Representing Populations: a Spatial Ecology
A subtitle to this post might also be: Are we all being mislead by the New York Times? In stating this I am referring to the recent maps released by the New York Times looking at ethnic distributions from the US Census Bureau’s American Community Survey.
The most immediate thing we can learn about this project is that it is a spatial ecology, that is, an examination of the spatial patterning of a phenomena, here it’s ethnicity, at a given level of spatial aggregation, in this case “every city, every block”.This much is apparent both when you drag the mouse across the geography of America and the Census areas are highlighted, as well as when you zoom in, and you navigate from the Census tract level to the Census block level, a finer scale areal aggregation.
On the one hand, what has been achieved in this map is tremendous, and the use of dot density mapping allows for a singular look at multivariate data. The sheer level of residential segregation in the US also makes the dot density approach a very persuasive cartographic representation. However, first let us consider what the dot density approach is.
First and foremost, it is important to note that the dot density approach does not represent the real-world locations of individuals, far from it, dot density maps are simply another way of drawing a choropleth map. Choropleth maps show data aggregated into predefined areas (e.g. Census Blocks) and thematically colour these areas based upon some classification of the share of the mapped phenomenon that each area has. In a dot density map, each dot represents an observation, or number of observations, that occur within an area, each dot is then randomly positioned within that area. This means that phenomena do not strictly occur where they were sampled, which can (in increasingly large areas) lead to increasingly large uncertainties and misrepresentations. A higher number of dots within an area indicates a greater number of observations, with density described by the relative spacing of the dots in each area: smaller spacings indicate higher density.
Herein lies the difficulty – most ways of dividing up territory, and census delineations in particular, use a space covering approach. This continuous, spatially extensive way of dividing up land means that all land areas, even areas that have no people living in them, are potentially subject to the random placement of a dot, in the image below this is shown by the placement of dots in water bodies. Dot density can be logically unsound, particularly when two adjoining census blocks have significantly different population densities, shown by the representation of apparently hard ‘edges’ at areal boundaries as in the image below.
One solution that could work to mitigate the issue of representing areal data using dot density maps would be to apply dasymetric mapping. The dasymetric mapping technique is a method of reallocating a population recorded on a continuous areal basis to one which is a better representation of where people actually are. To do this, more information than simply population counts are usually required, such as landuse classifications, or delineations of developed area. In reallocating population counts from an areal unit created on a continuous basis, to one which aims at a more realistic placing of people in space, the volume of people per area is preserved, this means that you will never end up with more or less people than you started with. David Martin has, in the UK, been responsible for some notable dasysemtric outputs with regard to the UK Census, and provides a software tool, SurfaceBuilder, here.
The overarching goal of dasymetric mapping is to circumnavigate the ecological fallacy, which manifests itself in issues I have suggested exist in the dot density mapping of the US. Whilst dasymetric mapping would resolve some issues, dot density would still be subject to some mislocation of data, which largely stems from the conflicting ontology of representing an areal-based data, such as a population count by census area, as a series of points within that area; it is too easy for the viewer to interpret the points as having some level of significance above and beyond the areal container within which they sit. Therefore it is useful that the New York Times mapping also provides an option to look solely at the thematic choropleths classified by colouring the areas for each individual ethnicity. In this representation the viewer cannot confer the same kind of absolute interpretation upon the meaning or location of points, as they may do for dot density representations.