enumeration units, which are too coarse for many applications. Accurate population downscaling methods are needed to obtain population data at finer spatial resolutions. In this study, a novel settlement-related database, Built-Up Property Records (BUPR) from the Historical Settlement Data Compilation for the United States (HISDAC-US), is used to downscale population from census tracts to block groups. The BUPR dataset provides the number of built-up property records for each 250-m grid at 5-year temporal resolution from 1810 to 2015 for most the contiguous United States. The ability of BUPR to downscale population from census tracts to corresponding block groups for four states, representing a range of population densities, is evaluated here by comparing against other commonly-used ancillary datasets. The BUPR-based method outperforms all other methods in all but one state with highly-incomplete BUPR. A more detailed accuracy assessment was also performed by dividing each state into low, medium, and high population density categories. The BUPR method produces more accurate downscaled population estimates for low and medium categories when compared with other datasets, though its performance deteriorates in the high density category due to its relatively coarse spatial resolution. BUPR-based dasymetric mapping was subsequently applied to the contiguous United States and found to generalize well beyond the four comparison states with high levels of downscaling accuracy. The long record of HISDAC-US dataset enables the possibility of constructing fine-temporal-resolution population data back to 1810.