Choropleth map

Abstract: Background: There are interests in the use geospatial data for development of acute stroke services given the importance of timely acess to acute reperfusion therapy. This paper aims to introduce clinicians and citizen scientists to the possibilities offered by open source softwares (R and Python) for analyzing geospatial data. It is hope that this introduction would stimulate interest in the field as well as generate ideas for improving stroke services. Method: Instructions on installation of libraries for R and Python, source codes and links to census data are provided in a notebook format to enhance experience with running these softwares. These codes illustrate different aspects of using geospatial analysis: 1)- creation of choropleth (thematic) map which depicts estimate of stroke cases per post codes; 2) use of map to help define service regions for rehabilitation after stroke. Results: Choropleth map showing estimate of stroke per post codes and service boundary map for rehabilitation after stroke. Conclusions The examples in this article illustrate the use of a range of components that underpin geospatial analysis. By providing an accessible introduction to these areas, clinicians and researchers can create code to answer clinically relevant questions on topics such as service delivery and service demand.

Abstract: Guidelines for choropleth map design have concentrated on printed maps. This paper examines whether the conventional use of darker symbols to mean “more” is applicable on maps presented in other media. Forty-seven subjects performed map reading tasks using slides photographed from a CRT screen. Results indicate that map readers take darker symbols for “more” in these displays. Further, the tendency for map readers to take darker symbols to represent greater magnitudes is modified by the value of a map's background. Approximately one-fifth of the experimental subjects reversed symbol order because of background value. Backgrounds of intermediate value impeded symbol ordering. This evidence suggests that for at least some subjects, a map's background anchors map symbols and influences their apparent order.

Abstract: This paper describes two interactive templates for representing spatially indexed estimates. Both templates use a matrix layout of small panels. The first template, called linked micromap plots, can represent multivariate estimates associated with each spatially indexed study unit. The second template, called conditioned choropleth maps, shows the connection between a dependent variable, as represented in a classed choropleth map, and two explanatory variables. The paper describes the cognitive considerations that motivate the layouts and representation details. The discussion also addresses topics of data quality and access, hypothesis generation, and interactive features such as pan and zoom and dynamic conditioning via sliders. The examples show epidemiological (mortality rates) and environmental (toxic concentrations) applications.