A Sensitivity Analysis for Deriving Dynamic and Evolutionary Rules in an Artificial Immune System- Cellular Automata Model

There have been several studies advocating the need for, and the feasibility of, using advanced techniques to support decision makers in urban planning and resource monitoring. One such advanced technique includes a framework that leverages the use of remote sensing and geospatial information systems (GIS) in conjunction with cellular automata (CA) to monitor land use / land change phenomena like urban sprawling. However, little research has been performed to analyze these frameworks’ sensitivity to the input data (e.g. imagery). New technology is promising better data more frequently; all with an associated price tag. Understanding sensitivity provides decision-makers and analysts the necessary information to procure just the right amount, and type, of data. Our research focuses on arming analysts and decision makers with this information.