Week 15 - Dasymetric Mapping

This lab marks our final lab of the semester.  In it we covered dasymetric mapping, which is a mapping style that has been around since the 1800s.  This technique involves using ancillary data such as land cover information to map where a given population is more likely to reside, based on various attributes of the ancillary data.  Dasymetric mapping is used when one wishes to extrapolate population information from an enumeration unit to another category, such as land cover cells for urban areas.  Since this type of mapping is an estimate, quite a bit of error can be introduced into the estimated results - particularly since one is estimating values from two different areas that do not cover the same spatial area.  Error checking is key to staying on track with dasymetric mapping.

For our lab we compared an areal weighting technique and a dasymetric mapping technique.  For the areal weighting we estimated the amount of the school aged population per a given high school zone, but that was located outside of areas covered in water. The theory here is that the population could reside anywhere within the census tract as it intersected with the high school zone, as long as that area was outside of a water polygon. 

View of impervious areas (in red) as they relate to census tract and high school zones.

The view above shows the dasymetric mapping result of our lab.  Instead of using land cover information for our ancillary data we instead used a measure of imperviousness.  The impervious areas are shown above in red; gray areas indicate zero imperviousness.  FYI, imperviousness indicates a built-up area (an impermeable area), and is a better measure of determining where people are more likely to reside than using land cover data alone.

The goal was to determine how many school aged children reside in the impervious areas per high school zone.  Each high school area (shown above bounded in dark gray) contains census tract data, but as the view shows the two are not spatially congruent.  This also holds true with the impervious areas, which are depicted above in raster format.

To make this all work I ended up using the Zonal Statistics to Table to determine the amount of impervious areas per census tracts.  This operation was completed first with my census tract and impervious data, and then again using an intersect of the census tract and high school zone information.  New fields were added to each result to account for a 'before' impervious area and an 'after' impervious area.  This was important because to ultimately determine the population of school age children per high school zone I used the following calculation: school aged children per high school = total school aged children * ('after' impervious area / 'before' impervious area).

The final result, after error checking against a reference population, showed that only 10% of the population was allocated incorrectly.  While not perfect it indicates a slight improvement over the areal weighting technique, which resulted in 11% of the population having been allocated incorrectly. 

*Originally published on December 17, 2015.  Updated on 2/27/2017 to repair image links.