Population density surveys based on expansive boundaries may lead the reader to the wrong conclusion. For example, a population density map of nations does not reflect the very dense nature of a nation's cities and sparse composition of its rural areas.
Population density studies may not reflect the surrounding topography. A density study comparing a large desert region to a region with normal topography could lead a reader to the wrong conclusion. The study may not demonstrate that the desert region's inhabitable area contains just a few square miles. The dense population statistics of the inhabitable area are camouflaged by the sparsely populated surrounding desert. A reader may incorrectly conclude that the first region's inhabitants live in a less-densely populated area.
A population density study's boundaries are based on subjective decision-making by those tasked with creating the study's specific geographic features. A population density survey of the United States broken down by census tract would in large part reflect a true local-level breakdown of population density. However, even these types of local-level density studies could appear distorted if the boundary bridges a rural-urban divide. For instance, in the book "E.E. Slutsky as Economist and Mathematician," author Vincent Barnett describes a density survey of Moscow, Russia, conducted in 1910. Barnett tells how the survey was skewed by the inclusion of rural residents into the survey. This had the effect of lessening the true population density of the city area.
Population density studies are only as dependable as the data upon which they are based. Population surveys conducted in rural or sparsely populated areas are likely effective at capturing most of the population. Surveys that take place within large metropolitan areas must account for varied living quarters, such as large tenant-occupied buildings, homelessness and transient populations. Understandably, survey takers sometimes miss counting all of the urban occupants. These mistakes affect the reliability of the population density study.