Which term refers to the level of detail in spatial data determined by the size of the smallest unit of measurement?

The term that refers to the level of detail in spatial data determined by the size of the smallest unit of measurement is data resolution. This concept encompasses how finely spatial data can depict characteristics of the landscape or phenomena. Essentially, higher resolution data implies a smaller unit of measurement, allowing for greater detail and granularity in the representation of the geographic area or features being studied.

For instance, in a raster dataset, resolution relates to the size of each pixel; smaller pixels represent a higher resolution and can reveal more features and nuances of the area compared to larger pixels, which provide a more generalized view. Therefore, understanding data resolution is critical in GIS as it influences the ability to capture specific phenomena and interpret spatial relationships effectively.

In contrast, data precision refers to the consistency of measurements, data clarity relates to how easily data can be understood, and data accuracy involves how closely data values match the true values. While these terms are important in the realm of data quality, they do not specifically address the level of detail dictated by measurement units like data resolution does.