What does 'data visualization' in spatial analysis refer to?

Data visualization in spatial analysis primarily refers to the graphical representation of spatial data to communicate complex information clearly and effectively. This process involves transforming raw data into visual formats such as maps, charts, and graphs, which help to highlight patterns, trends, and relationships within the data.

Visual representations can make it easier for users to understand intricate spatial concepts and draw insights from them, as opposed to interpreting numbers or text-based information alone. For example, thematic maps can display population density, land use patterns, or the spread of a phenomenon over time, facilitating a quicker and more effective decision-making process.

In contrast to this, using spreadsheets and tables limits the ability to convey complex spatial relationships visually and can lead to misunderstandings or oversight of important spatial context. Similarly, analyzing patterns in social media data or creating physical models may play roles in broader data analysis but do not define the specific aspect of data visualization in spatial analysis.