micromap: A Package for Linked Micromaps

Abstract

The R package micromap is used to create linked micromaps, which display statistical summaries associated with areal units, or polygons. Linked micromaps provide a means to simultaneously summarize and display both statistical and geographic distributions by linking statistical summaries to a series of small maps. The package contains functions dependent on the ggplot2 package to produce a row-oriented graph composed of different panels, or columns, of information. These panels at a minimum typically contain maps, a legend, and statistical summaries, with the color-coded legend linking the maps and statistical summaries. We first describe the layout of linked micromaps and then the structure required for both the spatial and statistical datasets. The function create_map_table in the micromap package converts the input of an sp SpatialPolygonsDataFrame into a data frame that can be linked with the statistical dataset. Highly detailed polygons are not appropriate for display in linked micromaps so we describe how polygon boundaries can be simplified, decreasing the time required to draw the graphs, while retaining adequate detail for detection of spatial patterns. Our worked examples of linked micromaps use public health data as well as environmental data collected from spatially balanced probabilistic surveys.

Multivariate Condition Assessment of Watersheds with Linked Micromaps

“…For fecal coliform, we estimated the proportion of sites that exceeded the criterion of 400 colonies/100 mL (WVDEP, ). We made linked micromaps using the R Linked Micromap Plots (micromap) package to visualize the statistical summaries and spatial context of the target population estimates among the WVDEP subbasins (Payton and Olsen, ; Payton et al ., ). These are row‐oriented graphs in which the data have been sorted, grouped, and color coded (Carr and Pickle, ).…”

“…Linked micromaps accomplish this by linking statistical summaries to a series of small maps. Although they were introduced in 1996, producing linked micromaps had been somewhat difficult, but making them now has been simplified with the introduction of the micromap R package (Symanzik et al, 2014;Payton and Olsen, 2015;Payton et al, 2015). Linked micromaps are a more informative alternative to traditional choropleth maps at summarizing data over areal units, such as watersheds, ecoregions, or states (Carr and Pierson, 1996;Symanzik and Carr, 2008).…”