Exploring the impact of dasymetric refinement on spatiotemporal small area estimates

摘要: Comparing demographic small area estimates across multiple time periods is hindered by boundary changes in census enumeration units. Areal interpolation can resolve temporal incompatibilities, but underlying assumptions of uniform population density within units sometimes flawed and results distorted estimates. Dasymetric modeling refines spatial precision limiting areal to the most likely residential areas. Here, a systematic examination impacts dasymetric refinement on accuracy compares errors that emerge as consequence differing spans. This paper three commonly utilized methods for analysis data over 1990–2010 decades. It examines whether multi-temporal prior improves estimates, comparing two different contexts. Data sets include tract-level demography exhibiting dramatic growth (L...