What do we call the process of analyzing spatial data to understand relationships and patterns?

The process of analyzing spatial data to understand relationships and patterns is known as geospatial analysis. This term specifically refers to techniques and methodologies used to examine the spatial aspect of data and how it relates to various geographic phenomena. Geospatial analysis often involves the application of spatial statistics, geographic information systems (GIS), and spatial reasoning to identify trends, correlations, and the implications of spatially referenced data.

In contrast, spatial modeling typically focuses on creating models to simulate spatial processes or predict future spatial patterns rather than analyzing existing data for patterns and relationships. Descriptive statistics, while useful for summarizing and analyzing the characteristics of data, do not inherently account for spatial relationships, as they often focus on numerical summaries rather than the spatial context. Data manipulation is the process of organizing and transforming data, but it does not specifically address the analysis of relationships and patterns within spatial data. Thus, geospatial analysis is the term that encompasses all of these aspects, specifically relating to the spatial context of the data being analyzed.