Dasymetric Population Mapping

The dasymetric techniques used for this map integrate 2010 Census population data at the block group level [A] with 2010 LULC data from NOAA’s Coastal Change Analysis Program (C-CAP) [B]. The population values from Census block groups are “dis-aggregated” by distributing their value into intersecting LULC raster cells. LULC cells classified as high, medium, or low development receive a different proportion of a block group’s population based on a weighting formula.


The output [C] is a raster grid where each cell’s value is an estimated population count within that cell’s area. In this map, each raster grid cell is 60 x 60 meters, which is approximately one acre. The dasymetric map layers we derived provide a more accurate representation of where people are in the landscape and thus a more accurate indication of social vulnerability.



The benefits become clear when one compares traditional areal weighting techniques to dasymetric techniques. When estimating a “vulnerable” population from natural hazards, or any other spatial variable that can be overlaid in a GIS map, dasymetric techniques have been shown to be much more accurate (Mennis & Hultgren 2006; Maantay & Maroko 2009; Montgomery & Chakraborty 2013).