What is overlay analysis based on?

Overlay analysis is fundamentally based on Boolean logic, which is essential for combining different spatial datasets to analyze their relationships and derive meaningful conclusions. In overlay analysis, different layers of spatial data are combined to create new information or to identify areas of interest based on specific criteria.

Boolean logic allows for the use of operators such as AND, OR, and NOT, which are used to filter and manipulate spatial data effectively. For example, if one layer represents areas with a certain land use type and another layer represents zones of high population density, Boolean logic can help determine areas that meet both criteria simultaneously, thus allowing geospatial analysts to synthesize their findings in a usable format.

The other specific choices, while relevant to different geospatial or analytical contexts, do not directly represent the foundational principle behind overlay analysis. Principal component analysis is more concerned with data reduction and summarization of attributes rather than spatial relationships. Spatial diffusion pertains to the spread of phenomena and is not focused on overlaying multiple datasets. Graph theory is a mathematical framework for analyzing relationships and networks but does not specifically drive the combined spatial analysis that overlay involves.