Dose-Response Calculator for ArcGIS

• Author(s) / Creator(s)

  • Leu M.
  • Aldridge C.L.
  • Nielsen S.E.
  • Hanser, S.E.

• The Dose-Response Calculator for ArcGIS is a tool that extends the Environmental Systems Research Institute (ESRI) ArcGIS 10 Desktop application to aid with the visualization of relationships between two raster GIS datasets. A dose-response curve is a line graph commonly used in medical research to examine the effects of different dosage rates of a drug or chemical (for example, carcinogen) on an outcome of interest (for example, cell mutations) (Russell and others, 1982). Dose-response curves have recently been used in ecological studies to examine the influence of an explanatory dose variable (for example, percentage of habitat cover, distance to disturbance) on a predicted response (for example, survival, probability of occurrence, abundance) (Aldridge and others, 2008). These dose curves have been created by calculating the predicted response value from a statistical model at different levels of the explanatory dose variable while holding values of other explanatory variables constant. Curves (plots) developed using the Dose-Response Calculator overcome the need to hold variables constant by using values extracted from the predicted response surface of a spatially explicit statistical model fit in a GIS, which include the variation of all explanatory variables, to visualize the univariate response to the dose variable. Application of the Dose-Response Calculator can be extended beyond the assessment of statistical model predictions and may be used to visualize the relationship between any two raster GIS datasets (see example in tool instructions). This tool generates tabular data for use in further exploration of dose-response relationships and a graph of the dose-response curve.

• Date created

  2011

• Subjects / Keywords

  • Raster datasets
  • GIS
  • Visualization

• Type of Item

  Research Material

• DOI

  https://doi.org/10.7939/R3GB1XJ87

• License

  © 2011 S.E. Hanser, C.L. Aldridge, M. Leu, S.E. Nielsen. This item is open access and can be downloaded and shared. The original author(s) and source must be cited.