Landscape metrics regularly outperform other traditionally-used ancillary datasets in dasymetric mapping of population

• DOI: 10.1016/j.compenvurbsys.2022.101899
• Publication Date: 2022-11-02T04:01:27Z
• Authors: Heng Wan; Jim Yoon; Vivek Srikrishnan; Brent Daniel; David Judi
• Keywords: Ancillary data; Impervious surface; Land Cover; Baseline (sea)

Population downscaling and interpolation methods are required to produce data which correspond spatial units used in urban planning, demography, environmental modeling. typically aggregated at census enumeration units, can have arbitrary, temporally-evolving boundaries. Previous approaches imperviousness-based dasymetric mapping ignore cell-level patterning of imperviousness within a unit prediction, potentially serve as strong indicator population. Landscape metrics derived from offer promising approach capture these patterns. In this study, we incorporate landscape impervious cover percentage maps into intelligent downscale population tracts block groups four states with varying densities: Connecticut, South Carolina, West Virginia, New Mexico. We compare the performance metrics-based models against two baseline all across three different time periods. The results show that using generally outperforms models. further an ancillary source information for other traditionally-used datasets (e.g., land use, roads, nighttime lights data) (Connecticut, Mexico) 2000. find class area, shape index, number patches consistently achieve lower error rates than states.