What does surface data represent when used in GIS?

Surface data in GIS refers to information that represents continuous phenomena across a geographic area, which can reflect changes in distance, elevation, temperature, or other metrics that exist over a surface. Distance values over an area can represent how far locations are from each other, which is relevant for applications such as transportation modeling, network analysis, and spatial distribution studies.

The concept of surface data can encompass representations such as raster data models, where each pixel corresponds to a specific value that can change across the landscape. This is in contrast to discrete data types that represent specific points or boundaries related to phenomena like population or hydrology.

While population density could be analyzed under certain contexts or raster-based formats, it typically relies on administrative boundaries and point data rather than being purely a surface phenomenon. Similarly, hydrologic data can be seen as surface data when discussing various hydrological models, but it more often relates to point or network connections rather than providing a continuous map of distance. Weather patterns, while they can be represented in a spatial context across landscapes, are generally more closely associated with atmospheric data than the concept of surface values mapped purely in distance terms.

By focusing on the idea of distance as it applies to surface data, the answer provides insight into how GIS can analyze