populR: a Package for Population Downscaling in R

Abstract

Population data provision is usually framed by regulations and restrictions and hence spatially aggregated in predefined enumeration units such as city blocks and census tracts. Many applications require population data at finer scale, and therefore, one may use downscaling methods to transform population counts from coarse spatial units into smaller ones. Although numerous methods for downscaling of population data have been reported in the scientific literature, only a limited number of implementation tools exist. In this study, we introduce populR, an R package that responds to this need. populR provides two downscaling methods, namely Areal Weighted Interpolation and Volume Weighted Interpolation, which are illustrated and compared to alternative implementations in the sf and areal packages using a case study from Mytilini, Greece. The results provide evidence that the vwi approach outperforms the others, and thus, we believe R users may gain significant advantage by using populR for population downscaling.

PoD: A Web Tool for Population Downscaling Using Areal Interpolation and Volunteered Geographic Information

“…PoD is a web tool focusing on population downscaling using areal interpolation methods and VGI, through a ready-to-work and easy-to-use UI with point-and-click features and minimum user inputs. PoD functionality adopts the areal interpolation schemes of the latest version (v0.2.1) of populR package (Batsaris, 2021) and is composed of a Data Upload module and four downscaling method modules namely: 1) AWI (Areal Weighted Interpolation), 2) VWI (Volume Weighted Interpolation), 3) BDI (Binary Dasymetric Interpolation) and 4) FDI (Float Dasymetric Interpolation).…”

“…Prener and Revord introduced areal (Prener & Revord, 2019) which extends the sf package's functionality by providing an additional formula suitable for data without complete overlap. Finally, a recent addition named populR (Batsaris & Kavroudakis, 2021) extends areal functionality by introducing a new method that uses a volume-weighted approach.…”