Which of the following best describes "data integration" in GIS?

Data integration in GIS refers to the act of combining data from various sources to create a cohesive dataset that is usable for analysis and decision-making. This process is crucial because geographic data often comes from different origins—such as satellite imagery, census data, and environmental records—and may have varying formats and structures. By integrating these datasets, GIS professionals can ensure that the data is compatible and can be analyzed collectively, leading to more comprehensive insights and effective visualizations.

Successful data integration allows for a more holistic understanding of geographic phenomena, enabling users to see relationships and patterns that may not be apparent when looking at isolated datasets. This is especially important for multi-faceted analyses, such as urban planning or environmental assessments, where information from various domains needs to be synthesized for informed decision-making.