The goal of
qualmap is to make it easy to enter data
from qualitative maps.
qualmap provides a set of functions
for taking qualitative GIS data, hand drawn on a map, and converting it
to a simple features object. These tools are focused on data that are
drawn on a map that contains some type of polygon features. For each
area identified on the map, the id numbers of these polygons can be
entered as vectors and transformed using
Qualitative GIS outputs are notoriously difficult to work with
because individuals’ conceptions of space can vary greatly from each
other and from the realities of physical geography themselves.
qualmap builds on a semi-structured approach to qualitative
GIS data collection. Respondents use a specially designed basemap that
allows them free reign to identify geographic features of interest and
makes it easy to convert their annotations into digital map features.
This is facilitated by including on the basemap a series of polygons,
such as neighborhood boundaries or census geography, along with an
identification number that can be used by
qualmap. A circle
drawn on the map can therefore be easily associated with the features
that it touches or contains.
qualmap provides a suite of functions for entering,
validating, and creating
sf objects based on these hand
drawn clusters and their associated identification numbers. Once the
clusters have been created, they can be summarized and analyzed either
within R or using another tool.
This approach provides an alternative to either unstructured qualitative GIS data, which are difficult to work with empirically, and to digitizing respondents’ annotations as rasters, which require a sophisticated workflow. This semi-structured approach makes integrating qualitative GIS with existing census and administrative data simple and straightforward, which in turn allows these data to be used as measures in spatial statistical models.
qualmap’s approach to qualitative GIS has
been published in Cartographica.
All data associated with the article are also available on Open Science Framework, and the code
are available via Open Science
Framework and GitHub. Please
cite the paper if you use areal in your work!
The easiest way to get
qualmap is to install it from
You can install the development version of
Github with the
# install.packages("remotes") ::install_github("chris-prener/qualmap")remotes
Note that installations that require
sf to be built from
source will require additional software regardless of operating
system. You should check the
website for the latest details on installing dependencies for that
package. Instructions vary significantly by operating system.
qualmap implements six primary verbs for working with
mental map data:
qm_define()- create a vector of feature id numbers that constitute a single “cluster”
qm_validate()- check feature id numbers against a reference data set to ensure that the values are valid
qm_preview()- plot cluster on an interactive map to ensure the feature ids have been entered correctly (the preview should match the map used as a data collection instrument)
qm_create()- create a single cluster object once the data have been validated and visually inspected
qm_combine()- combine multiple cluster objects together into a single tibble data object
qm_summarize()- summarize the combined data object based on a single qualitative construct to prepare for mapping
The primary vignette contains an overview of the workflow for implementing these functions.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.